diff --git a/moose-examples/.travis.yml b/moose-examples/.travis.yml
index f0ea25523a5b5b54333bba16da4395c656912e56..8799d5a775fd4da7347f8d539d697b64f00a0b2a 100644
--- a/moose-examples/.travis.yml
+++ b/moose-examples/.travis.yml
@@ -12,11 +12,12 @@ install:
- sudo apt-key add - < Release.key
- sudo sh -c "echo 'deb http://download.opensuse.org/repositories/home:/moose/xUbuntu_12.04/ /' >> /etc/apt/sources.list.d/moose.list"
- sudo apt-get -y update
- - sudo apt-get install python-h5py
+ - sudo apt-get -y install python-qt4
- sudo apt-get -y install moose
- - sudo apt-get -y install moogli
script:
+ - # Making sure no python3 incompatible file.
+ - python3 -m compileall -q .
+ - python2 -m compileall -q .
- python -c 'import moose'
- - python -c 'import moogli'
- cd _travis && ./find_scripts_to_run.sh && ./run_scripts.sh
diff --git a/moose-examples/_travis/run_scripts.sh b/moose-examples/_travis/run_scripts.sh
index c0140b9a0a56ff55f78c4327e9e6e837e4e09e17..4b4ea1062e689db9732dfa01aafa7443aa5c812e 100755
--- a/moose-examples/_travis/run_scripts.sh
+++ b/moose-examples/_travis/run_scripts.sh
@@ -10,7 +10,7 @@ TEMP=$PWD/__temp__
rm -f $BLACKLISTED $SUCCEEDED $FAILED $TEMP TORUN
$PWD/find_scripts_to_run.sh
-PYC=`which python`
+PYC=`which python2`
MATPLOTRC=$PWD/matplotlibrc
if [ ! -f $MATPLOTRC ]; then
echo "$MATPLOTRC not found"
diff --git a/moose-examples/hopfield/guiHopfield.py b/moose-examples/hopfield/guiHopfield.py
index 1df12e51348fab07bd4d68aee27905f8f6ba5113..37dc6b1d2c4f70fd0a2b28f7f7bf867cd0d8c835 100644
--- a/moose-examples/hopfield/guiHopfield.py
+++ b/moose-examples/hopfield/guiHopfield.py
@@ -53,7 +53,7 @@ class DesignerMainWindow(QtGui.QMainWindow, Ui_MainWindow):
self.connect(self.computeSynWeightsPushButton,QtCore.SIGNAL('clicked()'),self.computeAllWeights)
def saveInput(self):
- print 'saving current pattern as input'
+ print('saving current pattern as input')
inpList = []
for i in range(100):
exec(('inpList.append(int(self.pushButton_%s.isChecked()))' %i))
diff --git a/moose-examples/hopfield/hopfield.py b/moose-examples/hopfield/hopfield.py
index 870c9b317de6bf0d5edc48a00eeaef112e09d12a..534c19216db2eb24c44b2f01a58ca26b9828dfa5 100644
--- a/moose-examples/hopfield/hopfield.py
+++ b/moose-examples/hopfield/hopfield.py
@@ -58,9 +58,9 @@ class HopfieldNetwork():
memory[j] = -1
self.synWeights[i*len(memory)+j] += memory[i]*memory[j]
- print self.synWeights[0:100]
+ print((self.synWeights[0:100]))
self.numMemories += 1
- print self.numMemories, '#number Of saved memories'
+ print((self.numMemories, '#number Of saved memories'))
def createNetwork(self):
'''setting up of the cells and their connections'''
diff --git a/moose-examples/hopfield/test.py b/moose-examples/hopfield/test.py
index 8ff674c5fbdc8a37e12b59bdc940dab63b1c953c..4d296cda3e17a68e41d680620a4f65a4ebbaf0cc 100644
--- a/moose-examples/hopfield/test.py
+++ b/moose-examples/hopfield/test.py
@@ -37,20 +37,20 @@ cell.synapse[0].delay = 10e-3
#else, goes back to 0 in tau time
VmVal = moose.Table(cellPath+'/Vm_cell')
-print 'table>cellVm:', moose.connect(VmVal, 'requestOut', cell, 'getVm')
+print(('table>cellVm:', moose.connect(VmVal, 'requestOut', cell, 'getVm')))
spikeTime = moose.Table(cellPath+'/spikeTimes')
-print 'table>cellSpike:', moose.connect(cell, 'spike', spikeTime, 'input')
+print(('table>cellSpike:', moose.connect(cell, 'spike', spikeTime, 'input')))
inSpkGen = moose.SpikeGen(cellPath+'/inSpkGen')
inSpkGen.setField('threshold', 2.0)
inSpkGen.setField('edgeTriggered', True)
if inputGiven == 1:
- print 'pulse>spike:', moose.connect(pg, 'output', moose.element(cellPath+'/inSpkGen'), 'Vm')
+ print(('pulse>spike:', moose.connect(pg, 'output', moose.element(cellPath+'/inSpkGen'), 'Vm')))
inTable = moose.Table(cellPath+'/inSpkGen/inTable')
- print 'table>spike:',moose.connect(inTable, 'requestOut', inSpkGen, 'getHasFired')
+ print(('table>spike:',moose.connect(inTable, 'requestOut', inSpkGen, 'getHasFired')))
-print 'spike>cell:', moose.connect(inSpkGen, 'spikeOut', cell.synapse[0] ,'addSpike')
+print(('spike>cell:', moose.connect(inSpkGen, 'spikeOut', cell.synapse[0] ,'addSpike')))
#print 'spike>cell:', moose.connect(pg, 'output', cell ,'injectDest')
moose.setClock(0, 1e-4)
diff --git a/moose-examples/izhikevich/Izhikevich.py b/moose-examples/izhikevich/Izhikevich.py
index f6cf12ed94397ce9ae8a3bf247bffd22c324c636..00194c9909b808e0486e88f7cf775d7b02c06616 100644
--- a/moose-examples/izhikevich/Izhikevich.py
+++ b/moose-examples/izhikevich/Izhikevich.py
@@ -197,7 +197,7 @@ These neurons show bursting in response to inhibitory input."""
neuron = self._get_neuron(key)
pulsegen = self._make_pulse_input(key)
if pulsegen is None:
- print key, 'Not implemented.'
+ print((key, 'Not implemented.'))
def simulate(self, key):
self.setup(key)
@@ -207,7 +207,7 @@ These neurons show bursting in response to inhibitory input."""
try:
Vm = self.Vm_tables[key]
u = self.u_tables[key]
- except KeyError, e:
+ except KeyError as e:
Vm = moose.Table(self.data_container.path + '/' + key + '_Vm')
nrn = self.neurons[key]
moose.connect(Vm, 'requestOut', nrn, 'getVm')
@@ -217,7 +217,7 @@ These neurons show bursting in response to inhibitory input."""
self.u_tables[key] = utable
try:
Im = self.inject_tables[key]
- except KeyError, e:
+ except KeyError as e:
Im = moose.Table(self.data_container.path + '/' + key + '_inject') # May be different for non-pulsegen sources.
Im.connect('requestOut', self._get_neuron(key), 'getIm')
self.inject_tables[key] = Im
@@ -237,7 +237,7 @@ These neurons show bursting in response to inhibitory input."""
time = linspace(0, IzhikevichDemo.parameters[key][7], len(Vm.vector))
# DEBUG
nrn = self._get_neuron(key)
- print 'a = %g, b = %g, c = %g, d = %g, initVm = %g, initU = %g' % (nrn.a,nrn.b, nrn.c, nrn.d, nrn.initVm, nrn.initU)
+ print(('a = %g, b = %g, c = %g, d = %g, initVm = %g, initU = %g' % (nrn.a,nrn.b, nrn.c, nrn.d, nrn.initVm, nrn.initU)))
#! DEBUG
return (time, Vm, Im)
@@ -246,14 +246,14 @@ These neurons show bursting in response to inhibitory input."""
try:
params = IzhikevichDemo.parameters[key]
except KeyError as e:
- print ' %s : Invalid neuron type. The valid types are:' % (key)
+ print((' %s : Invalid neuron type. The valid types are:' % (key)))
for key in IzhikevichDemo.parameters:
- print key
+ print(key)
raise e
try:
neuron = self.neurons[key]
return neuron
- except KeyError, e:
+ except KeyError as e:
neuron = moose.IzhikevichNrn(self.model_container.path + '/' + key)
if key == 'integrator' or key == 'Class_1': # Integrator has different constants
@@ -354,7 +354,7 @@ These neurons show bursting in response to inhibitory input."""
self.inputs[key] = input_table
return input_table
else:
- print key, ': Stimulus is not based on pulse generator.'
+ print((key, ': Stimulus is not based on pulse generator.'))
raise
pulsegen = self._make_pulsegen(key,
firstLevel,
@@ -529,9 +529,9 @@ try:
plot(time, Im.vector)
subplot(3,1,3)
show()
- print 'Finished simulation.'
+ print('Finished simulation.')
except ImportError:
- print 'Matplotlib not installed.'
+ print('Matplotlib not installed.')
#
# Izhikevich.py ends here
diff --git a/moose-examples/izhikevich/demogui_qt.py b/moose-examples/izhikevich/demogui_qt.py
index 753e98ff3f92afc0f6cc827b1cc82f4982829091..62410ed4d47fbbcfd716faf059bd9c433efceeb0 100644
--- a/moose-examples/izhikevich/demogui_qt.py
+++ b/moose-examples/izhikevich/demogui_qt.py
@@ -62,11 +62,11 @@ class IzhikevichGui(QtGui.QMainWindow):
self.controlPanel = QtGui.QFrame(self.demoFrame)
self.figureNo = {}
self.buttons = {}
- for key, value in IzhikevichDemo.parameters.items():
+ for key, value in list(IzhikevichDemo.parameters.items()):
button = QtGui.QPushButton(key, self.controlPanel)
self.figureNo[value[0]] = key
self.buttons[key] = button
- keys = self.figureNo.keys()
+ keys = list(self.figureNo.keys())
keys.sort()
length = len(keys)
rows = int(numpy.rint(numpy.sqrt(length)))
diff --git a/moose-examples/kinetics/test_ksolve.py b/moose-examples/kinetics/test_ksolve.py
index 84ab0802e572b498d3a45e5b9c104e8d2070108d..373d7e26f9282dc86da1364b1c59028639af856d 100644
--- a/moose-examples/kinetics/test_ksolve.py
+++ b/moose-examples/kinetics/test_ksolve.py
@@ -306,7 +306,7 @@ def createChemModel( neuroCompt, spineCompt, psdCompt ):
# Just for printf debugging
def printMolVecs( title ):
- print title
+ print(title)
"""
nCa = moose.vec( '/model/chem/neuroMesh/Ca' )
sCa = moose.vec( '/model/chem/spineMesh/Ca' )
@@ -477,7 +477,7 @@ def testCubeMultiscale( useSolver ):
moose.reinit()
t = time.time()
moose.start( 1.0 )
- print("Total time taken: %s sec for 1.0 sec of simulation" % (time.time() - t))
+ print(("Total time taken: %s sec for 1.0 sec of simulation" % (time.time() - t)))
dumpPlots( plotName )
def main():
diff --git a/moose-examples/moogli/purkinje_simulation.py b/moose-examples/moogli/purkinje_simulation.py
index 02df05d29bb028425326f82fc1ffc1b7376aff40..07c10609dbdd1ddf289d649d95a390f72600dde4 100644
--- a/moose-examples/moogli/purkinje_simulation.py
+++ b/moose-examples/moogli/purkinje_simulation.py
@@ -26,8 +26,8 @@ filename = os.path.join( os.path.split(os.path.realpath(__file__))[0]
popdict, projdict = moose.neuroml.loadNeuroML_L123(filename)
# setting up hsolve object for each neuron
-for popinfo in popdict.values():
- for cell in popinfo[1].values():
+for popinfo in list(popdict.values()):
+ for cell in list(popinfo[1].values()):
solver = moose.HSolve(cell.path + "/hsolve")
solver.target = cell.path
@@ -37,9 +37,7 @@ moose.reinit()
SIMULATION_DELTA = 0.001
SIMULATION_TIME = 0.03
-ALL_COMPARTMENTS = map( lambda x : x.path
- , moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")
- )
+ALL_COMPARTMENTS = [x.path for x in moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")]
BASE_VM_VALUE = -0.065
PEAK_VM_VALUE = -0.060
BASE_VM_COLOR = [1.0, 0.0, 0.0, 0.1]
@@ -69,9 +67,7 @@ morphology.create_group( "group-all" # group name
# set initial color of all compartments in accordance with their vm
morphology.set_color( "group-all"
- , map( lambda x : moose.element(x).Vm
- , ALL_COMPARTMENTS
- )
+ , [moose.element(x).Vm for x in ALL_COMPARTMENTS]
)
# instantiate the visualizer with the morphology object created earlier
@@ -90,9 +86,7 @@ def callback(morphology, viewer):
# a value higher than peak value will be clamped to peak value
# a value lower than base value will be clamped to base value.
morphology.set_color( "group-all"
- , map( lambda x : x.Vm
- , moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")
- )
+ , [x.Vm for x in moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")]
)
# if the callback returns true, it will be called again.
# if it returns false it will not be called ever again.
diff --git a/moose-examples/moogli/purkinje_simulation_with_rm.py b/moose-examples/moogli/purkinje_simulation_with_rm.py
index 4957c69968c463ac5905816873fdd366c024f81d..fcf8c5856b89349a6fbcf1e0071518cdffbb0e98 100644
--- a/moose-examples/moogli/purkinje_simulation_with_rm.py
+++ b/moose-examples/moogli/purkinje_simulation_with_rm.py
@@ -28,8 +28,8 @@ filename = os.path.join( os.path.split(os.path.realpath(__file__))[0]
popdict, projdict = moose.neuroml.loadNeuroML_L123(filename)
# setting up hsolve object for each neuron
-for popinfo in popdict.values():
- for cell in popinfo[1].values():
+for popinfo in list(popdict.values()):
+ for cell in list(popinfo[1].values()):
solver = moose.HSolve(cell.path + "/hsolve")
solver.target = cell.path
@@ -39,17 +39,11 @@ moose.reinit()
SIMULATION_DELTA = 0.001
SIMULATION_TIME = 0.03
-ALL_COMPARTMENTS = map( lambda x : x.path
- , moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")
- )
+ALL_COMPARTMENTS = [x.path for x in moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")]
-BASE_RM_VALUE = min( map( lambda x : moose.element(x).Rm
- , ALL_COMPARTMENTS
- )
+BASE_RM_VALUE = min( [moose.element(x).Rm for x in ALL_COMPARTMENTS]
)
-PEAK_RM_VALUE = max( map( lambda x : moose.element(x).Rm
- , ALL_COMPARTMENTS
- )
+PEAK_RM_VALUE = max( [moose.element(x).Rm for x in ALL_COMPARTMENTS]
)
BASE_RM_COLOR = [0.0, 1.0, 0.0, 0.1]
PEAK_RM_COLOR = [1.0, 0.0, 0.0, 1.0]
@@ -86,9 +80,7 @@ def create_vm_visualizer():
# set initial color of all compartments in accordance with their vm
vm_morphology.set_color( "group-all"
- , map( lambda x : moose.element(x).Vm
- , ALL_COMPARTMENTS
- )
+ , [moose.element(x).Vm for x in ALL_COMPARTMENTS]
)
# instantiate the visualizer with the morphology object created earlier
@@ -105,9 +97,7 @@ def create_vm_visualizer():
# a value higher than peak value will be clamped to peak value
# a value lower than base value will be clamped to base value.
morphology.set_color( "group-all"
- , map( lambda x : moose.element(x).Vm
- , ALL_COMPARTMENTS
- )
+ , [moose.element(x).Vm for x in ALL_COMPARTMENTS]
)
# if the callback returns true, it will be called again.
# if it returns false it will not be called again.
@@ -148,9 +138,7 @@ def create_rm_visualizer():
# set initial color of all compartments in accordance with their rm
morphology.set_color( "group-all"
- , map( lambda x : moose.element(x).Rm
- , ALL_COMPARTMENTS
- )
+ , [moose.element(x).Rm for x in ALL_COMPARTMENTS]
)
# instantiate the visualizer with the morphology object created earlier
diff --git a/moose-examples/moogli/purkinje_simulation_with_rm_and_graph.py b/moose-examples/moogli/purkinje_simulation_with_rm_and_graph.py
index ec886b27541c7eb8e24692861d96f8c17ac91560..647e349144552500b53ac6b6512f51925a3b61a9 100644
--- a/moose-examples/moogli/purkinje_simulation_with_rm_and_graph.py
+++ b/moose-examples/moogli/purkinje_simulation_with_rm_and_graph.py
@@ -30,8 +30,8 @@ filename = os.path.join( os.path.split(os.path.realpath(__file__))[0]
popdict, projdict = moose.neuroml.loadNeuroML_L123(filename)
# setting up hsolve object for each neuron
-for popinfo in popdict.values():
- for cell in popinfo[1].values():
+for popinfo in list(popdict.values()):
+ for cell in list(popinfo[1].values()):
solver = moose.HSolve(cell.path + "/hsolve")
solver.target = cell.path
@@ -49,17 +49,11 @@ moose.reinit()
SIMULATION_DELTA = 0.001
SIMULATION_TIME = 0.03
-ALL_COMPARTMENTS = map( lambda x : x.path
- , moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")
- )
+ALL_COMPARTMENTS = [x.path for x in moose.wildcardFind("/cells[0]/##[ISA=CompartmentBase]")]
-BASE_RM_VALUE = min( map( lambda x : moose.element(x).Rm
- , ALL_COMPARTMENTS
- )
+BASE_RM_VALUE = min( [moose.element(x).Rm for x in ALL_COMPARTMENTS]
)
-PEAK_RM_VALUE = max( map( lambda x : moose.element(x).Rm
- , ALL_COMPARTMENTS
- )
+PEAK_RM_VALUE = max( [moose.element(x).Rm for x in ALL_COMPARTMENTS]
)
BASE_RM_COLOR = [0.0, 1.0, 0.0, 0.1]
PEAK_RM_COLOR = [1.0, 0.0, 0.0, 1.0]
@@ -111,9 +105,7 @@ def create_vm_visualizer():
# set initial color of all compartments in accordance with their vm
vm_morphology.set_color( "group-all"
- , map( lambda x : moose.element(x).Vm
- , ALL_COMPARTMENTS
- )
+ , [moose.element(x).Vm for x in ALL_COMPARTMENTS]
)
# instantiate the visualizer with the morphology object created earlier
@@ -130,9 +122,7 @@ def create_vm_visualizer():
# a value higher than peak value will be clamped to peak value
# a value lower than base value will be clamped to base value.
morphology.set_color( "group-all"
- , map( lambda x : moose.element(x).Vm
- , ALL_COMPARTMENTS
- )
+ , [moose.element(x).Vm for x in ALL_COMPARTMENTS]
)
# if the callback returns true, it will be called again.
# if it returns false it will not be called again.
@@ -181,9 +171,7 @@ def create_rm_visualizer():
# set initial color of all compartments in accordance with their rm
morphology.set_color( "group-all"
- , map( lambda x : moose.element(x).Rm
- , ALL_COMPARTMENTS
- )
+ , [moose.element(x).Rm for x in ALL_COMPARTMENTS]
)
# instantiate the visualizer with the morphology object created earlier
diff --git a/moose-examples/neuroml/CA1PyramidalCell/CA1.py b/moose-examples/neuroml/CA1PyramidalCell/CA1.py
index c8b8e74d65a6b3860fb05d2ca3f2ed8a04c2ca31..bbe90edb72de8fd79b63442880319079386925ea 100644
--- a/moose-examples/neuroml/CA1PyramidalCell/CA1.py
+++ b/moose-examples/neuroml/CA1PyramidalCell/CA1.py
@@ -31,16 +31,16 @@ def loadGran98NeuroML_L123(filename):
#somaIKCa = setupTable('somaIKCa',moose.HHChannel(soma_path+'/Gran_KCa_98'),'Gk')
#KDrX = setupTable('ChanX',moose.HHChannel(soma_path+'/Gran_KDr_98'),'X')
soma = moose.Compartment(soma_path)
- print "Reinit MOOSE ... "
+ print("Reinit MOOSE ... ")
resetSim(['/elec','/cells'],simdt,plotdt,simmethod='ee') # from moose.utils
- print "Running ... "
+ print("Running ... ")
moose.start(runtime)
tvec = arange(0.0,runtime,simdt)
plot(tvec,somaVm.vector[1:])
title('Soma Vm')
xlabel('time (s)')
ylabel('Voltage (V)')
- print "Showing plots ..."
+ print("Showing plots ...")
show()
if __name__ == "__main__":
diff --git a/moose-examples/neuroml/CA1PyramidalCell/CA1_hsolve.py b/moose-examples/neuroml/CA1PyramidalCell/CA1_hsolve.py
index 06f437ec27534244d4291f65767de66dc9b98d2d..5823db724ee9150805379dc010bc403db128731b 100644
--- a/moose-examples/neuroml/CA1PyramidalCell/CA1_hsolve.py
+++ b/moose-examples/neuroml/CA1PyramidalCell/CA1_hsolve.py
@@ -23,8 +23,8 @@ def loadGran98NeuroML_L123(filename,params):
neuromlR = NeuroML()
populationDict, projectionDict = \
neuromlR.readNeuroMLFromFile(filename,params=params)
- print "Number of compartments =",\
- len(moose.Neuron(populationDict['CA1group'][1][0].path).children)
+ print(("Number of compartments =",\
+ len(moose.Neuron(populationDict['CA1group'][1][0].path).children)))
soma_path = populationDict['CA1group'][1][0].path+'/Seg0_soma_0_0'
somaVm = setupTable('somaVm',moose.Compartment(soma_path),'Vm')
#somaCa = setupTable('somaCa',moose.CaConc(soma_path+'/Gran_CaPool_98'),'Ca')
@@ -32,16 +32,16 @@ def loadGran98NeuroML_L123(filename,params):
#KDrX = setupTable('ChanX',moose.HHChannel(soma_path+'/Gran_KDr_98'),'X')
soma = moose.Compartment(soma_path)
- print "Reinit MOOSE ... "
+ print("Reinit MOOSE ... ")
resetSim(['/elec','/cells'],simdt,plotdt,simmethod='hsolve') # from moose.utils
- print "Running ... "
+ print("Running ... ")
moose.start(runtime)
tvec = arange(0.0,runtime,simdt)
plot(tvec,somaVm.vector[1:])
title('Soma Vm')
xlabel('time (s)')
ylabel('Voltage (V)')
- print "Showing plots ..."
+ print("Showing plots ...")
show()
if __name__ == "__main__":
diff --git a/moose-examples/neuroml/CA1PyramidalCell/FvsI_CA1.py b/moose-examples/neuroml/CA1PyramidalCell/FvsI_CA1.py
index 28d13b09ba7ec3a69c2a3e4e4e7ccedddb23ec3e..3de7794d068d8eb67dc0bb4bbeecea427c7a88a4 100644
--- a/moose-examples/neuroml/CA1PyramidalCell/FvsI_CA1.py
+++ b/moose-examples/neuroml/CA1PyramidalCell/FvsI_CA1.py
@@ -1,4 +1,4 @@
-#!/usr/bin/python
+
# -*- coding: utf-8 -*-
## all SI units
########################################################################################
@@ -63,8 +63,8 @@ for currenti in currentvec:
spikesList = spikesList[where(spikesList>0.0)[0]]
spikesNow = len(spikesList)
else: spikesNow = 0.0
- print "For injected current =",currenti,\
- "number of spikes in",RUNTIME,"seconds =",spikesNow
+ print(("For injected current =",currenti,\
+ "number of spikes in",RUNTIME,"seconds =",spikesNow))
freqList.append( spikesNow/float(RUNTIME) )
## plot the F vs I curve of the neuron
diff --git a/moose-examples/neuroml/GranuleCell/FvsI_Granule98.py b/moose-examples/neuroml/GranuleCell/FvsI_Granule98.py
index 40f3fef612c17836f691a3427d4d8ca5400f1d1a..80c9ad6b0e7678ecbab004d895c9d86b11905c12 100644
--- a/moose-examples/neuroml/GranuleCell/FvsI_Granule98.py
+++ b/moose-examples/neuroml/GranuleCell/FvsI_Granule98.py
@@ -1,4 +1,4 @@
-#!/usr/bin/python
+
# -*- coding: utf-8 -*-
## all SI units
########################################################################################
@@ -56,8 +56,8 @@ for currenti in currentvec:
spikesList = spikesList[where(spikesList>0.0)[0]]
spikesNow = len(spikesList)
else: spikesNow = 0.0
- print "For injected current =",currenti,\
- "number of spikes in",RUNTIME,"seconds =",spikesNow
+ print(("For injected current =",currenti,\
+ "number of spikes in",RUNTIME,"seconds =",spikesNow))
freqList.append( spikesNow/float(RUNTIME) )
## plot the F vs I curve of the neuron
diff --git a/moose-examples/neuroml/GranuleCell/Granule98.py b/moose-examples/neuroml/GranuleCell/Granule98.py
index cde13f6b38dda87a742aac6dbc53b699a905537a..9a29370a8194f9f7b1a8d7a44272fe8c380e6577 100644
--- a/moose-examples/neuroml/GranuleCell/Granule98.py
+++ b/moose-examples/neuroml/GranuleCell/Granule98.py
@@ -31,9 +31,9 @@ def loadGran98NeuroML_L123(filename):
somaIKCa = setupTable('somaIKCa',moose.HHChannel(soma_path+'/Gran_KCa_98'),'Gk')
#KDrX = setupTable('ChanX',moose.HHChannel(soma_path+'/Gran_KDr_98'),'X')
soma = moose.Compartment(soma_path)
- print "Reinit MOOSE ... "
+ print("Reinit MOOSE ... ")
resetSim(['/elec','/cells'],simdt,plotdt,simmethod='ee') # from moose.utils
- print "Running ... "
+ print("Running ... ")
moose.start(runtime)
tvec = arange(0.0,runtime,plotdt)
plot(tvec,somaVm.vector[1:])
@@ -50,7 +50,7 @@ def loadGran98NeuroML_L123(filename):
title('KCa current (A)')
xlabel('time (s)')
ylabel('')
- print "Showing plots ..."
+ print("Showing plots ...")
show()
filename = "GranuleCell.net.xml"
diff --git a/moose-examples/neuroml/GranuleCell/Granule98_hsolve.py b/moose-examples/neuroml/GranuleCell/Granule98_hsolve.py
index 52a3f817bc73bc6a9992d94514e8f30c63409efe..7f62f0eb6e4d70da672f9dc3ec37a450c1aaac8c 100644
--- a/moose-examples/neuroml/GranuleCell/Granule98_hsolve.py
+++ b/moose-examples/neuroml/GranuleCell/Granule98_hsolve.py
@@ -34,10 +34,10 @@ def loadGran98NeuroML_L123(filename):
## Am not able to plot KDr gating variable X when running under hsolve
#KDrX = setupTable('ChanX',moose.HHChannel(soma_path+'/Gran_KDr_98'),'X')
- print "Reinit MOOSE ... "
+ print("Reinit MOOSE ... ")
resetSim(['/elec',cells_path], simdt, plotdt, simmethod='hsolve')
- print "Running ... "
+ print("Running ... ")
moose.start(runtime)
tvec = arange(0.0,runtime*2.0,plotdt)
tvec = tvec[ : somaVm.vector.size ]
@@ -55,7 +55,7 @@ def loadGran98NeuroML_L123(filename):
title('soma KCa current')
xlabel('time (s)')
ylabel('KCa current (A)')
- print "Showing plots ..."
+ print("Showing plots ...")
show()
filename = "GranuleCell.net.xml"
diff --git a/moose-examples/neuroml/LIF/FvsI_LIF.py b/moose-examples/neuroml/LIF/FvsI_LIF.py
index 91309e765e9e3cecbed53e23e355af0f6664dcf9..5dce5b7bf505b6c435133d91dacd2dbc60caba4d 100644
--- a/moose-examples/neuroml/LIF/FvsI_LIF.py
+++ b/moose-examples/neuroml/LIF/FvsI_LIF.py
@@ -1,4 +1,4 @@
-#!/usr/bin/python
+
# -*- coding: utf-8 -*-
## all SI units
########################################################################################
@@ -46,8 +46,8 @@ for currenti in currentvec:
spikesList = spikesList[where(spikesList>0.0)[0]]
spikesNow = len(spikesList)
else: spikesNow = 0.0
- print "For injected current =",currenti,\
- "number of spikes in",RUNTIME,"seconds =",spikesNow
+ print(("For injected current =",currenti,\
+ "number of spikes in",RUNTIME,"seconds =",spikesNow))
freqList.append( spikesNow/float(RUNTIME) )
## plot the F vs I curve of the neuron
diff --git a/moose-examples/neuroml/LIF/LIFxml_firing_hsolve.py b/moose-examples/neuroml/LIF/LIFxml_firing_hsolve.py
index 0e0e35fd76f3da993d7f2ac69029a544faae944e..79316641b60ea4f9ffedc55b7e2a1eb6d6453d07 100644
--- a/moose-examples/neuroml/LIF/LIFxml_firing_hsolve.py
+++ b/moose-examples/neuroml/LIF/LIFxml_firing_hsolve.py
@@ -16,7 +16,7 @@ injectI = 2.5e-12 # Amperes
## moose imports
import moose
-print( '[DBEUG] Using moose from %s' % moose.__file__ )
+print(( '[DBEUG] Using moose from %s' % moose.__file__ ))
from moose.neuroml import *
from moose.utils import * # has setupTable(), resetSim() etc
@@ -59,7 +59,7 @@ if __name__ == '__main__':
moose.connect(spikeGen,'event',IF1spikesTable,'input')
run_LIF()
- print("Spiketimes :",IF1spikesTable.vector)
+ print(("Spiketimes :",IF1spikesTable.vector))
## plot the membrane potential of the neuron
timevec = arange(0.0,RUNTIME+PLOTDT/2.0,PLOTDT)
figure(facecolor='w')
diff --git a/moose-examples/neuroml/LIF/twoLIFxml_firing.py b/moose-examples/neuroml/LIF/twoLIFxml_firing.py
index aed0ef29b58286a4c03737530955c3dcd0917be1..58aaef1301a7631a19f7eef31777cebafb7aadea 100644
--- a/moose-examples/neuroml/LIF/twoLIFxml_firing.py
+++ b/moose-examples/neuroml/LIF/twoLIFxml_firing.py
@@ -37,10 +37,10 @@ def create_twoLIFs():
def run_twoLIFs():
## reset and run the simulation
- print "Reinit MOOSE."
+ print("Reinit MOOSE.")
## from moose_utils.py sets clocks and resets
resetSim(['/cells[0]'], SIMDT, PLOTDT, simmethod='ee')
- print "Running now..."
+ print("Running now...")
moose.start(RUNTIME)
if __name__ == '__main__':
@@ -64,7 +64,7 @@ if __name__ == '__main__':
moose.connect(IF2SynChanTable,'requestOut',IF2Soma.path+'/exc_syn','getIk')
run_twoLIFs()
- print "Spiketimes :",IF1spikesTable.vector
+ print(("Spiketimes :",IF1spikesTable.vector))
## plot the membrane potential of the neuron
timevec = arange(0.0,RUNTIME+PLOTDT/2.0,PLOTDT)
figure(facecolor='w')
diff --git a/moose-examples/neuroml/allChannelsCell/allChannelsCell.py b/moose-examples/neuroml/allChannelsCell/allChannelsCell.py
index 99ae428436e8a2632b371d645f6b863cd65c2df8..7df463c13e68726d02a8cd3fbb655a2d5faef14f 100644
--- a/moose-examples/neuroml/allChannelsCell/allChannelsCell.py
+++ b/moose-examples/neuroml/allChannelsCell/allChannelsCell.py
@@ -32,9 +32,9 @@ def loadGran98NeuroML_L123(filename):
somaIKCa = setupTable('somaIKCa',moose.HHChannel(soma_path+'/Gran_KCa_98'),'Gk')
#KDrX = setupTable('ChanX',moose.HHChannel(soma_path+'/Gran_KDr_98'),'X')
soma = moose.Compartment(soma_path)
- print "Reinit MOOSE ... "
+ print("Reinit MOOSE ... ")
resetSim(['/elec','/cells'],simdt,plotdt) # from moose.utils
- print "Running ... "
+ print("Running ... ")
moose.start(runtime)
tvec = arange(0.0,runtime,simdt)
plot(tvec,somaVm.vector[1:])
@@ -56,7 +56,7 @@ def loadGran98NeuroML_L123(filename):
title('KC current (A)')
xlabel('time (s)')
ylabel('')
- print "Showing plots ..."
+ print("Showing plots ...")
show()
filename = "allChannelsCell.net.xml"
diff --git a/moose-examples/neuroml/lobster_pyloric/STG_net.py b/moose-examples/neuroml/lobster_pyloric/STG_net.py
index 91226362413d15b2943804a8a31f1c8641465036..ca4b5a9ef27edcd6253aaf5fb4d19d96b804ed3c 100644
--- a/moose-examples/neuroml/lobster_pyloric/STG_net.py
+++ b/moose-examples/neuroml/lobster_pyloric/STG_net.py
@@ -74,9 +74,9 @@ def loadRunSTGNeuroML_L123(filename):
# monitor synaptic current
soma2 = moose.element(soma2_path)
- print "Children of",soma2_path,"are:"
+ print(("Children of",soma2_path,"are:"))
for child in soma2.children:
- print child.className, child.path
+ print((child.className, child.path))
if graded_syn:
syn_path = soma2_path+'/DoubExpSyn_Ach__cells-0-_AB_PD_0-0-_Soma_0'
syn = moose.element(syn_path)
@@ -85,11 +85,11 @@ def loadRunSTGNeuroML_L123(filename):
syn = moose.element(syn_path)
syn_Ik = setupTable('DoubExpSyn_Ach_Ik',syn,'Ik')
- print "Reinit MOOSE ... "
+ print("Reinit MOOSE ... ")
resetSim(['/elec',cells_path], simdt, plotdt, simmethod='hsolve')
- print "Using graded synapses? = ", graded_syn
- print "Running model filename = ",filename," ... "
+ print(("Using graded synapses? = ", graded_syn))
+ print(("Running model filename = ",filename," ... "))
moose.start(runtime)
tvec = np.arange(0.0,runtime+2*plotdt,plotdt)
tvec = tvec[ : soma1Vm.vector.size ]
@@ -139,7 +139,7 @@ def loadRunSTGNeuroML_L123(filename):
plt.title('Ach syn current in '+soma2_path)
plt.xlabel('time (s)')
plt.ylabel('Isyn (S)')
- print "Showing plots ..."
+ print("Showing plots ...")
plt.show()
diff --git a/moose-examples/neuroml/lobster_pyloric/channels/ChannelTest.py b/moose-examples/neuroml/lobster_pyloric/channels/ChannelTest.py
index 1928c505c1518170dcbcc745e3a34711f954819d..8b1f3e1892d3f2e1c4a37db5e114d8a4b8a52a38 100644
--- a/moose-examples/neuroml/lobster_pyloric/channels/ChannelTest.py
+++ b/moose-examples/neuroml/lobster_pyloric/channels/ChannelTest.py
@@ -18,16 +18,16 @@ mechanisms = {
import sys
if len(sys.argv)<2:
- print("Selecting a channel randomly form %s" % list(mechanisms.keys()))
- channel_name = random.choice( mechanisms.keys() )
- print("Selected %s" % channel_name )
+ print(("Selecting a channel randomly form %s" % list(mechanisms.keys())))
+ channel_name = random.choice( list(mechanisms.keys()) )
+ print(("Selected %s" % channel_name ))
else:
channel_name = sys.argv[1]
if channel_name in mechanisms:
mechanism_vars = mechanisms[channel_name]
else:
- print("Undefined channel, please use one of", list(mechanisms.keys()))
+ print(("Undefined channel, please use one of", list(mechanisms.keys())))
sys.exit(1)
CELSIUS = 35 # degrees Centigrade
@@ -39,7 +39,7 @@ from pylab import *
if __name__ == "__main__":
for varidx in range(len(mechanism_vars)/2): # loop over each inf and tau
- print( "Running for %s" % varidx )
+ print(( "Running for %s" % varidx ))
var = ['X','Y','Z'][varidx]
gate = moose.element('/library/'+channel_name+'/gate'+var)
VMIN = gate.min
diff --git a/moose-examples/neuroml/lobster_pyloric/synapses/AchSyn_STG.py b/moose-examples/neuroml/lobster_pyloric/synapses/AchSyn_STG.py
index 65c6a88080089342602ed10cbe6704c6c5ceee6e..8a56bbcf1a6c42ff3bc372e7b231f42845f2472f 100644
--- a/moose-examples/neuroml/lobster_pyloric/synapses/AchSyn_STG.py
+++ b/moose-examples/neuroml/lobster_pyloric/synapses/AchSyn_STG.py
@@ -8,7 +8,7 @@ from pylab import *
try:
import moose
except ImportError:
- print "ERROR: Could not import moose. Please add the directory containing moose.py in your PYTHONPATH"
+ print("ERROR: Could not import moose. Please add the directory containing moose.py in your PYTHONPATH")
import sys
sys.exit(1)
diff --git a/moose-examples/neuroml/lobster_pyloric/synapses/GluSyn_STG.py b/moose-examples/neuroml/lobster_pyloric/synapses/GluSyn_STG.py
index c8cdbecdb6bb4f964ff19c7a4a49d40243ca2149..b03142f21b25ab5926ab3ddb913e85bebe61a9cf 100644
--- a/moose-examples/neuroml/lobster_pyloric/synapses/GluSyn_STG.py
+++ b/moose-examples/neuroml/lobster_pyloric/synapses/GluSyn_STG.py
@@ -8,7 +8,7 @@ from pylab import *
try:
import moose
except ImportError:
- print "ERROR: Could not import moose. Please add the directory containing moose.py in your PYTHONPATH"
+ print("ERROR: Could not import moose. Please add the directory containing moose.py in your PYTHONPATH")
import sys
sys.exit(1)
diff --git a/moose-examples/paper-2015/Fig2_elecModels/Fig2A.py b/moose-examples/paper-2015/Fig2_elecModels/Fig2A.py
index 560167da637eaa587de30ab4e7aaedc1ff0da6d5..0a50accfbbad718010e1ca1db8a93fa7548e149b 100644
--- a/moose-examples/paper-2015/Fig2_elecModels/Fig2A.py
+++ b/moose-examples/paper-2015/Fig2_elecModels/Fig2A.py
@@ -224,15 +224,15 @@ class ExcInhNetBase:
t1 = time.time()
print('reinit MOOSE -- takes a while ~20s.')
moose.reinit()
- print('reinit time t = ', time.time() - t1)
+ print(('reinit time t = ', time.time() - t1))
t1 = time.time()
print('starting')
simadvance = self.simtime / 50.0
for i in range( 50 ):
moose.start( simadvance )
- print('at t = ', i * simadvance, 'realtime = ', time.time() - t1)
+ print(('at t = ', i * simadvance, 'realtime = ', time.time() - t1))
#moose.start(self.simtime)
- print('runtime for ', self.simtime, 'sec, is t = ', time.time() - t1)
+ print(('runtime for ', self.simtime, 'sec, is t = ', time.time() - t1))
if plotif:
self._plot()
diff --git a/moose-examples/paper-2015/Fig2_elecModels/Fig2A_analysis.py b/moose-examples/paper-2015/Fig2_elecModels/Fig2A_analysis.py
index 8caeccb58d2c43e0508a7c10c30f5b56dcd478cf..0514bca5e55e8ee42d0e74768df554be54685d53 100644
--- a/moose-examples/paper-2015/Fig2_elecModels/Fig2A_analysis.py
+++ b/moose-examples/paper-2015/Fig2_elecModels/Fig2A_analysis.py
@@ -13,7 +13,7 @@ fulltime = 1200 #s
plotdt = 1 #s
numpts = int(fulltime/plotdt)+1
-print 'reading'
+print('reading')
wts = []
while True:
next_line = ''
@@ -23,7 +23,7 @@ while True:
if next_line == '': break
next_wt = [float(fh.readline()) for i in range(numpts)]
wts.append(next_wt)
- print 'weight',len(wts)
+ print(('weight',len(wts)))
hiAve = np.zeros( len( wts[0] ) )
@@ -54,7 +54,7 @@ dumpVec( f, 'lowExample', wts[5] )
f.close()
-print 'numHi = ', numHi, ' plotting...'
+print(('numHi = ', numHi, ' plotting...'))
figure()
plot(transpose(wts))
plot( hiAve, linewidth=4 )
diff --git a/moose-examples/paper-2015/Fig2_elecModels/Fig2C.py b/moose-examples/paper-2015/Fig2_elecModels/Fig2C.py
index 5314c3ac7a3e801320e14ac7a4f0d17498b62478..396040263086c111f38aa07d2b00d2c0be382c14 100644
--- a/moose-examples/paper-2015/Fig2_elecModels/Fig2C.py
+++ b/moose-examples/paper-2015/Fig2_elecModels/Fig2C.py
@@ -182,10 +182,10 @@ def displayPlots():
pylab.figure(2, figsize= (8,10))
ax = pylab.subplot( 1,1,1 )
neuron = moose.element( '/model/elec' )
- comptDistance = dict( zip( neuron.compartments, neuron.pathDistanceFromSoma ) )
+ comptDistance = dict( list(zip( neuron.compartments, neuron.pathDistanceFromSoma )) )
for i in moose.wildcardFind( '/library/#[ISA=ChanBase]' ):
chans = moose.wildcardFind( '/model/elec/#/' + i.name )
- print i.name, len( chans )
+ print((i.name, len( chans )))
p = [ 1e6*comptDistance.get( j.parent, 0) for j in chans ]
Gbar = [ j.Gbar/(j.parent.length * j.parent.diameter * PI) for j in chans ]
if len( p ) > 2:
@@ -213,7 +213,7 @@ def create_vm_viewer(rdes):
0.0,
0.1)])
mapper = moogli.utilities.mapper(colormap, normalizer)
- vms = [moose.element(x).Vm for x in network.shapes.keys()]
+ vms = [moose.element(x).Vm for x in list(network.shapes.keys())]
network.set("color", vms, mapper)
def prelude(view):
@@ -222,7 +222,7 @@ def create_vm_viewer(rdes):
def interlude(view):
moose.start(frameRunTime)
- vms = [moose.element(x).Vm for x in network.shapes.keys()]
+ vms = [moose.element(x).Vm for x in list(network.shapes.keys())]
network.set("color", vms, mapper)
view.yaw(0.01)
currTime = moose.element('/clock').currentTime
@@ -235,7 +235,7 @@ def create_vm_viewer(rdes):
displayPlots()
viewer = moogli.Viewer("vm-viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
view = moogli.View("vm-view",
prelude=prelude,
interlude=interlude,
@@ -247,7 +247,7 @@ def create_vm_viewer(rdes):
def create_ca_viewer(rdes):
network = moogli.extensions.moose.read(rdes.elecid.path)
ca_elements = []
- for compartment_path in network.shapes.keys():
+ for compartment_path in list(network.shapes.keys()):
if moose.exists(compartment_path + '/Ca_conc'):
ca_elements.append(moose.element(compartment_path + '/Ca_conc'))
else:
@@ -286,7 +286,7 @@ def create_ca_viewer(rdes):
view.stop()
viewer = moogli.Viewer("ca-viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
view = moogli.View("ca-view",
prelude=prelude,
interlude=interlude)
@@ -294,7 +294,7 @@ def create_ca_viewer(rdes):
return viewer
def build3dDisplay(rdes):
- print "building 3d Display"
+ print("building 3d Display")
app = QtGui.QApplication(sys.argv)
vm_viewer = create_vm_viewer(rdes)
@@ -325,7 +325,7 @@ def deliverStim( currTime ):
step = int (currTime / frameRunTime )
probeStep = int( probeInterval / frameRunTime )
if step % probeStep == 0:
- print "Doing probe Stim at ", currTime
+ print(("Doing probe Stim at ", currTime))
for i in synSpineList:
i.activation( probeAmplitude )
@@ -341,7 +341,7 @@ def main():
temp = set( moose.wildcardFind( "/model/elec/#/glu,/model/elec/#/NMDA" ) )
synDendList = list( temp - set( synSpineList ) )
- print "num spine, dend syns = ", len( synSpineList ), len( synDendList )
+ print(("num spine, dend syns = ", len( synSpineList ), len( synDendList )))
moose.reinit()
#for i in moose.wildcardFind( '/model/elec/#apical#/#[ISA=CaConcBase]' ):
#print i.path, i.length, i.diameter, i.parent.length, i.parent.diameter
@@ -350,7 +350,7 @@ def main():
# Run for baseline, tetanus, and post-tetanic settling time
t1 = time.time()
build3dDisplay(rdes)
- print 'real time = ', time.time() - t1
+ print(('real time = ', time.time() - t1))
if __name__ == '__main__':
main()
diff --git a/moose-examples/paper-2015/Fig2_elecModels/Fig2D.py b/moose-examples/paper-2015/Fig2_elecModels/Fig2D.py
index ef8a05eb360abf0d054d9e1733b54b8e9abc919e..94ffcd83e8fd5bf6d0922e8d33da418b25ae047b 100644
--- a/moose-examples/paper-2015/Fig2_elecModels/Fig2D.py
+++ b/moose-examples/paper-2015/Fig2_elecModels/Fig2D.py
@@ -49,7 +49,7 @@ def create_vm_viewer(rdes):
0.0,
0.9)])
mapper = moogli.utilities.mapper(colormap, normalizer)
- vms = [moose.element(x).Vm for x in network.shapes.keys()]
+ vms = [moose.element(x).Vm for x in list(network.shapes.keys())]
network.set("color", vms, mapper)
def interlude(view):
@@ -62,7 +62,7 @@ def create_vm_viewer(rdes):
view.stop()
viewer = moogli.Viewer("vm-viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
view = moogli.View("vm-view",
interlude=interlude)
viewer.attach_view(view)
@@ -93,7 +93,7 @@ def main():
compts[0].inject = inject
################## Now we set up the display ########################
- print "Setting Up 3D Display"
+ print("Setting Up 3D Display")
app = QtGui.QApplication(sys.argv)
vm_viewer = create_vm_viewer(rdes)
vm_viewer.showMaximized()
diff --git a/moose-examples/paper-2015/Fig2_elecModels/Fig2E.py b/moose-examples/paper-2015/Fig2_elecModels/Fig2E.py
index 1a02727ad02c284a9be0e8b25cd6a4052835f5e2..08d64060a50e9e9db9f0fd75be805b5bfed14308 100644
--- a/moose-examples/paper-2015/Fig2_elecModels/Fig2E.py
+++ b/moose-examples/paper-2015/Fig2_elecModels/Fig2E.py
@@ -59,7 +59,7 @@ def create_vm_viewer(rdes, somaVm):
0.9)])
mapper = moogli.utilities.mapper(colormap, normalizer)
- vms = [moose.element(x).Vm for x in network.shapes.keys()]
+ vms = [moose.element(x).Vm for x in list(network.shapes.keys())]
network.set("color", vms, mapper)
def prelude(view):
@@ -67,7 +67,7 @@ def create_vm_viewer(rdes, somaVm):
def interlude(view):
moose.start(frameRunTime)
- vms = [moose.element(x).Vm for x in network.shapes.keys()]
+ vms = [moose.element(x).Vm for x in list(network.shapes.keys())]
network.set("color", vms, mapper)
view.yaw(0.01)
currTime = moose.element('/clock').currentTime
@@ -84,7 +84,7 @@ def create_vm_viewer(rdes, somaVm):
pylab.show()
viewer = moogli.Viewer("vm-viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
view = moogli.View("vm-view",
prelude=prelude,
interlude=interlude,
@@ -114,7 +114,7 @@ def main():
compts = moose.wildcardFind( "/model/elec/#[ISA=CompartmentBase]" )
compts[0].inject = inject
- print "Setting Up 3D Display"
+ print("Setting Up 3D Display")
app = QtGui.QApplication(sys.argv)
vm_viewer = create_vm_viewer(rdes, somaVm)
vm_viewer.show()
diff --git a/moose-examples/paper-2015/Fig3_chemModels/Fig3D.py b/moose-examples/paper-2015/Fig3_chemModels/Fig3D.py
index b2117f22bcb0661fa88a369670b177f0be9f395d..8cd2be9a5be09a84886e120995f474d53934dacd 100644
--- a/moose-examples/paper-2015/Fig3_chemModels/Fig3D.py
+++ b/moose-examples/paper-2015/Fig3_chemModels/Fig3D.py
@@ -59,7 +59,7 @@ t1 = time.time()
for t in range( 0, runtime-1, updateDt ):
moose.start( updateDt )
plt = pylab.plot( x, c.vec.n, label='t = '+str(t + updateDt) )
-print "Time = ", time.time() - t1
+print(("Time = ", time.time() - t1))
pylab.ylim( 0, 1.05 )
pylab.legend()
diff --git a/moose-examples/paper-2015/Fig3_chemModels/Fig3_NEURON.py b/moose-examples/paper-2015/Fig3_chemModels/Fig3_NEURON.py
index ea4330c41b72538109803273637dc740f8673c53..66d03f7a655b824a1b77273d5c2646d986a34e15 100644
--- a/moose-examples/paper-2015/Fig3_chemModels/Fig3_NEURON.py
+++ b/moose-examples/paper-2015/Fig3_chemModels/Fig3_NEURON.py
@@ -36,9 +36,9 @@ plot_it('r')
interval = 50
t1 = time.time()
-for i in xrange(1, 5):
+for i in range(1, 5):
h.continuerun(i * interval)
plot_it()
-print "Time = ", time.time() - t1
+print(("Time = ", time.time() - t1))
pyplot.show()
diff --git a/moose-examples/paper-2015/Fig4_ReacDiff/Fig4B.py b/moose-examples/paper-2015/Fig4_ReacDiff/Fig4B.py
index fd3029f1af86fe8976d87650d10fe3537a3767f4..cc19cba3777cb0bc3577bb0460b01dd5e9a363cd 100644
--- a/moose-examples/paper-2015/Fig4_ReacDiff/Fig4B.py
+++ b/moose-examples/paper-2015/Fig4_ReacDiff/Fig4B.py
@@ -130,7 +130,7 @@ def createVmViewer(rdes):
mapper = moogli.utilities.mapper(colormap, normalizer)
def prelude(view):
- vms = [moose.element(x).Vm for x in network.shapes.keys()]
+ vms = [moose.element(x).Vm for x in list(network.shapes.keys())]
network.set("color", vms, mapper)
view.pitch(PI/2.0)
view.down(450)
@@ -145,7 +145,7 @@ def createVmViewer(rdes):
view.yaw(0.01)
viewer = moogli.Viewer("vm-viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
view = moogli.View("vm-view",
prelude=prelude,
interlude=interlude)
@@ -167,7 +167,7 @@ def main():
if do3D:
app = QtGui.QApplication(sys.argv)
compts = moose.wildcardFind( "/model/elec/#[ISA=CompartmentBase]" )
- print "LEN = ", len( compts )
+ print(("LEN = ", len( compts )))
for i in compts:
n = i.name[:4]
if ( n == 'head' or n == 'shaf' ):
diff --git a/moose-examples/paper-2015/Fig4_ReacDiff/Fig4CDEF.py b/moose-examples/paper-2015/Fig4_ReacDiff/Fig4CDEF.py
index 5d769096ecd263e67ea27394fb7713ecbeb4e79e..5b9a1ddf493908d65556574bc95fb36c8b4cb8ed 100644
--- a/moose-examples/paper-2015/Fig4_ReacDiff/Fig4CDEF.py
+++ b/moose-examples/paper-2015/Fig4_ReacDiff/Fig4CDEF.py
@@ -175,7 +175,7 @@ def displayPlots():
for k in i[0].vec:
plt.plot( timePts, k.vector * i[4] )
#plt.title( i.name )
- print i[0].name
+ print((i[0].name))
plt.xlabel( 'Time (s)', fontsize = 16 )
plt.show()
@@ -194,7 +194,7 @@ def main():
moose.reinit()
buildPlots()
# Run for baseline, tetanus, and post-tetanic settling time
- print 'starting...'
+ print('starting...')
t1 = time.time()
moose.start( baselineTime )
caPsd = moose.vec( '/model/chem/psd/Ca_input' )
@@ -218,12 +218,12 @@ def main():
caPsd.concInit = basalCa
caDend.concInit = basalCa
moose.start( postLtdTime )
- print 'real time = ', time.time() - t1
+ print(('real time = ', time.time() - t1))
if do3D:
app = QtGui.QApplication(sys.argv)
compts = moose.wildcardFind( "/model/elec/#[ISA=compartmentBase]" )
- ecomptPath = map( lambda x : x.path, compts )
+ ecomptPath = [x.path for x in compts]
morphology = moogli.read_morphology_from_moose(name = "", path = "/model/elec")
morphology.create_group( "group_all", ecomptPath, -0.08, 0.02, \
[0.0, 0.5, 1.0, 1.0], [1.0, 0.0, 0.0, 0.9] )
diff --git a/moose-examples/paper-2015/Fig4_ReacDiff/Fig4GHIJ.py b/moose-examples/paper-2015/Fig4_ReacDiff/Fig4GHIJ.py
index 997dfd916d583d487ed22f4efc2dd8ed4ee10a97..aec72b1f453867edd681478645a8e0e1ec654de0 100644
--- a/moose-examples/paper-2015/Fig4_ReacDiff/Fig4GHIJ.py
+++ b/moose-examples/paper-2015/Fig4_ReacDiff/Fig4GHIJ.py
@@ -175,7 +175,7 @@ def displayPlots():
for k in i[0].vec:
plt.plot( timePts, k.vector * i[4] )
#plt.title( i.name )
- print i[0].name
+ print((i[0].name))
plt.xlabel( 'Time (s)', fontsize = 16 )
plt.show()
@@ -194,7 +194,7 @@ def main():
moose.reinit()
buildPlots()
# Run for baseline, tetanus, and post-tetanic settling time
- print 'starting...'
+ print('starting...')
t1 = time.time()
moose.start( baselineTime )
caPsd = moose.vec( '/model/chem/psd/Ca_input' )
@@ -218,12 +218,12 @@ def main():
caPsd.concInit = basalCa
caDend.concInit = basalCa
moose.start( postLtdTime )
- print 'real time = ', time.time() - t1
+ print(('real time = ', time.time() - t1))
if do3D:
app = QtGui.QApplication(sys.argv)
compts = moose.wildcardFind( "/model/elec/#[ISA=compartmentBase]" )
- ecomptPath = map( lambda x : x.path, compts )
+ ecomptPath = [x.path for x in compts]
morphology = moogli.read_morphology_from_moose(name = "", path = "/model/elec")
morphology.create_group( "group_all", ecomptPath, -0.08, 0.02, \
[0.0, 0.5, 1.0, 1.0], [1.0, 0.0, 0.0, 0.9] )
diff --git a/moose-examples/paper-2015/Fig4_ReacDiff/rxdSpineSize.py b/moose-examples/paper-2015/Fig4_ReacDiff/rxdSpineSize.py
index 1d071aba3aceba2f52303e4404d90aea61aaf852..544adc56cca8b4a302b2457358323c1e384fac28 100644
--- a/moose-examples/paper-2015/Fig4_ReacDiff/rxdSpineSize.py
+++ b/moose-examples/paper-2015/Fig4_ReacDiff/rxdSpineSize.py
@@ -54,7 +54,7 @@ def makeChemProto( name ):
chem = moose.Neutral( '/library/' + name )
comptVol = diffLen * dendDia * dendDia * PI / 4.0
for i in ( ['dend', comptVol], ['spine', 1e-19], ['psd', 1e-20] ):
- print 'making ', i
+ print(('making ', i))
compt = moose.CubeMesh( chem.path + '/' + i[0] )
compt.volume = i[1]
#x = moose.Pool( compt.path + '/x' )
@@ -72,7 +72,7 @@ def makeChemProto( name ):
x.diffConst = diffConst
func = moose.Function( x.path + '/func' )
func.expr = "-x0 * (0.3 - " + nstr + " * x0) * ( 1 - " + nstr + " * x0)"
- print func.expr
+ print((func.expr))
func.x.num = 1
moose.connect( x, 'nOut', func.x[0], 'input' )
moose.connect( func, 'valueOut', x, 'increment' )
@@ -264,9 +264,9 @@ def create_viewer(path, moose_dendrite, dendZ, diaTab, psdZ):
view.stop()
viewer = moogli.Viewer("Viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
viewer.detach_shape(dendrite)
- viewer.attach_shapes(chem_compt_group.shapes.values())
+ viewer.attach_shapes(list(chem_compt_group.shapes.values()))
view = moogli.View("main-view",
prelude=prelude,
diff --git a/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5A.py b/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5A.py
index 330516ea1a36b29b354d416343f32f966f73f5a0..0aa1e00b24fc41a4a5104104245d2eb56544e639 100644
--- a/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5A.py
+++ b/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5A.py
@@ -109,7 +109,7 @@ def interlude( view ):
view.yaw( 0.01 )
def create_viewer(rdes):
- print ' doing viewer for ', rdes.soma.path
+ print((' doing viewer for ', rdes.soma.path))
network = moogli.extensions.moose.read(rdes.elecid.path)
normalizer = moogli.utilities.normalizer(-0.08,
0.02,
@@ -125,10 +125,10 @@ def create_viewer(rdes):
0.9)])
mapper = moogli.utilities.mapper(colormap, normalizer)
- vms = [moose.element(x).Vm for x in network.shapes.keys()]
+ vms = [moose.element(x).Vm for x in list(network.shapes.keys())]
network.set("color", vms, mapper)
viewer = moogli.Viewer("vm-viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
view = moogli.View("vm-view", interlude=interlude )
viewer.attach_view(view)
viewer.show()
@@ -143,7 +143,7 @@ def main():
viewers = []
j = 0
for i in elecFileNames:
- print i
+ print(i)
ename = '/model' + str(j)
rdes.cellProtoList = [ ['./cells/' + i, 'elec' ] ]
rdes.buildModel( ename )
diff --git a/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5BCD.py b/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5BCD.py
index 78595b4d1e0186cc5c0721a721ccf25bd9b5a976..7e3889cd860876bb58c7e0ad0840e225013dc1cb 100644
--- a/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5BCD.py
+++ b/moose-examples/paper-2015/Fig5_CellMultiscale/Fig5BCD.py
@@ -197,7 +197,7 @@ def buildPlots( rdes ):
moose.connect( eSpineGkTab, 'requestOut', path, 'getGk' )
def saveAndClearPlots( name ):
- print 'saveAndClearPlots( ', name, ' )'
+ print(('saveAndClearPlots( ', name, ' )'))
for i in moose.wildcardFind( "/graphs/#" ):
#plot stuff
i.xplot( name + '.xplot', i.name )
@@ -208,8 +208,8 @@ def printPsd( name ):
psdR = moose.vec( '/model/chem/psd/tot_PSD_R' )
neuronVoxel = moose.element( '/model/chem/spine' ).neuronVoxel
elecComptMap = moose.element( '/model/chem/dend' ).elecComptMap
- print "len( neuronVoxel = ", len( neuronVoxel), min( neuronVoxel), max( neuronVoxel)
- print len( elecComptMap), elecComptMap[0], elecComptMap[12]
+ print(("len( neuronVoxel = ", len( neuronVoxel), min( neuronVoxel), max( neuronVoxel)))
+ print((len( elecComptMap), elecComptMap[0], elecComptMap[12]))
neuron = moose.element( '/model/elec' )
ncompts = neuron.compartments
d = {}
@@ -255,7 +255,7 @@ def main():
numpy.random.seed( 1234 )
rdes = buildRdesigneur()
for i in elecFileNames:
- print i
+ print(i)
rdes.cellProtoList = [ ['./cells/' + i, 'elec'] ]
rdes.buildModel( '/model' )
assert( moose.exists( '/model' ) )
@@ -270,7 +270,7 @@ def main():
probeStimulus( baselineTime )
tetanicStimulus( tetTime )
probeStimulus( postTetTime )
- print 'real time = ', time.time() - t1
+ print(('real time = ', time.time() - t1))
printPsd( i + ".fig5" )
saveAndClearPlots( i + ".fig5" )
diff --git a/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6A.py b/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6A.py
index 88193dbc4a88bf2cdc85d91aa8225e030d0eed09..489b1b7655abd2833e1f28984e98975f29168f3b 100644
--- a/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6A.py
+++ b/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6A.py
@@ -319,7 +319,7 @@ class ExcInhNetBase:
numVms = 10
self.plots = moose.Table( '/plotVms', numVms )
## draw numVms out of N neurons
- nrnIdxs = random.sample(range(self.N),numVms)
+ nrnIdxs = random.sample(list(range(self.N)),numVms)
for i in range( numVms ):
moose.connect( self.network.vec[nrnIdxs[i]], 'VmOut', \
self.plots.vec[i], 'input')
@@ -444,7 +444,7 @@ def create_viewer(rdes):
# dendrite.set_colors(moogli.core.Vec4f(173 / 255.0, 216 / 255.0, 230 / 255.0, 1.0))
[shape.set_radius(shape.get_apex_radius() * 4.0) for shape in
- network.groups["spine"].groups["head"].shapes.values()]
+ list(network.groups["spine"].groups["head"].shapes.values())]
# print "Creating LIFS"
soma = network.shapes[rdes.soma.path]
@@ -474,8 +474,8 @@ def create_viewer(rdes):
# print "Creating Viewer"
viewer = moogli.Viewer("viewer") # prelude = prelude, interlude = interlude)
# print "Created Viewer"
- viewer.attach_shapes(network.shapes.values())
- viewer.attach_shapes(lifs.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
+ viewer.attach_shapes(list(lifs.shapes.values()))
# print "Attached Shapes"
view = moogli.View("view", interlude=interlude)
viewer.attach_view(view)
@@ -492,7 +492,7 @@ if __name__=='__main__':
## Instantiate either ExcInhNetBase or ExcInhNet below
#net = ExcInhNetBase(N=N)
net = ExcInhNet(N=N)
- print net
+ print(net)
moose.le( '/' )
moose.le( '/network' )
rdes = buildRdesigneur()
diff --git a/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6BCDE.py b/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6BCDE.py
index 82a9ece3a68a9665c0615a17480a06df9ce8a35b..9a5fb80661ca0b395fd985f6cf31381ef1f1d7f2 100644
--- a/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6BCDE.py
+++ b/moose-examples/paper-2015/Fig6_NetMultiscale/Fig6BCDE.py
@@ -1,5 +1,3 @@
-from __future__ import print_function
-
#/**********************************************************************
#** This program is part of 'MOOSE', the
#** Messaging Object Oriented Simulation Environment.
@@ -12,6 +10,7 @@ from __future__ import print_function
'''
This LIF network with Ca plasticity is based on:
David Higgins, Michael Graupner, Nicolas Brunel
+
Memory Maintenance in Synapses with Calcium-Based
Plasticity in the Presence of Background Activity
PLOS Computational Biology, 2014.
@@ -22,8 +21,11 @@ This variant has 2500 LIF neurons
Upi Bhalla, Nov 2014: Appended single neuron model.
This script generates the panels in Figure 6. It takes a long time,
about 65 minutes to run 30 seconds of simulation time.
+
'''
+from __future__ import print_function
+
## import modules and functions to be used
import numpy as np
import matplotlib.pyplot as plt
@@ -936,4 +938,4 @@ if __name__=='__main__':
plt.show()
plt.savefig( fname + '.svg', bbox_inches='tight')
print( "Hit 'enter' to exit" )
- input()
+ eval(input())
diff --git a/moose-examples/paper-2015/Fig6_NetMultiscale/ReducedModel.py b/moose-examples/paper-2015/Fig6_NetMultiscale/ReducedModel.py
index 75c51617477a0ec208570ec5ff5251bc7b4d4bba..3f151cb3f6c5e8fad454c98c956cb1b6ed003a9e 100644
--- a/moose-examples/paper-2015/Fig6_NetMultiscale/ReducedModel.py
+++ b/moose-examples/paper-2015/Fig6_NetMultiscale/ReducedModel.py
@@ -1,4 +1,3 @@
-
#/**********************************************************************
#** This program is part of 'MOOSE', the
#** Messaging Object Oriented Simulation Environment.
@@ -8,6 +7,8 @@
#** See the file COPYING.LIB for the full notice.
#**********************************************************************/
+from __future__ import print_function
+
'''
This LIF network with Ca plasticity is based on:
David Higgins, Michael Graupner, Nicolas Brunel
@@ -314,7 +315,7 @@ def connectDetailedNeuron():
x.vec.weight = nprand.rand( exc.numEntries ) * excWeightMax
#x.parent.tick = 4
x.parent.parent.tick = 4
- print '+',
+ print('+', end=' ')
totGluWt += sum(x.vec.weight) * x.parent.parent.Gbar
seed = excSeed
@@ -330,7 +331,7 @@ def connectDetailedNeuron():
x.vec.weight = nprand.rand( exc.numEntries ) * nmdaWeightMax
#x.parent.tick = 4
x.parent.parent.tick = 4
- print '*',
+ print('*', end=' ')
totNMDAWt += sum(x.vec.weight) * x.parent.parent.Gbar
seed = inhSeed
@@ -345,11 +346,11 @@ def connectDetailedNeuron():
x.vec.weight = nprand.rand( inh.numEntries ) * inhWeightMax
#x.parent.tick = 4
x.parent.parent.tick = 4
- print '-',
+ print('-', end=' ')
totGABAWt += sum(x.vec.weight) * x.parent.parent.Gbar
- print 'connectDetailedNeuron: numExc = ', numExc, ', numNMDA=', numNMDA, ', numInh = ', numInh
- print 'connectDetailedNeuron: totWts Glu = ', totGluWt, ', NMDA = ', totNMDAWt, ', GABA = ', totGABAWt
+ print('connectDetailedNeuron: numExc = ', numExc, ', numNMDA=', numNMDA, ', numInh = ', numInh)
+ print('connectDetailedNeuron: totWts Glu = ', totGluWt, ', NMDA = ', totNMDAWt, ', GABA = ', totGABAWt)
#############################################
# Exc-Inh network base class without connections
@@ -452,7 +453,7 @@ class ExcInhNetBase:
numVms = 10
self.plots = moose.Table( '/plotVms', numVms )
## draw numVms out of N neurons
- nrnIdxs = random.sample(range(self.N),numVms)
+ nrnIdxs = random.sample(list(range(self.N)),numVms)
for i in range( numVms ):
moose.connect( self.network.vec[nrnIdxs[i]], 'VmOut', \
self.plots.vec[i], 'input')
@@ -577,7 +578,7 @@ class ExcInhNet(ExcInhNetBase):
## Connections from some Exc neurons to each Exc neuron
## draw excC number of neuron indices out of NmaxExc neurons
- preIdxs = random.sample(range(self.NmaxExc),self.excC)
+ preIdxs = random.sample(list(range(self.NmaxExc)),self.excC)
## connect these presynaptically to i-th post-synaptic neuron
for synnum,preIdx in enumerate(preIdxs):
synidx = i*self.excC+synnum
@@ -630,7 +631,7 @@ class ExcInhNet(ExcInhNetBase):
## Connections from some Inh neurons to each Exc neuron
## draw inhC=incC-excC number of neuron indices out of inhibitory neurons
- preIdxs = random.sample(range(self.NmaxExc,self.N),self.incC-self.excC)
+ preIdxs = random.sample(list(range(self.NmaxExc,self.N)),self.incC-self.excC)
## connect these presynaptically to i-th post-synaptic neuron
for synnum,preIdx in enumerate(preIdxs):
synij = self.synsIE.vec[i].synapse[synnum]
@@ -645,7 +646,7 @@ class ExcInhNet(ExcInhNetBase):
self.synsI.vec[i].numSynapses = self.incC
## draw excC number of neuron indices out of NmaxExc neurons
- preIdxs = random.sample(range(self.NmaxExc),self.excC)
+ preIdxs = random.sample(list(range(self.NmaxExc)),self.excC)
## connect these presynaptically to i-th post-synaptic neuron
for synnum,preIdx in enumerate(preIdxs):
synij = self.synsI.vec[i].synapse[synnum]
@@ -655,7 +656,7 @@ class ExcInhNet(ExcInhNetBase):
synij.weight = self.J # activation = weight
## draw inhC=incC-excC number of neuron indices out of inhibitory neurons
- preIdxs = random.sample(range(self.NmaxExc,self.N),self.incC-self.excC)
+ preIdxs = random.sample(list(range(self.NmaxExc,self.N)),self.incC-self.excC)
## connect these presynaptically to i-th post-synaptic neuron
for synnum,preIdx in enumerate(preIdxs):
synij = self.synsI.vec[i].synapse[ self.excC + synnum ]
@@ -829,7 +830,7 @@ if __name__=='__main__':
## Instantiate either ExcInhNetBase or ExcInhNet below
#net = ExcInhNetBase(N=N)
net = ExcInhNet(N=N)
- print net
+ print(net)
moose.le( '/' )
moose.le( '/network' )
rdes = buildRdesigneur()
@@ -865,7 +866,7 @@ if __name__=='__main__':
moose.reinit()
t1 = time.time()
- print 'starting'
+ print('starting')
for currTime in np.arange( 0, simtime, updateDt ):
moose.start(updateDt)
lastt = net.network.vec.lastEventTime
@@ -874,7 +875,7 @@ if __name__=='__main__':
ret.set_array( lastt )
fig2.canvas.draw()
- print 'runtime, t = ', time.time() - t1
+ print('runtime, t = ', time.time() - t1)
if plotif:
net._plot( fig )
@@ -884,4 +885,4 @@ if __name__=='__main__':
plt.show()
plt.savefig( fname + '.svg', bbox_inches='tight')
print( "Hit 'enter' to exit" )
- raw_input()
+ input()
diff --git a/moose-examples/paper-2015/rxdSpineSize.py b/moose-examples/paper-2015/rxdSpineSize.py
index c6fb82808c8bdf9fb3390f0b4a77ebe49d5cded7..77a9fec80c87a5998d69d09a9682055f3957d75f 100644
--- a/moose-examples/paper-2015/rxdSpineSize.py
+++ b/moose-examples/paper-2015/rxdSpineSize.py
@@ -54,7 +54,7 @@ def makeChemProto( name ):
chem = moose.Neutral( '/library/' + name )
comptVol = diffLen * dendDia * dendDia * PI / 4.0
for i in ( ['dend', comptVol], ['spine', 1e-19], ['psd', 1e-20] ):
- print 'making ', i
+ print(('making ', i))
compt = moose.CubeMesh( chem.path + '/' + i[0] )
compt.volume = i[1]
#x = moose.Pool( compt.path + '/x' )
@@ -72,7 +72,7 @@ def makeChemProto( name ):
x.diffConst = diffConst
func = moose.Function( x.path + '/func' )
func.expr = "-x0 * (0.3 - " + nstr + " * x0) * ( 1 - " + nstr + " * x0)"
- print func.expr
+ print((func.expr))
func.x.num = 1
moose.connect( x, 'nOut', func.x[0], 'input' )
moose.connect( func, 'valueOut', x, 'increment' )
@@ -264,9 +264,9 @@ def create_viewer(path, moose_dendrite, dendZ, diaTab, psdZ):
view.stop()
viewer = moogli.Viewer("Viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
viewer.detach_shape(dendrite)
- viewer.attach_shapes(chem_compt_group.shapes.values())
+ viewer.attach_shapes(list(chem_compt_group.shapes.values()))
view = moogli.View("main-view",
prelude=prelude,
diff --git a/moose-examples/parallelSolver/Fig2_v4.py b/moose-examples/parallelSolver/Fig2_v4.py
index 87888ade01d5bd32d0bf8e46279ac3501486e6b8..52535a3bcb8334c50190c63f8c2bbede77886ee8 100644
--- a/moose-examples/parallelSolver/Fig2_v4.py
+++ b/moose-examples/parallelSolver/Fig2_v4.py
@@ -1,229 +1,229 @@
-# Generates time-series response to a Ca pulse for each of the models. No
-# diffusion involved.
-
-import sys
-import numpy as np
-import pylab
-import matplotlib.pyplot as plt
-import moose
-import abstrModelEqns2
-import rdesigneur as rd
-import time
-
-
-def singleCompt( name, params ):
- mod = moose.copy( '/library/' + name + '/' + name, '/model' )
- A = moose.element( mod.path + '/A' )
- Z = moose.element( mod.path + '/Z' )
- Z.nInit = 1
- Ca = moose.element( mod.path + '/Ca' )
- CaStim = moose.element( Ca.path + '/CaStim' )
- runtime = params['preStimTime'] + params['stimWidth'] + params['postStimTime']
- steptime = 100
-
- CaStim.expr += ' + x2 * (t > ' + str( runtime ) + ' ) * ( t < ' + str( runtime + steptime ) + ' )'
- print CaStim.expr
- tab = moose.Table2( '/model/' + name + '/Atab' )
- #for i in range( 10, 19 ):
- #moose.setClock( i, 0.01 )
- ampl = moose.element( mod.path + '/ampl' )
- phase = moose.element( mod.path + '/phase' )
- moose.connect( tab, 'requestOut', A, 'getN' )
- ampl.nInit = params['stimAmplitude'] * 1
- phase.nInit = params['preStimTime']
-
- ksolve = moose.Ksolve( mod.path + '/ksolve' )
- stoich = moose.Stoich( mod.path + '/stoich' )
- stoich.compartment = mod
- stoich.ksolve = ksolve
- stoich.path = mod.path + '/##'
- runtime += 2 * steptime
-
- moose.reinit()
- moose.start( runtime )
- t = np.arange( 0, runtime + 1e-9, tab.dt )
- return name, t, tab.vector
- #pylab.plot( t, tab.vector, label='[A] (mM)' )
-
- #pylab.show()
-
-def plotBoilerplate( panelTitle, plotPos, xlabel = ''):
- ax = plt.subplot( 8,4,plotPos )
- #ax.xaxis.set_ticks( i[1] )
- #ax.locator_params(
- ax.spines['top'].set_visible( False )
- ax.spines['right'].set_visible( False )
- ax.tick_params( direction = 'out' )
- if (((plotPos -1)/4) % 2) == 0:
- ax.set_xticklabels([])
- else:
- ax.set_xlabel( xlabel )
- for tick in ax.xaxis.get_major_ticks():
- tick.tick2On = False
- for tick in ax.yaxis.get_major_ticks():
- tick.tick2On = False
-
- if (plotPos % 4) == 1:
- plt.ylabel( 'conc', fontsize = 16 )
- # alternate way of doing this separately.
- #plt.yaxis.label.size_size(16)
- #plt.title( 'B' )
- ax.text( -0.3, 1, panelTitle, fontsize = 18, weight = 'bold',
- transform=ax.transAxes )
- return ax
-
-def plotPanelB():
- panelB = []
- panelBticks = []
- panelB.append( singleCompt( 'fhn', abstrModelEqns2.makeFHN() ) )
- panelB.append( singleCompt( 'bis', abstrModelEqns2.makeBis() ) )
- panelB.append( singleCompt( 'negFB', abstrModelEqns2.makeNegFB() ) )
- panelB.append( singleCompt( 'negFF', abstrModelEqns2.makeNegFF() ) )
-
- panelBticks.append( np.arange( 0, 4.00001, 1 ) )
- panelBticks.append( np.arange( 0, 4.00001, 1 ) )
- panelBticks.append( np.arange( 0, 15.00001, 5 ) )
- panelBticks.append( np.arange( 0, 6.00001, 2 ) )
- moose.delete( '/model' )
-
- for i in zip( panelB, panelBticks, range( len( panelB ) ) ):
- plotPos = i[2] + 5
- ax = plotBoilerplate( 'B', plotPos )
- plt.plot( i[0][1], i[0][2] )
- xmax = ax.get_xlim()[1]
- #ax.xaxis.set_ticks( np.arange( 0, xmax, 50 ) )
- ax.xaxis.set_ticks( np.arange( 0, 200.001, 50 ) )
- ax.yaxis.set_ticks( i[1] )
-
-def runPanelCDEF( name, dist, seqDt, numSpine, seq, stimAmpl ):
- preStim = 10.0
- blanks = 20
- rdes = rd.rdesigneur(
- useGssa = False,
- turnOffElec = True,
- chemPlotDt = 0.1,
- #diffusionLength = params['diffusionLength'],
- diffusionLength = 1e-6,
- cellProto = [['cell', 'soma']],
- chemProto = [['dend', name]],
- chemDistrib = [['dend', 'soma', 'install', '1' ]],
- plotList = [['soma', '1', 'dend' + '/A', 'n', '# of A']],
- )
- rdes.buildModel()
- #for i in range( 20 ):
- #moose.setClock( i, 0.02 )
- A = moose.vec( '/model/chem/dend/A' )
- Z = moose.vec( '/model/chem/dend/Z' )
- print moose.element( '/model/chem/dend/A/Adot' ).expr
- print moose.element( '/model/chem/dend/B/Bdot' ).expr
- print moose.element( '/model/chem/dend/Ca/CaStim' ).expr
- phase = moose.vec( '/model/chem/dend/phase' )
- ampl = moose.vec( '/model/chem/dend/ampl' )
- vel = moose.vec( '/model/chem/dend/vel' )
- vel.nInit = 1e-6 * seqDt
- ampl.nInit = stimAmpl
- stride = int( dist ) / numSpine
- phase.nInit = 10000
- Z.nInit = 0
- for j in range( numSpine ):
- k = blanks + j * stride
- Z[k].nInit = 1
- phase[k].nInit = preStim + seq[j] * seqDt
- moose.reinit()
- runtime = 50
- snapshot = preStim + seqDt * (numSpine - 0.8)
- print snapshot
- #snapshot = 26
- moose.start( snapshot )
- avec = moose.vec( '/model/chem/dend/A' ).n
- moose.start( runtime - snapshot )
- tvec = []
- for i in range( 5 ):
- tab = moose.element( '/model/graphs/plot0[' + str( blanks + i * stride ) + ']' )
- dt = tab.dt
- tvec.append( tab.vector )
- moose.delete( '/model' )
- return dt, tvec, avec
-
-def makePassiveSoma( name, length, diameter ):
- elecid = moose.Neuron( '/library/' + name )
- dend = moose.Compartment( elecid.path + '/soma' )
- dend.diameter = diameter
- dend.length = length
- dend.x = length
- return elecid
-
-def plotOnePanel( tLabel, dt, tplot, numSyn, plotRange, tick ):
- t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
- ax = plotBoilerplate( tLabel, 1 + start )
- for i in range( 5 ):
- plt.plot( t, tplot[i] )
- ax.yaxis.set_ticks( np.arange( 0, plotRange, tick ) )
-
-
-def plotPanelCDEF( seq, row ):
- makePassiveSoma( 'cell', 100e-6, 10e-6 )
- start = (row -1) * 4
- tLabel = chr( ord( 'A' ) + row - 1 )
- xLabel = chr( ord( 'C' ) + row - 1 )
- xplot = []
- #dt, tplot, avec = runPanelCDEF( 'fhn', 15.0, 3.0, 5, seq, 0.4 )
- dt, tplot, avec = runPanelCDEF( 'fhn', 5.0, 0.5, 5, seq, 0.4 )
- xplot.append( avec )
- #plotOnePanel( dt, 'B', tplot, 5, 1.5, 0.5 )
- t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
- #ax = plotBoilerplate( tLabel, 1 + start )
- ax = plotBoilerplate( tLabel, 1 + start, 'Time (s)')
- for i in range( 5 ):
- plt.plot( t, tplot[i] )
- yl = ax.get_ylim()[1]
- ax.yaxis.set_ticks( np.arange( 0, 4.0001, 1.0 ) )
-
- #dt, tplot, avec = runPanelCDEF( 'bis', 5.0, 4.0, 5, seq, 1.0 )
- dt, tplot, avec = runPanelCDEF( 'bis', 15.0, 2.0, 5, seq, 1.0 )
- xplot.append( avec )
- t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
- ax = plotBoilerplate( tLabel, 2 + start, 'Time (s)' )
- for i in range( 5 ):
- plt.plot( t, tplot[i] )
- yl = ax.get_ylim()[1]
- ax.yaxis.set_ticks( np.arange( 0, 3.0001, 1.0 ) )
-
- dt, tplot, avec = runPanelCDEF( 'negFB', 5.0, 2.0, 5, seq, 1.0 )
- xplot.append( avec )
- t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
- ax = plotBoilerplate( tLabel, 3 + start, 'Time (s)')
- for i in range( 5 ):
- plt.plot( t, tplot[i] )
- ax.yaxis.set_ticks( np.arange( 0, 10.00001, 5.0 ) )
-
- dt, tplot, avec = runPanelCDEF( 'negFF', 5.0, 4.0, 5, seq, 1.0 )
- xplot.append( avec )
- t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
- ax = plotBoilerplate( tLabel, 4 + start, 'Time (s)')
- for i in range( 5 ):
- plt.plot( t, tplot[i] )
- ax.yaxis.set_ticks( np.arange( 0, 5.00001, 2.0 ) )
-
- for i in zip( range(4), (4.0, 3.0, 10, 4 ), (1, 1, 5, 2) ):
- ax = plotBoilerplate( xLabel, 9 + start + i[0], 'Position( um)' )
- plt.plot( xplot[i[0]][:50] )
- ax.yaxis.set_ticks( np.arange( 0, i[1] * 1.0000001, i[2] ) )
-
-##################################################################
-if __name__ == '__main__':
- moose.Neutral( '/library' )
- moose.Neutral( '/model' )
-
- t1 = time.time()
- fig = plt.figure( figsize = (10,10), facecolor='white' )
- fig.subplots_adjust( left = 0.18 )
- plotPanelB()
- plotPanelCDEF( [0,1,2,3,4], 3 )
- plotPanelCDEF( [4,1,0,3,2], 4 )
- print ("Time taken = ", time.time() - t1)
- plt.tight_layout()
-
- plt.show()
-
-
+# Generates time-series response to a Ca pulse for each of the models. No
+# diffusion involved.
+
+import sys
+import numpy as np
+import pylab
+import matplotlib.pyplot as plt
+import moose
+import abstrModelEqns2
+import rdesigneur as rd
+import time
+
+
+def singleCompt( name, params ):
+ mod = moose.copy( '/library/' + name + '/' + name, '/model' )
+ A = moose.element( mod.path + '/A' )
+ Z = moose.element( mod.path + '/Z' )
+ Z.nInit = 1
+ Ca = moose.element( mod.path + '/Ca' )
+ CaStim = moose.element( Ca.path + '/CaStim' )
+ runtime = params['preStimTime'] + params['stimWidth'] + params['postStimTime']
+ steptime = 100
+
+ CaStim.expr += ' + x2 * (t > ' + str( runtime ) + ' ) * ( t < ' + str( runtime + steptime ) + ' )'
+ print(CaStim.expr)
+ tab = moose.Table2( '/model/' + name + '/Atab' )
+ #for i in range( 10, 19 ):
+ #moose.setClock( i, 0.01 )
+ ampl = moose.element( mod.path + '/ampl' )
+ phase = moose.element( mod.path + '/phase' )
+ moose.connect( tab, 'requestOut', A, 'getN' )
+ ampl.nInit = params['stimAmplitude'] * 1
+ phase.nInit = params['preStimTime']
+
+ ksolve = moose.Ksolve( mod.path + '/ksolve' )
+ stoich = moose.Stoich( mod.path + '/stoich' )
+ stoich.compartment = mod
+ stoich.ksolve = ksolve
+ stoich.path = mod.path + '/##'
+ runtime += 2 * steptime
+
+ moose.reinit()
+ moose.start( runtime )
+ t = np.arange( 0, runtime + 1e-9, tab.dt )
+ return name, t, tab.vector
+ #pylab.plot( t, tab.vector, label='[A] (mM)' )
+
+ #pylab.show()
+
+def plotBoilerplate( panelTitle, plotPos, xlabel = ''):
+ ax = plt.subplot( 8,4,plotPos )
+ #ax.xaxis.set_ticks( i[1] )
+ #ax.locator_params(
+ ax.spines['top'].set_visible( False )
+ ax.spines['right'].set_visible( False )
+ ax.tick_params( direction = 'out' )
+ if (((plotPos -1)/4) % 2) == 0:
+ ax.set_xticklabels([])
+ else:
+ ax.set_xlabel( xlabel )
+ for tick in ax.xaxis.get_major_ticks():
+ tick.tick2On = False
+ for tick in ax.yaxis.get_major_ticks():
+ tick.tick2On = False
+
+ if (plotPos % 4) == 1:
+ plt.ylabel( 'conc', fontsize = 16 )
+ # alternate way of doing this separately.
+ #plt.yaxis.label.size_size(16)
+ #plt.title( 'B' )
+ ax.text( -0.3, 1, panelTitle, fontsize = 18, weight = 'bold',
+ transform=ax.transAxes )
+ return ax
+
+def plotPanelB():
+ panelB = []
+ panelBticks = []
+ panelB.append( singleCompt( 'fhn', abstrModelEqns2.makeFHN() ) )
+ panelB.append( singleCompt( 'bis', abstrModelEqns2.makeBis() ) )
+ panelB.append( singleCompt( 'negFB', abstrModelEqns2.makeNegFB() ) )
+ panelB.append( singleCompt( 'negFF', abstrModelEqns2.makeNegFF() ) )
+
+ panelBticks.append( np.arange( 0, 4.00001, 1 ) )
+ panelBticks.append( np.arange( 0, 4.00001, 1 ) )
+ panelBticks.append( np.arange( 0, 15.00001, 5 ) )
+ panelBticks.append( np.arange( 0, 6.00001, 2 ) )
+ moose.delete( '/model' )
+
+ for i in zip( panelB, panelBticks, list(range( len( panelB ))) ):
+ plotPos = i[2] + 5
+ ax = plotBoilerplate( 'B', plotPos )
+ plt.plot( i[0][1], i[0][2] )
+ xmax = ax.get_xlim()[1]
+ #ax.xaxis.set_ticks( np.arange( 0, xmax, 50 ) )
+ ax.xaxis.set_ticks( np.arange( 0, 200.001, 50 ) )
+ ax.yaxis.set_ticks( i[1] )
+
+def runPanelCDEF( name, dist, seqDt, numSpine, seq, stimAmpl ):
+ preStim = 10.0
+ blanks = 20
+ rdes = rd.rdesigneur(
+ useGssa = False,
+ turnOffElec = True,
+ chemPlotDt = 0.1,
+ #diffusionLength = params['diffusionLength'],
+ diffusionLength = 1e-6,
+ cellProto = [['cell', 'soma']],
+ chemProto = [['dend', name]],
+ chemDistrib = [['dend', 'soma', 'install', '1' ]],
+ plotList = [['soma', '1', 'dend' + '/A', 'n', '# of A']],
+ )
+ rdes.buildModel()
+ #for i in range( 20 ):
+ #moose.setClock( i, 0.02 )
+ A = moose.vec( '/model/chem/dend/A' )
+ Z = moose.vec( '/model/chem/dend/Z' )
+ print(moose.element( '/model/chem/dend/A/Adot' ).expr)
+ print(moose.element( '/model/chem/dend/B/Bdot' ).expr)
+ print(moose.element( '/model/chem/dend/Ca/CaStim' ).expr)
+ phase = moose.vec( '/model/chem/dend/phase' )
+ ampl = moose.vec( '/model/chem/dend/ampl' )
+ vel = moose.vec( '/model/chem/dend/vel' )
+ vel.nInit = 1e-6 * seqDt
+ ampl.nInit = stimAmpl
+ stride = int( dist ) / numSpine
+ phase.nInit = 10000
+ Z.nInit = 0
+ for j in range( numSpine ):
+ k = blanks + j * stride
+ Z[k].nInit = 1
+ phase[k].nInit = preStim + seq[j] * seqDt
+ moose.reinit()
+ runtime = 50
+ snapshot = preStim + seqDt * (numSpine - 0.8)
+ print(snapshot)
+ #snapshot = 26
+ moose.start( snapshot )
+ avec = moose.vec( '/model/chem/dend/A' ).n
+ moose.start( runtime - snapshot )
+ tvec = []
+ for i in range( 5 ):
+ tab = moose.element( '/model/graphs/plot0[' + str( blanks + i * stride ) + ']' )
+ dt = tab.dt
+ tvec.append( tab.vector )
+ moose.delete( '/model' )
+ return dt, tvec, avec
+
+def makePassiveSoma( name, length, diameter ):
+ elecid = moose.Neuron( '/library/' + name )
+ dend = moose.Compartment( elecid.path + '/soma' )
+ dend.diameter = diameter
+ dend.length = length
+ dend.x = length
+ return elecid
+
+def plotOnePanel( tLabel, dt, tplot, numSyn, plotRange, tick ):
+ t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
+ ax = plotBoilerplate( tLabel, 1 + start )
+ for i in range( 5 ):
+ plt.plot( t, tplot[i] )
+ ax.yaxis.set_ticks( np.arange( 0, plotRange, tick ) )
+
+
+def plotPanelCDEF( seq, row ):
+ makePassiveSoma( 'cell', 100e-6, 10e-6 )
+ start = (row -1) * 4
+ tLabel = chr( ord( 'A' ) + row - 1 )
+ xLabel = chr( ord( 'C' ) + row - 1 )
+ xplot = []
+ #dt, tplot, avec = runPanelCDEF( 'fhn', 15.0, 3.0, 5, seq, 0.4 )
+ dt, tplot, avec = runPanelCDEF( 'fhn', 5.0, 0.5, 5, seq, 0.4 )
+ xplot.append( avec )
+ #plotOnePanel( dt, 'B', tplot, 5, 1.5, 0.5 )
+ t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
+ #ax = plotBoilerplate( tLabel, 1 + start )
+ ax = plotBoilerplate( tLabel, 1 + start, 'Time (s)')
+ for i in range( 5 ):
+ plt.plot( t, tplot[i] )
+ yl = ax.get_ylim()[1]
+ ax.yaxis.set_ticks( np.arange( 0, 4.0001, 1.0 ) )
+
+ #dt, tplot, avec = runPanelCDEF( 'bis', 5.0, 4.0, 5, seq, 1.0 )
+ dt, tplot, avec = runPanelCDEF( 'bis', 15.0, 2.0, 5, seq, 1.0 )
+ xplot.append( avec )
+ t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
+ ax = plotBoilerplate( tLabel, 2 + start, 'Time (s)' )
+ for i in range( 5 ):
+ plt.plot( t, tplot[i] )
+ yl = ax.get_ylim()[1]
+ ax.yaxis.set_ticks( np.arange( 0, 3.0001, 1.0 ) )
+
+ dt, tplot, avec = runPanelCDEF( 'negFB', 5.0, 2.0, 5, seq, 1.0 )
+ xplot.append( avec )
+ t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
+ ax = plotBoilerplate( tLabel, 3 + start, 'Time (s)')
+ for i in range( 5 ):
+ plt.plot( t, tplot[i] )
+ ax.yaxis.set_ticks( np.arange( 0, 10.00001, 5.0 ) )
+
+ dt, tplot, avec = runPanelCDEF( 'negFF', 5.0, 4.0, 5, seq, 1.0 )
+ xplot.append( avec )
+ t = np.arange( 0, len( tplot[0] ), 1.0 ) * dt
+ ax = plotBoilerplate( tLabel, 4 + start, 'Time (s)')
+ for i in range( 5 ):
+ plt.plot( t, tplot[i] )
+ ax.yaxis.set_ticks( np.arange( 0, 5.00001, 2.0 ) )
+
+ for i in zip( list(range(4)), (4.0, 3.0, 10, 4 ), (1, 1, 5, 2) ):
+ ax = plotBoilerplate( xLabel, 9 + start + i[0], 'Position( um)' )
+ plt.plot( xplot[i[0]][:50] )
+ ax.yaxis.set_ticks( np.arange( 0, i[1] * 1.0000001, i[2] ) )
+
+##################################################################
+if __name__ == '__main__':
+ moose.Neutral( '/library' )
+ moose.Neutral( '/model' )
+
+ t1 = time.time()
+ fig = plt.figure( figsize = (10,10), facecolor='white' )
+ fig.subplots_adjust( left = 0.18 )
+ plotPanelB()
+ plotPanelCDEF( [0,1,2,3,4], 3 )
+ plotPanelCDEF( [4,1,0,3,2], 4 )
+ print(("Time taken = ", time.time() - t1))
+ plt.tight_layout()
+
+ plt.show()
+
+
diff --git a/moose-examples/parallelSolver/abstrModelEqns2.py b/moose-examples/parallelSolver/abstrModelEqns2.py
index 42ce9e51e789a3f70b2045dd957cae09b0a6e8d0..16fb3e91ca87c08ea1535c2e51226a2354a9815d 100644
--- a/moose-examples/parallelSolver/abstrModelEqns2.py
+++ b/moose-examples/parallelSolver/abstrModelEqns2.py
@@ -1,219 +1,219 @@
-import re
-import moose
-# Equations here are:
-# Adot = 1 -6A + 5A^2 - A^3, or spread out as:
-# Adot = k0a + k1a.A + k2a.A.A + k3a.A.A.A + k4a.Ca.A/(1+A+10*B) - k5a.A.B
-# Bdot = k1b.A - k2b.B
-#
-
-
-def parseExpr( expr, params, hasCa ):
- if hasCa:
- expr = expr.replace( 'Ca', 'x0' )
- expr = expr.replace( 'A', 'x1' )
- expr = expr.replace( 'B', 'x2' )
- else:
- expr = expr.replace( 'Ca', 'x0' ) # happens in the negFF model
- expr = expr.replace( 'A', 'x0' ) # This is the usual case.
- expr = expr.replace( 'B', 'x1' )
-
- parts = re.split( 'k', expr )
- ret = parts[0]
- for i in parts[1:]:
- ret += str( params[ 'k' + i[:2] ] )
- ret += i[2:]
-
- if hasCa:
- return 'x3*( ' + ret + ')'
- else:
- return 'x2*( ' + ret + ')'
-
-def makeChemProto( name, Aexpr, Bexpr, params ):
- sw = params['stimWidth']
- diffLength = params['diffusionLength']
- dca = params['diffConstA'] * diffLength * diffLength
- dcb = params['diffConstB'] * diffLength * diffLength
-
- # Objects
- chem = moose.Neutral( '/library/' + name )
- compt = moose.CubeMesh( '/library/' + name + '/' + name )
- A = moose.Pool( compt.path + '/A' )
- B = moose.Pool( compt.path + '/B' )
- Z = moose.BufPool( compt.path + '/Z' )
- Ca = moose.BufPool( compt.path + '/Ca' )
- phase = moose.BufPool( compt.path + '/phase' )
- vel = moose.BufPool( compt.path + '/vel' )
- ampl = moose.BufPool( compt.path + '/ampl' )
- Adot = moose.Function( A.path + '/Adot' )
- Bdot = moose.Function( B.path + '/Bdot' )
- CaStim = moose.Function( Ca.path + '/CaStim' )
- A.diffConst = dca
- B.diffConst = dcb
-
- # Equations
-
- Adot.expr = parseExpr( Aexpr, params, True )
- Bdot.expr = parseExpr( Bexpr, params, False )
- CaStim.expr = 'x2 * exp( -((x0 - t)^2)/(2* ' + str(sw*sw) + ') )'
-
- print Adot.expr
- print Bdot.expr
- print CaStim.expr
-
- # Connections
- Adot.x.num = 4
- moose.connect( Ca, 'nOut', Adot.x[0], 'input' )
- moose.connect( A, 'nOut', Adot.x[1], 'input' )
- moose.connect( B, 'nOut', Adot.x[2], 'input' )
- moose.connect( Z, 'nOut', Adot.x[3], 'input' )
- moose.connect( Adot, 'valueOut', A, 'increment' )
-
- Bdot.x.num = 3
- if name == 'negFF':
- moose.connect( Ca, 'nOut', Bdot.x[0], 'input' )
- else:
- moose.connect( A, 'nOut', Bdot.x[0], 'input' )
- moose.connect( B, 'nOut', Bdot.x[1], 'input' )
- moose.connect( Z, 'nOut', Bdot.x[2], 'input' )
- moose.connect( Bdot, 'valueOut', B, 'increment' )
-
- CaStim.x.num = 3
- moose.connect( phase, 'nOut', CaStim.x[0], 'input' )
- moose.connect( vel, 'nOut', CaStim.x[1], 'input' )
- moose.connect( ampl, 'nOut', CaStim.x[2], 'input' )
- moose.connect( CaStim, 'valueOut', Ca, 'setN' )
-
- return compt
-
-
-def makeBis():
- params = {
- 'k0a':0.1, # Constant
- 'k1a':-5.0, # Coeff for A
- 'k2a':5.0, # Coeff for A^2
- 'k3a':-1.0, # Coeff for A^3
- 'k4a':10.0, # turnon of A by A and Ca
- 'k5a':-5.0, # Turnoff of A by B
- 'k1b':0.1, # turnon of B by A
- 'k2b':-0.01, # Decay rate of B
- 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
- 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
- 'dendLength': 100e-6, # Length of section of dendrite in model
- 'diffConstA':1.0, # Diffusion constant of A
- 'diffConstB':1.0, # Diffusion constant of B
- 'stimWidth' :5.0, # Stimulus width in seconds
- 'stimAmplitude':1.0, # Stimulus amplitude, arb units. From FHN review
- 'blankVoxelsAtEnd':10, # of voxels to leave blank at end of cylinder
- 'preStimTime':40.0, # Time to run before turning on stimulus.
- 'postStimTime':80.0, # Time to run after stimulus. ~3x decay time
- 'settleTime':20.0, # Settling time of response, after stimulus.
- # To include in analysis of total response over
- # entire dendrite.
- 'fnumber':1, # Number to append to fname
- }
-
- makeChemProto( 'bis',
- 'k0a + k1a*A + k2a*A*A + k3a*A*A*A + k4a*Ca*A/(1+A+10*B) + k5a*A*B',
- 'k1b*A*A + k2b*B',
- params )
- return params
-
-def makeFHN():
- params = {
- 'k_t':2.5, # Time-const.
- 'k_a':0.7, # Coeff1
- 'k_b':0.8, # Coeff2
- 'kxa': 2.0, # Offset for V for FHN eqns.
- 'kxb': 0.8, # Offset for W for FHN eqns.
- 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
- 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
- 'dendLength': 100e-6, # Length of section of dendrite in model
- 'diffConstA':7.5, # Diffusion constant of A
- 'diffConstB':5.0, # Diffusion constant of B
- 'stimWidth' :1.0, # Stimulus width in seconds
- 'stimAmplitude':0.4, # Stimulus amplitude, arb units. From FHN review
- 'blankVoxelsAtEnd':10, # of voxels to leave blank at end of cylinder
- 'preStimTime':30.0, # Time to run before turning on stimulus.
- 'postStimTime':40.0, # Time to run after stimulus. ~3x decay time
- 'settleTime':20.0, # Settling time of response, after stimulus.
- # To include in analysis of total response over
- # entire dendrite.
- 'fnumber': 1, # Number to append to fname
- }
- makeChemProto( 'fhn',
- '5.0*(A - kxa - (A-kxa)^3/3 - (B-kxb) + Ca)',
- '(A-kxa + k_a - k_b*(B-kxb))/k_t',
- params )
- return params
-
-
-def makeNegFB():
- params = {
- 'k1a':-0.1, # Coeff for decay of A, slow.
- 'k2a':-0.2, # Coeff for turnoff of A by B, medium.
- 'k3a':10.0, # turnon of A by Ca, fast.
- 'k1b':0.2, # turnon of B by A, medium
- 'k2b':-0.1, # Decay rate of B, slow
- 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
- 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
- 'dendLength': 100e-6, # Length of section of dendrite in model
- 'diffConstA':0.5, # Diffusion constant of A
- 'diffConstB':1.0, # Diffusion constant of B
- 'stimWidth' :1.0, # Stimulus width in seconds
- 'stimAmplitude':1.0, # Stimulus amplitude, arb units. From FHN review
- 'blankVoxelsAtEnd':10, #of voxels to leave blank at end of cylinder
- 'preStimTime':10.0, # Time to run before turning on stimulus.
- 'postStimTime':60.0, # Time to run after stimulus. ~3x decay time
- 'settleTime':20.0, # Settling time of response, after stimulus.
- # To include in analysis of total response over
- # entire dendrite.
- 'fnumber':1, # Number to append to fname
- }
- makeChemProto( 'negFB',
- 'k1a*A + k2a*A*B + k3a*Ca',
- 'k1b*A + k2b*B',
- params )
- return params
-
-
-def makeNegFF():
- params = {
- 'k1a':-0.1, # Coeff for decay of A, slow.
- 'k2a':-1.0, # Coeff for turnoff of A by B, medium.
- 'k3a':10.0, # turnon of A by Ca, fast.
- 'k1b':2.0, # turnon of B by Ca, medium
- 'k2b':-0.1, # Decay rate of B, slow
- 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
- 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
- 'dendLength': 100e-6, # Length of section of dendrite in model
- 'diffConstA':1.0, # Diffusion constant of A
- 'diffConstB':2.0, # Diffusion constant of B
- 'stimWidth' :1.0, # Stimulus width in seconds
- 'stimAmplitude':1.0, # Stimulus amplitude, arb units. From FHN review
- 'blankVoxelsAtEnd':10, # of voxels to leave blank at end of cylinder
- 'preStimTime':10.0, # Time to run before turning on stimulus.
- 'postStimTime':60.0, # Time to run after stimulus. ~3x decay time
- 'settleTime':20.0, # Settling time of response, after stimulus.
- # To include in analysis of total response over
- # entire dendrite.
- 'fnumber':1, # Number to append to fname
- }
- makeChemProto( 'negFF',
- 'k1a*A + k2a*A*B + k3a*Ca',
- 'k1b*Ca + k2b*B',
- params )
-
- return params
-
-if __name__ == '__main__':
- moose.Neutral( '/library' )
- print "Making Bistable model"
- makeBis()
- print "Making FHN model"
- makeFHN()
- print "Making Negative Feedback model"
- makeNegFB()
- print "Making Negative Feedforward model"
- makeNegFF()
-
-
+import re
+import moose
+# Equations here are:
+# Adot = 1 -6A + 5A^2 - A^3, or spread out as:
+# Adot = k0a + k1a.A + k2a.A.A + k3a.A.A.A + k4a.Ca.A/(1+A+10*B) - k5a.A.B
+# Bdot = k1b.A - k2b.B
+#
+
+
+def parseExpr( expr, params, hasCa ):
+ if hasCa:
+ expr = expr.replace( 'Ca', 'x0' )
+ expr = expr.replace( 'A', 'x1' )
+ expr = expr.replace( 'B', 'x2' )
+ else:
+ expr = expr.replace( 'Ca', 'x0' ) # happens in the negFF model
+ expr = expr.replace( 'A', 'x0' ) # This is the usual case.
+ expr = expr.replace( 'B', 'x1' )
+
+ parts = re.split( 'k', expr )
+ ret = parts[0]
+ for i in parts[1:]:
+ ret += str( params[ 'k' + i[:2] ] )
+ ret += i[2:]
+
+ if hasCa:
+ return 'x3*( ' + ret + ')'
+ else:
+ return 'x2*( ' + ret + ')'
+
+def makeChemProto( name, Aexpr, Bexpr, params ):
+ sw = params['stimWidth']
+ diffLength = params['diffusionLength']
+ dca = params['diffConstA'] * diffLength * diffLength
+ dcb = params['diffConstB'] * diffLength * diffLength
+
+ # Objects
+ chem = moose.Neutral( '/library/' + name )
+ compt = moose.CubeMesh( '/library/' + name + '/' + name )
+ A = moose.Pool( compt.path + '/A' )
+ B = moose.Pool( compt.path + '/B' )
+ Z = moose.BufPool( compt.path + '/Z' )
+ Ca = moose.BufPool( compt.path + '/Ca' )
+ phase = moose.BufPool( compt.path + '/phase' )
+ vel = moose.BufPool( compt.path + '/vel' )
+ ampl = moose.BufPool( compt.path + '/ampl' )
+ Adot = moose.Function( A.path + '/Adot' )
+ Bdot = moose.Function( B.path + '/Bdot' )
+ CaStim = moose.Function( Ca.path + '/CaStim' )
+ A.diffConst = dca
+ B.diffConst = dcb
+
+ # Equations
+
+ Adot.expr = parseExpr( Aexpr, params, True )
+ Bdot.expr = parseExpr( Bexpr, params, False )
+ CaStim.expr = 'x2 * exp( -((x0 - t)^2)/(2* ' + str(sw*sw) + ') )'
+
+ print(Adot.expr)
+ print(Bdot.expr)
+ print(CaStim.expr)
+
+ # Connections
+ Adot.x.num = 4
+ moose.connect( Ca, 'nOut', Adot.x[0], 'input' )
+ moose.connect( A, 'nOut', Adot.x[1], 'input' )
+ moose.connect( B, 'nOut', Adot.x[2], 'input' )
+ moose.connect( Z, 'nOut', Adot.x[3], 'input' )
+ moose.connect( Adot, 'valueOut', A, 'increment' )
+
+ Bdot.x.num = 3
+ if name == 'negFF':
+ moose.connect( Ca, 'nOut', Bdot.x[0], 'input' )
+ else:
+ moose.connect( A, 'nOut', Bdot.x[0], 'input' )
+ moose.connect( B, 'nOut', Bdot.x[1], 'input' )
+ moose.connect( Z, 'nOut', Bdot.x[2], 'input' )
+ moose.connect( Bdot, 'valueOut', B, 'increment' )
+
+ CaStim.x.num = 3
+ moose.connect( phase, 'nOut', CaStim.x[0], 'input' )
+ moose.connect( vel, 'nOut', CaStim.x[1], 'input' )
+ moose.connect( ampl, 'nOut', CaStim.x[2], 'input' )
+ moose.connect( CaStim, 'valueOut', Ca, 'setN' )
+
+ return compt
+
+
+def makeBis():
+ params = {
+ 'k0a':0.1, # Constant
+ 'k1a':-5.0, # Coeff for A
+ 'k2a':5.0, # Coeff for A^2
+ 'k3a':-1.0, # Coeff for A^3
+ 'k4a':10.0, # turnon of A by A and Ca
+ 'k5a':-5.0, # Turnoff of A by B
+ 'k1b':0.1, # turnon of B by A
+ 'k2b':-0.01, # Decay rate of B
+ 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
+ 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
+ 'dendLength': 100e-6, # Length of section of dendrite in model
+ 'diffConstA':1.0, # Diffusion constant of A
+ 'diffConstB':1.0, # Diffusion constant of B
+ 'stimWidth' :5.0, # Stimulus width in seconds
+ 'stimAmplitude':1.0, # Stimulus amplitude, arb units. From FHN review
+ 'blankVoxelsAtEnd':10, # of voxels to leave blank at end of cylinder
+ 'preStimTime':40.0, # Time to run before turning on stimulus.
+ 'postStimTime':80.0, # Time to run after stimulus. ~3x decay time
+ 'settleTime':20.0, # Settling time of response, after stimulus.
+ # To include in analysis of total response over
+ # entire dendrite.
+ 'fnumber':1, # Number to append to fname
+ }
+
+ makeChemProto( 'bis',
+ 'k0a + k1a*A + k2a*A*A + k3a*A*A*A + k4a*Ca*A/(1+A+10*B) + k5a*A*B',
+ 'k1b*A*A + k2b*B',
+ params )
+ return params
+
+def makeFHN():
+ params = {
+ 'k_t':2.5, # Time-const.
+ 'k_a':0.7, # Coeff1
+ 'k_b':0.8, # Coeff2
+ 'kxa': 2.0, # Offset for V for FHN eqns.
+ 'kxb': 0.8, # Offset for W for FHN eqns.
+ 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
+ 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
+ 'dendLength': 100e-6, # Length of section of dendrite in model
+ 'diffConstA':7.5, # Diffusion constant of A
+ 'diffConstB':5.0, # Diffusion constant of B
+ 'stimWidth' :1.0, # Stimulus width in seconds
+ 'stimAmplitude':0.4, # Stimulus amplitude, arb units. From FHN review
+ 'blankVoxelsAtEnd':10, # of voxels to leave blank at end of cylinder
+ 'preStimTime':30.0, # Time to run before turning on stimulus.
+ 'postStimTime':40.0, # Time to run after stimulus. ~3x decay time
+ 'settleTime':20.0, # Settling time of response, after stimulus.
+ # To include in analysis of total response over
+ # entire dendrite.
+ 'fnumber': 1, # Number to append to fname
+ }
+ makeChemProto( 'fhn',
+ '5.0*(A - kxa - (A-kxa)^3/3 - (B-kxb) + Ca)',
+ '(A-kxa + k_a - k_b*(B-kxb))/k_t',
+ params )
+ return params
+
+
+def makeNegFB():
+ params = {
+ 'k1a':-0.1, # Coeff for decay of A, slow.
+ 'k2a':-0.2, # Coeff for turnoff of A by B, medium.
+ 'k3a':10.0, # turnon of A by Ca, fast.
+ 'k1b':0.2, # turnon of B by A, medium
+ 'k2b':-0.1, # Decay rate of B, slow
+ 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
+ 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
+ 'dendLength': 100e-6, # Length of section of dendrite in model
+ 'diffConstA':0.5, # Diffusion constant of A
+ 'diffConstB':1.0, # Diffusion constant of B
+ 'stimWidth' :1.0, # Stimulus width in seconds
+ 'stimAmplitude':1.0, # Stimulus amplitude, arb units. From FHN review
+ 'blankVoxelsAtEnd':10, #of voxels to leave blank at end of cylinder
+ 'preStimTime':10.0, # Time to run before turning on stimulus.
+ 'postStimTime':60.0, # Time to run after stimulus. ~3x decay time
+ 'settleTime':20.0, # Settling time of response, after stimulus.
+ # To include in analysis of total response over
+ # entire dendrite.
+ 'fnumber':1, # Number to append to fname
+ }
+ makeChemProto( 'negFB',
+ 'k1a*A + k2a*A*B + k3a*Ca',
+ 'k1b*A + k2b*B',
+ params )
+ return params
+
+
+def makeNegFF():
+ params = {
+ 'k1a':-0.1, # Coeff for decay of A, slow.
+ 'k2a':-1.0, # Coeff for turnoff of A by B, medium.
+ 'k3a':10.0, # turnon of A by Ca, fast.
+ 'k1b':2.0, # turnon of B by Ca, medium
+ 'k2b':-0.1, # Decay rate of B, slow
+ 'diffusionLength':1.0e-6, # Diffusion characteristic length, used as voxel length too.
+ 'dendDiameter': 10e-6, # Diameter of section of dendrite in model
+ 'dendLength': 100e-6, # Length of section of dendrite in model
+ 'diffConstA':1.0, # Diffusion constant of A
+ 'diffConstB':2.0, # Diffusion constant of B
+ 'stimWidth' :1.0, # Stimulus width in seconds
+ 'stimAmplitude':1.0, # Stimulus amplitude, arb units. From FHN review
+ 'blankVoxelsAtEnd':10, # of voxels to leave blank at end of cylinder
+ 'preStimTime':10.0, # Time to run before turning on stimulus.
+ 'postStimTime':60.0, # Time to run after stimulus. ~3x decay time
+ 'settleTime':20.0, # Settling time of response, after stimulus.
+ # To include in analysis of total response over
+ # entire dendrite.
+ 'fnumber':1, # Number to append to fname
+ }
+ makeChemProto( 'negFF',
+ 'k1a*A + k2a*A*B + k3a*Ca',
+ 'k1b*Ca + k2b*B',
+ params )
+
+ return params
+
+if __name__ == '__main__':
+ moose.Neutral( '/library' )
+ print("Making Bistable model")
+ makeBis()
+ print("Making FHN model")
+ makeFHN()
+ print("Making Negative Feedback model")
+ makeNegFB()
+ print("Making Negative Feedforward model")
+ makeNegFF()
+
+
diff --git a/moose-examples/rall_1964/rall64.py b/moose-examples/rall_1964/rall64.py
index 7b016ad86b5fe107790cfd1aa089ecc5260b16e7..5dff8a17000935b22fc7d2205f061412e22d60af 100755
--- a/moose-examples/rall_1964/rall64.py
+++ b/moose-examples/rall_1964/rall64.py
@@ -44,11 +44,17 @@
#
# Code:
-"""Implementation of Rall 1964 model of dendritic branching. All units
-SI."""
-import sys
+
+"""
+Implementation of Rall 1964 model of dendritic branching. All units
+SI.
+
+"""
+from __future__ import print_function
+
+import sys
import math
import pylab
import moose
@@ -73,7 +79,7 @@ Ra = RA * length / (math.pi * diameter * diameter / 4.0)
Ek = Em + 1e-3
-print 'tau =', tau, 'lambda =', lambda_
+print('tau =', tau, 'lambda =', lambda_)
# Rall used `0.05 * tau`, but that does not reproduce in our
# case. Why? Sym vs Asym comp??
@@ -176,7 +182,7 @@ def run_model_fig6():
"""Do a simulation for fig6 and plot data."""
for ch in moose.wildcardFind('/model/##[ISA=ChanBase]'):
ch.Gk = 1.0/Rm
- print 'Starting for', inject_time
+ print('Starting for', inject_time)
moose.start(inject_time)
for ch in moose.wildcardFind('/model/##[ISA=ChanBase]'):
ch.Gk = 0.0
@@ -235,8 +241,8 @@ def run_model_fig7(chans_1, chans_2, chans_3):
to_run = simtime
delta_t = 0.25 * tau
for ii in range(0, len(chans_1), 2):
- print ii
- print '-----------------'
+ print(ii)
+ print('-----------------')
chans_1[ii].Gk = 1 / Rm
chans_1[ii+1].Gk = 1 / Rm
chans_2[-ii-1].Gk = 1 / Rm
@@ -245,11 +251,11 @@ def run_model_fig7(chans_1, chans_2, chans_3):
chan.Gk = 0.25 / Rm
for chan in chans_1:
- print chan.Gk,
- print
+ print(chan.Gk, end=' ')
+ print()
for chan in chans_2:
- print chan.Gk,
- print
+ print(chan.Gk, end=' ')
+ print()
moose.start(delta_t)
for chan in chans_1:
chan.Gk = 0.0
diff --git a/moose-examples/rall_1964/rall64_graphic.py b/moose-examples/rall_1964/rall64_graphic.py
index a8b9d178dad2b06b745bbc3986de96d7bbbe6a90..f5dc7dcdb1fe8fb4b45e25ff6a777898ea6ce692 100755
--- a/moose-examples/rall_1964/rall64_graphic.py
+++ b/moose-examples/rall_1964/rall64_graphic.py
@@ -133,7 +133,7 @@ ax_data.set_xlim(0, simtime/tau)
ax_data.set_ylim(0, 0.15)
ax_data.set_xlabel('Time (t/tau)')
ax_data.set_ylabel('Membrane voltage (Vm - Em)/(Ek - Vm)')
-print lines
+print(lines)
plt.legend()
schedule()
fanim = anim.FuncAnimation(fig, update, fargs=None, interval=25, repeat=False)
diff --git a/moose-examples/snippets/GraupnerBrunel2012_STDPfromCaPlasticity.py b/moose-examples/snippets/GraupnerBrunel2012_STDPfromCaPlasticity.py
index ee0ab8a9470d574535b2f81bd2376f3dc2ea399a..257add4833b5c355792e22dc261df84fde6f7819 100644
--- a/moose-examples/snippets/GraupnerBrunel2012_STDPfromCaPlasticity.py
+++ b/moose-examples/snippets/GraupnerBrunel2012_STDPfromCaPlasticity.py
@@ -208,7 +208,7 @@ t_extent = 100e-3 # s # STDP kernel extent,
# t_extent > t_between_pairs/2 inverts pre-post pairing!
# dt = tpost - tpre
# negative dt corresponds to post before pre
-print '-----------------------------------------------'
+print('-----------------------------------------------')
for deltat in arange(t_extent,0.0,-ddt):
reset_settle()
for i in range(numpairs):
@@ -220,9 +220,9 @@ for deltat in arange(t_extent,0.0,-ddt):
moose.start(t_between_pairs) # weight changes after pre-spike+delayD
# must run for at least delayD after pre-spike
dw = ( syn.synapse[0].weight - weight ) / weight
- print 'post before pre, dt = %1.3f s, dw/w = %1.3f'%(-deltat,dw)
+ print(('post before pre, dt = %1.3f s, dw/w = %1.3f'%(-deltat,dw)))
dwlist_neg.append(dw)
-print '-----------------------------------------------'
+print('-----------------------------------------------')
# positive dt corresponds to pre before post
dwlist_pos = []
for deltat in arange(ddt,t_extent+ddt,ddt):
@@ -235,24 +235,24 @@ for deltat in arange(ddt,t_extent+ddt,ddt):
make_neuron_spike(1)
moose.start(t_between_pairs)
dw = ( syn.synapse[0].weight - weight ) / weight
- print 'pre before post, dt = %1.3f s, dw/w = %1.3f'%(deltat,dw)
+ print(('pre before post, dt = %1.3f s, dw/w = %1.3f'%(deltat,dw)))
dwlist_pos.append(dw)
-print '-----------------------------------------------'
-print 'Each of the above pre-post pairs was repeated',\
- numpairs,'times, with',t_between_pairs,'s between pairs.'
-print
-print 'Due to event based updates, Ca decays suddenly at events:'
-print 'pre-spike, pre-spike + delayD, and post-spike;'
-print 'apart from the usual CaPre and CaPost jumps at'
-print 'pre-spike + delayD and post-spike respectively.'
-print 'Because of the event based update, multiple pre-post pairs are used.'
-print
-print 'If you reduce the t_between_pairs,'
-print ' you\'ll see potentiation for the LTD part without using any triplet rule!'
-print
-print "If you turn on noise, the weights fluctuate too much,"
-print " not sure if there's a bug in my noise implementation."
-print '-----------------------------------------------'
+print('-----------------------------------------------')
+print(('Each of the above pre-post pairs was repeated',\
+ numpairs,'times, with',t_between_pairs,'s between pairs.'))
+print()
+print('Due to event based updates, Ca decays suddenly at events:')
+print('pre-spike, pre-spike + delayD, and post-spike;')
+print('apart from the usual CaPre and CaPost jumps at')
+print('pre-spike + delayD and post-spike respectively.')
+print('Because of the event based update, multiple pre-post pairs are used.')
+print()
+print('If you reduce the t_between_pairs,')
+print(' you\'ll see potentiation for the LTD part without using any triplet rule!')
+print()
+print("If you turn on noise, the weights fluctuate too much,")
+print(" not sure if there's a bug in my noise implementation.")
+print('-----------------------------------------------')
# ###########################################
# Plot the simulated Vm-s and STDP curve
diff --git a/moose-examples/snippets/HigginsGraupnerBrunel2014_LifetimeCaPlasticity.py b/moose-examples/snippets/HigginsGraupnerBrunel2014_LifetimeCaPlasticity.py
index f4647cc0f088c58a72a4dde92cb4519d3b91088a..1d3ddff2b9b8a5931eb66e5cab764c41461b02fb 100644
--- a/moose-examples/snippets/HigginsGraupnerBrunel2014_LifetimeCaPlasticity.py
+++ b/moose-examples/snippets/HigginsGraupnerBrunel2014_LifetimeCaPlasticity.py
@@ -126,18 +126,18 @@ moose.seed(100)
moose.reinit()
# function to make the aPlus and aMinus settle to equilibrium values
-print "Rates of pre- and post-syanptic neurons =",frate
+print(("Rates of pre- and post-syanptic neurons =",frate))
WtSeries = []
numsteps = int(runtime/dt)
for i in range(numrepeats):
syn.synapse[0].weight = 1.0 # starting weight to decay from
syn.Ca = 0.0
- print "Repeat number",i,"running..."
+ print(("Repeat number",i,"running..."))
moose.start(runtime)
WtSeries.append(WtTable.vector[i*numsteps:(i+1)*numsteps])
WtSeries = array(WtSeries)
WtMean = mean(WtSeries,axis=0)
-print "plotting..."
+print("plotting...")
# ###########################################
# Plot the simulated weights and Ca vs time
diff --git a/moose-examples/snippets/HsolveInstability.py b/moose-examples/snippets/HsolveInstability.py
index 61ac1df23973c4de12dd75ded861a221424e2441..467bd7ee17e460a84a76db82d9ed5c84c9e2207d 100644
--- a/moose-examples/snippets/HsolveInstability.py
+++ b/moose-examples/snippets/HsolveInstability.py
@@ -187,7 +187,7 @@ def create_spine( parentCompt, parentObj, index, frac, length, dia, theta ):
return head
def create_spine_with_receptor( compt, cell, index, frac ):
- FaradayConst = 96485.3415 # s A / mol
+ FaradayConst = 96485.3415 # s A / mol
spineLength = 5.0e-6
spineDia = 4.0e-6
head = create_spine( compt, cell, index, frac, spineLength, spineDia, 0.0 )
@@ -199,10 +199,10 @@ def create_spine_with_receptor( compt, cell, index, frac ):
moose.connect( head, 'channel', gluR, 'channel', 'single' )
caPool = moose.CaConc( head.path + '/ca' )
- caPool.CaBasal = 1e-4 # 0.1 micromolar
+ caPool.CaBasal = 1e-4 # 0.1 micromolar
caPool.tau = 0.01
B = 1.0 / ( FaradayConst * spineLength * spineDia * spineDia *math.pi/4)
- B = B / 20.0 # scaling factor for Ca buffering
+ B = B / 20.0 # scaling factor for Ca buffering
caPool.B = B
moose.connect( gluR, 'IkOut', caPool, 'current', 'single' )
@@ -227,7 +227,7 @@ def display_plots( name ):
pylab.figure()
for x in moose.wildcardFind( '/graphs/#' ):
pos = numpy.arange( 0, x.vector.size ) * x.dt
- print len( pos ), len( x.vector )
+ print((len( pos ), len( x.vector )))
pylab.plot( pos, x.vector, label=x.name )
pylab.legend()
pylab.title( name )
diff --git a/moose-examples/snippets/IntegrateFireZoo.py b/moose-examples/snippets/IntegrateFireZoo.py
index b715519b1c9b734288ef8381ae9b61afd416a469..be88545651458c8523fe93788b31422709c0f5c5 100644
--- a/moose-examples/snippets/IntegrateFireZoo.py
+++ b/moose-examples/snippets/IntegrateFireZoo.py
@@ -119,9 +119,9 @@ def main():
#### CHOOSE ONE OF THE NEURON KEYS AS choiceKey FROM BELOW DICTIONARY ####
#choiceKey = 'LIF'
#### No need, am inputting it from the user on the terminal
- choiceKeys = neuronChoices.keys() # keys() does not retain the order in dict defn above!
- choiceIndex = input('Choose a number corresponding to your desired neuron: '+ \
- str([(i,key) for (i,key) in enumerate(choiceKeys)])+' -- ')
+ choiceKeys = list(neuronChoices.keys()) # keys() does not retain the order in dict defn above!
+ choiceIndex = eval(input('Choose a number corresponding to your desired neuron: '+ \
+ str([(i,key) for (i,key) in enumerate(choiceKeys)])+' -- '))
choiceKey = choiceKeys[choiceIndex]
neuronChoice = neuronChoices[choiceKey]
@@ -171,7 +171,7 @@ def main():
network.vec.vPeak = vPeak # reset at vPeak, not at thresh
network.vec.inject = 5e-9 # Amp # injected current I
- print "Injecting current =",network.vec[0].inject,"in",choiceKey,"neuron."
+ print(("Injecting current =",network.vec[0].inject,"in",choiceKey,"neuron."))
# ###########################################
# Setting up table
diff --git a/moose-examples/snippets/MULTI/TuringInNeuron.py b/moose-examples/snippets/MULTI/TuringInNeuron.py
index 1f38df813a889cb7cb56a7abff81fbe3d9371d46..7f1c7a1e4d4bd15d887747a33d16430f894f2f8a 100644
--- a/moose-examples/snippets/MULTI/TuringInNeuron.py
+++ b/moose-examples/snippets/MULTI/TuringInNeuron.py
@@ -19,185 +19,183 @@ import moose
import proto18
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- model = moose.element( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ model = moose.element( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
+ return cellId
def makeChemModel( cellId ):
- # create container for model
- r0 = 1e-6 # m
- r1 = 1e-6 # m
- num = 2800
- diffLength = 1e-6 # m
- diffConst = 5e-12 # m^2/sec
- motorRate = 1e-6 # m/sec
- concA = 1 # millimolar
-
- model = moose.element( '/model' )
- compartment = moose.NeuroMesh( '/model/compartment' )
- # FIXME: No attribute cell
- compartment.cell = cellId
- compartment.diffLength = diffLength
- print "cell NeuroMesh parameters: numSeg and numDiffCompt: ", compartment.numSegments, compartment.numDiffCompts
-
- print "compartment.numDiffCompts == num: ", compartment.numDiffCompts, num
- assert( compartment.numDiffCompts == num )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- s = moose.Pool( '/model/compartment/s' )
- e1 = moose.MMenz( '/model/compartment/e1' )
- e2 = moose.MMenz( '/model/compartment/e2' )
- e3 = moose.MMenz( '/model/compartment/e3' )
- r1 = moose.Reac( '/model/compartment/r1' )
- moose.connect( e1, 'sub', s, 'reac' )
- moose.connect( e1, 'prd', a, 'reac' )
- moose.connect( a, 'nOut', e1, 'enzDest' )
- e1.Km = 1
- e1.kcat = 1
-
- moose.connect( e2, 'sub', s, 'reac' )
- moose.connect( e2, 'prd', b, 'reac' )
- moose.connect( a, 'nOut', e2, 'enzDest' )
- e2.Km = 1
- e2.kcat = 0.5
-
- moose.connect( e3, 'sub', a, 'reac' )
- moose.connect( e3, 'prd', s, 'reac' )
- moose.connect( b, 'nOut', e3, 'enzDest' )
- e3.Km = 0.1
- e3.kcat = 1
-
- moose.connect( r1, 'sub', b, 'reac' )
- moose.connect( r1, 'prd', s, 'reac' )
- r1.Kf = 0.3 # 1/sec
- r1.Kb = 0 # 1/sec
-
- # Assign parameters
- a.diffConst = diffConst/10
- b.diffConst = diffConst
- s.diffConst = 0
+ # create container for model
+ r0 = 1e-6 # m
+ r1 = 1e-6 # m
+ num = 2800
+ diffLength = 1e-6 # m
+ diffConst = 5e-12 # m^2/sec
+ motorRate = 1e-6 # m/sec
+ concA = 1 # millimolar
+
+ model = moose.element( '/model' )
+ compartment = moose.NeuroMesh( '/model/compartment' )
+ # FIXME: No attribute cell
+ compartment.cell = cellId
+ compartment.diffLength = diffLength
+ print(("cell NeuroMesh parameters: numSeg and numDiffCompt: ", compartment.numSegments, compartment.numDiffCompts))
+
+ print(("compartment.numDiffCompts == num: ", compartment.numDiffCompts, num))
+ assert( compartment.numDiffCompts == num )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ s = moose.Pool( '/model/compartment/s' )
+ e1 = moose.MMenz( '/model/compartment/e1' )
+ e2 = moose.MMenz( '/model/compartment/e2' )
+ e3 = moose.MMenz( '/model/compartment/e3' )
+ r1 = moose.Reac( '/model/compartment/r1' )
+ moose.connect( e1, 'sub', s, 'reac' )
+ moose.connect( e1, 'prd', a, 'reac' )
+ moose.connect( a, 'nOut', e1, 'enzDest' )
+ e1.Km = 1
+ e1.kcat = 1
+
+ moose.connect( e2, 'sub', s, 'reac' )
+ moose.connect( e2, 'prd', b, 'reac' )
+ moose.connect( a, 'nOut', e2, 'enzDest' )
+ e2.Km = 1
+ e2.kcat = 0.5
+
+ moose.connect( e3, 'sub', a, 'reac' )
+ moose.connect( e3, 'prd', s, 'reac' )
+ moose.connect( b, 'nOut', e3, 'enzDest' )
+ e3.Km = 0.1
+ e3.kcat = 1
+
+ moose.connect( r1, 'sub', b, 'reac' )
+ moose.connect( r1, 'prd', s, 'reac' )
+ r1.Kf = 0.3 # 1/sec
+ r1.Kb = 0 # 1/sec
+
+ # Assign parameters
+ a.diffConst = diffConst/10
+ b.diffConst = diffConst
+ s.diffConst = 0
#b.motorConst = motorRate
- # Make solvers
- ksolve = moose.Ksolve( '/model/compartment/ksolve' )
- dsolve = moose.Dsolve( '/model/compartment/dsolve' )
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = compartment
- #ksolve.numAllVoxels = compartment.numDiffCompts
- stoich.ksolve = ksolve
- stoich.dsolve = dsolve
- stoich.path = "/model/compartment/##"
- assert( dsolve.numPools == 3 )
- a.vec.concInit = [0.1]*num
- a.vec[0].concInit += 0.5
- a.vec[400].concInit += 0.5
- a.vec[800].concInit += 0.5
- a.vec[1200].concInit += 0.5
- a.vec[1600].concInit += 0.5
- a.vec[2000].concInit += 0.5
- a.vec[2400].concInit += 0.5
- #a.vec[num/2].concInit -= 0.1
- b.vec.concInit = [0.1]*num
- s.vec.concInit = [1]*num
+ # Make solvers
+ ksolve = moose.Ksolve( '/model/compartment/ksolve' )
+ dsolve = moose.Dsolve( '/model/compartment/dsolve' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = compartment
+ #ksolve.numAllVoxels = compartment.numDiffCompts
+ stoich.ksolve = ksolve
+ stoich.dsolve = dsolve
+ stoich.path = "/model/compartment/##"
+ assert( dsolve.numPools == 3 )
+ a.vec.concInit = [0.1]*num
+ a.vec[0].concInit += 0.5
+ a.vec[400].concInit += 0.5
+ a.vec[800].concInit += 0.5
+ a.vec[1200].concInit += 0.5
+ a.vec[1600].concInit += 0.5
+ a.vec[2000].concInit += 0.5
+ a.vec[2400].concInit += 0.5
+ #a.vec[num/2].concInit -= 0.1
+ b.vec.concInit = [0.1]*num
+ s.vec.concInit = [1]*num
def displayPlots( num ):
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
- print '/newplot\n/plotname a' + str(num)
- for x in a.vec.conc:
- print x
- print '/newplot\n/plotname b' + str(num)
- for y in b.vec.conc:
- print y
- """
- print '/newplot\n/plotname bvol'
- for z in a.vec.volume:
- print z * 1e18
- print '/newplot\n/plotname aInit'
- for x in a.vec.concInit:
- print x
- pos = numpy.arange( 0, a.vec.conc.size, 1.0 )
- aconc = numpy.array( a.vec.conc )
- bconc = numpy.array( b.vec.conc )
- print "pos a, b = ", pos, b.vec.conc.size
- pylab.plot( pos[:100], aconc[:100], label='a' )
- pylab.plot( pos[:100], bconc[:100], label='b' )
- #pylab.plot( pos, a.vec.conc, label='a' )
- #pylab.plot( pos, b.vec.conc, label='b' )
- print "plotting done"
- pylab.legend()
- print "legend done"
- pylab.show()
- print "show done"
- """
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
+ print(('/newplot\n/plotname a' + str(num)))
+ for x in a.vec.conc:
+ print(x)
+ print(('/newplot\n/plotname b' + str(num)))
+ for y in b.vec.conc:
+ print(y)
+ """
+ print '/newplot\n/plotname bvol'
+ for z in a.vec.volume:
+ print z * 1e18
+ print '/newplot\n/plotname aInit'
+ for x in a.vec.concInit:
+ print x
+ pos = numpy.arange( 0, a.vec.conc.size, 1.0 )
+ aconc = numpy.array( a.vec.conc )
+ bconc = numpy.array( b.vec.conc )
+ print "pos a, b = ", pos, b.vec.conc.size
+ pylab.plot( pos[:100], aconc[:100], label='a' )
+ pylab.plot( pos[:100], bconc[:100], label='b' )
+ #pylab.plot( pos, a.vec.conc, label='a' )
+ #pylab.plot( pos, b.vec.conc, label='b' )
+ print "plotting done"
+ pylab.legend()
+ print "legend done"
+ pylab.show()
+ print "show done"
+ """
def main():
- runtime = 400
- dt4 = 0.02 # for the diffusion
- dt5 = 0.2 # for the reaction
- # Set up clocks. The dsolver to know before assigning stoich
- moose.setClock( 4, dt4 )
- moose.setClock( 5, dt5 )
- model = moose.Neutral( '/model' )
- cellId = loadElec()
- makeChemModel( cellId )
- moose.useClock( 4, '/model/compartment/dsolve', 'process' )
- # Ksolve must be scheduled after dsolve.
- moose.useClock( 5, '/model/compartment/ksolve', 'process' )
- print "finished loading"
- moose.reinit()
- for i in range( 10 ):
- moose.start( runtime / 10 ) # Run the model for 10 seconds.
- # print 'done', i
- displayPlots( i )
- print "finished running"
-
- """
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
- s = moose.element( '/model/compartment/s' )
-
- atot = sum( a.vec.conc )
- btot = sum( b.vec.conc )
- stot = sum( s.vec.conc )
- print "a = ", a.vec.conc
- print "b = ", b.vec.conc
- print "s = ", s.vec.conc
-
- print 'tot = ', atot, btot, atot + btot + stot
- displayPlots()
- """
-
- """
- dsolve = moose.element( '/model/compartment/dsolve' )
-
- print '**************** dsolve.nvecs'
- x = dsolve.nVec[0]
- print dsolve.numPools, x, sum(x)
- print dsolve.nVec[1], sum( dsolve.nVec[1] )
- print dsolve.nVec[2], sum( dsolve.nVec[2] )
- print dsolve.nVec[3], sum( dsolve.nVec[3] )
- """
-
- quit()
+ runtime = 400
+ dt4 = 0.02 # for the diffusion
+ dt5 = 0.2 # for the reaction
+ # Set up clocks. The dsolver to know before assigning stoich
+ moose.setClock( 4, dt4 )
+ moose.setClock( 5, dt5 )
+ model = moose.Neutral( '/model' )
+ cellId = loadElec()
+ makeChemModel( cellId )
+ moose.useClock( 4, '/model/compartment/dsolve', 'process' )
+ # Ksolve must be scheduled after dsolve.
+ moose.useClock( 5, '/model/compartment/ksolve', 'process' )
+ print("finished loading")
+ moose.reinit()
+ for i in range( 10 ):
+ moose.start( runtime / 10 ) # Run the model for 10 seconds.
+ # print 'done', i
+ displayPlots( i )
+ print("finished running")
+
+ """
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
+ s = moose.element( '/model/compartment/s' )
+
+ atot = sum( a.vec.conc )
+ btot = sum( b.vec.conc )
+ stot = sum( s.vec.conc )
+ print "a = ", a.vec.conc
+ print "b = ", b.vec.conc
+ print "s = ", s.vec.conc
+
+ print 'tot = ', atot, btot, atot + btot + stot
+ displayPlots()
+ """
+
+ """
+ dsolve = moose.element( '/model/compartment/dsolve' )
+ x = dsolve.nVec[0]
+ print dsolve.numPools, x, sum(x)
+ print dsolve.nVec[1], sum( dsolve.nVec[1] )
+ print dsolve.nVec[2], sum( dsolve.nVec[2] )
+ print dsolve.nVec[3], sum( dsolve.nVec[3] )
+ """
+
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/MULTI/diffusionOnly.py b/moose-examples/snippets/MULTI/diffusionOnly.py
index 68faddb92e42772f68dd73f5535ec287bf54f784..9797c50dc9b9e38fbc53cccecf0b39ed1d990586 100644
--- a/moose-examples/snippets/MULTI/diffusionOnly.py
+++ b/moose-examples/snippets/MULTI/diffusionOnly.py
@@ -43,30 +43,30 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "hsolve" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "hsolve" )
+ return cellId
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if ( moose.exists( objpath ) ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- moose.connect( tab, 'requestOut', obj, field )
+ #assert moose.exists( objpath )
+ if ( moose.exists( objpath ) ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ moose.connect( tab, 'requestOut', obj, field )
def dumpPlots( fname ):
@@ -78,231 +78,231 @@ def dumpPlots( fname ):
moose.element( x[0] ).xplot( fname, x[0].name + '_e' )
def moveCompt( path, oldParent, newParent ):
- meshEntries = moose.element( newParent.path + '/mesh' )
- # Set up vol messaging from new compts to all their child objects.
- for x in moose.wildcardFind( path + '/##[ISA=PoolBase]' ):
- moose.connect( meshEntries, 'mesh', x, 'mesh', 'OneToOne' )
- #print 'path = ', path, ', oldparent = ', oldParent.path
- orig = moose.element( path )
- moose.move( orig, newParent )
- moose.delete( moose.vec( oldParent.path ) )
- chem = moose.element( '/model/chem' )
- moose.move( newParent, chem )
+ meshEntries = moose.element( newParent.path + '/mesh' )
+ # Set up vol messaging from new compts to all their child objects.
+ for x in moose.wildcardFind( path + '/##[ISA=PoolBase]' ):
+ moose.connect( meshEntries, 'mesh', x, 'mesh', 'OneToOne' )
+ #print 'path = ', path, ', oldparent = ', oldParent.path
+ orig = moose.element( path )
+ moose.move( orig, newParent )
+ moose.delete( moose.vec( oldParent.path ) )
+ chem = moose.element( '/model/chem' )
+ moose.move( newParent, chem )
def loadChem( neuroCompt, spineCompt, psdCompt ):
- # We need the compartments to come in with a volume of 1 to match the
- # original CubeMesh.
- assert( neuroCompt.volume == 1.0 )
- assert( spineCompt.volume == 1.0 )
- assert( psdCompt.volume == 1.0 )
- assert( neuroCompt.mesh.num == 1 )
- print('volume = ', neuroCompt.mesh[0].volume)
- #assert( neuroCompt.mesh[0].volume == 1.0 )
- #an unfortunate mismatch
- # So we'll have to resize the volumes of the current compartments to the
- # new ones.
-
- modelId = moose.loadModel( 'diffonly.g', '/model', 'ee' )
- #moose.le( '/model/model' )
- #moose.le( '/model/model/kinetics' )
- #moose.le( '/model/model/kinetics/PSD' )
- #moose.le( '/model/model/kinetics/SPINE' )
- moose.delete( moose.vec( '/model/model/kinetics/PSD/kreac' ) )
- moose.delete( moose.vec( '/model/model/kinetics/SPINE/kreac' ) )
- #moose.le( '/model/model/kinetics/PSD' )
- #moose.le( '/model/model/kinetics/SPINE' )
- pCaCaM = moose.element( '/model/model/kinetics/PSD/Ca_CaM' )
- pCaCaM.concInit = 0.001
- dCaCaM = moose.element( '/model/model/kinetics/PSD/Ca_CaM' )
- sCaCaM = moose.element( '/model/model/kinetics/SPINE/Ca_CaM' )
- print("CaCaM.concInit[p,s,d] = ", pCaCaM.concInit, sCaCaM.concInit, dCaCaM.concInit)
- #moose.delete( moose.vec( '/model/model/kinetics/SPINE/Ca_CaM' ) )
- #CaCaM2 = moose.element( '/model/model/kinetics/SPINE/Ca_CaM' )
- #CaCaM2.concInit = 0.001
- chem = moose.element( '/model/model' )
- chem.name = 'chem'
- oldS = moose.element( '/model/chem/compartment_1' )
- oldP = moose.element( '/model/chem/compartment_2' )
- oldN = moose.element( '/model/chem/kinetics' )
- print('oldvols[p,s,d] = ', oldP.volume, oldS.volume, oldN.volume)
- print('newvols[p,s,d] = ', psdCompt.mesh[0].volume, spineCompt.mesh[0].volume, neuroCompt.mesh[0].volume)
- oldN.volume = neuroCompt.mesh[0].volume
- oldS.volume = spineCompt.mesh[0].volume
- oldP.volume = psdCompt.mesh[0].volume
- print('after redoing vols')
- print("CaCaM.concInit[p,s,d] = ", pCaCaM.concInit, sCaCaM.concInit, dCaCaM.concInit)
- moveCompt( '/model/chem/kinetics/SPINE', oldS, spineCompt )
- moveCompt( '/model/chem/kinetics/PSD', oldP, psdCompt )
- # Need to do the DEND last because the oldN is /kinetics,
- # and it will be deleted.
- moveCompt( '/model/chem/kinetics/DEND', oldN, neuroCompt )
- print('after moving to new compts')
- print("CaCaM.concInit[p,s,d] = ", pCaCaM.concInit, sCaCaM.concInit, dCaCaM.concInit)
+ # We need the compartments to come in with a volume of 1 to match the
+ # original CubeMesh.
+ assert( neuroCompt.volume == 1.0 )
+ assert( spineCompt.volume == 1.0 )
+ assert( psdCompt.volume == 1.0 )
+ assert( neuroCompt.mesh.num == 1 )
+ print(('volume = ', neuroCompt.mesh[0].volume))
+ #assert( neuroCompt.mesh[0].volume == 1.0 )
+ #an unfortunate mismatch
+ # So we'll have to resize the volumes of the current compartments to the
+ # new ones.
+
+ modelId = moose.loadModel( 'diffonly.g', '/model', 'ee' )
+ #moose.le( '/model/model' )
+ #moose.le( '/model/model/kinetics' )
+ #moose.le( '/model/model/kinetics/PSD' )
+ #moose.le( '/model/model/kinetics/SPINE' )
+ moose.delete( moose.vec( '/model/model/kinetics/PSD/kreac' ) )
+ moose.delete( moose.vec( '/model/model/kinetics/SPINE/kreac' ) )
+ #moose.le( '/model/model/kinetics/PSD' )
+ #moose.le( '/model/model/kinetics/SPINE' )
+ pCaCaM = moose.element( '/model/model/kinetics/PSD/Ca_CaM' )
+ pCaCaM.concInit = 0.001
+ dCaCaM = moose.element( '/model/model/kinetics/PSD/Ca_CaM' )
+ sCaCaM = moose.element( '/model/model/kinetics/SPINE/Ca_CaM' )
+ print(("CaCaM.concInit[p,s,d] = ", pCaCaM.concInit, sCaCaM.concInit, dCaCaM.concInit))
+ #moose.delete( moose.vec( '/model/model/kinetics/SPINE/Ca_CaM' ) )
+ #CaCaM2 = moose.element( '/model/model/kinetics/SPINE/Ca_CaM' )
+ #CaCaM2.concInit = 0.001
+ chem = moose.element( '/model/model' )
+ chem.name = 'chem'
+ oldS = moose.element( '/model/chem/compartment_1' )
+ oldP = moose.element( '/model/chem/compartment_2' )
+ oldN = moose.element( '/model/chem/kinetics' )
+ print(('oldvols[p,s,d] = ', oldP.volume, oldS.volume, oldN.volume))
+ print(('newvols[p,s,d] = ', psdCompt.mesh[0].volume, spineCompt.mesh[0].volume, neuroCompt.mesh[0].volume))
+ oldN.volume = neuroCompt.mesh[0].volume
+ oldS.volume = spineCompt.mesh[0].volume
+ oldP.volume = psdCompt.mesh[0].volume
+ print('after redoing vols')
+ print(("CaCaM.concInit[p,s,d] = ", pCaCaM.concInit, sCaCaM.concInit, dCaCaM.concInit))
+ moveCompt( '/model/chem/kinetics/SPINE', oldS, spineCompt )
+ moveCompt( '/model/chem/kinetics/PSD', oldP, psdCompt )
+ # Need to do the DEND last because the oldN is /kinetics,
+ # and it will be deleted.
+ moveCompt( '/model/chem/kinetics/DEND', oldN, neuroCompt )
+ print('after moving to new compts')
+ print(("CaCaM.concInit[p,s,d] = ", pCaCaM.concInit, sCaCaM.concInit, dCaCaM.concInit))
def makeNeuroMeshModel():
- diffLength = 20e-6 # But we only want diffusion over part of the model.
- numSyn = 13
- elec = loadElec()
- synInput = moose.SpikeGen( '/model/elec/synInput' )
- synInput.refractT = 47e-3
- synInput.threshold = -1.0
- synInput.edgeTriggered = 0
- synInput.Vm( 0 )
-
- synInput.refractT = 47e-3
- for i in range( numSyn ):
- name = '/model/elec/spine_head_14_' + str( i + 1 )
- r = moose.element( name + '/glu' )
- r.synapse.num = 1
- syn = moose.element( r.path + '/synapse' )
- moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
- syn.weight = 0.2 * i * ( numSyn - 1 - i )
- syn.delay = i * 1.0e-3
-
- neuroCompt = moose.NeuroMesh( '/model/neuroMesh' )
- #print 'neuroMeshvolume = ', neuroCompt.mesh[0].volume
- neuroCompt.separateSpines = 1
- neuroCompt.diffLength = diffLength
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/spineMesh' )
- #print 'spineMeshvolume = ', spineCompt.mesh[0].volume
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/psdMesh' )
- #print 'psdMeshvolume = ', psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- loadChem( neuroCompt, spineCompt, psdCompt )
-
- # Put in the solvers, see how they fare.
- nmksolve = moose.GslStoich( '/model/chem/neuroMesh/ksolve' )
- nmksolve.path = '/model/chem/neuroMesh/##'
- nmksolve.compartment = moose.element( '/model/chem/neuroMesh' )
- nmksolve.method = 'rk5'
- nm = moose.element( '/model/chem/neuroMesh/mesh' )
- moose.connect( nm, 'remesh', nmksolve, 'remesh' )
+ diffLength = 20e-6 # But we only want diffusion over part of the model.
+ numSyn = 13
+ elec = loadElec()
+ synInput = moose.SpikeGen( '/model/elec/synInput' )
+ synInput.refractT = 47e-3
+ synInput.threshold = -1.0
+ synInput.edgeTriggered = 0
+ synInput.Vm( 0 )
+
+ synInput.refractT = 47e-3
+ for i in range( numSyn ):
+ name = '/model/elec/spine_head_14_' + str( i + 1 )
+ r = moose.element( name + '/glu' )
+ r.synapse.num = 1
+ syn = moose.element( r.path + '/synapse' )
+ moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
+ syn.weight = 0.2 * i * ( numSyn - 1 - i )
+ syn.delay = i * 1.0e-3
+
+ neuroCompt = moose.NeuroMesh( '/model/neuroMesh' )
+ #print 'neuroMeshvolume = ', neuroCompt.mesh[0].volume
+ neuroCompt.separateSpines = 1
+ neuroCompt.diffLength = diffLength
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/spineMesh' )
+ #print 'spineMeshvolume = ', spineCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/psdMesh' )
+ #print 'psdMeshvolume = ', psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ loadChem( neuroCompt, spineCompt, psdCompt )
+
+ # Put in the solvers, see how they fare.
+ nmksolve = moose.GslStoich( '/model/chem/neuroMesh/ksolve' )
+ nmksolve.path = '/model/chem/neuroMesh/##'
+ nmksolve.compartment = moose.element( '/model/chem/neuroMesh' )
+ nmksolve.method = 'rk5'
+ nm = moose.element( '/model/chem/neuroMesh/mesh' )
+ moose.connect( nm, 'remesh', nmksolve, 'remesh' )
#print "neuron: nv=", nmksolve.numLocalVoxels, ", nav=", nmksolve.numAllVoxels, nmksolve.numVarPools, nmksolve.numAllPools
#print 'setting up smksolve'
- smksolve = moose.GslStoich( '/model/chem/spineMesh/ksolve' )
- smksolve.path = '/model/chem/spineMesh/##'
- smksolve.compartment = moose.element( '/model/chem/spineMesh' )
- smksolve.method = 'rk5'
- sm = moose.element( '/model/chem/spineMesh/mesh' )
- moose.connect( sm, 'remesh', smksolve, 'remesh' )
- #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
- #
- #print 'setting up pmksolve'
- pmksolve = moose.GslStoich( '/model/chem/psdMesh/ksolve' )
- pmksolve.path = '/model/chem/psdMesh/##'
- pmksolve.compartment = moose.element( '/model/chem/psdMesh' )
- pmksolve.method = 'rk5'
- pm = moose.element( '/model/chem/psdMesh/mesh' )
- moose.connect( pm, 'remesh', pmksolve, 'remesh' )
- #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
- #
- print('neuroMeshvolume = ', neuroCompt.mesh[0].volume)
-
- #print 'Assigning the cell model'
- # Now to set up the model.
- #neuroCompt.cell = elec
- neuroCompt.cellPortion( elec, '/model/elec/lat_14_#,/model/elec/spine_neck#,/model/elec/spine_head#' )
- """
- ns = neuroCompt.numSegments
- #assert( ns == 11 ) # dend, 5x (shaft+head)
- ndc = neuroCompt.numDiffCompts
- #print 'numDiffCompts = ', ndc
- assert( ndc == 145 )
- ndc = neuroCompt.mesh.num
- #print 'NeuroMeshNum = ', ndc
- assert( ndc == 145 )
-
- sdc = spineCompt.mesh.num
- #print 'SpineMeshNum = ', sdc
- assert( sdc == 13 )
- pdc = psdCompt.mesh.num
- #print 'PsdMeshNum = ', pdc
- assert( pdc == 13 )
- """
-
- mesh = moose.vec( '/model/chem/neuroMesh/mesh' )
- #for i in range( ndc ):
- # print 's[', i, '] = ', mesh[i].volume
- mesh2 = moose.vec( '/model/chem/spineMesh/mesh' )
-# for i in range( sdc ):
-# print 's[', i, '] = ', mesh2[i].volume
- #print 'numPSD = ', moose.element( '/model/chem/psdMesh/mesh' ).localNumField
- mesh = moose.vec( '/model/chem/psdMesh/mesh' )
- #print 'psd mesh.volume = ', mesh.volume
- #for i in range( pdc ):
- # print 's[', i, '] = ', mesh[i].volume
- #
- # We need to use the spine solver as the master for the purposes of
- # these calculations. This will handle the diffusion calculations
- # between head and dendrite, and between head and PSD.
- smksolve.addJunction( nmksolve )
- #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
- smksolve.addJunction( pmksolve )
- #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
- ndc = neuroCompt.numDiffCompts
- #print 'numDiffCompts = ', ndc
- assert( ndc == 13 )
- ndc = neuroCompt.mesh.num
- #print 'NeuroMeshNum = ', ndc
- assert( ndc == 13 )
- sdc = spineCompt.mesh.num
- #print 'SpineMeshNum = ', sdc
- assert( sdc == 13 )
- pdc = psdCompt.mesh.num
- #print 'PsdMeshNum = ', pdc
- assert( pdc == 13 )
-
- """
- print 'neuroCompt'
- for i in range( ndc ):
- print i, neuroCompt.stencilIndex[i]
- print i, neuroCompt.stencilRate[i]
-
- print 'spineCompt'
- for i in range( sdc * 3 ):
- print i, spineCompt.stencilIndex[i]
- print i, spineCompt.stencilRate[i]
-
- print 'psdCompt'
- for i in range( pdc ):
- print i, psdCompt.stencilIndex[i]
- print i, psdCompt.stencilRate[i]
- print 'Spine parents:'
- pavoxel = spineCompt.parentVoxel
- for i in range( sdc ):
- print i, pavoxel[i]
- """
-
- # oddly, numLocalFields does not work.
- #moose.le( '/model/chem/neuroMesh' )
- ca = moose.element( '/model/chem/neuroMesh/DEND/Ca' )
- assert( ca.lastDimension == ndc )
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spineMesh/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/psdMesh/adaptCa', pdc )
- adaptCa = moose.vec( '/model/chem/psdMesh/adaptCa' )
- chemCa = moose.vec( '/model/chem/psdMesh/PSD/Ca' )
- assert( len( adaptCa ) == pdc )
- assert( len( chemCa ) == pdc )
- for i in range( pdc ):
- path = '/model/elec/spine_head_14_' + str( i + 1 ) + '/NMDA_Ca_conc'
- elecCa = moose.element( path )
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'outputSrc', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 80e-6 # 80 nM offset in chem.
- adaptCa.scale = 1e-5 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
- #print adaptCa.scale
+ smksolve = moose.GslStoich( '/model/chem/spineMesh/ksolve' )
+ smksolve.path = '/model/chem/spineMesh/##'
+ smksolve.compartment = moose.element( '/model/chem/spineMesh' )
+ smksolve.method = 'rk5'
+ sm = moose.element( '/model/chem/spineMesh/mesh' )
+ moose.connect( sm, 'remesh', smksolve, 'remesh' )
+ #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
+ #
+ #print 'setting up pmksolve'
+ pmksolve = moose.GslStoich( '/model/chem/psdMesh/ksolve' )
+ pmksolve.path = '/model/chem/psdMesh/##'
+ pmksolve.compartment = moose.element( '/model/chem/psdMesh' )
+ pmksolve.method = 'rk5'
+ pm = moose.element( '/model/chem/psdMesh/mesh' )
+ moose.connect( pm, 'remesh', pmksolve, 'remesh' )
+ #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
+ #
+ print(('neuroMeshvolume = ', neuroCompt.mesh[0].volume))
+
+ #print 'Assigning the cell model'
+ # Now to set up the model.
+ #neuroCompt.cell = elec
+ neuroCompt.cellPortion( elec, '/model/elec/lat_14_#,/model/elec/spine_neck#,/model/elec/spine_head#' )
+ """
+ ns = neuroCompt.numSegments
+ #assert( ns == 11 ) # dend, 5x (shaft+head)
+ ndc = neuroCompt.numDiffCompts
+ #print 'numDiffCompts = ', ndc
+ assert( ndc == 145 )
+ ndc = neuroCompt.mesh.num
+ #print 'NeuroMeshNum = ', ndc
+ assert( ndc == 145 )
+
+ sdc = spineCompt.mesh.num
+ #print 'SpineMeshNum = ', sdc
+ assert( sdc == 13 )
+ pdc = psdCompt.mesh.num
+ #print 'PsdMeshNum = ', pdc
+ assert( pdc == 13 )
+ """
+
+ mesh = moose.vec( '/model/chem/neuroMesh/mesh' )
+ #for i in range( ndc ):
+ # print 's[', i, '] = ', mesh[i].volume
+ mesh2 = moose.vec( '/model/chem/spineMesh/mesh' )
+# for i in range( sdc ):
+# print 's[', i, '] = ', mesh2[i].volume
+ #print 'numPSD = ', moose.element( '/model/chem/psdMesh/mesh' ).localNumField
+ mesh = moose.vec( '/model/chem/psdMesh/mesh' )
+ #print 'psd mesh.volume = ', mesh.volume
+ #for i in range( pdc ):
+ # print 's[', i, '] = ', mesh[i].volume
+ #
+ # We need to use the spine solver as the master for the purposes of
+ # these calculations. This will handle the diffusion calculations
+ # between head and dendrite, and between head and PSD.
+ smksolve.addJunction( nmksolve )
+ #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
+ smksolve.addJunction( pmksolve )
+ #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
+ ndc = neuroCompt.numDiffCompts
+ #print 'numDiffCompts = ', ndc
+ assert( ndc == 13 )
+ ndc = neuroCompt.mesh.num
+ #print 'NeuroMeshNum = ', ndc
+ assert( ndc == 13 )
+ sdc = spineCompt.mesh.num
+ #print 'SpineMeshNum = ', sdc
+ assert( sdc == 13 )
+ pdc = psdCompt.mesh.num
+ #print 'PsdMeshNum = ', pdc
+ assert( pdc == 13 )
+
+ """
+ print 'neuroCompt'
+ for i in range( ndc ):
+ print i, neuroCompt.stencilIndex[i]
+ print i, neuroCompt.stencilRate[i]
+
+ print 'spineCompt'
+ for i in range( sdc * 3 ):
+ print i, spineCompt.stencilIndex[i]
+ print i, spineCompt.stencilRate[i]
+
+ print 'psdCompt'
+ for i in range( pdc ):
+ print i, psdCompt.stencilIndex[i]
+ print i, psdCompt.stencilRate[i]
+ print 'Spine parents:'
+ pavoxel = spineCompt.parentVoxel
+ for i in range( sdc ):
+ print i, pavoxel[i]
+ """
+
+ # oddly, numLocalFields does not work.
+ #moose.le( '/model/chem/neuroMesh' )
+ ca = moose.element( '/model/chem/neuroMesh/DEND/Ca' )
+ assert( ca.lastDimension == ndc )
+ """
+ CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
+ print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
+ CaNspine = moose.vec( '/model/chem/spineMesh/SPINE/CaN_BULK/CaN' )
+ print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
+ """
+
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/psdMesh/adaptCa', pdc )
+ adaptCa = moose.vec( '/model/chem/psdMesh/adaptCa' )
+ chemCa = moose.vec( '/model/chem/psdMesh/PSD/Ca' )
+ assert( len( adaptCa ) == pdc )
+ assert( len( chemCa ) == pdc )
+ for i in range( pdc ):
+ path = '/model/elec/spine_head_14_' + str( i + 1 ) + '/NMDA_Ca_conc'
+ elecCa = moose.element( path )
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'outputSrc', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 80e-6 # 80 nM offset in chem.
+ adaptCa.scale = 1e-5 # 520 to 0.0052 mM
+ #print adaptCa.outputOffset
+ #print adaptCa.scale
def makeElecPlots():
graphs = moose.Neutral( '/graphs' )
@@ -317,121 +317,121 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head_14_13/NMDA_Ca_conc', 'getCa', 'elec/spine_13Ca' )
def makeChemPlots():
- spineMesh = moose.element( '/model/chem/spineMesh' )
- middleSpine = 6
- midSpineVoxel = spineMesh.parentVoxel[middleSpine]
- graphs = moose.Neutral( '/graphs' )
- addPlot( '/model/chem/psdMesh/PSD/Ca[0]', 'getConc', 'pCa0' )
- addPlot( '/model/chem/psdMesh/PSD/Ca[6]', 'getConc', 'pCa6' )
- addPlot( '/model/chem/psdMesh/PSD/Ca[12]', 'getConc', 'pCa12' )
-
- addPlot( '/model/chem/spineMesh/SPINE/Ca[0]', 'getConc', 'sCa0' )
- addPlot( '/model/chem/spineMesh/SPINE/Ca[6]', 'getConc', 'sCa6' )
- addPlot( '/model/chem/spineMesh/SPINE/Ca[12]', 'getConc', 'sCa12' )
-
- addPlot( '/model/chem/neuroMesh/DEND/Ca[0]', 'getConc', 'dend0Ca' )
- addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel ) + ']', 'getConc', 'dendMidCa' )
- addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel+2 ) + ']', 'getConc', 'dendMid2' )
- addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel+4 ) + ']', 'getConc', 'dendMid4' )
- addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel+6 ) + ']', 'getConc', 'dendMid6' )
- addPlot( '/model/chem/neuroMesh/DEND/Ca[144]', 'getConc', 'dend144Ca' )
-
- addPlot( '/model/chem/psdMesh/PSD/CaM[0]', 'getConc', 'pCaM0' )
- addPlot( '/model/chem/psdMesh/PSD/CaM[6]', 'getConc', 'pCaM6' )
- addPlot( '/model/chem/psdMesh/PSD/CaM[12]', 'getConc', 'pCaM12' )
-
- addPlot( '/model/chem/spineMesh/SPINE/CaM[0]', 'getConc', 'sCaM0' )
- addPlot( '/model/chem/spineMesh/SPINE/CaM[6]', 'getConc', 'sCaM6' )
- addPlot( '/model/chem/spineMesh/SPINE/CaM[12]', 'getConc', 'sCaM12' )
-
- addPlot( '/model/chem/psdMesh/PSD/Ca_CaM[0]', 'getConc', 'pCaCaM0' )
- addPlot( '/model/chem/psdMesh/PSD/Ca_CaM[6]', 'getConc', 'pCaCaM6' )
- addPlot( '/model/chem/psdMesh/PSD/Ca_CaM[12]', 'getConc', 'pCaCaM12' )
-
- addPlot( '/model/chem/spineMesh/SPINE/Ca_CaM[0]', 'getConc', 'sCaCaM0' )
- addPlot( '/model/chem/spineMesh/SPINE/Ca_CaM[6]', 'getConc', 'sCaCaM6' )
- addPlot( '/model/chem/spineMesh/SPINE/Ca_CaM[12]', 'getConc', 'sCaCaM12' )
-
- addPlot( '/model/chem/neuroMesh/DEND/Ca_CaM[0]', 'getConc', 'dCaCaM0' )
- addPlot( '/model/chem/neuroMesh/DEND/Ca_CaM[' + str( midSpineVoxel ) + ']', 'getConc', 'dendMidCaCaM' )
- addPlot( '/model/chem/neuroMesh/DEND/Ca_CaM[144]', 'getConc', 'dCaCaM144' )
+ spineMesh = moose.element( '/model/chem/spineMesh' )
+ middleSpine = 6
+ midSpineVoxel = spineMesh.parentVoxel[middleSpine]
+ graphs = moose.Neutral( '/graphs' )
+ addPlot( '/model/chem/psdMesh/PSD/Ca[0]', 'getConc', 'pCa0' )
+ addPlot( '/model/chem/psdMesh/PSD/Ca[6]', 'getConc', 'pCa6' )
+ addPlot( '/model/chem/psdMesh/PSD/Ca[12]', 'getConc', 'pCa12' )
+
+ addPlot( '/model/chem/spineMesh/SPINE/Ca[0]', 'getConc', 'sCa0' )
+ addPlot( '/model/chem/spineMesh/SPINE/Ca[6]', 'getConc', 'sCa6' )
+ addPlot( '/model/chem/spineMesh/SPINE/Ca[12]', 'getConc', 'sCa12' )
+
+ addPlot( '/model/chem/neuroMesh/DEND/Ca[0]', 'getConc', 'dend0Ca' )
+ addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel ) + ']', 'getConc', 'dendMidCa' )
+ addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel+2 ) + ']', 'getConc', 'dendMid2' )
+ addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel+4 ) + ']', 'getConc', 'dendMid4' )
+ addPlot( '/model/chem/neuroMesh/DEND/Ca[' + str( midSpineVoxel+6 ) + ']', 'getConc', 'dendMid6' )
+ addPlot( '/model/chem/neuroMesh/DEND/Ca[144]', 'getConc', 'dend144Ca' )
+
+ addPlot( '/model/chem/psdMesh/PSD/CaM[0]', 'getConc', 'pCaM0' )
+ addPlot( '/model/chem/psdMesh/PSD/CaM[6]', 'getConc', 'pCaM6' )
+ addPlot( '/model/chem/psdMesh/PSD/CaM[12]', 'getConc', 'pCaM12' )
+
+ addPlot( '/model/chem/spineMesh/SPINE/CaM[0]', 'getConc', 'sCaM0' )
+ addPlot( '/model/chem/spineMesh/SPINE/CaM[6]', 'getConc', 'sCaM6' )
+ addPlot( '/model/chem/spineMesh/SPINE/CaM[12]', 'getConc', 'sCaM12' )
+
+ addPlot( '/model/chem/psdMesh/PSD/Ca_CaM[0]', 'getConc', 'pCaCaM0' )
+ addPlot( '/model/chem/psdMesh/PSD/Ca_CaM[6]', 'getConc', 'pCaCaM6' )
+ addPlot( '/model/chem/psdMesh/PSD/Ca_CaM[12]', 'getConc', 'pCaCaM12' )
+
+ addPlot( '/model/chem/spineMesh/SPINE/Ca_CaM[0]', 'getConc', 'sCaCaM0' )
+ addPlot( '/model/chem/spineMesh/SPINE/Ca_CaM[6]', 'getConc', 'sCaCaM6' )
+ addPlot( '/model/chem/spineMesh/SPINE/Ca_CaM[12]', 'getConc', 'sCaCaM12' )
+
+ addPlot( '/model/chem/neuroMesh/DEND/Ca_CaM[0]', 'getConc', 'dCaCaM0' )
+ addPlot( '/model/chem/neuroMesh/DEND/Ca_CaM[' + str( midSpineVoxel ) + ']', 'getConc', 'dendMidCaCaM' )
+ addPlot( '/model/chem/neuroMesh/DEND/Ca_CaM[144]', 'getConc', 'dCaCaM144' )
def testNeuroMeshMultiscale():
- elecDt = 50e-6
- chemDt = 1e-4
- plotDt = 5e-4
- plotName = 'diffonly.plot'
-
- makeNeuroMeshModel()
- """
- for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if ( i[0].diffConst > 0 ):
- grandpaname = i.parent[0].parent.name + '/'
- paname = i.parent[0].name + '/'
- print grandpaname + paname + i[0].name, i[0].diffConst
- moose.le( '/model/chem/spineMesh/ksolve' )
- print 'Neighbors:'
- for t in moose.element( '/model/chem/spineMesh/ksolve/junction' ).neighbors['masterJunction']:
- print 'masterJunction <-', t.path
- for t in moose.wildcardFind( '/model/chem/#Mesh/ksolve' ):
- k = moose.element( t[0] )
- print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
- """
-
- makeChemPlots()
- makeElecPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, plotDt )
- moose.setClock( 8, plotDt )
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- moose.useClock( 6, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 7, '/graphs/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#', 'process' )
- moose.useClock( 5, '/model/chem/#Mesh/ksolve', 'init' )
- moose.useClock( 6, '/model/chem/#Mesh/ksolve', 'process' )
- hsolve = moose.HSolve( '/model/elec/hsolve' )
- moose.useClock( 1, '/model/elec/hsolve', 'process' )
- hsolve.dt = elecDt
- hsolve.target = '/model/elec/compt'
- moose.reinit()
- moose.reinit()
- """
- print 'pre'
- eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'dend'
- eca = moose.vec( '/model/chem/neuroMesh/DEND/Ca' )
- for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
- print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
-
- print 'PSD'
- eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'spine'
- eca = moose.vec( '/model/chem/spineMesh/SPINE/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- """
-
- moose.start( 0.5 )
- dumpPlots( plotName )
- print('All done')
+ elecDt = 50e-6
+ chemDt = 1e-4
+ plotDt = 5e-4
+ plotName = 'diffonly.plot'
+
+ makeNeuroMeshModel()
+ """
+ for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if ( i[0].diffConst > 0 ):
+ grandpaname = i.parent[0].parent.name + '/'
+ paname = i.parent[0].name + '/'
+ print grandpaname + paname + i[0].name, i[0].diffConst
+ moose.le( '/model/chem/spineMesh/ksolve' )
+ print 'Neighbors:'
+ for t in moose.element( '/model/chem/spineMesh/ksolve/junction' ).neighbors['masterJunction']:
+ print 'masterJunction <-', t.path
+ for t in moose.wildcardFind( '/model/chem/#Mesh/ksolve' ):
+ k = moose.element( t[0] )
+ print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
+ """
+
+ makeChemPlots()
+ makeElecPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, plotDt )
+ moose.setClock( 8, plotDt )
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
+ moose.useClock( 6, '/model/chem/##[ISA=Adaptor]', 'process' )
+ moose.useClock( 7, '/graphs/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#', 'process' )
+ moose.useClock( 5, '/model/chem/#Mesh/ksolve', 'init' )
+ moose.useClock( 6, '/model/chem/#Mesh/ksolve', 'process' )
+ hsolve = moose.HSolve( '/model/elec/hsolve' )
+ moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ hsolve.dt = elecDt
+ hsolve.target = '/model/elec/compt'
+ moose.reinit()
+ moose.reinit()
+ """
+ print 'pre'
+ eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'dend'
+ eca = moose.vec( '/model/chem/neuroMesh/DEND/Ca' )
+ for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
+ print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+
+ print 'PSD'
+ eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'spine'
+ eca = moose.vec( '/model/chem/spineMesh/SPINE/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ """
+
+ moose.start( 0.5 )
+ dumpPlots( plotName )
+ print('All done')
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# loadMulti.py ends here.
diff --git a/moose-examples/snippets/MULTI/loadMulti.py b/moose-examples/snippets/MULTI/loadMulti.py
index d4e92aa3787752581d7ca9a90a21f4e3a92c665d..128acd3b4aa8aff8ca88cae654e9663848ebc3cc 100644
--- a/moose-examples/snippets/MULTI/loadMulti.py
+++ b/moose-examples/snippets/MULTI/loadMulti.py
@@ -35,39 +35,39 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
+ return cellId
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print("addPlot failed: object is a Neutral: ", objpath)
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print("addPlot failed: object not found: ", objpath)
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def dumpPlots( fname ):
if ( os.path.exists( fname ) ):
@@ -78,143 +78,141 @@ def dumpPlots( fname ):
moose.element( x[0] ).xplot( fname, x[0].name + '_e' )
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 10e-6 # But we only want diffusion over part of the model.
- numSyn = 13
- elec = loadElec()
- synInput = moose.SpikeGen( '/model/elec/synInput' )
- synInput.threshold = -1.0
- synInput.edgeTriggered = 0
- synInput.Vm( 0 )
- synInput.refractT = 47e-3
-
- for i in range( numSyn ):
- name = '/model/elec/spine_head_14_' + str( i + 1 )
- r = moose.element( name + '/glu' )
- r.synapse.num = 1
- syn = moose.element( r.path + '/synapse' )
- moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
- syn.weight = 0.2 * i * ( numSyn - 1 - i )
- syn.delay = i * 1.0e-3
-
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
-
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print('ns = ', ns, ', ndc = ', ndc)
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 36 ) # dend, 5x (shaft+head)
- assert( ndc == 278 )
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print('done setting path, numPools = ', nmdsolve.numPools)
- assert( nmdsolve.numPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
+ diffLength = 10e-6 # But we only want diffusion over part of the model.
+ numSyn = 13
+ elec = loadElec()
+ synInput = moose.SpikeGen( '/model/elec/synInput' )
+ synInput.threshold = -1.0
+ synInput.edgeTriggered = 0
+ synInput.Vm( 0 )
+ synInput.refractT = 47e-3
+
+ for i in range( numSyn ):
+ name = '/model/elec/spine_head_14_' + str( i + 1 )
+ r = moose.element( name + '/glu' )
+ r.synapse.num = 1
+ syn = moose.element( r.path + '/synapse' )
+ moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
+ syn.weight = 0.2 * i * ( numSyn - 1 - i )
+ syn.delay = i * 1.0e-3
+
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
+
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 36 ) # dend, 5x (shaft+head)
+ assert( ndc == 278 )
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print('sdc = ', sdc)
- assert( sdc == 13 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- assert( smstoich.numAllPools == 36 )
-
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 13 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- print('numAllPools = ', pmstoich.numAllPools)
- assert( pmstoich.numAllPools == 56 )
- foo = moose.element( '/model/chem/psd/Ca' )
- bar = moose.element( '/model/chem/psd/I1_p' )
- print('PSD: numfoo = ', foo.numData, 'numbar = ', bar.numData)
- print('PSD: numAllVoxels = ', pmksolve.numAllVoxels)
-
- # Put in junctions between diffusion solvers
- nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
-
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/psd/adaptCa', pdc )
- adaptCa = moose.vec( '/model/chem/psd/adaptCa' )
- chemCa = moose.vec( '/model/chem/psd/Ca' )
- print('aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData)
- assert( len( adaptCa ) == pdc )
- assert( len( chemCa ) == pdc )
- for i in range( pdc ):
- path = '/model/elec/spine_head_14_' + str( i + 1 ) + '/NMDA_Ca_conc'
- elecCa = moose.element( path )
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
- adaptCa[i].inputOffset = 0.0 #
- adaptCa[i].outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa[i].scale = 1e-5 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
- #print adaptCa.scale
- """
- """
-
- """
- aGluR = moose.Adaptor( '/model/chem/psd/adaptGluR', 5 )
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print(('sdc = ', sdc))
+ assert( sdc == 13 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ assert( smstoich.numAllPools == 36 )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 13 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ print(('numAllPools = ', pmstoich.numAllPools))
+ assert( pmstoich.numAllPools == 56 )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ bar = moose.element( '/model/chem/psd/I1_p' )
+ print(('PSD: numfoo = ', foo.numData, 'numbar = ', bar.numData))
+ print(('PSD: numAllVoxels = ', pmksolve.numAllVoxels))
+
+ # Put in junctions between diffusion solvers
+ nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
+
+ """
+ CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
+ print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
+ CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
+ print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
+ """
+
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/psd/adaptCa', pdc )
+ adaptCa = moose.vec( '/model/chem/psd/adaptCa' )
+ chemCa = moose.vec( '/model/chem/psd/Ca' )
+ print( 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = "
+ , len( chemCa ), ", numData = ", chemCa.numData
+ )
+ assert( len( adaptCa ) == pdc )
+ assert( len( chemCa ) == pdc )
+ for i in range( pdc ):
+ path = '/model/elec/spine_head_14_' + str( i + 1 ) + '/NMDA_Ca_conc'
+ elecCa = moose.element( path )
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
+ adaptCa[i].inputOffset = 0.0 #
+ adaptCa[i].outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa[i].scale = 1e-5 # 520 to 0.0052 mM
+
+ """
+ aGluR = moose.Adaptor( '/model/chem/psd/adaptGluR', 5 )
adaptGluR = moose.vec( '/model/chem/psd/adaptGluR' )
- chemR = moose.vec( '/model/chem/psd/psdGluR' )
- assert( len( adaptGluR ) == 5 )
- for i in range( 5 ):
- path = '/model/elec/head' + str( i ) + '/gluR'
- elecR = moose.element( path )
- moose.connect( adaptGluR[i], 'outputSrc', elecR, 'setGbar', 'Single' )
+ chemR = moose.vec( '/model/chem/psd/psdGluR' )
+ assert( len( adaptGluR ) == 5 )
+ for i in range( 5 ):
+ path = '/model/elec/head' + str( i ) + '/gluR'
+ elecR = moose.element( path )
+ moose.connect( adaptGluR[i], 'outputSrc', elecR, 'setGbar', 'Single' )
#moose.connect( chemR, 'nOut', adaptGluR, 'input', 'OneToOne' )
- # Ksolve isn't sending nOut. Not good. So have to use requestOut.
+ # Ksolve isn't sending nOut. Not good. So have to use requestOut.
moose.connect( adaptGluR, 'requestOut', chemR, 'getN', 'OneToOne' )
adaptGluR.outputOffset = 1e-7 # pS
adaptGluR.scale = 1e-6 / 100 # from n to pS
@@ -222,10 +220,10 @@ def makeNeuroMeshModel():
adaptK = moose.Adaptor( '/model/chem/dend/adaptK' )
chemK = moose.element( '/model/chem/dend/kChan' )
elecK = moose.element( '/model/elec/compt/K' )
- moose.connect( adaptK, 'requestOut', chemK, 'getConc', 'OneToAll' )
- moose.connect( adaptK, 'outputSrc', elecK, 'setGbar', 'Single' )
- adaptK.scale = 0.3 # from mM to Siemens
- """
+ moose.connect( adaptK, 'requestOut', chemK, 'getConc', 'OneToAll' )
+ moose.connect( adaptK, 'outputSrc', elecK, 'setGbar', 'Single' )
+ adaptK.scale = 0.3 # from mM to Siemens
+ """
def makeElecPlots():
graphs = moose.Neutral( '/graphs' )
@@ -240,134 +238,134 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head_14_13/NMDA_Ca_conc', 'getCa', 'elec/spine_13Ca' )
def makeChemPlots():
- spineMesh = moose.element( '/model/chem/spine' )
- middleSpine = 6
- # handy lookup function to find which voxel # the spine is on.
- midSpineVoxel = spineMesh.parentVoxel[middleSpine]
- print(spineMesh.parentVoxel)
- graphs = moose.Neutral( '/graphs' )
- addPlot( '/model/chem/psd/tot_PSD_R[0]', 'getN', 'psd0R' )
- addPlot( '/model/chem/psd/tot_PSD_R[1]', 'getN', 'psd1R' )
- addPlot( '/model/chem/psd/tot_PSD_R[2]', 'getN', 'psd2R' )
- addPlot( '/model/chem/psd/CaM_dash_Ca4[0]', 'getConc', 'psdCaM0' )
- addPlot( '/model/chem/psd/CaM_dash_Ca4[6]', 'getConc', 'psdCaM6' )
- addPlot( '/model/chem/psd/CaM_CaN[0]', 'getConc', 'CaM_CaN' )
- addPlot( '/model/chem/psd/PP1_dash_active[0]', 'getConc', 'PP1_active0' )
- addPlot( '/model/chem/psd/PP1_dash_active[6]', 'getConc', 'psdPP1_active6' )
- addPlot( '/model/chem/psd/actCaMKII[6]', 'getConc', 'psdCaMKII6' )
- addPlot( '/model/chem/spine/actCaMKII[6]', 'getConc', 'spineCaMKII6' )
- addPlot( '/model/chem/psd/Ca[0]', 'getConc', 'psd0Ca' )
- addPlot( '/model/chem/psd/Ca[6]', 'getConc', 'psd6Ca' )
- addPlot( '/model/chem/psd/Ca[12]', 'getConc', 'psd12Ca' )
-
- addPlot( '/model/chem/spine/Ca[0]', 'getConc', 'spine0Ca' )
- addPlot( '/model/chem/spine/Ca[6]', 'getConc', 'spine6Ca' )
- addPlot( '/model/chem/spine/Ca[12]', 'getConc', 'spine12Ca' )
-
- addPlot( '/model/chem/dend/DEND/Ca[0]', 'getConc', 'dend0Ca' )
- path = '/model/chem/dend/DEND/Ca['
- addPlot( path + str( midSpineVoxel ) + ']', 'getConc', 'dendMidCa' )
- addPlot( path + str( midSpineVoxel+2 ) + ']', 'getConc', 'dendMid2Ca' )
- addPlot( path + str( midSpineVoxel+4 ) + ']', 'getConc', 'dendMid4Ca' )
- addPlot( path + str( midSpineVoxel+6 ) + ']', 'getConc', 'dendMid6Ca' )
- addPlot( '/model/chem/dend/DEND/Ca[144]', 'getConc', 'dend144Ca' )
-
- #addPlot( '/n/dend/Ca', 'getConc', 'dendCa' )
- #addPlot( '/n/dend/inact_kinase', 'getConc', 'inactDendKinase' )
- #addPlot( '/n/psd/psdGluR', 'getN', 'psdGluR' )
- addPlot( '/model/chem/psd/CaMKII_dash_CaM[6]', 'getConc', 'psdCaM_CaMKII6' )
- addPlot( '/model/chem/spine/CaMKII_dash_CaM[6]', 'getConc', 'spineCaM_CaMKII6' )
- addPlot( '/model/chem/spine/NMDAR[6]', 'getConc', 'psd_NMDAR6' )
+ spineMesh = moose.element( '/model/chem/spine' )
+ middleSpine = 6
+ # handy lookup function to find which voxel # the spine is on.
+ midSpineVoxel = spineMesh.parentVoxel[middleSpine]
+ print((spineMesh.parentVoxel))
+ graphs = moose.Neutral( '/graphs' )
+ addPlot( '/model/chem/psd/tot_PSD_R[0]', 'getN', 'psd0R' )
+ addPlot( '/model/chem/psd/tot_PSD_R[1]', 'getN', 'psd1R' )
+ addPlot( '/model/chem/psd/tot_PSD_R[2]', 'getN', 'psd2R' )
+ addPlot( '/model/chem/psd/CaM_dash_Ca4[0]', 'getConc', 'psdCaM0' )
+ addPlot( '/model/chem/psd/CaM_dash_Ca4[6]', 'getConc', 'psdCaM6' )
+ addPlot( '/model/chem/psd/CaM_CaN[0]', 'getConc', 'CaM_CaN' )
+ addPlot( '/model/chem/psd/PP1_dash_active[0]', 'getConc', 'PP1_active0' )
+ addPlot( '/model/chem/psd/PP1_dash_active[6]', 'getConc', 'psdPP1_active6' )
+ addPlot( '/model/chem/psd/actCaMKII[6]', 'getConc', 'psdCaMKII6' )
+ addPlot( '/model/chem/spine/actCaMKII[6]', 'getConc', 'spineCaMKII6' )
+ addPlot( '/model/chem/psd/Ca[0]', 'getConc', 'psd0Ca' )
+ addPlot( '/model/chem/psd/Ca[6]', 'getConc', 'psd6Ca' )
+ addPlot( '/model/chem/psd/Ca[12]', 'getConc', 'psd12Ca' )
+
+ addPlot( '/model/chem/spine/Ca[0]', 'getConc', 'spine0Ca' )
+ addPlot( '/model/chem/spine/Ca[6]', 'getConc', 'spine6Ca' )
+ addPlot( '/model/chem/spine/Ca[12]', 'getConc', 'spine12Ca' )
+
+ addPlot( '/model/chem/dend/DEND/Ca[0]', 'getConc', 'dend0Ca' )
+ path = '/model/chem/dend/DEND/Ca['
+ addPlot( path + str( midSpineVoxel ) + ']', 'getConc', 'dendMidCa' )
+ addPlot( path + str( midSpineVoxel+2 ) + ']', 'getConc', 'dendMid2Ca' )
+ addPlot( path + str( midSpineVoxel+4 ) + ']', 'getConc', 'dendMid4Ca' )
+ addPlot( path + str( midSpineVoxel+6 ) + ']', 'getConc', 'dendMid6Ca' )
+ addPlot( '/model/chem/dend/DEND/Ca[144]', 'getConc', 'dend144Ca' )
+
+ #addPlot( '/n/dend/Ca', 'getConc', 'dendCa' )
+ #addPlot( '/n/dend/inact_kinase', 'getConc', 'inactDendKinase' )
+ #addPlot( '/n/psd/psdGluR', 'getN', 'psdGluR' )
+ addPlot( '/model/chem/psd/CaMKII_dash_CaM[6]', 'getConc', 'psdCaM_CaMKII6' )
+ addPlot( '/model/chem/spine/CaMKII_dash_CaM[6]', 'getConc', 'spineCaM_CaMKII6' )
+ addPlot( '/model/chem/spine/NMDAR[6]', 'getConc', 'psd_NMDAR6' )
def testNeuroMeshMultiscale():
- elecDt = 50e-6
- chemDt = 1e-2
- cplotDt = 1e-2
- eplotDt = 1e-3
- plotName = 'nm.plot'
-
- makeNeuroMeshModel()
- print("after model is completely done")
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print(i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb)
-
- """
- for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if ( i[0].diffConst > 0 ):
- grandpaname = i.parent[0].parent.name + '/'
- paname = i.parent[0].name + '/'
- print grandpaname + paname + i[0].name, i[0].diffConst
- print 'Neighbors:'
- for t in moose.element( '/model/chem/spine/ksolve/junction' ).neighbors['masterJunction']:
- print 'masterJunction <-', t.path
- for t in moose.wildcardFind( '/model/chem/#/ksolve' ):
- k = moose.element( t[0] )
- print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
- """
- """
+ elecDt = 50e-6
+ chemDt = 1e-2
+ cplotDt = 1e-2
+ eplotDt = 1e-3
+ plotName = 'nm.plot'
+
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
+
+ """
+ for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if ( i[0].diffConst > 0 ):
+ grandpaname = i.parent[0].parent.name + '/'
+ paname = i.parent[0].name + '/'
+ print grandpaname + paname + i[0].name, i[0].diffConst
+ print 'Neighbors:'
+ for t in moose.element( '/model/chem/spine/ksolve/junction' ).neighbors['masterJunction']:
+ print 'masterJunction <-', t.path
+ for t in moose.wildcardFind( '/model/chem/#/ksolve' ):
+ k = moose.element( t[0] )
+ print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
+ """
+ """
moose.useClock( 4, '/model/chem/dend/dsolve', 'process' )
moose.useClock( 5, '/model/chem/dend/ksolve', 'process' )
moose.useClock( 5, '/model/chem/spine/ksolve', 'process' )
moose.useClock( 5, '/model/chem/psd/ksolve', 'process' )
- """
-
- makeChemPlots()
- makeElecPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 4, chemDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, cplotDt )
- moose.setClock( 8, eplotDt )
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
- moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
- moose.useClock( 6, '/model/chem/psd/adaptCa', 'process' )
- moose.useClock( 7, '/graphs/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#', 'process' )
- #hsolve = moose.HSolve( '/model/elec/hsolve' )
- #moose.useClock( 1, '/model/elec/hsolve', 'process' )
- #hsolve.dt = elecDt
- #hsolve.target = '/model/elec/compt'
- #moose.reinit()
- moose.reinit()
- """
- print 'pre'
- eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'dend'
- eca = moose.vec( '/model/chem/dend/DEND/Ca' )
- #for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
- for i in range( 13 ):
- print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
-
- print 'PSD'
- eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'spine'
- eca = moose.vec( '/model/chem/spine/SPINE/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- """
-
- moose.start( 0.5 )
- dumpPlots( plotName )
- print('All done')
+ """
+
+ makeChemPlots()
+ makeElecPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 4, chemDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, cplotDt )
+ moose.setClock( 8, eplotDt )
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
+ moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
+ moose.useClock( 6, '/model/chem/psd/adaptCa', 'process' )
+ moose.useClock( 7, '/graphs/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#', 'process' )
+ #hsolve = moose.HSolve( '/model/elec/hsolve' )
+ #moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ #hsolve.dt = elecDt
+ #hsolve.target = '/model/elec/compt'
+ #moose.reinit()
+ moose.reinit()
+ """
+ print 'pre'
+ eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'dend'
+ eca = moose.vec( '/model/chem/dend/DEND/Ca' )
+ #for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
+ for i in range( 13 ):
+ print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+
+ print 'PSD'
+ eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'spine'
+ eca = moose.vec( '/model/chem/spine/SPINE/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ """
+
+ moose.start( 0.5 )
+ dumpPlots( plotName )
+ print('All done')
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# loadMulti.py ends here.
diff --git a/moose-examples/snippets/MULTI/midchan.py b/moose-examples/snippets/MULTI/midchan.py
index 46890fae7207e5fda9a9e493c0c310039f92e4b1..af26757d85ccb6d0b229a191deef18363726c4a7 100644
--- a/moose-examples/snippets/MULTI/midchan.py
+++ b/moose-examples/snippets/MULTI/midchan.py
@@ -40,179 +40,168 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- moose.setCwe( '/library' )
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ moose.setCwe( '/library' )
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
+ return cellId
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
- #modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
+ #modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 10e-6 # Aim for 2 soma compartments.
- elec = loadElec()
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
-
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print 'ns = ', ns, ', ndc = ', ndc
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 36 ) #
- assert( ndc == 278 ) #
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print 'done setting path, numPools = ', nmdsolve.numPools
- assert( nmdsolve.numPools == 1 )
- assert( nmdsolve.numAllVoxels == ndc )
- assert( nmstoich.numAllPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
-
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print 'sdc = ', sdc
- assert( sdc == 13 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- print 'spine num Pools = ', smstoich.numAllPools
- assert( smstoich.numAllPools == 3 )
- assert( smdsolve.numPools == 3 )
- assert( smdsolve.numAllVoxels == sdc )
+ diffLength = 10e-6 # Aim for 2 soma compartments.
+ elec = loadElec()
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
+
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 36 ) #
+ assert( ndc == 278 ) #
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ assert( nmdsolve.numAllVoxels == ndc )
+ assert( nmstoich.numAllPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 13 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- assert( pmstoich.numAllPools == 3 )
- assert( pmdsolve.numPools == 3 )
- assert( pmdsolve.numAllVoxels == pdc )
- foo = moose.element( '/model/chem/psd/Ca' )
- print 'PSD: numfoo = ', foo.numData
- print 'PSD: numAllVoxels = ', pmksolve.numAllVoxels
-
- # Put in junctions between the diffusion solvers
- nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
-
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- ##################################################################
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
- adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
- chemCa = moose.vec( '/model/chem/spine/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( adaptCa ) == sdc )
- assert( len( chemCa ) == sdc )
- for i in range( sdc ):
- elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
- #print elecCa
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 1e-4 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
-
-
- moose.le( '/model/chem/dend/DEND' )
-
-
- compts = neuroCompt.elecComptList
- begin = neuroCompt.startVoxelInCompt
- end = neuroCompt.endVoxelInCompt
- aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
- adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
- chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( chemCa ) == ndc )
- for i in zip( compts, adaptCa, begin, end ):
- name = i[0].path + '/Ca_conc'
- if ( moose.exists( name ) ):
- elecCa = moose.element( name )
- #print i[2], i[3], ' ', elecCa
- #print i[1]
- moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
- for j in range( i[2], i[3] ):
- moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print('sdc = ', sdc)
+ assert( sdc == 13 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ print('spine num Pools = ', smstoich.numAllPools)
+ assert( smstoich.numAllPools == 3 )
+ assert( smdsolve.numPools == 3 )
+ assert( smdsolve.numAllVoxels == sdc )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 13 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ assert( pmstoich.numAllPools == 3 )
+ assert( pmdsolve.numPools == 3 )
+ assert( pmdsolve.numAllVoxels == pdc )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ print('PSD: numfoo = ', foo.numData)
+ print('PSD: numAllVoxels = ', pmksolve.numAllVoxels)
+
+ # Put in junctions between the diffusion solvers
+ nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
+
+
+ ##################################################################
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
+ adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
+ chemCa = moose.vec( '/model/chem/spine/Ca' )
+ assert( len( adaptCa ) == sdc )
+ assert( len( chemCa ) == sdc )
+ for i in range( sdc ):
+ elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
+ #print elecCa
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 1e-4 # 520 to 0.0052 mM
+
+
+ moose.le( '/model/chem/dend/DEND' )
+ compts = neuroCompt.elecComptList
+ begin = neuroCompt.startVoxelInCompt
+ end = neuroCompt.endVoxelInCompt
+ aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
+ adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
+ chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ assert( len( chemCa ) == ndc )
+ for i in zip( compts, adaptCa, begin, end ):
+ name = i[0].path + '/Ca_conc'
+ if ( moose.exists( name ) ):
+ elecCa = moose.element( name )
+ #print i[2], i[3], ' ', elecCa
+ #print i[1]
+ moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
+ for j in range( i[2], i[3] ):
+ moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print "addPlot failed: object is a Neutral: ", objpath
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print "addPlot failed: object not found: ", objpath
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def makeElecPlots():
graphs = moose.Neutral( '/graphs' )
@@ -225,121 +214,105 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head_14_12/NMDA_Ca_conc', 'getCa', 'elec/spine12Ca' )
def makeChemPlots():
- graphs = moose.Neutral( '/graphs' )
- chem = moose.Neutral( '/graphs/chem' )
- addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
- addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
- addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
- addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
- addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
- addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
- addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
+ graphs = moose.Neutral( '/graphs' )
+ chem = moose.Neutral( '/graphs/chem' )
+ addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
+ addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
+ addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
+ addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
+ addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
+ addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
+ addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
def testNeuroMeshMultiscale():
- elecDt = 50e-6
- chemDt = 0.005
- ePlotDt = 0.5e-3
- cPlotDt = 0.005
- plotName = 'nm.plot'
-
- makeNeuroMeshModel()
- print "after model is completely done"
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
-
- makeChemPlots()
- makeElecPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 4, chemDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, cPlotDt )
- moose.setClock( 8, ePlotDt )
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
- moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
- moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
- moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
- moose.useClock( 7, '/graphs/chem/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#', 'process' )
- #hsolve = moose.HSolve( '/model/elec/hsolve' )
- #moose.useClock( 1, '/model/elec/hsolve', 'process' )
- #hsolve.dt = elecDt
- #hsolve.target = '/model/elec/compt'
- #moose.reinit()
- moose.element( '/model/elec/soma' ).inject = 2e-10
- moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
- moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
- moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
- moose.reinit()
-
- moose.start( 0.25 )
-# moose.element( '/model/elec/soma' ).inject = 0
-# moose.start( 0.25 )
- plt.ion()
- fig = plt.figure( figsize=(8,8) )
- chem = fig.add_subplot( 311 )
- chem.set_ylim( 0, 0.002 )
- plt.ylabel( 'Conc (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
- line1, = chem.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- elec = fig.add_subplot( 312 )
- plt.ylabel( 'Vm (V)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = elec.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- lenplot = fig.add_subplot( 313 )
- plt.ylabel( 'Ca (mM )' )
- plt.xlabel( 'Voxel#)' )
-
- spineCa = moose.vec( '/model/chem/spine/Ca' )
- dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- line1, = lenplot.plot( range( len( spineCa ) ), spineCa.conc, label='spine' )
- line2, = lenplot.plot( range( len( dendCa ) ), dendCa.conc, label='dend' )
-
- ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConc]') ]
- line3, = lenplot.plot( range( len( ca ) ), ca, label='elec' )
-
- spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
- line4, = lenplot.plot( range( len( spineCaM ) ), spineCaM.conc, label='spineCaM' )
- psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
- line5, = lenplot.plot( range( len( psdCaM ) ), psdCaM.conc, label='psdCaM' )
- plt.legend()
-
-
- fig.canvas.draw()
- raw_input()
-
- '''
- for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
- t = numpy.arange( 0, x.vector.size, 1 )
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
- '''
-
- print 'All done'
+ elecDt = 50e-6
+ chemDt = 0.005
+ ePlotDt = 0.5e-3
+ cPlotDt = 0.005
+ plotName = 'nm.plot'
+
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
+
+ makeChemPlots()
+ makeElecPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 4, chemDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, cPlotDt )
+ moose.setClock( 8, ePlotDt )
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
+ #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
+ moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
+ moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
+ moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
+ moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
+ moose.useClock( 7, '/graphs/chem/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#', 'process' )
+ moose.element( '/model/elec/soma' ).inject = 2e-10
+ moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
+ moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
+ moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
+ moose.reinit()
+
+ moose.start( 0.25 )
+ plt.ion()
+ fig = plt.figure( figsize=(8,8) )
+ chem = fig.add_subplot( 311 )
+ chem.set_ylim( 0, 0.002 )
+ plt.ylabel( 'Conc (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
+ line1, = chem.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ elec = fig.add_subplot( 312 )
+ plt.ylabel( 'Vm (V)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = elec.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ lenplot = fig.add_subplot( 313 )
+ plt.ylabel( 'Ca (mM )' )
+ plt.xlabel( 'Voxel#)' )
+
+ spineCa = moose.vec( '/model/chem/spine/Ca' )
+ dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ line1, = lenplot.plot( list(range( len( spineCa ))), spineCa.conc, label='spine' )
+ line2, = lenplot.plot( list(range( len( dendCa ))), dendCa.conc, label='dend' )
+
+ ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConc]') ]
+ line3, = lenplot.plot( list(range( len( ca ))), ca, label='elec' )
+
+ spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
+ line4, = lenplot.plot( list(range( len( spineCaM ))), spineCaM.conc, label='spineCaM' )
+ psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
+ line5, = lenplot.plot( list(range( len( psdCaM ))), psdCaM.conc, label='psdCaM' )
+ plt.legend()
+
+
+ fig.canvas.draw()
+ eval(input())
+ print('All done')
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# minimal.py ends here.
diff --git a/moose-examples/snippets/MULTI/minchan.py b/moose-examples/snippets/MULTI/minchan.py
index 0f654f957290f6b1a1c3881cfb6457a18baaebb5..e2c30afffcbfeb4b7e359a912824b66a7df7be18 100644
--- a/moose-examples/snippets/MULTI/minchan.py
+++ b/moose-examples/snippets/MULTI/minchan.py
@@ -36,157 +36,150 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- moose.setCwe( '/library' )
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'mincell2.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ moose.setCwe( '/library' )
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'mincell2.p', '/model/elec', "Neutral" )
+ return cellId
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 6e-6 # Aim for 2 soma compartments.
- elec = loadElec()
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
+ diffLength = 6e-6 # Aim for 2 soma compartments.
+ elec = loadElec()
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print 'ns = ', ns, ', ndc = ', ndc
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 1 ) # soma/dend only
- assert( ndc == 2 ) # split into 2.
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print 'done setting path, numPools = ', nmdsolve.numPools
- assert( nmdsolve.numPools == 1 )
- assert( nmdsolve.numAllVoxels == 2 )
- assert( nmstoich.numAllPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 1 ) # soma/dend only
+ assert( ndc == 2 ) # split into 2.
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ assert( nmdsolve.numAllVoxels == 2 )
+ assert( nmstoich.numAllPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print 'sdc = ', sdc
- assert( sdc == 1 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- assert( smstoich.numAllPools == 3 )
- assert( smdsolve.numPools == 3 )
- assert( smdsolve.numAllVoxels == 1 )
-
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 1 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- assert( pmstoich.numAllPools == 3 )
- assert( pmdsolve.numPools == 3 )
- assert( pmdsolve.numAllVoxels == 1 )
- foo = moose.element( '/model/chem/psd/Ca' )
- print 'PSD: numfoo = ', foo.numData
- print 'PSD: numAllVoxels = ', pmksolve.numAllVoxels
-
- # Put in junctions between the diffusion solvers
- nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print(('sdc = ', sdc))
+ assert( sdc == 1 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ assert( smstoich.numAllPools == 3 )
+ assert( smdsolve.numPools == 3 )
+ assert( smdsolve.numAllVoxels == 1 )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 1 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ assert( pmstoich.numAllPools == 3 )
+ assert( pmdsolve.numPools == 3 )
+ assert( pmdsolve.numAllVoxels == 1 )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ print(('PSD: numfoo = ', foo.numData))
+ print(('PSD: numAllVoxels = ', pmksolve.numAllVoxels))
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
+ # Put in junctions between the diffusion solvers
+ nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', ndc )
- adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
- chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( adaptCa ) == ndc )
- assert( len( chemCa ) == ndc )
- path = '/model/elec/soma/Ca_conc'
- elecCa = moose.element( path )
- print "=========="
- print elecCa
- print adaptCa
- print chemCa
- moose.connect( elecCa, 'concOut', adaptCa[0], 'input', 'Single' )
- moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 1e-3 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
- #print adaptCa.scale
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', ndc )
+ adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
+ chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ print(('aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )))
+ assert( len( adaptCa ) == ndc )
+ assert( len( chemCa ) == ndc )
+ path = '/model/elec/soma/Ca_conc'
+ elecCa = moose.element( path )
+ print("==========")
+ print(elecCa)
+ print(adaptCa)
+ print(chemCa)
+ moose.connect( elecCa, 'concOut', adaptCa[0], 'input', 'Single' )
+ moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 1e-3 # 520 to 0.0052 mM
+ #print adaptCa.outputOffset
+ #print adaptCa.scale
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print "addPlot failed: object is a Neutral: ", objpath
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print "addPlot failed: object not found: ", objpath
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def makeElecPlots():
graphs = moose.Neutral( '/graphs' )
@@ -196,138 +189,128 @@ def makeElecPlots():
addPlot( '/model/elec/soma/Ca_conc', 'getCa', 'elec/somaCa' )
def makeChemPlots():
- graphs = moose.Neutral( '/graphs' )
- chem = moose.Neutral( '/graphs/chem' )
- addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
- addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
- addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
- addPlot( '/model/chem/spine/Ca', 'getConc', 'chem/spineCa' )
- addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
+ graphs = moose.Neutral( '/graphs' )
+ chem = moose.Neutral( '/graphs/chem' )
+ addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
+ addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
+ addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
+ addPlot( '/model/chem/spine/Ca', 'getConc', 'chem/spineCa' )
+ addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
def testNeuroMeshMultiscale():
- elecDt = 50e-6
- chemDt = 0.01
- ePlotDt = 0.5e-3
- cPlotDt = 0.01
- plotName = 'nm.plot'
-
- makeNeuroMeshModel()
- print "after model is completely done"
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
-
- """
- for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if ( i[0].diffConst > 0 ):
- grandpaname = i.parent[0].parent.name + '/'
- paname = i.parent[0].name + '/'
- print grandpaname + paname + i[0].name, i[0].diffConst
- print 'Neighbors:'
- for t in moose.element( '/model/chem/spine/ksolve/junction' ).neighbors['masterJunction']:
- print 'masterJunction <-', t.path
- for t in moose.wildcardFind( '/model/chem/#/ksolve' ):
- k = moose.element( t[0] )
- print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
- """
- '''
- moose.useClock( 4, '/model/chem/dend/dsolve', 'process' )
- moose.useClock( 5, '/model/chem/dend/ksolve', 'process' )
- moose.useClock( 5, '/model/chem/spine/ksolve', 'process' )
- moose.useClock( 5, '/model/chem/psd/ksolve', 'process' )
- '''
+ elecDt = 50e-6
+ chemDt = 0.01
+ ePlotDt = 0.5e-3
+ cPlotDt = 0.01
+ plotName = 'nm.plot'
- makeChemPlots()
- makeElecPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 4, chemDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, cPlotDt )
- moose.setClock( 8, ePlotDt )
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
- moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
- moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
- moose.useClock( 7, '/graphs/chem/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#', 'process' )
- #hsolve = moose.HSolve( '/model/elec/hsolve' )
- #moose.useClock( 1, '/model/elec/hsolve', 'process' )
- #hsolve.dt = elecDt
- #hsolve.target = '/model/elec/compt'
- #moose.reinit()
- moose.element( '/model/elec/spine_head' ).inject = 5e-12
- moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
- moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
- moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
- moose.reinit()
- """
- print 'pre'
- eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'dend'
- eca = moose.vec( '/model/chem/dend/DEND/Ca' )
- #for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
- for i in range( 13 ):
- print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
- print 'PSD'
- eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'spine'
- eca = moose.vec( '/model/chem/spine/SPINE/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- """
+ """
+ for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if ( i[0].diffConst > 0 ):
+ grandpaname = i.parent[0].parent.name + '/'
+ paname = i.parent[0].name + '/'
+ print grandpaname + paname + i[0].name, i[0].diffConst
+ print 'Neighbors:'
+ for t in moose.element( '/model/chem/spine/ksolve/junction' ).neighbors['masterJunction']:
+ print 'masterJunction <-', t.path
+ for t in moose.wildcardFind( '/model/chem/#/ksolve' ):
+ k = moose.element( t[0] )
+ print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
+ """
+ '''
+ moose.useClock( 4, '/model/chem/dend/dsolve', 'process' )
+ moose.useClock( 5, '/model/chem/dend/ksolve', 'process' )
+ moose.useClock( 5, '/model/chem/spine/ksolve', 'process' )
+ moose.useClock( 5, '/model/chem/psd/ksolve', 'process' )
+ '''
- moose.start( 0.5 )
- plt.ion()
- fig = plt.figure( figsize=(8,8) )
- chem = fig.add_subplot( 211 )
- chem.set_ylim( 0, 0.004 )
- plt.ylabel( 'Conc (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
- line1, = chem.plot( pos, x.vector, label=x.name )
- plt.legend()
+ makeChemPlots()
+ makeElecPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 4, chemDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, cPlotDt )
+ moose.setClock( 8, ePlotDt )
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
+ #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
+ moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
+ moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
+ moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
+ moose.useClock( 7, '/graphs/chem/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#', 'process' )
+ #hsolve = moose.HSolve( '/model/elec/hsolve' )
+ #moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ #hsolve.dt = elecDt
+ #hsolve.target = '/model/elec/compt'
+ #moose.reinit()
+ moose.element( '/model/elec/spine_head' ).inject = 5e-12
+ moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
+ moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
+ moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
+ moose.reinit()
+ """
+ print 'pre'
+ eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'dend'
+ eca = moose.vec( '/model/chem/dend/DEND/Ca' )
+ #for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
+ for i in range( 13 ):
+ print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- elec = fig.add_subplot( 212 )
- plt.ylabel( 'Vm (V)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = elec.plot( pos, x.vector, label=x.name )
- plt.legend()
+ print 'PSD'
+ eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'spine'
+ eca = moose.vec( '/model/chem/spine/SPINE/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ """
- fig.canvas.draw()
- raw_input()
-
- '''
- for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
- t = numpy.arange( 0, x.vector.size, 1 )
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
- '''
+ moose.start( 0.5 )
+ plt.ion()
+ fig = plt.figure( figsize=(8,8) )
+ chem = fig.add_subplot( 211 )
+ chem.set_ylim( 0, 0.004 )
+ plt.ylabel( 'Conc (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
+ line1, = chem.plot( pos, x.vector, label=x.name )
+ plt.legend()
- pylab.show()
- print 'All done'
+ elec = fig.add_subplot( 212 )
+ plt.ylabel( 'Vm (V)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = elec.plot( pos, x.vector, label=x.name )
+ plt.legend()
+ fig.canvas.draw()
+ eval(input())
+ pylab.show()
+ print('All done')
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# minimal.py ends here.
diff --git a/moose-examples/snippets/MULTI/minimal.py b/moose-examples/snippets/MULTI/minimal.py
index 5035acdf0edf761a36c03cd72ada8f2c3b33393f..b5c018da1fb5d517465a8ff26797fc8811a9be2b 100644
--- a/moose-examples/snippets/MULTI/minimal.py
+++ b/moose-examples/snippets/MULTI/minimal.py
@@ -36,138 +36,138 @@ import moose
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'mincell.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'mincell.p', '/model/elec', "Neutral" )
+ return cellId
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 20e-6 # Aim for just 3 compts.
- elec = loadElec()
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
+ diffLength = 20e-6 # Aim for just 3 compts.
+ elec = loadElec()
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print 'ns = ', ns, ', ndc = ', ndc
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 1 ) # dend, 5x (shaft+head)
- assert( ndc == 1 )
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print 'done setting path, numPools = ', nmdsolve.numPools
- assert( nmdsolve.numPools == 1 )
- assert( nmdsolve.numAllVoxels == 1 )
- assert( nmstoich.numAllPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 1 ) # dend, 5x (shaft+head)
+ assert( ndc == 1 )
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ assert( nmdsolve.numAllVoxels == 1 )
+ assert( nmstoich.numAllPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print 'sdc = ', sdc
- assert( sdc == 1 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- assert( smstoich.numAllPools == 3 )
- assert( smdsolve.numPools == 3 )
- assert( smdsolve.numAllVoxels == 1 )
-
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 1 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- assert( pmstoich.numAllPools == 3 )
- assert( pmdsolve.numPools == 3 )
- assert( pmdsolve.numAllVoxels == 1 )
- foo = moose.element( '/model/chem/psd/Ca' )
- print 'PSD: numfoo = ', foo.numData
- print 'PSD: numAllVoxels = ', pmksolve.numAllVoxels
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print(('sdc = ', sdc))
+ assert( sdc == 1 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ assert( smstoich.numAllPools == 3 )
+ assert( smdsolve.numPools == 3 )
+ assert( smdsolve.numAllVoxels == 1 )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 1 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ assert( pmstoich.numAllPools == 3 )
+ assert( pmdsolve.numPools == 3 )
+ assert( pmdsolve.numAllVoxels == 1 )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ print(('PSD: numfoo = ', foo.numData))
+ print(('PSD: numAllVoxels = ', pmksolve.numAllVoxels))
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
+ """
+ CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
+ print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
+ CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
+ print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
+ """
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/psd/adaptCa', pdc )
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/psd/adaptCa', pdc )
- adaptCa = moose.vec( '/model/chem/psd/adaptCa' )
- chemCa = moose.vec( '/model/chem/psd/Ca' )
- print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData
- assert( len( adaptCa ) == pdc )
- assert( len( chemCa ) == pdc )
- path = '/model/elec/spine_head'
- elecCa = moose.element( path )
- moose.connect( elecCa, 'VmOut', adaptCa[0], 'input', 'Single' )
- #moose.connect( adaptCa, 'outputSrc', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 1e-5 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
- #print adaptCa.scale
+ adaptCa = moose.vec( '/model/chem/psd/adaptCa' )
+ chemCa = moose.vec( '/model/chem/psd/Ca' )
+ print(('aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData))
+ assert( len( adaptCa ) == pdc )
+ assert( len( chemCa ) == pdc )
+ path = '/model/elec/spine_head'
+ elecCa = moose.element( path )
+ moose.connect( elecCa, 'VmOut', adaptCa[0], 'input', 'Single' )
+ #moose.connect( adaptCa, 'outputSrc', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 1e-5 # 520 to 0.0052 mM
+ #print adaptCa.outputOffset
+ #print adaptCa.scale
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print "addPlot failed: object is a Neutral: ", objpath
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print "addPlot failed: object not found: ", objpath
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def makeElecPlots():
graphs = moose.Neutral( '/graphs' )
@@ -176,135 +176,127 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head', 'getVm', 'elec/spineVm' )
def makeChemPlots():
- graphs = moose.Neutral( '/graphs' )
- chem = moose.Neutral( '/graphs/chem' )
- addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
- addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
- addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
- addPlot( '/model/chem/spine/Ca', 'getConc', 'chem/spineCa' )
- addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
+ graphs = moose.Neutral( '/graphs' )
+ chem = moose.Neutral( '/graphs/chem' )
+ addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
+ addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
+ addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
+ addPlot( '/model/chem/spine/Ca', 'getConc', 'chem/spineCa' )
+ addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
def testNeuroMeshMultiscale():
- elecDt = 50e-6
- chemDt = 1e-1
- plotDt = 1e-1
- plotName = 'nm.plot'
+ elecDt = 50e-6
+ chemDt = 1e-1
+ plotDt = 1e-1
+ plotName = 'nm.plot'
- makeNeuroMeshModel()
- print "after model is completely done"
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
- """
- for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if ( i[0].diffConst > 0 ):
- grandpaname = i.parent[0].parent.name + '/'
- paname = i.parent[0].name + '/'
- print grandpaname + paname + i[0].name, i[0].diffConst
- print 'Neighbors:'
- for t in moose.element( '/model/chem/spine/ksolve/junction' ).neighbors['masterJunction']:
- print 'masterJunction <-', t.path
- for t in moose.wildcardFind( '/model/chem/#/ksolve' ):
- k = moose.element( t[0] )
- print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
- """
- '''
- moose.useClock( 4, '/model/chem/dend/dsolve', 'process' )
- moose.useClock( 5, '/model/chem/dend/ksolve', 'process' )
- moose.useClock( 5, '/model/chem/spine/ksolve', 'process' )
- moose.useClock( 5, '/model/chem/psd/ksolve', 'process' )
- '''
+ """
+ for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if ( i[0].diffConst > 0 ):
+ grandpaname = i.parent[0].parent.name + '/'
+ paname = i.parent[0].name + '/'
+ print grandpaname + paname + i[0].name, i[0].diffConst
+ print 'Neighbors:'
+ for t in moose.element( '/model/chem/spine/ksolve/junction' ).neighbors['masterJunction']:
+ print 'masterJunction <-', t.path
+ for t in moose.wildcardFind( '/model/chem/#/ksolve' ):
+ k = moose.element( t[0] )
+ print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
+ """
- makeChemPlots()
- makeElecPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 4, chemDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, plotDt )
- moose.setClock( 8, plotDt )
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- #moose.useClock( 6, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 7, '/graphs/chem/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#', 'process' )
- moose.useClock( 5, '/model/chem/#/dsolve', 'process' )
- moose.useClock( 6, '/model/chem/#/ksolve', 'process' )
- #hsolve = moose.HSolve( '/model/elec/hsolve' )
- #moose.useClock( 1, '/model/elec/hsolve', 'process' )
- #hsolve.dt = elecDt
- #hsolve.target = '/model/elec/compt'
- #moose.reinit()
- moose.element( '/model/elec/spine_head' ).inject = 1e-9
- moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
- moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
- moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
- moose.reinit()
- """
- print 'pre'
- eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'dend'
- eca = moose.vec( '/model/chem/dend/DEND/Ca' )
- #for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
- for i in range( 13 ):
- print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ '''
+ moose.useClock( 4, '/model/chem/dend/dsolve', 'process' )
+ moose.useClock( 5, '/model/chem/dend/ksolve', 'process' )
+ moose.useClock( 5, '/model/chem/spine/ksolve', 'process' )
+ moose.useClock( 5, '/model/chem/psd/ksolve', 'process' )
+ '''
- print 'PSD'
- eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'spine'
- eca = moose.vec( '/model/chem/spine/SPINE/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- """
+ makeChemPlots()
+ makeElecPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 4, chemDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, plotDt )
+ moose.setClock( 8, plotDt )
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
+ #moose.useClock( 6, '/model/chem/##[ISA=Adaptor]', 'process' )
+ moose.useClock( 7, '/graphs/chem/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#', 'process' )
+ moose.useClock( 5, '/model/chem/#/dsolve', 'process' )
+ moose.useClock( 6, '/model/chem/#/ksolve', 'process' )
+ #hsolve = moose.HSolve( '/model/elec/hsolve' )
+ #moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ #hsolve.dt = elecDt
+ #hsolve.target = '/model/elec/compt'
+ #moose.reinit()
+ moose.element( '/model/elec/spine_head' ).inject = 1e-9
+ moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
+ moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
+ moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
+ moose.reinit()
+ """
+ print 'pre'
+ eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'dend'
+ eca = moose.vec( '/model/chem/dend/DEND/Ca' )
+ #for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
+ for i in range( 13 ):
+ print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- moose.start( 0.5 )
- plt.ion()
- fig = plt.figure( figsize=(8,8) )
- chem = fig.add_subplot( 211 )
- chem.set_ylim( 0, 0.004 )
- plt.ylabel( 'Conc (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
- pos = numpy.arange( 0, len(x.vector), 1 )
- line1, = chem.plot( pos, x.vector, label=x.name )
- plt.legend()
+ print 'PSD'
+ eca = moose.vec( '/model/chem/psd/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'spine'
+ eca = moose.vec( '/model/chem/spine/SPINE/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ """
- elec = fig.add_subplot( 212 )
- plt.ylabel( 'Vm (V)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
- pos = numpy.arange( 0, len(x.vector), 1 )
- line1, = elec.plot( pos, x.vector, label=x.name )
- plt.legend()
+ moose.start( 0.5 )
+ plt.ion()
+ fig = plt.figure( figsize=(8,8) )
+ chem = fig.add_subplot( 211 )
+ chem.set_ylim( 0, 0.004 )
+ plt.ylabel( 'Conc (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
+ pos = numpy.arange( 0, len(x.vector), 1 )
+ line1, = chem.plot( pos, x.vector, label=x.name )
+ plt.legend()
- fig.canvas.draw()
- raw_input()
-
- '''
- for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
- t = numpy.arange( 0, x.vector.size, 1 )
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
- '''
+ elec = fig.add_subplot( 212 )
+ plt.ylabel( 'Vm (V)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
+ pos = numpy.arange( 0, len(x.vector), 1 )
+ line1, = elec.plot( pos, x.vector, label=x.name )
+ plt.legend()
- print 'All done'
+ fig.canvas.draw()
+ eval(input())
+ print('All done')
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# minimal.py ends here.
diff --git a/moose-examples/snippets/MULTI/multi1.py b/moose-examples/snippets/MULTI/multi1.py
index f4fc54ef6badc8f213866781c5ca997a07d2a261..4f60c8d7ac244755f226cf3403bffd9941513f13 100644
--- a/moose-examples/snippets/MULTI/multi1.py
+++ b/moose-examples/snippets/MULTI/multi1.py
@@ -29,7 +29,6 @@
# Code:
import sys
-sys.path.append('../../python')
import os
os.environ['NUMPTHREADS'] = '1'
import math
@@ -41,179 +40,165 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- moose.setCwe( '/library' )
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ moose.setCwe( '/library' )
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
+ return cellId
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
- #modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
+ #modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 10e-6 # Aim for 2 soma compartments.
- elec = loadElec()
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
-
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print 'ns = ', ns, ', ndc = ', ndc
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 36 ) #
- assert( ndc == 278 ) #
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print 'done setting path, numPools = ', nmdsolve.numPools
- assert( nmdsolve.numPools == 1 )
- assert( nmdsolve.numAllVoxels == ndc )
- assert( nmstoich.numAllPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
+ diffLength = 10e-6 # Aim for 2 soma compartments.
+ elec = loadElec()
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
+
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 36 ) #
+ assert( ndc == 278 ) #
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ assert( nmdsolve.numAllVoxels == ndc )
+ assert( nmstoich.numAllPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print 'sdc = ', sdc
- assert( sdc == 13 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- print 'spine num Pools = ', smstoich.numAllPools
- assert( smstoich.numAllPools == 3 )
- assert( smdsolve.numPools == 3 )
- assert( smdsolve.numAllVoxels == sdc )
-
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 13 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- assert( pmstoich.numAllPools == 3 )
- assert( pmdsolve.numPools == 3 )
- assert( pmdsolve.numAllVoxels == pdc )
- foo = moose.element( '/model/chem/psd/Ca' )
- print 'PSD: numfoo = ', foo.numData
- print 'PSD: numAllVoxels = ', pmksolve.numAllVoxels
-
- # Put in junctions between the diffusion solvers
- nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
-
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- ##################################################################
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
- adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
- chemCa = moose.vec( '/model/chem/spine/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( adaptCa ) == sdc )
- assert( len( chemCa ) == sdc )
- for i in range( sdc ):
- elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
- #print elecCa
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 1e-4 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
-
-
- moose.le( '/model/chem/dend/DEND' )
-
-
- compts = neuroCompt.elecComptList
- begin = neuroCompt.startVoxelInCompt
- end = neuroCompt.endVoxelInCompt
- aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
- adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
- chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( chemCa ) == ndc )
- for i in zip( compts, adaptCa, begin, end ):
- name = i[0].path + '/Ca_conc'
- if ( moose.exists( name ) ):
- elecCa = moose.element( name )
- #print i[2], i[3], ' ', elecCa
- #print i[1]
- moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
- for j in range( i[2], i[3] ):
- moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print(('sdc = ', sdc))
+ assert( sdc == 13 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ print(('spine num Pools = ', smstoich.numAllPools))
+ assert( smstoich.numAllPools == 3 )
+ assert( smdsolve.numPools == 3 )
+ assert( smdsolve.numAllVoxels == sdc )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 13 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ assert( pmstoich.numAllPools == 3 )
+ assert( pmdsolve.numPools == 3 )
+ assert( pmdsolve.numAllVoxels == pdc )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ print(('PSD: numfoo = ', foo.numData))
+ print(('PSD: numAllVoxels = ', pmksolve.numAllVoxels))
+
+ # Put in junctions between the diffusion solvers
+ nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
+
+ ##################################################################
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
+ adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
+ chemCa = moose.vec( '/model/chem/spine/Ca' )
+ assert( len( adaptCa ) == sdc )
+ assert( len( chemCa ) == sdc )
+ for i in range( sdc ):
+ elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 1e-4 # 520 to 0.0052 mM
+
+ moose.le( '/model/chem/dend/DEND' )
+ compts = neuroCompt.elecComptList
+ begin = neuroCompt.startVoxelInCompt
+ end = neuroCompt.endVoxelInCompt
+ aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
+ adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
+ chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ assert( len( chemCa ) == ndc )
+ for i in zip( compts, adaptCa, begin, end ):
+ name = i[0].path + '/Ca_conc'
+ if ( moose.exists( name ) ):
+ elecCa = moose.element( name )
+ #print i[2], i[3], ' ', elecCa
+ #print i[1]
+ moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
+ for j in range( i[2], i[3] ):
+ moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print "addPlot failed: object is a Neutral: ", objpath
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print "addPlot failed: object not found: ", objpath
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def makeCaPlots():
graphs = moose.Neutral( '/graphs' )
@@ -230,68 +215,68 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head_14_4', 'getVm', 'elec/spineVm' )
def makeChemPlots():
- graphs = moose.Neutral( '/graphs' )
- chem = moose.Neutral( '/graphs/chem' )
- addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
- addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
- addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
- addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
- addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
- addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
- addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
+ graphs = moose.Neutral( '/graphs' )
+ chem = moose.Neutral( '/graphs/chem' )
+ addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
+ addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
+ addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
+ addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
+ addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
+ addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
+ addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
def makeGraphics():
- plt.ion()
- fig = plt.figure( figsize=(10,16) )
- chem = fig.add_subplot( 411 )
- chem.set_ylim( 0, 0.006 )
- plt.ylabel( 'Conc (mM)' )
- plt.xlabel( 'time (seconds)' )
- plt.legend()
-
- elec = fig.add_subplot( 412 )
- plt.ylabel( 'Vm (V)' )
- plt.xlabel( 'time (seconds)' )
- plt.legend()
-
- ca = fig.add_subplot( 413 )
- plt.ylabel( '[Ca] (mM)' )
- plt.xlabel( 'time (seconds)' )
- plt.legend()
-
- lenplot = fig.add_subplot( 414 )
- plt.ylabel( 'Ca (mM )' )
- plt.xlabel( 'Voxel#)' )
- plt.legend()
- spineCa = moose.vec( '/model/chem/spine/Ca' )
- dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- line1, = lenplot.plot( range( len( spineCa ) ), spineCa.conc, label='spine' )
- line2, = lenplot.plot( range( len( dendCa ) ), dendCa.conc, label='dend' )
-
- Ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
- line3, = lenplot.plot( range( len( Ca ) ), Ca, label='elec' )
-
- spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
- line4, = lenplot.plot( range( len( spineCaM ) ), spineCaM.conc, label='spineCaM' )
- psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
- line5, = lenplot.plot( range( len( psdCaM ) ), psdCaM.conc, label='psdCaM' )
- lenplot.set_ylim( 0, 0.01 )
- fig.canvas.draw()
- return ( chem, elec, ca, lenplot, fig, line1, line2, line3, line4, line5 )
+ plt.ion()
+ fig = plt.figure( figsize=(10,16) )
+ chem = fig.add_subplot( 411 )
+ chem.set_ylim( 0, 0.006 )
+ plt.ylabel( 'Conc (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ plt.legend()
+
+ elec = fig.add_subplot( 412 )
+ plt.ylabel( 'Vm (V)' )
+ plt.xlabel( 'time (seconds)' )
+ plt.legend()
+
+ ca = fig.add_subplot( 413 )
+ plt.ylabel( '[Ca] (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ plt.legend()
+
+ lenplot = fig.add_subplot( 414 )
+ plt.ylabel( 'Ca (mM )' )
+ plt.xlabel( 'Voxel#)' )
+ plt.legend()
+ spineCa = moose.vec( '/model/chem/spine/Ca' )
+ dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ line1, = lenplot.plot( list(range( len( spineCa ))), spineCa.conc, label='spine' )
+ line2, = lenplot.plot( list(range( len( dendCa ))), dendCa.conc, label='dend' )
+
+ Ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
+ line3, = lenplot.plot( list(range( len( Ca ))), Ca, label='elec' )
+
+ spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
+ line4, = lenplot.plot( list(range( len( spineCaM ))), spineCaM.conc, label='spineCaM' )
+ psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
+ line5, = lenplot.plot( list(range( len( psdCaM ))), psdCaM.conc, label='psdCaM' )
+ lenplot.set_ylim( 0, 0.01 )
+ fig.canvas.draw()
+ return ( chem, elec, ca, lenplot, fig, line1, line2, line3, line4, line5 )
def updateGraphics( plotlist ):
- spineCa = moose.vec( '/model/chem/spine/Ca' )
- dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- plotlist[5].set_ydata( spineCa.conc )
- plotlist[6].set_ydata( dendCa.conc )
-
- ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
- plotlist[7].set_ydata( ca )
- spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
- plotlist[8].set_ydata( spineCaM.conc )
- psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
- plotlist[9].set_ydata( psdCaM.conc )
- plotlist[4].canvas.draw()
+ spineCa = moose.vec( '/model/chem/spine/Ca' )
+ dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ plotlist[5].set_ydata( spineCa.conc )
+ plotlist[6].set_ydata( dendCa.conc )
+
+ ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
+ plotlist[7].set_ydata( ca )
+ spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
+ plotlist[8].set_ydata( spineCaM.conc )
+ psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
+ plotlist[9].set_ydata( psdCaM.conc )
+ plotlist[4].canvas.draw()
def finalizeGraphics( plotlist, cPlotDt, ePlotDt ):
for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
@@ -306,59 +291,49 @@ def finalizeGraphics( plotlist, cPlotDt, ePlotDt ):
pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
line1, = plotlist[2].plot( pos, x.vector, label=x.name )
plotlist[4].canvas.draw()
- raw_input()
+ eval(input())
def testNeuroMeshMultiscale():
- runtime = 0.5
- #elecDt = 0.2e-6
- elecDt = 10e-6
- chemDt = 0.0025
- ePlotDt = 0.5e-3
- cPlotDt = 0.0025
- plotName = 'nm.plot'
-
- makeNeuroMeshModel()
- print "after model is completely done"
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
-
- makeChemPlots()
- makeElecPlots()
- makeCaPlots()
- for i in range (10):
- moose.setClock( i, elecDt )
- for i in range ( 10, 20 ):
- moose.setClock( i, chemDt )
- moose.setClock( 8, ePlotDt )
- moose.setClock( 18, cPlotDt )
- moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
- moose.useClock( 18, '/graphs/chem/#', 'process' )
- hsolve = moose.HSolve( '/model/elec/hsolve' )
- hsolve.dt = elecDt
- hsolve.target = '/model/elec/compt'
- plotlist = makeGraphics()
- moose.reinit()
- moose.element( '/model/elec/soma' ).inject = 2e-10
- moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
- moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
- moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
- moose.reinit()
-
- numDivs = 200
- partialRuntime = runtime / numDivs
- for i in range( numDivs ):
- moose.start( partialRuntime )
- updateGraphics( plotlist )
-# moose.element( '/model/elec/soma' ).inject = 0
-# moose.start( 0.25 )
- finalizeGraphics( plotlist, cPlotDt, ePlotDt )
+ runtime = 0.5
+ #elecDt = 0.2e-6
+ elecDt = 10e-6
+ chemDt = 0.0025
+ ePlotDt = 0.5e-3
+ cPlotDt = 0.0025
+ plotName = 'nm.plot'
+
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
+
+ makeChemPlots()
+ makeElecPlots()
+ makeCaPlots()
+ hsolve = moose.HSolve( '/model/elec/hsolve' )
+ hsolve.dt = elecDt
+ hsolve.target = '/model/elec/compt'
+ plotlist = makeGraphics()
+ moose.reinit()
+ moose.element( '/model/elec/soma' ).inject = 2e-10
+ moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
+ moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
+ moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
+ moose.reinit()
+
+ numDivs = 200
+ partialRuntime = runtime / numDivs
+ for i in range( numDivs ):
+ moose.start( partialRuntime )
+ updateGraphics( plotlist )
+ finalizeGraphics( plotlist, cPlotDt, ePlotDt )
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# minimal.py ends here.
diff --git a/moose-examples/snippets/MULTI/multi1_ee.py b/moose-examples/snippets/MULTI/multi1_ee.py
index 3f3dc43dfc7fb95b45979b52b6fc6427d100af82..e37a2e17ccac75a5182c42325c3bc7cc5c7a15b2 100644
--- a/moose-examples/snippets/MULTI/multi1_ee.py
+++ b/moose-examples/snippets/MULTI/multi1_ee.py
@@ -29,9 +29,7 @@
# Code:
import sys
-sys.path.append('../../python')
import os
-os.environ['NUMPTHREADS'] = '1'
import math
import numpy
import matplotlib.pyplot as plt
@@ -41,179 +39,161 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- moose.setCwe( '/library' )
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ moose.setCwe( '/library' )
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
+ return cellId
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
- #modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ modelId = moose.loadModel( 'minimal.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 10e-6 # Aim for 2 soma compartments.
- elec = loadElec()
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
-
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print 'ns = ', ns, ', ndc = ', ndc
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 36 ) #
- assert( ndc == 278 ) #
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print 'done setting path, numPools = ', nmdsolve.numPools
- assert( nmdsolve.numPools == 1 )
- assert( nmdsolve.numAllVoxels == ndc )
- assert( nmstoich.numAllPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
-
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print 'sdc = ', sdc
- assert( sdc == 13 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- print 'spine num Pools = ', smstoich.numAllPools
- assert( smstoich.numAllPools == 3 )
- assert( smdsolve.numPools == 3 )
- assert( smdsolve.numAllVoxels == sdc )
+ diffLength = 10e-6 # Aim for 2 soma compartments.
+ elec = loadElec()
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
+
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 36 ) #
+ assert( ndc == 278 ) #
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ assert( nmdsolve.numAllVoxels == ndc )
+ assert( nmstoich.numAllPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 13 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- assert( pmstoich.numAllPools == 3 )
- assert( pmdsolve.numPools == 3 )
- assert( pmdsolve.numAllVoxels == pdc )
- foo = moose.element( '/model/chem/psd/Ca' )
- print 'PSD: numfoo = ', foo.numData
- print 'PSD: numAllVoxels = ', pmksolve.numAllVoxels
-
- # Put in junctions between the diffusion solvers
- nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
-
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- ##################################################################
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
- adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
- chemCa = moose.vec( '/model/chem/spine/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( adaptCa ) == sdc )
- assert( len( chemCa ) == sdc )
- for i in range( sdc ):
- elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
- #print elecCa
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 1e-4 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
-
-
- moose.le( '/model/chem/dend/DEND' )
-
-
- compts = neuroCompt.elecComptList
- begin = neuroCompt.startVoxelInCompt
- end = neuroCompt.endVoxelInCompt
- aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
- adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
- chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( chemCa ) == ndc )
- for i in zip( compts, adaptCa, begin, end ):
- name = i[0].path + '/Ca_conc'
- if ( moose.exists( name ) ):
- elecCa = moose.element( name )
- #print i[2], i[3], ' ', elecCa
- #print i[1]
- moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
- for j in range( i[2], i[3] ):
- moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print(('sdc = ', sdc))
+ assert( sdc == 13 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ print(('spine num Pools = ', smstoich.numAllPools))
+ assert( smstoich.numAllPools == 3 )
+ assert( smdsolve.numPools == 3 )
+ assert( smdsolve.numAllVoxels == sdc )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 13 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ assert( pmstoich.numAllPools == 3 )
+ assert( pmdsolve.numPools == 3 )
+ assert( pmdsolve.numAllVoxels == pdc )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ print(('PSD: numfoo = ', foo.numData))
+ print(('PSD: numAllVoxels = ', pmksolve.numAllVoxels))
+
+ # Put in junctions between the diffusion solvers
+ nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
+
+ ##################################################################
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
+ adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
+ chemCa = moose.vec( '/model/chem/spine/Ca' )
+ assert( len( adaptCa ) == sdc )
+ assert( len( chemCa ) == sdc )
+ for i in range( sdc ):
+ elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
+ #print elecCa
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 1e-4 # 520 to 0.0052 mM
+ moose.le( '/model/chem/dend/DEND' )
+ compts = neuroCompt.elecComptList
+ begin = neuroCompt.startVoxelInCompt
+ end = neuroCompt.endVoxelInCompt
+ aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
+ adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
+ chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ assert( len( chemCa ) == ndc )
+ for i in zip( compts, adaptCa, begin, end ):
+ name = i[0].path + '/Ca_conc'
+ if ( moose.exists( name ) ):
+ elecCa = moose.element( name )
+ moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
+ for j in range( i[2], i[3] ):
+ moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print "addPlot failed: object is a Neutral: ", objpath
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print "addPlot failed: object not found: ", objpath
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def makeCaPlots():
graphs = moose.Neutral( '/graphs' )
@@ -230,137 +210,135 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head_14_4', 'getVm', 'elec/spineVm' )
def makeChemPlots():
- graphs = moose.Neutral( '/graphs' )
- chem = moose.Neutral( '/graphs/chem' )
- addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
- addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
- addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
- addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
- addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
- addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
- addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
+ graphs = moose.Neutral( '/graphs' )
+ chem = moose.Neutral( '/graphs/chem' )
+ addPlot( '/model/chem/psd/Ca_CaM', 'getConc', 'chem/psdCaCam' )
+ addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
+ addPlot( '/model/chem/spine/Ca_CaM', 'getConc', 'chem/spineCaCam' )
+ addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
+ addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
+ addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
+ addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
def makeGraphics( cPlotDt, ePlotDt ):
- plt.ion()
- fig = plt.figure( figsize=(10,16) )
- chem = fig.add_subplot( 411 )
- chem.set_ylim( 0, 0.006 )
- plt.ylabel( 'Conc (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
- line1, = chem.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- elec = fig.add_subplot( 412 )
- plt.ylabel( 'Vm (V)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = elec.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- ca = fig.add_subplot( 413 )
- plt.ylabel( '[Ca] (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/ca/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = ca.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- lenplot = fig.add_subplot( 414 )
- plt.ylabel( 'Ca (mM )' )
- plt.xlabel( 'Voxel#)' )
-
- spineCa = moose.vec( '/model/chem/spine/Ca' )
- dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- line1, = lenplot.plot( range( len( spineCa ) ), spineCa.conc, label='spine' )
- line2, = lenplot.plot( range( len( dendCa ) ), dendCa.conc, label='dend' )
-
- ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
- line3, = lenplot.plot( range( len( ca ) ), ca, label='elec' )
-
- spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
- line4, = lenplot.plot( range( len( spineCaM ) ), spineCaM.conc, label='spineCaM' )
- psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
- line5, = lenplot.plot( range( len( psdCaM ) ), psdCaM.conc, label='psdCaM' )
- plt.legend()
-
-
- fig.canvas.draw()
- raw_input()
+ plt.ion()
+ fig = plt.figure( figsize=(10,16) )
+ chem = fig.add_subplot( 411 )
+ chem.set_ylim( 0, 0.006 )
+ plt.ylabel( 'Conc (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
+ line1, = chem.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ elec = fig.add_subplot( 412 )
+ plt.ylabel( 'Vm (V)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = elec.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ ca = fig.add_subplot( 413 )
+ plt.ylabel( '[Ca] (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/ca/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = ca.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ lenplot = fig.add_subplot( 414 )
+ plt.ylabel( 'Ca (mM )' )
+ plt.xlabel( 'Voxel#)' )
+
+ spineCa = moose.vec( '/model/chem/spine/Ca' )
+ dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ line1, = lenplot.plot( list(range( len( spineCa ))), spineCa.conc, label='spine' )
+ line2, = lenplot.plot( list(range( len( dendCa ))), dendCa.conc, label='dend' )
+
+ ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
+ line3, = lenplot.plot( list(range( len( ca ))), ca, label='elec' )
+
+ spineCaM = moose.vec( '/model/chem/spine/Ca_CaM' )
+ line4, = lenplot.plot( list(range( len( spineCaM ))), spineCaM.conc, label='spineCaM' )
+ psdCaM = moose.vec( '/model/chem/psd/Ca_CaM' )
+ line5, = lenplot.plot( list(range( len( psdCaM ))), psdCaM.conc, label='psdCaM' )
+ plt.legend()
+
+
+ fig.canvas.draw()
+ eval(input())
- '''
- for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
- t = numpy.arange( 0, x.vector.size, 1 )
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
- '''
+ '''
+ for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
+ t = numpy.arange( 0, x.vector.size, 1 )
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
+ '''
- print 'All done'
+ print('All done')
def testNeuroMeshMultiscale():
- runtime = 0.5
- elecDt = 0.2e-6
- chemDt = 0.005
- ePlotDt = 0.5e-3
- cPlotDt = 0.005
- plotName = 'nm.plot'
-
- makeNeuroMeshModel()
- print "after model is completely done"
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
-
- makeChemPlots()
- makeElecPlots()
- makeCaPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 4, chemDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, cPlotDt )
- moose.setClock( 8, ePlotDt )
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- #moose.useClock( 2, '/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
- moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
- moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
- moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
- moose.useClock( 7, '/graphs/chem/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
- '''
- hsolve = moose.HSolve( '/model/elec/hsolve' )
- moose.useClock( 1, '/model/elec/hsolve', 'process' )
- hsolve.dt = elecDt
- hsolve.target = '/model/elec/compt'
- '''
- moose.reinit()
- moose.element( '/model/elec/soma' ).inject = 2e-10
- moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
- moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
- moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
- moose.reinit()
-
- moose.start( runtime )
-# moose.element( '/model/elec/soma' ).inject = 0
-# moose.start( 0.25 )
- makeGraphics( cPlotDt, ePlotDt )
+ runtime = 0.5
+ elecDt = 0.2e-6
+ chemDt = 0.005
+ ePlotDt = 0.5e-3
+ cPlotDt = 0.005
+ plotName = 'nm.plot'
+
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
+
+ makeChemPlots()
+ makeElecPlots()
+ makeCaPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 4, chemDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, cPlotDt )
+ moose.setClock( 8, ePlotDt )
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ #moose.useClock( 2, '/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
+ #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
+ moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
+ moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
+ moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
+ moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
+ moose.useClock( 7, '/graphs/chem/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
+ '''
+ hsolve = moose.HSolve( '/model/elec/hsolve' )
+ moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ hsolve.dt = elecDt
+ hsolve.target = '/model/elec/compt'
+ '''
+ moose.reinit()
+ moose.element( '/model/elec/soma' ).inject = 2e-10
+ moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
+ moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
+ moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
+ moose.reinit()
+
+ moose.start( runtime )
+ makeGraphics( cPlotDt, ePlotDt )
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# minimal.py ends here.
diff --git a/moose-examples/snippets/MULTI/multi2.py b/moose-examples/snippets/MULTI/multi2.py
index 373e25a7ad949abacbde64c2f5a2afc801e272ae..cae9588080f90ab9fc069f13c0e09392319376bc 100644
--- a/moose-examples/snippets/MULTI/multi2.py
+++ b/moose-examples/snippets/MULTI/multi2.py
@@ -44,180 +44,165 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- moose.setCwe( '/library' )
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ moose.setCwe( '/library' )
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
+ return cellId
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- modelId = moose.loadModel( 'separate_compts.g', '/model/chem', 'ee' )
- #modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ modelId = moose.loadModel( 'separate_compts.g', '/model/chem', 'ee' )
+ #modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 10e-6 # Aim for 2 soma compartments.
- elec = loadElec()
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
-
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print 'ns = ', ns, ', ndc = ', ndc
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 36 ) #
- assert( ndc == 278 ) #
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print 'done setting path, numPools = ', nmdsolve.numPools
- assert( nmdsolve.numPools == 1 )
- assert( nmdsolve.numAllVoxels == ndc )
- assert( nmstoich.numAllPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
-
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print 'sdc = ', sdc
- assert( sdc == 13 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- print 'spine num Pools = ', smstoich.numAllPools, smdsolve.numPools
- assert( smstoich.numAllPools == 35 )
- assert( smdsolve.numPools == 30 )
- assert( smdsolve.numAllVoxels == sdc )
+ diffLength = 10e-6 # Aim for 2 soma compartments.
+ elec = loadElec()
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
+
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 36 ) #
+ assert( ndc == 278 ) #
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ assert( nmdsolve.numAllVoxels == ndc )
+ assert( nmstoich.numAllPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 13 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- print 'psd num Pools = ', pmstoich.numAllPools, pmdsolve.numPools
- assert( pmstoich.numAllPools == 55 )
- assert( pmdsolve.numPools == 48 )
- assert( pmdsolve.numAllVoxels == pdc )
- foo = moose.element( '/model/chem/psd/Ca' )
- print 'PSD: numfoo = ', foo.numData
- print 'PSD: numAllVoxels = ', pmksolve.numAllVoxels
-
- # Put in junctions between the diffusion solvers
- nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
-
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- ##################################################################
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
- adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
- chemCa = moose.vec( '/model/chem/spine/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( adaptCa ) == sdc )
- assert( len( chemCa ) == sdc )
- for i in range( sdc ):
- elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
- #print elecCa
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 5e-3 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
-
-
- moose.le( '/model/chem/dend/DEND' )
-
-
- compts = neuroCompt.elecComptList
- begin = neuroCompt.startVoxelInCompt
- end = neuroCompt.endVoxelInCompt
- aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
- adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
- chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( chemCa ) == ndc )
- for i in zip( compts, adaptCa, begin, end ):
- name = i[0].path + '/Ca_conc'
- if ( moose.exists( name ) ):
- elecCa = moose.element( name )
- #print i[2], i[3], ' ', elecCa
- #print i[1]
- moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
- for j in range( i[2], i[3] ):
- moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print(('sdc = ', sdc))
+ assert( sdc == 13 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ print(('spine num Pools = ', smstoich.numAllPools, smdsolve.numPools))
+ assert( smstoich.numAllPools == 35 )
+ assert( smdsolve.numPools == 30 )
+ assert( smdsolve.numAllVoxels == sdc )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 13 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ print(('psd num Pools = ', pmstoich.numAllPools, pmdsolve.numPools))
+ assert( pmstoich.numAllPools == 55 )
+ assert( pmdsolve.numPools == 48 )
+ assert( pmdsolve.numAllVoxels == pdc )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ print(('PSD: numfoo = ', foo.numData))
+ print(('PSD: numAllVoxels = ', pmksolve.numAllVoxels))
+
+ # Put in junctions between the diffusion solvers
+ nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
+
+ ##################################################################
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
+ adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
+ chemCa = moose.vec( '/model/chem/spine/Ca' )
+ #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
+ assert( len( adaptCa ) == sdc )
+ assert( len( chemCa ) == sdc )
+ for i in range( sdc ):
+ elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 5e-3 # 520 to 0.0052 mM
+
+ moose.le( '/model/chem/dend/DEND' )
+ compts = neuroCompt.elecComptList
+ begin = neuroCompt.startVoxelInCompt
+ end = neuroCompt.endVoxelInCompt
+ aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
+ adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
+ chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ assert( len( chemCa ) == ndc )
+ for i in zip( compts, adaptCa, begin, end ):
+ name = i[0].path + '/Ca_conc'
+ if ( moose.exists( name ) ):
+ elecCa = moose.element( name )
+ moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
+ for j in range( i[2], i[3] ):
+ moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print "addPlot failed: object is a Neutral: ", objpath
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print "addPlot failed: object not found: ", objpath
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def makeCaPlots():
graphs = moose.Neutral( '/graphs' )
@@ -234,146 +219,117 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head_14_4', 'getVm', 'elec/spineVm' )
def makeChemPlots():
- graphs = moose.Neutral( '/graphs' )
- chem = moose.Neutral( '/graphs/chem' )
- addPlot( '/model/chem/psd/CaM_dash_Ca4', 'getConc', 'chem/psdCaCam' )
- addPlot( '/model/chem/psd/actCaMKII', 'getConc', 'chem/psdActCaMKII' )
- addPlot( '/model/chem/spine/CaM_dash_Ca4', 'getConc', 'chem/spineCaCam' )
- addPlot( '/model/chem/spine/CaM_dash_Ca4[12]', 'getConc', 'chem/spine12CaCam' )
- addPlot( '/model/chem/spine/actCaMKII', 'getConc', 'chem/spineActCaMKII' )
- addPlot( '/model/chem/spine/actCaMKII[11]', 'getConc', 'chem/spine12ActCaMKII' )
- addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
- addPlot( '/model/chem/psd/Ca[11]', 'getConc', 'chem/psd12Ca' )
- addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
- addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
- #addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
- #addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
+ graphs = moose.Neutral( '/graphs' )
+ chem = moose.Neutral( '/graphs/chem' )
+ addPlot( '/model/chem/psd/CaM_dash_Ca4', 'getConc', 'chem/psdCaCam' )
+ addPlot( '/model/chem/psd/actCaMKII', 'getConc', 'chem/psdActCaMKII' )
+ addPlot( '/model/chem/spine/CaM_dash_Ca4', 'getConc', 'chem/spineCaCam' )
+ addPlot( '/model/chem/spine/CaM_dash_Ca4[12]', 'getConc', 'chem/spine12CaCam' )
+ addPlot( '/model/chem/spine/actCaMKII', 'getConc', 'chem/spineActCaMKII' )
+ addPlot( '/model/chem/spine/actCaMKII[11]', 'getConc', 'chem/spine12ActCaMKII' )
+ addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
+ addPlot( '/model/chem/psd/Ca[11]', 'getConc', 'chem/psd12Ca' )
+ addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
+ addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
+ #addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
+ #addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
def makeGraphics( cPlotDt, ePlotDt ):
- plt.ion()
- fig = plt.figure( figsize=(10,16) )
- chem = fig.add_subplot( 411 )
- chem.set_ylim( 0, 0.006 )
- plt.ylabel( 'Conc (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
- line1, = chem.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- elec = fig.add_subplot( 412 )
- plt.ylabel( 'Vm (V)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = elec.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- ca = fig.add_subplot( 413 )
- plt.ylabel( '[Ca] (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/ca/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = ca.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- lenplot = fig.add_subplot( 414 )
- plt.ylabel( 'Ca (mM )' )
- plt.xlabel( 'Voxel#)' )
-
- spineCa = moose.vec( '/model/chem/spine/Ca' )
- dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- line1, = lenplot.plot( range( len( spineCa ) ), spineCa.conc, label='spine' )
- line2, = lenplot.plot( range( len( dendCa ) ), dendCa.conc, label='dend' )
-
- ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
- line3, = lenplot.plot( range( len( ca ) ), ca, label='elec' )
-
- spineCaM = moose.vec( '/model/chem/spine/CaM_dash_Ca4' )
- line4, = lenplot.plot( range( len( spineCaM ) ), spineCaM.conc, label='spineCaM' )
- psdCaM = moose.vec( '/model/chem/psd/CaM_dash_Ca4' )
- line5, = lenplot.plot( range( len( psdCaM ) ), psdCaM.conc, label='psdCaM' )
- plt.legend()
-
-
- fig.canvas.draw()
- raw_input()
-
- '''
- for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
- t = numpy.arange( 0, x.vector.size, 1 )
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
- '''
-
- print 'All done'
+ plt.ion()
+ fig = plt.figure( figsize=(10,16) )
+ chem = fig.add_subplot( 411 )
+ chem.set_ylim( 0, 0.006 )
+ plt.ylabel( 'Conc (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
+ line1, = chem.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ elec = fig.add_subplot( 412 )
+ plt.ylabel( 'Vm (V)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = elec.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ ca = fig.add_subplot( 413 )
+ plt.ylabel( '[Ca] (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/ca/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = ca.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ lenplot = fig.add_subplot( 414 )
+ plt.ylabel( 'Ca (mM )' )
+ plt.xlabel( 'Voxel#)' )
+
+ spineCa = moose.vec( '/model/chem/spine/Ca' )
+ dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ line1, = lenplot.plot( list(range( len( spineCa ))), spineCa.conc, label='spine' )
+ line2, = lenplot.plot( list(range( len( dendCa ))), dendCa.conc, label='dend' )
+
+ ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
+ line3, = lenplot.plot( list(range( len( ca ))), ca, label='elec' )
+
+ spineCaM = moose.vec( '/model/chem/spine/CaM_dash_Ca4' )
+ line4, = lenplot.plot( list(range( len( spineCaM ))), spineCaM.conc, label='spineCaM' )
+ psdCaM = moose.vec( '/model/chem/psd/CaM_dash_Ca4' )
+ line5, = lenplot.plot( list(range( len( psdCaM ))), psdCaM.conc, label='psdCaM' )
+ plt.legend()
+
+ fig.canvas.draw()
+ eval(input())
+ print('All done')
def testNeuroMeshMultiscale():
- useHsolve = 0
- runtime = 0.5
- elecDt = 10e-6
- chemDt = 0.005
- ePlotDt = 0.5e-3
- cPlotDt = 0.005
- plotName = 'nm.plot'
-
- makeNeuroMeshModel()
- print "after model is completely done"
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
-
- makeChemPlots()
- makeElecPlots()
- makeCaPlots()
- for i in range( 10 ):
- moose.setClock( i, elecDt )
- for i in range( 10, 20 ):
- moose.setClock( i, chemDt )
- moose.setClock( 8, ePlotDt )
- moose.setClock( 18, cPlotDt )
- if useHsolve:
- hsolve = moose.HSolve( '/model/elec/hsolve' )
- #moose.useClock( 1, '/model/elec/hsolve', 'process' )
- hsolve.dt = elecDt
- hsolve.target = '/model/elec/compt'
- moose.reinit()
- #soma = moose.element( '/model/elec/soma' )
- '''
- else:
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
-
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
- moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
- moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
- moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
- '''
-
- moose.useClock( 18, '/graphs/chem/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
- moose.element( '/model/elec/soma' ).inject = 2e-10
- moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
- moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
- moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
- moose.reinit()
-
- moose.start( runtime )
-# moose.element( '/model/elec/soma' ).inject = 0
-# moose.start( 0.25 )
- makeGraphics( cPlotDt, ePlotDt )
-
+ useHsolve = 0
+ runtime = 0.5
+ elecDt = 10e-6
+ chemDt = 0.005
+ ePlotDt = 0.5e-3
+ cPlotDt = 0.005
+ plotName = 'nm.plot'
+
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
+
+ makeChemPlots()
+ makeElecPlots()
+ makeCaPlots()
+ for i in range( 10 ):
+ moose.setClock( i, elecDt )
+ for i in range( 10, 20 ):
+ moose.setClock( i, chemDt )
+ moose.setClock( 8, ePlotDt )
+ moose.setClock( 18, cPlotDt )
+ if useHsolve:
+ hsolve = moose.HSolve( '/model/elec/hsolve' )
+ #moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ hsolve.dt = elecDt
+ hsolve.target = '/model/elec/compt'
+ moose.reinit()
+ #soma = moose.element( '/model/elec/soma' )
+ moose.useClock( 18, '/graphs/chem/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
+ moose.element( '/model/elec/soma' ).inject = 2e-10
+ moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
+ moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
+ moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
+ moose.reinit()
+
+ moose.start( runtime )
+ makeGraphics( cPlotDt, ePlotDt )
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# minimal.py ends here.
diff --git a/moose-examples/snippets/MULTI/multi3.py b/moose-examples/snippets/MULTI/multi3.py
index 005738ce4ca03fe581dcc24181914a953d2c02f6..d6cc945f94174e9bad2cd335ea8292e090ae9ae7 100644
--- a/moose-examples/snippets/MULTI/multi3.py
+++ b/moose-examples/snippets/MULTI/multi3.py
@@ -32,7 +32,6 @@
# Code:
import sys
-sys.path.append('../../python')
import os
os.environ['NUMPTHREADS'] = '1'
import math
@@ -44,184 +43,184 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- moose.setCwe( '/library' )
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ moose.setCwe( '/library' )
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "Neutral" )
+ return cellId
def loadChem( diffLength ):
- chem = moose.Neutral( '/model/chem' )
- neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
- neuroCompt.separateSpines = 1
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
- #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- #modelId = moose.loadModel( 'separate_compts.g', '/model/chem', 'ee' )
- modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
- neuroCompt.name = 'dend'
- spineCompt.name = 'spine'
- psdCompt.name = 'psd'
+ chem = moose.Neutral( '/model/chem' )
+ neuroCompt = moose.NeuroMesh( '/model/chem/kinetics' )
+ neuroCompt.separateSpines = 1
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/chem/compartment_1' )
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/chem/compartment_2' )
+ #print 'Meshvolume[neuro, spine, psd] = ', neuroCompt.mesh[0].volume, spineCompt.mesh[0].volume, psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ #modelId = moose.loadModel( 'separate_compts.g', '/model/chem', 'ee' )
+ modelId = moose.loadModel( 'psd_merged31d.g', '/model/chem', 'ee' )
+ neuroCompt.name = 'dend'
+ spineCompt.name = 'spine'
+ psdCompt.name = 'psd'
def makeNeuroMeshModel():
- diffLength = 10e-6 # Aim for 2 soma compartments.
- elec = loadElec()
- loadChem( diffLength )
- neuroCompt = moose.element( '/model/chem/dend' )
- neuroCompt.diffLength = diffLength
- neuroCompt.cellPortion( elec, '/model/elec/#' )
- for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if (x.diffConst > 0):
- x.diffConst = 1e-11
- for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- x.diffConst = 1e-10
-
- # Put in dend solvers
- ns = neuroCompt.numSegments
- ndc = neuroCompt.numDiffCompts
- print 'ns = ', ns, ', ndc = ', ndc
- assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
- assert( ns == 36 ) #
- assert( ndc == 278 ) #
- nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
- nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
- nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
- nmstoich.compartment = neuroCompt
- nmstoich.ksolve = nmksolve
- nmstoich.dsolve = nmdsolve
- nmstoich.path = "/model/chem/dend/##"
- print 'done setting path, numPools = ', nmdsolve.numPools
- assert( nmdsolve.numPools == 1 )
- assert( nmdsolve.numAllVoxels == ndc )
- assert( nmstoich.numAllPools == 1 )
- # oddly, numLocalFields does not work.
- ca = moose.element( '/model/chem/dend/DEND/Ca' )
- assert( ca.numData == ndc )
+ diffLength = 10e-6 # Aim for 2 soma compartments.
+ elec = loadElec()
+ loadChem( diffLength )
+ neuroCompt = moose.element( '/model/chem/dend' )
+ neuroCompt.diffLength = diffLength
+ neuroCompt.cellPortion( elec, '/model/elec/#' )
+ for x in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if (x.diffConst > 0):
+ x.diffConst = 1e-11
+ for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ x.diffConst = 1e-10
+
+ # Put in dend solvers
+ ns = neuroCompt.numSegments
+ ndc = neuroCompt.numDiffCompts
+ print(('ns = ', ns, ', ndc = ', ndc))
+ assert( neuroCompt.numDiffCompts == neuroCompt.mesh.num )
+ assert( ns == 36 ) #
+ assert( ndc == 278 ) #
+ nmksolve = moose.Ksolve( '/model/chem/dend/ksolve' )
+ nmdsolve = moose.Dsolve( '/model/chem/dend/dsolve' )
+ nmstoich = moose.Stoich( '/model/chem/dend/stoich' )
+ nmstoich.compartment = neuroCompt
+ nmstoich.ksolve = nmksolve
+ nmstoich.dsolve = nmdsolve
+ nmstoich.path = "/model/chem/dend/##"
+ print(('done setting path, numPools = ', nmdsolve.numPools))
+ assert( nmdsolve.numPools == 1 )
+ assert( nmdsolve.numAllVoxels == ndc )
+ assert( nmstoich.numAllPools == 1 )
+ # oddly, numLocalFields does not work.
+ ca = moose.element( '/model/chem/dend/DEND/Ca' )
+ assert( ca.numData == ndc )
- # Put in spine solvers. Note that these get info from the neuroCompt
- spineCompt = moose.element( '/model/chem/spine' )
- sdc = spineCompt.mesh.num
- print 'sdc = ', sdc
- assert( sdc == 13 )
- smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
- smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
- smstoich = moose.Stoich( '/model/chem/spine/stoich' )
- smstoich.compartment = spineCompt
- smstoich.ksolve = smksolve
- smstoich.dsolve = smdsolve
- smstoich.path = "/model/chem/spine/##"
- print 'spine num Pools = ', smstoich.numAllPools, 'dsolve n = ', smdsolve.numPools
- assert( smstoich.numAllPools == 36 )
- assert( smdsolve.numPools == 31 )
- assert( smdsolve.numAllVoxels == sdc )
-
- # Put in PSD solvers. Note that these get info from the neuroCompt
- psdCompt = moose.element( '/model/chem/psd' )
- pdc = psdCompt.mesh.num
- assert( pdc == 13 )
- pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
- pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
- pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
- pmstoich.compartment = psdCompt
- pmstoich.ksolve = pmksolve
- pmstoich.dsolve = pmdsolve
- pmstoich.path = "/model/chem/psd/##"
- print 'psd num Pools = ', pmstoich.numAllPools
- assert( pmstoich.numAllPools == 56 )
- assert( pmdsolve.numPools == 49 )
- assert( pmdsolve.numAllVoxels == pdc )
- foo = moose.element( '/model/chem/psd/Ca' )
- print 'PSD: numfoo = ', foo.numData
- print 'PSD: numAllVoxels = ', pmksolve.numAllVoxels
-
- # Put in junctions between the diffusion solvers
- nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
-
- # Put in cross-compartment reactions between ksolvers
- nmstoich.buildXreacs( smstoich )
- smstoich.buildXreacs( pmstoich )
-
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- ##################################################################
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
- adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
- chemCa = moose.vec( '/model/chem/spine/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( adaptCa ) == sdc )
- assert( len( chemCa ) == sdc )
- for i in range( sdc ):
- elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
- #print elecCa
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 5e-3 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
-
-
- moose.le( '/model/chem/dend/DEND' )
-
-
- compts = neuroCompt.elecComptList
- begin = neuroCompt.startVoxelInCompt
- end = neuroCompt.endVoxelInCompt
- aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
- adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
- chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
- assert( len( chemCa ) == ndc )
- for i in zip( compts, adaptCa, begin, end ):
- name = i[0].path + '/Ca_conc'
- if ( moose.exists( name ) ):
- elecCa = moose.element( name )
- #print i[2], i[3], ' ', elecCa
- #print i[1]
- moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
- for j in range( i[2], i[3] ):
- moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
- adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
+ # Put in spine solvers. Note that these get info from the neuroCompt
+ spineCompt = moose.element( '/model/chem/spine' )
+ sdc = spineCompt.mesh.num
+ print(('sdc = ', sdc))
+ assert( sdc == 13 )
+ smksolve = moose.Ksolve( '/model/chem/spine/ksolve' )
+ smdsolve = moose.Dsolve( '/model/chem/spine/dsolve' )
+ smstoich = moose.Stoich( '/model/chem/spine/stoich' )
+ smstoich.compartment = spineCompt
+ smstoich.ksolve = smksolve
+ smstoich.dsolve = smdsolve
+ smstoich.path = "/model/chem/spine/##"
+ print(('spine num Pools = ', smstoich.numAllPools, 'dsolve n = ', smdsolve.numPools))
+ assert( smstoich.numAllPools == 36 )
+ assert( smdsolve.numPools == 31 )
+ assert( smdsolve.numAllVoxels == sdc )
+
+ # Put in PSD solvers. Note that these get info from the neuroCompt
+ psdCompt = moose.element( '/model/chem/psd' )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 13 )
+ pmksolve = moose.Ksolve( '/model/chem/psd/ksolve' )
+ pmdsolve = moose.Dsolve( '/model/chem/psd/dsolve' )
+ pmstoich = moose.Stoich( '/model/chem/psd/stoich' )
+ pmstoich.compartment = psdCompt
+ pmstoich.ksolve = pmksolve
+ pmstoich.dsolve = pmdsolve
+ pmstoich.path = "/model/chem/psd/##"
+ print(('psd num Pools = ', pmstoich.numAllPools))
+ assert( pmstoich.numAllPools == 56 )
+ assert( pmdsolve.numPools == 49 )
+ assert( pmdsolve.numAllVoxels == pdc )
+ foo = moose.element( '/model/chem/psd/Ca' )
+ print(('PSD: numfoo = ', foo.numData))
+ print(('PSD: numAllVoxels = ', pmksolve.numAllVoxels))
+
+ # Put in junctions between the diffusion solvers
+ nmdsolve.buildNeuroMeshJunctions( smdsolve, pmdsolve )
+
+ # Put in cross-compartment reactions between ksolvers
+ nmstoich.buildXreacs( smstoich )
+ smstoich.buildXreacs( pmstoich )
+
+ """
+ CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
+ print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
+ CaNspine = moose.vec( '/model/chem/spine/SPINE/CaN_BULK/CaN' )
+ print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
+ """
+
+ ##################################################################
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/spine/adaptCa', sdc )
+ adaptCa = moose.vec( '/model/chem/spine/adaptCa' )
+ chemCa = moose.vec( '/model/chem/spine/Ca' )
+ #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
+ assert( len( adaptCa ) == sdc )
+ assert( len( chemCa ) == sdc )
+ for i in range( sdc ):
+ elecCa = moose.element( '/model/elec/spine_head_14_' + str(i+1) + '/NMDA_Ca_conc' )
+ #print elecCa
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'output', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 5e-3 # 520 to 0.0052 mM
+ #print adaptCa.outputOffset
+
+
+ moose.le( '/model/chem/dend/DEND' )
+
+
+ compts = neuroCompt.elecComptList
+ begin = neuroCompt.startVoxelInCompt
+ end = neuroCompt.endVoxelInCompt
+ aCa = moose.Adaptor( '/model/chem/dend/DEND/adaptCa', len( compts))
+ adaptCa = moose.vec( '/model/chem/dend/DEND/adaptCa' )
+ chemCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ #print 'aCa = ', aCa, ' foo = ', foo, "len( ChemCa ) = ", len( chemCa ), ", numData = ", chemCa.numData, "len( adaptCa ) = ", len( adaptCa )
+ assert( len( chemCa ) == ndc )
+ for i in zip( compts, adaptCa, begin, end ):
+ name = i[0].path + '/Ca_conc'
+ if ( moose.exists( name ) ):
+ elecCa = moose.element( name )
+ #print i[2], i[3], ' ', elecCa
+ #print i[1]
+ moose.connect( elecCa, 'concOut', i[1], 'input', 'Single' )
+ for j in range( i[2], i[3] ):
+ moose.connect( i[1], 'output', chemCa[j], 'setConc', 'Single' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.00008 # 80 nM offset in chem.
+ adaptCa.scale = 20e-6 # 10 arb units to 2 uM.
def addPlot( objpath, field, plot ):
- #assert moose.exists( objpath )
- if moose.exists( objpath ):
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- if obj.className == 'Neutral':
- print "addPlot failed: object is a Neutral: ", objpath
- return moose.element( '/' )
- else:
- #print "object was found: ", objpath, obj.className
- moose.connect( tab, 'requestOut', obj, field )
- return tab
- else:
- print "addPlot failed: object not found: ", objpath
- return moose.element( '/' )
+ #assert moose.exists( objpath )
+ if moose.exists( objpath ):
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ if obj.className == 'Neutral':
+ print(("addPlot failed: object is a Neutral: ", objpath))
+ return moose.element( '/' )
+ else:
+ #print "object was found: ", objpath, obj.className
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
+ else:
+ print(("addPlot failed: object not found: ", objpath))
+ return moose.element( '/' )
def makeCaPlots():
graphs = moose.Neutral( '/graphs' )
@@ -238,148 +237,144 @@ def makeElecPlots():
addPlot( '/model/elec/spine_head_14_4', 'getVm', 'elec/spineVm' )
def makeChemPlots():
- graphs = moose.Neutral( '/graphs' )
- chem = moose.Neutral( '/graphs/chem' )
- addPlot( '/model/chem/psd/CaM_dash_Ca4', 'getConc', 'chem/psdCaCam' )
- addPlot( '/model/chem/psd/actCaMKII', 'getConc', 'chem/psdActCaMKII' )
- addPlot( '/model/chem/spine/CaM_dash_Ca4', 'getConc', 'chem/spineCaCam' )
- addPlot( '/model/chem/spine/CaM_dash_Ca4[12]', 'getConc', 'chem/spine12CaCam' )
- addPlot( '/model/chem/spine/actCaMKII', 'getConc', 'chem/spineActCaMKII' )
- addPlot( '/model/chem/spine/actCaMKII[11]', 'getConc', 'chem/spine12ActCaMKII' )
- addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
- addPlot( '/model/chem/psd/Ca[11]', 'getConc', 'chem/psd12Ca' )
- addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
- addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
- #addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
- #addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
+ graphs = moose.Neutral( '/graphs' )
+ chem = moose.Neutral( '/graphs/chem' )
+ addPlot( '/model/chem/psd/CaM_dash_Ca4', 'getConc', 'chem/psdCaCam' )
+ addPlot( '/model/chem/psd/actCaMKII', 'getConc', 'chem/psdActCaMKII' )
+ addPlot( '/model/chem/spine/CaM_dash_Ca4', 'getConc', 'chem/spineCaCam' )
+ addPlot( '/model/chem/spine/CaM_dash_Ca4[12]', 'getConc', 'chem/spine12CaCam' )
+ addPlot( '/model/chem/spine/actCaMKII', 'getConc', 'chem/spineActCaMKII' )
+ addPlot( '/model/chem/spine/actCaMKII[11]', 'getConc', 'chem/spine12ActCaMKII' )
+ addPlot( '/model/chem/psd/Ca', 'getConc', 'chem/psdCa' )
+ addPlot( '/model/chem/psd/Ca[11]', 'getConc', 'chem/psd12Ca' )
+ addPlot( '/model/chem/spine/Ca[3]', 'getConc', 'chem/spine4Ca' )
+ addPlot( '/model/chem/spine/Ca[11]', 'getConc', 'chem/spine12Ca' )
+ #addPlot( '/model/chem/dend/DEND/Ca', 'getConc', 'chem/dendCa' )
+ #addPlot( '/model/chem/dend/DEND/Ca[20]', 'getConc', 'chem/dendCa20' )
def makeGraphics( cPlotDt, ePlotDt ):
- plt.ion()
- fig = plt.figure( figsize=(10,16) )
- chem = fig.add_subplot( 411 )
- chem.set_ylim( 0, 0.006 )
- plt.ylabel( 'Conc (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
- line1, = chem.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- elec = fig.add_subplot( 412 )
- plt.ylabel( 'Vm (V)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = elec.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- ca = fig.add_subplot( 413 )
- plt.ylabel( '[Ca] (mM)' )
- plt.xlabel( 'time (seconds)' )
- for x in moose.wildcardFind( '/graphs/ca/#[ISA=Table]' ):
- pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
- line1, = ca.plot( pos, x.vector, label=x.name )
- plt.legend()
-
- lenplot = fig.add_subplot( 414 )
- plt.ylabel( 'Ca (mM )' )
- plt.xlabel( 'Voxel#)' )
-
- spineCa = moose.vec( '/model/chem/spine/Ca' )
- dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
- line1, = lenplot.plot( range( len( spineCa ) ), spineCa.conc, label='spine' )
- line2, = lenplot.plot( range( len( dendCa ) ), dendCa.conc, label='dend' )
-
- ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
- line3, = lenplot.plot( range( len( ca ) ), ca, label='elec' )
-
- spineCaM = moose.vec( '/model/chem/spine/CaM_dash_Ca4' )
- line4, = lenplot.plot( range( len( spineCaM ) ), spineCaM.conc, label='spineCaM' )
- psdCaM = moose.vec( '/model/chem/psd/CaM_dash_Ca4' )
- line5, = lenplot.plot( range( len( psdCaM ) ), psdCaM.conc, label='psdCaM' )
- plt.legend()
-
-
- fig.canvas.draw()
- raw_input()
+ plt.ion()
+ fig = plt.figure( figsize=(10,16) )
+ chem = fig.add_subplot( 411 )
+ chem.set_ylim( 0, 0.006 )
+ plt.ylabel( 'Conc (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/chem/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * cPlotDt
+ line1, = chem.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ elec = fig.add_subplot( 412 )
+ plt.ylabel( 'Vm (V)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/elec/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = elec.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ ca = fig.add_subplot( 413 )
+ plt.ylabel( '[Ca] (mM)' )
+ plt.xlabel( 'time (seconds)' )
+ for x in moose.wildcardFind( '/graphs/ca/#[ISA=Table]' ):
+ pos = numpy.arange( 0, x.vector.size, 1 ) * ePlotDt
+ line1, = ca.plot( pos, x.vector, label=x.name )
+ plt.legend()
+
+ lenplot = fig.add_subplot( 414 )
+ plt.ylabel( 'Ca (mM )' )
+ plt.xlabel( 'Voxel#)' )
+
+ spineCa = moose.vec( '/model/chem/spine/Ca' )
+ dendCa = moose.vec( '/model/chem/dend/DEND/Ca' )
+ line1, = lenplot.plot( list(range( len( spineCa ))), spineCa.conc, label='spine' )
+ line2, = lenplot.plot( list(range( len( dendCa ))), dendCa.conc, label='dend' )
+
+ ca = [ x.Ca * 0.0001 for x in moose.wildcardFind( '/model/elec/##[ISA=CaConcBase]') ]
+ line3, = lenplot.plot( list(range( len( ca ))), ca, label='elec' )
+
+ spineCaM = moose.vec( '/model/chem/spine/CaM_dash_Ca4' )
+ line4, = lenplot.plot( list(range( len( spineCaM ))), spineCaM.conc, label='spineCaM' )
+ psdCaM = moose.vec( '/model/chem/psd/CaM_dash_Ca4' )
+ line5, = lenplot.plot( list(range( len( psdCaM ))), psdCaM.conc, label='psdCaM' )
+ plt.legend()
+
+
+ fig.canvas.draw()
+ eval(input())
- '''
- for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
- t = numpy.arange( 0, x.vector.size, 1 )
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
- '''
+ '''
+ for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
+ t = numpy.arange( 0, x.vector.size, 1 )
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
+ '''
- print 'All done'
+ print('All done')
def testNeuroMeshMultiscale():
- useHsolve = 1
- runtime = 0.5
- if useHsolve:
- elecDt = 50e-6
- else:
- elecDt = 10e-6
- chemDt = 0.005
- ePlotDt = 0.5e-3
- cPlotDt = 0.005
- plotName = 'nm.plot'
-
- makeNeuroMeshModel()
- print "after model is completely done"
- for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
- print i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb
-
- makeChemPlots()
- makeElecPlots()
- makeCaPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 4, chemDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, cPlotDt )
- moose.setClock( 8, ePlotDt )
- if useHsolve:
- hsolve = moose.HSolve( '/model/elec/hsolve' )
- moose.useClock( 1, '/model/elec/hsolve', 'process' )
- hsolve.dt = elecDt
- hsolve.target = '/model/elec/compt'
- moose.reinit()
- else:
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
-
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- #moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- #moose.useClock( 4, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
- moose.useClock( 4, '/model/chem/#/ksolve', 'init' )
- moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
- moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
- moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
- moose.useClock( 7, '/graphs/chem/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
- moose.element( '/model/elec/soma' ).inject = 2e-10
- moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
- moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
- moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
- moose.reinit()
-
- moose.start( runtime )
-# moose.element( '/model/elec/soma' ).inject = 0
-# moose.start( 0.25 )
- makeGraphics( cPlotDt, ePlotDt )
+ useHsolve = 1
+ runtime = 0.5
+ if useHsolve:
+ elecDt = 50e-6
+ else:
+ elecDt = 10e-6
+ chemDt = 0.005
+ ePlotDt = 0.5e-3
+ cPlotDt = 0.005
+ plotName = 'nm.plot'
+ makeNeuroMeshModel()
+ print("after model is completely done")
+ for i in moose.wildcardFind( '/model/chem/#/#/#/transloc#' ):
+ print((i[0].name, i[0].Kf, i[0].Kb, i[0].kf, i[0].kb))
+
+ makeChemPlots()
+ makeElecPlots()
+ makeCaPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 4, chemDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, cPlotDt )
+ moose.setClock( 8, ePlotDt )
+ if useHsolve:
+ hsolve = moose.HSolve( '/model/elec/hsolve' )
+ moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ hsolve.dt = elecDt
+ hsolve.target = '/model/elec/compt'
+ moose.reinit()
+ else:
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=Compartment]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+
+ moose.useClock( 4, '/model/chem/#/dsolve', 'process' )
+ moose.useClock( 4, '/model/chem/#/ksolve', 'init' )
+ moose.useClock( 5, '/model/chem/#/ksolve', 'process' )
+ moose.useClock( 6, '/model/chem/spine/adaptCa', 'process' )
+ moose.useClock( 6, '/model/chem/dend/DEND/adaptCa', 'process' )
+ moose.useClock( 7, '/graphs/chem/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#,/graphs/ca/#', 'process' )
+ moose.element( '/model/elec/soma' ).inject = 2e-10
+ moose.element( '/model/chem/psd/Ca' ).concInit = 0.001
+ moose.element( '/model/chem/spine/Ca' ).concInit = 0.002
+ moose.element( '/model/chem/dend/DEND/Ca' ).concInit = 0.003
+ moose.reinit()
+
+ moose.start( runtime )
+ makeGraphics( cPlotDt, ePlotDt )
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# minimal.py ends here.
diff --git a/moose-examples/snippets/MULTI/proto18.py b/moose-examples/snippets/MULTI/proto18.py
index 06057af60b1cde37dfb2693bb9d180b88ba9e37e..05ba3d549fc67b8401765b174aa5bb7ea516ded9 100644
--- a/moose-examples/snippets/MULTI/proto18.py
+++ b/moose-examples/snippets/MULTI/proto18.py
@@ -4,7 +4,7 @@
#** The 1991 Traub set of voltage and concentration dependent channels
#** Implemented as tabchannels by : Dave Beeman
#** R.D.Traub, R. K. S. Wong, R. Miles, and H. Michelson
-#** Journal of Neurophysiology, Vol. 66, p. 635 (1991)
+#** Journal of Neurophysiology, Vol. 66, p. 635 (1991)
#**
#** This file depends on functions and constants defined in defaults.g
#** As it is also intended as an example of the use of the tabchannel
@@ -52,61 +52,61 @@ SOMA_A = 3.320e-9 #// soma area in square meters
#//========================================================================
def make_Ca():
- if moose.exists( 'Ca' ):
- return
- Ca = moose.HHChannel( 'Ca' )
- Ca.Ek = ECA
- Ca.Gbar = 40 * SOMA_A
- Ca.Gk = 0
- Ca.Xpower = 2
- Ca.Ypower = 1
- Ca.Zpower = 0
-
- xgate = moose.element( 'Ca/gateX' )
- xA = numpy.array( [ 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389, -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3, 3000, -0.1, 0.05 ] )
-# xgate.min = -0.1
-# xgate.max = 0.05
-# xgate.divs = 3000
+ if moose.exists( 'Ca' ):
+ return
+ Ca = moose.HHChannel( 'Ca' )
+ Ca.Ek = ECA
+ Ca.Gbar = 40 * SOMA_A
+ Ca.Gk = 0
+ Ca.Xpower = 2
+ Ca.Ypower = 1
+ Ca.Zpower = 0
+
+ xgate = moose.element( 'Ca/gateX' )
+ xA = numpy.array( [ 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389, -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3, 3000, -0.1, 0.05 ] )
+# xgate.min = -0.1
+# xgate.max = 0.05
+# xgate.divs = 3000
#// Converting Traub's expressions for the gCa/s alpha and beta functions
#// to SI units and entering the A, B, C, D and F parameters, we get:
-# xgate.alpha( 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389 )
-# xgate.beta( -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3 )
- #xgate.setupAlpha( xA )
- xgate.alphaParms = xA
+# xgate.alpha( 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389 )
+# xgate.beta( -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3 )
+ #xgate.setupAlpha( xA )
+ xgate.alphaParms = xA
# The Y gate (gCa/r) is not quite of this form. For V > EREST_ACT, alpha =
# 5*{exp({-50*(V - EREST_ACT)})}. Otherwise, alpha = 5. Over the entire
# range, alpha + beta = 5. To create the Y_A and Y_B tables, we use some
# of the pieces of the setupalpha function.
- ygate = moose.element( 'Ca/gateY' )
- ygate.min = -0.1
- ygate.max = 0.05
- ygate.divs = 3000
- yA = numpy.zeros( (ygate.divs + 1), dtype=float)
- yB = numpy.zeros( (ygate.divs + 1), dtype=float)
+ ygate = moose.element( 'Ca/gateY' )
+ ygate.min = -0.1
+ ygate.max = 0.05
+ ygate.divs = 3000
+ yA = numpy.zeros( (ygate.divs + 1), dtype=float)
+ yB = numpy.zeros( (ygate.divs + 1), dtype=float)
#Fill the Y_A table with alpha values and the Y_B table with (alpha+beta)
- dx = (ygate.max - ygate.min)/ygate.divs
- x = ygate.min
- for i in range( ygate.divs + 1 ):
- if ( x > EREST_ACT):
- yA[i] = 5.0 * math.exp( -50 * (x - EREST_ACT) )
- else:
- yA[i] = 5.0
- yB[i] = 5.0
- x += dx
- ygate.tableA = yA
- ygate.tableB = yB
+ dx = (ygate.max - ygate.min)/ygate.divs
+ x = ygate.min
+ for i in range( ygate.divs + 1 ):
+ if ( x > EREST_ACT):
+ yA[i] = 5.0 * math.exp( -50 * (x - EREST_ACT) )
+ else:
+ yA[i] = 5.0
+ yB[i] = 5.0
+ x += dx
+ ygate.tableA = yA
+ ygate.tableB = yB
# Tell the cell reader that the current from this channel must be fed into
# the Ca_conc pool of calcium.
- addmsg1 = moose.Mstring( '/library/Ca/addmsg1' )
- addmsg1.value = '. IkOut ../Ca_conc current'
+ addmsg1 = moose.Mstring( '/library/Ca/addmsg1' )
+ addmsg1.value = '. IkOut ../Ca_conc current'
# in some compartments, whe have an NMDA_Ca_conc object to put the current
# into.
- addmsg2 = moose.Mstring( '/library/Ca/addmsg2' )
- addmsg2.value = '. IkOut ../NMDA_Ca_conc current'
+ addmsg2 = moose.Mstring( '/library/Ca/addmsg2' )
+ addmsg2.value = '. IkOut ../NMDA_Ca_conc current'
# As we typically use the cell reader to create copies of these prototype
#elements in one or more compartments, we need some way to be sure that the
#needed messages are established. Although the cell reader has enough
@@ -153,12 +153,12 @@ def make_Ca():
#//========================================================================
def make_Ca_conc():
- if moose.exists( 'Ca_conc' ):
- return
- conc = moose.CaConc( 'Ca_conc' )
- conc.tau = 0.013333 # sec
- conc.B = 17.402e12 # Curr to conc conversion for soma
- conc.Ca_base = 0.0
+ if moose.exists( 'Ca_conc' ):
+ return
+ conc = moose.CaConc( 'Ca_conc' )
+ conc.tau = 0.013333 # sec
+ conc.B = 17.402e12 # Curr to conc conversion for soma
+ conc.Ca_base = 0.0
#This Ca_concen element should receive a message from any calcium channels
# with the current going through the channel. Here we have this specified
@@ -176,38 +176,38 @@ def make_Ca_conc():
# functions of concentration, instead of voltage.
def make_K_AHP():
- if moose.exists( 'K_AHP' ):
- return
-
- K_AHP = moose.HHChannel( 'K_AHP' )
- K_AHP.Ek = EK # V
- K_AHP.Gbar = 8 * SOMA_A # S
- K_AHP.Gk = 0 # S
- K_AHP.Xpower = 0
- K_AHP.Ypower = 0
- K_AHP.Zpower = 1
-
- zgate = moose.element( 'K_AHP/gateZ' )
- xmax = 500.0
- zgate.min = 0
- zgate.max = xmax
- zgate.divs = 3000
- zA = numpy.zeros( (zgate.divs + 1), dtype=float)
- zB = numpy.zeros( (zgate.divs + 1), dtype=float)
- dx = (zgate.max - zgate.min)/zgate.divs
- x = zgate.min
- for i in range( zgate.divs + 1 ):
- if (x < (xmax / 2.0 )):
- zA[i] = 0.02*x
- else:
- zA[i] = 10.0
- zB[i] = zA[i] + 1.0
- x = x + dx
-
- zgate.tableA = zA
- zgate.tableB = zB
- addmsg1 = moose.Mstring( '/library/K_AHP/addmsg1' )
- addmsg1.value = '../Ca_conc concOut . concen'
+ if moose.exists( 'K_AHP' ):
+ return
+
+ K_AHP = moose.HHChannel( 'K_AHP' )
+ K_AHP.Ek = EK # V
+ K_AHP.Gbar = 8 * SOMA_A # S
+ K_AHP.Gk = 0 # S
+ K_AHP.Xpower = 0
+ K_AHP.Ypower = 0
+ K_AHP.Zpower = 1
+
+ zgate = moose.element( 'K_AHP/gateZ' )
+ xmax = 500.0
+ zgate.min = 0
+ zgate.max = xmax
+ zgate.divs = 3000
+ zA = numpy.zeros( (zgate.divs + 1), dtype=float)
+ zB = numpy.zeros( (zgate.divs + 1), dtype=float)
+ dx = (zgate.max - zgate.min)/zgate.divs
+ x = zgate.min
+ for i in range( zgate.divs + 1 ):
+ if (x < (xmax / 2.0 )):
+ zA[i] = 0.02*x
+ else:
+ zA[i] = 10.0
+ zB[i] = zA[i] + 1.0
+ x = x + dx
+
+ zgate.tableA = zA
+ zgate.tableB = zB
+ addmsg1 = moose.Mstring( '/library/K_AHP/addmsg1' )
+ addmsg1.value = '../Ca_conc concOut . concen'
# Use an added field to tell the cell reader to set up a message from the
# Ca_Conc with concentration info, to the current K_AHP object.
@@ -228,71 +228,71 @@ def make_K_AHP():
#the multiplicative Ca-dependent factor in the conductance.
def make_K_C():
- if moose.exists( 'K_C'):
- return
-
- K_C = moose.HHChannel( 'K_C' )
- K_C.Ek = EK # V
- K_C.Gbar = 100.0 * SOMA_A # S
- K_C.Gk = 0 # S
- K_C.Xpower = 1
- K_C.Zpower = 1
- K_C.instant = 4 # Flag: 0x100 means Z gate is instant.
-
- # Now make a X-table for the voltage-dependent activation parameter.
- xgate = moose.element( 'K_C/gateX' )
- xgate.min = -0.1
- xgate.max = 0.05
- xgate.divs = 3000
- xA = numpy.zeros( (xgate.divs + 1), dtype=float)
- xB = numpy.zeros( (xgate.divs + 1), dtype=float)
- dx = (xgate.max - xgate.min)/xgate.divs
- x = xgate.min
- for i in range( xgate.divs + 1 ):
- alpha = 0.0
- beta = 0.0
- if (x < EREST_ACT + 0.05):
- alpha = math.exp( 53.872 * (x - EREST_ACT) - 0.66835 ) / 0.018975
- beta = 2000* (math.exp ( (EREST_ACT + 0.0065 - x)/0.027)) - alpha
- else:
- alpha = 2000 * math.exp( ( EREST_ACT + 0.0065 - x)/0.027 )
- beta = 0.0
- xA[i] = alpha
- xB[i] = alpha + beta
- x = x + dx
- xgate.tableA = xA
- xgate.tableB = xB
+ if moose.exists( 'K_C'):
+ return
+
+ K_C = moose.HHChannel( 'K_C' )
+ K_C.Ek = EK # V
+ K_C.Gbar = 100.0 * SOMA_A # S
+ K_C.Gk = 0 # S
+ K_C.Xpower = 1
+ K_C.Zpower = 1
+ K_C.instant = 4 # Flag: 0x100 means Z gate is instant.
+
+ # Now make a X-table for the voltage-dependent activation parameter.
+ xgate = moose.element( 'K_C/gateX' )
+ xgate.min = -0.1
+ xgate.max = 0.05
+ xgate.divs = 3000
+ xA = numpy.zeros( (xgate.divs + 1), dtype=float)
+ xB = numpy.zeros( (xgate.divs + 1), dtype=float)
+ dx = (xgate.max - xgate.min)/xgate.divs
+ x = xgate.min
+ for i in range( xgate.divs + 1 ):
+ alpha = 0.0
+ beta = 0.0
+ if (x < EREST_ACT + 0.05):
+ alpha = math.exp( 53.872 * (x - EREST_ACT) - 0.66835 ) / 0.018975
+ beta = 2000* (math.exp ( (EREST_ACT + 0.0065 - x)/0.027)) - alpha
+ else:
+ alpha = 2000 * math.exp( ( EREST_ACT + 0.0065 - x)/0.027 )
+ beta = 0.0
+ xA[i] = alpha
+ xB[i] = alpha + beta
+ x = x + dx
+ xgate.tableA = xA
+ xgate.tableB = xB
# Create a table for the function of concentration, allowing a
# concentration range of 0 to 1000, with 50 divisions. This is done
# using the Z gate, which can receive a CONCEN message. By using
# the "instant" flag, the A and B tables are evaluated as lookup tables,
# rather than being used in a differential equation.
- zgate = moose.element( 'K_C/gateZ' )
- zgate.min = 0.0
- xmax = 500.0
- zgate.max = xmax
- zgate.divs = 3000
- zA = numpy.zeros( (zgate.divs + 1), dtype=float)
- zB = numpy.zeros( (zgate.divs + 1), dtype=float)
- dx = ( zgate.max - zgate.min)/ zgate.divs
- x = zgate.min
- for i in range( xgate.divs + 1 ):
- if ( x < ( xmax / 4.0 ) ):
- zA[i] = x * 4.0 / xmax
- else:
- zA[i] = 1.0
- zB[i] = 1.0
- x += dx
- zgate.tableA = zA
- zgate.tableB = zB
+ zgate = moose.element( 'K_C/gateZ' )
+ zgate.min = 0.0
+ xmax = 500.0
+ zgate.max = xmax
+ zgate.divs = 3000
+ zA = numpy.zeros( (zgate.divs + 1), dtype=float)
+ zB = numpy.zeros( (zgate.divs + 1), dtype=float)
+ dx = ( zgate.max - zgate.min)/ zgate.divs
+ x = zgate.min
+ for i in range( xgate.divs + 1 ):
+ if ( x < ( xmax / 4.0 ) ):
+ zA[i] = x * 4.0 / xmax
+ else:
+ zA[i] = 1.0
+ zB[i] = 1.0
+ x += dx
+ zgate.tableA = zA
+ zgate.tableB = zB
# Now we need to provide for messages that link to external elements.
# The message that sends the Ca concentration to the Z gate tables is stored
# in an added field of the channel, so that it may be found by the cell
# reader.
- addmsg1 = moose.Mstring( '/library/K_C/addmsg1' )
- addmsg1.value = '../Ca_conc concOut . concen'
+ addmsg1 = moose.Mstring( '/library/K_C/addmsg1' )
+ addmsg1.value = '../Ca_conc concOut . concen'
# The remaining channels are straightforward tabchannel implementations
@@ -301,133 +301,133 @@ def make_K_C():
#/ Tabchannel Na Hippocampal cell channel
#/========================================================================
def make_Na():
- if moose.exists( 'Na' ):
- return
- Na = moose.HHChannel( 'Na' )
- Na.Ek = ENA # V
- Na.Gbar = 300 * SOMA_A # S
- Na.Gk = 0 # S
- Na.Xpower = 2
- Na.Ypower = 1
- Na.Zpower = 0
-
- xgate = moose.element( 'Na/gateX' )
- xA = numpy.array( [ 320e3 * (0.0131 + EREST_ACT),
- -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004,
- -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0,
- -1.0 * (0.0401 + EREST_ACT), 5.0e-3,
- 3000, -0.1, 0.05 ] )
- xgate.alphaParms = xA
-
-
- #xgate.alpha( 320e3 * (0.0131 + EREST_ACT), -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004 )
- #xgate.beta( -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 5.0e-3 )
-
- ygate = moose.element( 'Na/gateY' )
- yA = numpy.array( [ 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018,
- 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3,
- 3000, -0.1, 0.05 ] )
- ygate.alphaParms = yA
-
- #ygate.alpha( 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018 )
- #ygate.beta( 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3 )
+ if moose.exists( 'Na' ):
+ return
+ Na = moose.HHChannel( 'Na' )
+ Na.Ek = ENA # V
+ Na.Gbar = 300 * SOMA_A # S
+ Na.Gk = 0 # S
+ Na.Xpower = 2
+ Na.Ypower = 1
+ Na.Zpower = 0
+
+ xgate = moose.element( 'Na/gateX' )
+ xA = numpy.array( [ 320e3 * (0.0131 + EREST_ACT),
+ -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004,
+ -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0,
+ -1.0 * (0.0401 + EREST_ACT), 5.0e-3,
+ 3000, -0.1, 0.05 ] )
+ xgate.alphaParms = xA
+
+
+ #xgate.alpha( 320e3 * (0.0131 + EREST_ACT), -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004 )
+ #xgate.beta( -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 5.0e-3 )
+
+ ygate = moose.element( 'Na/gateY' )
+ yA = numpy.array( [ 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018,
+ 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3,
+ 3000, -0.1, 0.05 ] )
+ ygate.alphaParms = yA
+
+ #ygate.alpha( 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018 )
+ #ygate.beta( 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3 )
#========================================================================
# Tabchannel K(DR) Hippocampal cell channel
#========================================================================
def make_K_DR():
- if moose.exists( 'K_DR' ):
- return
- K_DR = moose.HHChannel( 'K_DR' )
- K_DR.Ek = EK # V
- K_DR.Gbar = 150 * SOMA_A # S
- K_DR.Gk = 0 # S
- K_DR.Xpower = 1
- K_DR.Ypower = 0
- K_DR.Zpower = 0
-
- xgate = moose.element( 'K_DR/gateX' )
- xA = numpy.array( [ 16e3 * (0.0351 + EREST_ACT),
- -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005,
- 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04,
- 3000, -0.1, 0.05 ] )
- xgate.alphaParms = xA
- #xgate.alpha( 16e3 * (0.0351 + EREST_ACT), -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005 )
- #xgate.beta( 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04 )
+ if moose.exists( 'K_DR' ):
+ return
+ K_DR = moose.HHChannel( 'K_DR' )
+ K_DR.Ek = EK # V
+ K_DR.Gbar = 150 * SOMA_A # S
+ K_DR.Gk = 0 # S
+ K_DR.Xpower = 1
+ K_DR.Ypower = 0
+ K_DR.Zpower = 0
+
+ xgate = moose.element( 'K_DR/gateX' )
+ xA = numpy.array( [ 16e3 * (0.0351 + EREST_ACT),
+ -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005,
+ 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04,
+ 3000, -0.1, 0.05 ] )
+ xgate.alphaParms = xA
+ #xgate.alpha( 16e3 * (0.0351 + EREST_ACT), -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005 )
+ #xgate.beta( 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04 )
#========================================================================
# Tabchannel K(A) Hippocampal cell channel
#========================================================================
def make_K_A():
- if moose.exists( 'K_A' ):
- return
- K_A = moose.HHChannel( 'K_A' )
- K_A.Ek = EK # V
- K_A.Gbar = 50 * SOMA_A # S
- K_A.Gk = 0 # S
- K_A.Xpower = 1
- K_A.Ypower = 1
- K_A.Zpower = 0
-
- xgate = moose.element( 'K_A/gateX' )
- xA = numpy.array( [ 20e3 * (0.0131 + EREST_ACT),
- -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01,
- -17.5e3 * (0.0401 + EREST_ACT),
- 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01,
- 3000, -0.1, 0.05 ] )
- xgate.alphaParms = xA
- # xgate.alpha( 20e3 * (0.0131 + EREST_ACT), -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01 )
- # xgate.beta( -17.5e3 * (0.0401 + EREST_ACT), 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01 )
-
- ygate = moose.element( 'K_A/gateY' )
- yA = numpy.array( [ 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018,
- 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005,
- 3000, -0.1, 0.05 ] )
- ygate.alphaParms = yA
- # ygate.alpha( 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018 )
- # ygate.beta( 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005 )
+ if moose.exists( 'K_A' ):
+ return
+ K_A = moose.HHChannel( 'K_A' )
+ K_A.Ek = EK # V
+ K_A.Gbar = 50 * SOMA_A # S
+ K_A.Gk = 0 # S
+ K_A.Xpower = 1
+ K_A.Ypower = 1
+ K_A.Zpower = 0
+
+ xgate = moose.element( 'K_A/gateX' )
+ xA = numpy.array( [ 20e3 * (0.0131 + EREST_ACT),
+ -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01,
+ -17.5e3 * (0.0401 + EREST_ACT),
+ 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01,
+ 3000, -0.1, 0.05 ] )
+ xgate.alphaParms = xA
+ # xgate.alpha( 20e3 * (0.0131 + EREST_ACT), -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01 )
+ # xgate.beta( -17.5e3 * (0.0401 + EREST_ACT), 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01 )
+
+ ygate = moose.element( 'K_A/gateY' )
+ yA = numpy.array( [ 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018,
+ 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005,
+ 3000, -0.1, 0.05 ] )
+ ygate.alphaParms = yA
+ # ygate.alpha( 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018 )
+ # ygate.beta( 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005 )
#========================================================================
# SynChan: Glu receptor
#========================================================================
def make_glu():
- if moose.exists( 'glu' ):
- return
- glu = moose.SynChan( 'glu' )
- glu.Ek = 0.0
- glu.tau1 = 2.0e-3
- glu.tau2 = 9.0e-3
- glu.Gbar = 40 * SOMA_A
+ if moose.exists( 'glu' ):
+ return
+ glu = moose.SynChan( 'glu' )
+ glu.Ek = 0.0
+ glu.tau1 = 2.0e-3
+ glu.tau2 = 9.0e-3
+ glu.Gbar = 40 * SOMA_A
#========================================================================
# SynChan: NMDA receptor
#========================================================================
def make_NMDA():
- if moose.exists( 'NMDA' ):
- return
- NMDA = moose.SynChan( 'NMDA' )
- NMDA.Ek = 0.0
- NMDA.tau1 = 20.0e-3
- NMDA.tau2 = 20.0e-3
- NMDA.Gbar = 5 * SOMA_A
-
- block = moose.MgBlock( '/library/NMDA/block' )
- block.CMg = 1.2 # [Mg] in mM
- block.Zk = 2
- block.KMg_A = 1.0/0.28
- block.KMg_B = 1.0/62
-
- moose.connect( NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
- addmsg1 = moose.Mstring( '/library/NMDA/addmsg1' )
- addmsg1.value = '.. channel ./block channel'
- #Here we want to also tell the cell reader to _remove_ the original
- #Gk, Ek term going from the channel to the compartment, as this is
- # now handled by the MgBlock.
- #addmsg2 = moose.Mstring( 'NMDA/addmsg2'
- #addmsg2.value = 'DropMsg .. channel'
- addmsg3 = moose.Mstring( '/library/NMDA/addmsg3' )
- addmsg3.value = '.. VmOut . Vm'
+ if moose.exists( 'NMDA' ):
+ return
+ NMDA = moose.SynChan( 'NMDA' )
+ NMDA.Ek = 0.0
+ NMDA.tau1 = 20.0e-3
+ NMDA.tau2 = 20.0e-3
+ NMDA.Gbar = 5 * SOMA_A
+
+ block = moose.MgBlock( '/library/NMDA/block' )
+ block.CMg = 1.2 # [Mg] in mM
+ block.Zk = 2
+ block.KMg_A = 1.0/0.28
+ block.KMg_B = 1.0/62
+
+ moose.connect( NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
+ addmsg1 = moose.Mstring( '/library/NMDA/addmsg1' )
+ addmsg1.value = '.. channel ./block channel'
+ #Here we want to also tell the cell reader to _remove_ the original
+ #Gk, Ek term going from the channel to the compartment, as this is
+ # now handled by the MgBlock.
+ #addmsg2 = moose.Mstring( 'NMDA/addmsg2'
+ #addmsg2.value = 'DropMsg .. channel'
+ addmsg3 = moose.Mstring( '/library/NMDA/addmsg3' )
+ addmsg3.value = '.. VmOut . Vm'
#addfield NMDA addmsg1
@@ -448,37 +448,37 @@ def make_NMDA():
#========================================================================
def make_Ca_NMDA():
- if moose.exists( 'Ca_NMDA' ):
- return
- Ca_NMDA = moose.SynChan( 'Ca_NMDA' )
- Ca_NMDA.Ek = ECA
- Ca_NMDA.tau1 = 20.0e-3
- Ca_NMDA.tau2 = 20.0e-3
- Ca_NMDA.Gbar = 5 * SOMA_A
-
- block = moose.MgBlock( '/library/Ca_NMDA/block' )
- block.CMg = 1.2 # [Mg] in mM
- block.Zk = 2
- block.KMg_A = 1.0/0.28
- block.KMg_B = 1.0/62
-
- moose.connect( Ca_NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
- addmsg1 = moose.Mstring( '/library/Ca_NMDA/addmsg1' )
- addmsg1.value = '.. VmOut ./block Vm'
- addmsg2 = moose.Mstring( '/library/Ca_NMDA/addmsg2' )
- addmsg2.value = './block IkOut ../NMDA_Ca_conc current'
- # The original model has the Ca current also coming here.
+ if moose.exists( 'Ca_NMDA' ):
+ return
+ Ca_NMDA = moose.SynChan( 'Ca_NMDA' )
+ Ca_NMDA.Ek = ECA
+ Ca_NMDA.tau1 = 20.0e-3
+ Ca_NMDA.tau2 = 20.0e-3
+ Ca_NMDA.Gbar = 5 * SOMA_A
+
+ block = moose.MgBlock( '/library/Ca_NMDA/block' )
+ block.CMg = 1.2 # [Mg] in mM
+ block.Zk = 2
+ block.KMg_A = 1.0/0.28
+ block.KMg_B = 1.0/62
+
+ moose.connect( Ca_NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
+ addmsg1 = moose.Mstring( '/library/Ca_NMDA/addmsg1' )
+ addmsg1.value = '.. VmOut ./block Vm'
+ addmsg2 = moose.Mstring( '/library/Ca_NMDA/addmsg2' )
+ addmsg2.value = './block IkOut ../NMDA_Ca_conc current'
+ # The original model has the Ca current also coming here.
#========================================================================
# Ca pool for influx through Ca_NMDA
#========================================================================
def make_NMDA_Ca_conc():
- if moose.exists( 'NMDA_Ca_conc' ):
- return
- NMDA_Ca_conc = moose.CaConc( 'NMDA_Ca_conc' )
- NMDA_Ca_conc.tau = 0.004 # sec. Faster in spine than dend
- NMDA_Ca_conc.B = 17.402e12 # overridden by cellreader.
- NMDA_Ca_conc.Ca_base = 0.0
+ if moose.exists( 'NMDA_Ca_conc' ):
+ return
+ NMDA_Ca_conc = moose.CaConc( 'NMDA_Ca_conc' )
+ NMDA_Ca_conc.tau = 0.004 # sec. Faster in spine than dend
+ NMDA_Ca_conc.B = 17.402e12 # overridden by cellreader.
+ NMDA_Ca_conc.Ca_base = 0.0
# This pool used to set up Ca info coming to it. Now we insist that the
# originating channel should specify the deferred message.
@@ -489,9 +489,9 @@ def make_NMDA_Ca_conc():
#//addmsg axon/spike axon BUFFER name
def make_axon():
- if moose.exists( 'axon' ):
- return
- axon = moose.SpikeGen( 'axon' )
- axon.threshold = -40e-3 # V
- axon.abs_refract = 10e-3 # sec
+ if moose.exists( 'axon' ):
+ return
+ axon = moose.SpikeGen( 'axon' )
+ axon.threshold = -40e-3 # V
+ axon.abs_refract = 10e-3 # sec
diff --git a/moose-examples/snippets/MULTI/runcell18.py b/moose-examples/snippets/MULTI/runcell18.py
index 3007dd726d8c871ef3e674a7501af74d48f83974..cbe5037c594bb37eca4086c9fcd286e24e89f723 100644
--- a/moose-examples/snippets/MULTI/runcell18.py
+++ b/moose-examples/snippets/MULTI/runcell18.py
@@ -6,10 +6,10 @@ import moose
import proto18
def dumpPlots( fname ):
- if ( os.path.exists( fname ) ):
- os.remove( fname )
- tab.xplot( fname, 'soma.Vm' )
- catab.xplot( fname, 'soma.Ca' )
+ if ( os.path.exists( fname ) ):
+ os.remove( fname )
+ tab.xplot( fname, 'soma.Vm' )
+ catab.xplot( fname, 'soma.Ca' )
library = moose.Neutral( '/library' )
moose.setCwe( '/library' )
@@ -38,7 +38,7 @@ soma.inject = 2e-10
moose.connect( tab, 'requestOut', soma, 'getVm' )
capool = moose.element( '/cell/soma/Ca_conc' )
moose.connect( catab, 'requestOut', capool, 'getCa' )
-print 1
+print((1))
dt = 50e-6
moose.setClock( 0, dt )
moose.setClock( 1, dt )
@@ -49,12 +49,12 @@ moose.useClock( 1, '/cell/##[ISA=Compartment]', 'process' )
moose.useClock( 2, '/cell/##[ISA!=Compartment]', 'process' )
moose.useClock( 3, '/graphs/soma,/graphs/ca', 'process' )
-print 2
+print((2))
moose.reinit()
-print 3
+print((3))
moose.start( 0.1 )
dumpPlots( '50usec.plot' )
-print 4
+print((4))
moose.reinit()
hsolve = moose.HSolve( '/cell/hsolve' )
moose.useClock( 1, '/cell/hsolve', 'process' )
@@ -62,10 +62,10 @@ hsolve.dt = dt
hsolve.target = '/cell/soma'
moose.reinit()
moose.reinit()
-print 5
+print((5))
moose.start( 0.1 )
-print 6
+print((6))
dumpPlots( 'h50usec.plot' )
-print 7
+print((7))
diff --git a/moose-examples/snippets/MULTI/x_compt.py b/moose-examples/snippets/MULTI/x_compt.py
index 1aeba1f2c41183c4e259b8165358b4a065090730..62c20560e896179a52787a05c2fbdba6b7ffccdc 100644
--- a/moose-examples/snippets/MULTI/x_compt.py
+++ b/moose-examples/snippets/MULTI/x_compt.py
@@ -44,23 +44,23 @@ import proto18
EREST_ACT = -70e-3
def loadElec():
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- proto18.make_Ca()
- proto18.make_Ca_conc()
- proto18.make_K_AHP()
- proto18.make_K_C()
- proto18.make_Na()
- proto18.make_K_DR()
- proto18.make_K_A()
- proto18.make_glu()
- proto18.make_NMDA()
- proto18.make_Ca_NMDA()
- proto18.make_NMDA_Ca_conc()
- proto18.make_axon()
- model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "hsolve" )
- return cellId
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ proto18.make_Ca()
+ proto18.make_Ca_conc()
+ proto18.make_K_AHP()
+ proto18.make_K_C()
+ proto18.make_Na()
+ proto18.make_K_DR()
+ proto18.make_K_A()
+ proto18.make_glu()
+ proto18.make_NMDA()
+ proto18.make_Ca_NMDA()
+ proto18.make_NMDA_Ca_conc()
+ proto18.make_axon()
+ model = moose.Neutral( '/model' )
+ cellId = moose.loadModel( 'ca1_asym.p', '/model/elec', "hsolve" )
+ return cellId
def addPlot( objpath, field, plot ):
assert moose.exists( objpath )
@@ -79,169 +79,169 @@ def dumpPlots( fname ):
moose.element( x[0] ).xplot( fname, x[0].name + '_e' )
def moveCompt( path, oldParent, newParent ):
- meshEntries = moose.element( newParent.path + '/mesh' )
- # Set up vol messaging from new compts to all their child objects.
- for x in moose.wildcardFind( path + '/##[ISA=PoolBase]' ):
- moose.connect( meshEntries, 'mesh', x, 'mesh', 'OneToOne' )
- orig = moose.element( path )
- moose.move( orig, newParent )
- moose.delete( moose.vec( oldParent.path ) )
- chem = moose.element( '/model/chem' )
- moose.move( newParent, chem )
+ meshEntries = moose.element( newParent.path + '/mesh' )
+ # Set up vol messaging from new compts to all their child objects.
+ for x in moose.wildcardFind( path + '/##[ISA=PoolBase]' ):
+ moose.connect( meshEntries, 'mesh', x, 'mesh', 'OneToOne' )
+ orig = moose.element( path )
+ moose.move( orig, newParent )
+ moose.delete( moose.vec( oldParent.path ) )
+ chem = moose.element( '/model/chem' )
+ moose.move( newParent, chem )
def loadChem( neuroCompt, spineCompt, psdCompt ):
- # We need the compartments to come in with a volume of 1 to match the
- # original CubeMesh.
- assert( neuroCompt.volume == 1.0 )
- assert( spineCompt.volume == 1.0 )
- assert( psdCompt.volume == 1.0 )
- assert( neuroCompt.mesh.num == 1 )
- #print 'volume = ', neuroCompt.mesh[0].volume
- #assert( neuroCompt.mesh[0].volume == 1.0 )
- #an unfortunate mismatch
- # So we'll have to resize the volumes of the current compartments to the
- # new ones.
-
- modelId = moose.loadModel( 'x_compt.g', '/model', 'ee' )
- chem = moose.element( '/model/model' )
- chem.name = 'chem'
- oldN = moose.element( '/model/chem/compartment_1' )
- oldS = moose.element( '/model/chem/compartment_2' )
- oldP = moose.element( '/model/chem/kinetics' )
- oldN.volume = neuroCompt.mesh[0].volume
- oldS.volume = spineCompt.mesh[0].volume
- oldP.volume = psdCompt.mesh[0].volume
- moveCompt( '/model/chem/kinetics/DEND', oldN, neuroCompt )
- moveCompt( '/model/chem/kinetics/SPINE', oldS, spineCompt )
- moveCompt( '/model/chem/kinetics/PSD', oldP, psdCompt )
+ # We need the compartments to come in with a volume of 1 to match the
+ # original CubeMesh.
+ assert( neuroCompt.volume == 1.0 )
+ assert( spineCompt.volume == 1.0 )
+ assert( psdCompt.volume == 1.0 )
+ assert( neuroCompt.mesh.num == 1 )
+ #print 'volume = ', neuroCompt.mesh[0].volume
+ #assert( neuroCompt.mesh[0].volume == 1.0 )
+ #an unfortunate mismatch
+ # So we'll have to resize the volumes of the current compartments to the
+ # new ones.
+
+ modelId = moose.loadModel( 'x_compt.g', '/model', 'ee' )
+ chem = moose.element( '/model/model' )
+ chem.name = 'chem'
+ oldN = moose.element( '/model/chem/compartment_1' )
+ oldS = moose.element( '/model/chem/compartment_2' )
+ oldP = moose.element( '/model/chem/kinetics' )
+ oldN.volume = neuroCompt.mesh[0].volume
+ oldS.volume = spineCompt.mesh[0].volume
+ oldP.volume = psdCompt.mesh[0].volume
+ moveCompt( '/model/chem/kinetics/DEND', oldN, neuroCompt )
+ moveCompt( '/model/chem/kinetics/SPINE', oldS, spineCompt )
+ moveCompt( '/model/chem/kinetics/PSD', oldP, psdCompt )
def makeNeuroMeshModel():
- diffLength = 20e-6 # But we only want diffusion over part of the model.
- numSyn = 13
- elec = loadElec()
- synInput = moose.SpikeGen( '/model/elec/synInput' )
- synInput.threshold = -1.0
- synInput.edgeTriggered = 0
- synInput.Vm( 0 )
- synInput.refractT = 47e-3
-
- for i in range( numSyn ):
- name = '/model/elec/spine_head_14_' + str( i + 1 )
- r = moose.element( name + '/glu' )
- r.synapse.num = 1
- syn = moose.element( r.path + '/synapse' )
- moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
- syn.weight = 0.2 * i * ( numSyn - 1 - i )
- syn.delay = i * 1.0e-3
-
- neuroCompt = moose.NeuroMesh( '/model/neuroMesh' )
- #print 'neuroMeshvolume = ', neuroCompt.mesh[0].volume
- neuroCompt.separateSpines = 1
- neuroCompt.diffLength = diffLength
- neuroCompt.geometryPolicy = 'cylinder'
- spineCompt = moose.SpineMesh( '/model/spineMesh' )
- #print 'spineMeshvolume = ', spineCompt.mesh[0].volume
- moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
- psdCompt = moose.PsdMesh( '/model/psdMesh' )
- #print 'psdMeshvolume = ', psdCompt.mesh[0].volume
- moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
- loadChem( neuroCompt, spineCompt, psdCompt )
- #for x in moose.wildcardFind( '/model/chem/##/Ca' ):
- # x.diffConst = 1e-11
-
- # Put in the solvers, see how they fare.
- nmksolve = moose.GslStoich( '/model/chem/neuroMesh/ksolve' )
- nmksolve.path = '/model/chem/neuroMesh/##'
- nmksolve.compartment = moose.element( '/model/chem/neuroMesh' )
- nmksolve.method = 'rk5'
- nm = moose.element( '/model/chem/neuroMesh/mesh' )
- moose.connect( nm, 'remesh', nmksolve, 'remesh' )
+ diffLength = 20e-6 # But we only want diffusion over part of the model.
+ numSyn = 13
+ elec = loadElec()
+ synInput = moose.SpikeGen( '/model/elec/synInput' )
+ synInput.threshold = -1.0
+ synInput.edgeTriggered = 0
+ synInput.Vm( 0 )
+ synInput.refractT = 47e-3
+
+ for i in range( numSyn ):
+ name = '/model/elec/spine_head_14_' + str( i + 1 )
+ r = moose.element( name + '/glu' )
+ r.synapse.num = 1
+ syn = moose.element( r.path + '/synapse' )
+ moose.connect( synInput, 'spikeOut', syn, 'addSpike', 'Single' )
+ syn.weight = 0.2 * i * ( numSyn - 1 - i )
+ syn.delay = i * 1.0e-3
+
+ neuroCompt = moose.NeuroMesh( '/model/neuroMesh' )
+ #print 'neuroMeshvolume = ', neuroCompt.mesh[0].volume
+ neuroCompt.separateSpines = 1
+ neuroCompt.diffLength = diffLength
+ neuroCompt.geometryPolicy = 'cylinder'
+ spineCompt = moose.SpineMesh( '/model/spineMesh' )
+ #print 'spineMeshvolume = ', spineCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'spineListOut', spineCompt, 'spineList', 'OneToOne' )
+ psdCompt = moose.PsdMesh( '/model/psdMesh' )
+ #print 'psdMeshvolume = ', psdCompt.mesh[0].volume
+ moose.connect( neuroCompt, 'psdListOut', psdCompt, 'psdList', 'OneToOne' )
+ loadChem( neuroCompt, spineCompt, psdCompt )
+ #for x in moose.wildcardFind( '/model/chem/##/Ca' ):
+ # x.diffConst = 1e-11
+
+ # Put in the solvers, see how they fare.
+ nmksolve = moose.GslStoich( '/model/chem/neuroMesh/ksolve' )
+ nmksolve.path = '/model/chem/neuroMesh/##'
+ nmksolve.compartment = moose.element( '/model/chem/neuroMesh' )
+ nmksolve.method = 'rk5'
+ nm = moose.element( '/model/chem/neuroMesh/mesh' )
+ moose.connect( nm, 'remesh', nmksolve, 'remesh' )
#print "neuron: nv=", nmksolve.numLocalVoxels, ", nav=", nmksolve.numAllVoxels, nmksolve.numVarPools, nmksolve.numAllPools
#print 'setting up smksolve'
- smksolve = moose.GslStoich( '/model/chem/spineMesh/ksolve' )
- smksolve.path = '/model/chem/spineMesh/##'
- smksolve.compartment = moose.element( '/model/chem/spineMesh' )
- smksolve.method = 'rk5'
- sm = moose.element( '/model/chem/spineMesh/mesh' )
- moose.connect( sm, 'remesh', smksolve, 'remesh' )
- #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
- #
- #print 'setting up pmksolve'
- pmksolve = moose.GslStoich( '/model/chem/psdMesh/ksolve' )
- pmksolve.path = '/model/chem/psdMesh/##'
- pmksolve.compartment = moose.element( '/model/chem/psdMesh' )
- pmksolve.method = 'rk5'
- pm = moose.element( '/model/chem/psdMesh/mesh' )
- moose.connect( pm, 'remesh', pmksolve, 'remesh' )
- #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
- #
- #print 'neuroMeshvolume = ', neuroCompt.mesh[0].volume
-
- #print 'Assigning the cell model'
- # Now to set up the model.
- #neuroCompt.cell = elec
- neuroCompt.cellPortion( elec, '/model/elec/lat_14_#,/model/elec/spine_neck#,/model/elec/spine_head#' )
- ns = neuroCompt.numSegments
- #assert( ns == 11 ) # dend, 5x (shaft+head)
- ndc = neuroCompt.numDiffCompts
- assert( ndc == 13 )
- ndc = neuroCompt.mesh.num
- assert( ndc == 13 )
-
- sdc = spineCompt.mesh.num
- assert( sdc == 13 )
- pdc = psdCompt.mesh.num
- assert( pdc == 13 )
- #print 'mesh nums ( neuro, spine, psd ) = ', ndc, sdc, pdc, ', numSeg = ', ns
-
- mesh = moose.vec( '/model/chem/neuroMesh/mesh' )
- #for i in range( ndc ):
- # print 's[', i, '] = ', mesh[i].volume
- mesh2 = moose.vec( '/model/chem/spineMesh/mesh' )
-# for i in range( sdc ):
-# print 's[', i, '] = ', mesh2[i].volume
- #print 'numPSD = ', moose.element( '/model/chem/psdMesh/mesh' ).localNumField
- mesh = moose.vec( '/model/chem/psdMesh/mesh' )
- #print 'psd mesh.volume = ', mesh.volume
- #for i in range( pdc ):
- # print 's[', i, '] = ', mesh[i].volume
- #
- # We need to use the spine solver as the master for the purposes of
- # these calculations. This will handle the diffusion calculations
- # between head and dendrite, and between head and PSD.
- smksolve.addJunction( nmksolve )
- #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
- smksolve.addJunction( pmksolve )
- #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
-
- # oddly, numLocalFields does not work.
- #moose.le( '/model/chem/neuroMesh' )
- ca = moose.element( '/model/chem/neuroMesh/DEND/Ca' )
- assert( ca.lastDimension == ndc )
- """
- CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
- print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
- CaNspine = moose.vec( '/model/chem/spineMesh/SPINE/CaN_BULK/CaN' )
- print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
- """
-
- # set up adaptors
- aCa = moose.Adaptor( '/model/chem/psdMesh/adaptCa', pdc )
- adaptCa = moose.vec( '/model/chem/psdMesh/adaptCa' )
- chemCa = moose.vec( '/model/chem/psdMesh/PSD/Ca' )
- assert( len( adaptCa ) == pdc )
- assert( len( chemCa ) == pdc )
- for i in range( pdc ):
- path = '/model/elec/spine_head_14_' + str( i + 1 ) + '/NMDA_Ca_conc'
- elecCa = moose.element( path )
- moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
- moose.connect( adaptCa, 'outputSrc', chemCa, 'setConc', 'OneToOne' )
- adaptCa.inputOffset = 0.0 #
- adaptCa.outputOffset = 0.000 # 100 nM offset in chem.
- adaptCa.scale = 1e-5 # 520 to 0.0052 mM
- #print adaptCa.outputOffset
- #print adaptCa.scale
+ smksolve = moose.GslStoich( '/model/chem/spineMesh/ksolve' )
+ smksolve.path = '/model/chem/spineMesh/##'
+ smksolve.compartment = moose.element( '/model/chem/spineMesh' )
+ smksolve.method = 'rk5'
+ sm = moose.element( '/model/chem/spineMesh/mesh' )
+ moose.connect( sm, 'remesh', smksolve, 'remesh' )
+ #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
+ #
+ #print 'setting up pmksolve'
+ pmksolve = moose.GslStoich( '/model/chem/psdMesh/ksolve' )
+ pmksolve.path = '/model/chem/psdMesh/##'
+ pmksolve.compartment = moose.element( '/model/chem/psdMesh' )
+ pmksolve.method = 'rk5'
+ pm = moose.element( '/model/chem/psdMesh/mesh' )
+ moose.connect( pm, 'remesh', pmksolve, 'remesh' )
+ #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
+ #
+ #print 'neuroMeshvolume = ', neuroCompt.mesh[0].volume
+
+ #print 'Assigning the cell model'
+ # Now to set up the model.
+ #neuroCompt.cell = elec
+ neuroCompt.cellPortion( elec, '/model/elec/lat_14_#,/model/elec/spine_neck#,/model/elec/spine_head#' )
+ ns = neuroCompt.numSegments
+ #assert( ns == 11 ) # dend, 5x (shaft+head)
+ ndc = neuroCompt.numDiffCompts
+ assert( ndc == 13 )
+ ndc = neuroCompt.mesh.num
+ assert( ndc == 13 )
+
+ sdc = spineCompt.mesh.num
+ assert( sdc == 13 )
+ pdc = psdCompt.mesh.num
+ assert( pdc == 13 )
+ #print 'mesh nums ( neuro, spine, psd ) = ', ndc, sdc, pdc, ', numSeg = ', ns
+
+ mesh = moose.vec( '/model/chem/neuroMesh/mesh' )
+ #for i in range( ndc ):
+ # print 's[', i, '] = ', mesh[i].volume
+ mesh2 = moose.vec( '/model/chem/spineMesh/mesh' )
+# for i in range( sdc ):
+# print 's[', i, '] = ', mesh2[i].volume
+ #print 'numPSD = ', moose.element( '/model/chem/psdMesh/mesh' ).localNumField
+ mesh = moose.vec( '/model/chem/psdMesh/mesh' )
+ #print 'psd mesh.volume = ', mesh.volume
+ #for i in range( pdc ):
+ # print 's[', i, '] = ', mesh[i].volume
+ #
+ # We need to use the spine solver as the master for the purposes of
+ # these calculations. This will handle the diffusion calculations
+ # between head and dendrite, and between head and PSD.
+ smksolve.addJunction( nmksolve )
+ #print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
+ smksolve.addJunction( pmksolve )
+ #print "psd: nv=", pmksolve.numLocalVoxels, ", nav=", pmksolve.numAllVoxels, pmksolve.numVarPools, pmksolve.numAllPools
+
+ # oddly, numLocalFields does not work.
+ #moose.le( '/model/chem/neuroMesh' )
+ ca = moose.element( '/model/chem/neuroMesh/DEND/Ca' )
+ assert( ca.lastDimension == ndc )
+ """
+ CaNpsd = moose.vec( '/model/chem/psdMesh/PSD/PP1_PSD/CaN' )
+ print 'numCaN in PSD = ', CaNpsd.nInit, ', vol = ', CaNpsd.volume
+ CaNspine = moose.vec( '/model/chem/spineMesh/SPINE/CaN_BULK/CaN' )
+ print 'numCaN in spine = ', CaNspine.nInit, ', vol = ', CaNspine.volume
+ """
+
+ # set up adaptors
+ aCa = moose.Adaptor( '/model/chem/psdMesh/adaptCa', pdc )
+ adaptCa = moose.vec( '/model/chem/psdMesh/adaptCa' )
+ chemCa = moose.vec( '/model/chem/psdMesh/PSD/Ca' )
+ assert( len( adaptCa ) == pdc )
+ assert( len( chemCa ) == pdc )
+ for i in range( pdc ):
+ path = '/model/elec/spine_head_14_' + str( i + 1 ) + '/NMDA_Ca_conc'
+ elecCa = moose.element( path )
+ moose.connect( elecCa, 'concOut', adaptCa[i], 'input', 'Single' )
+ moose.connect( adaptCa, 'outputSrc', chemCa, 'setConc', 'OneToOne' )
+ adaptCa.inputOffset = 0.0 #
+ adaptCa.outputOffset = 0.000 # 100 nM offset in chem.
+ adaptCa.scale = 1e-5 # 520 to 0.0052 mM
+ #print adaptCa.outputOffset
+ #print adaptCa.scale
def makeElecPlots():
graphs = moose.Neutral( '/graphs' )
@@ -294,83 +294,83 @@ def makeChemPlots():
addPlot( '/model/chem/spineMesh/SPINE/bar[6]', 'getConc', 'bar6' )
def testNeuroMeshMultiscale():
- elecDt = 50e-6
- chemDt = 1e-4
- plotDt = 5e-4
- plotName = 'x_compt.plot'
-
- makeNeuroMeshModel()
- """
- for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
- if ( i[0].diffConst > 0 ):
- grandpaname = i.parent[0].parent.name + '/'
- paname = i.parent[0].name + '/'
- print grandpaname + paname + i[0].name, i[0].diffConst
- """
- """
- moose.le( '/model/chem/spineMesh/ksolve' )
- print 'Neighbors:'
- for t in moose.element( '/model/chem/spineMesh/ksolve/junction' ).neighbors['masterJunction']:
- print 'masterJunction <-', t.path
- for t in moose.wildcardFind( '/model/chem/#Mesh/ksolve' ):
- k = moose.element( t[0] )
- print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
- """
-
- makeChemPlots()
- makeElecPlots()
- moose.setClock( 0, elecDt )
- moose.setClock( 1, elecDt )
- moose.setClock( 2, elecDt )
- moose.setClock( 5, chemDt )
- moose.setClock( 6, chemDt )
- moose.setClock( 7, plotDt )
- moose.setClock( 8, plotDt )
- moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
- moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
- moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
- moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
- moose.useClock( 6, '/model/chem/##[ISA=Adaptor]', 'process' )
- moose.useClock( 7, '/graphs/#', 'process' )
- moose.useClock( 8, '/graphs/elec/#', 'process' )
- moose.useClock( 5, '/model/chem/#Mesh/ksolve', 'init' )
- moose.useClock( 6, '/model/chem/#Mesh/ksolve', 'process' )
- hsolve = moose.HSolve( '/model/elec/hsolve' )
- moose.useClock( 1, '/model/elec/hsolve', 'process' )
- hsolve.dt = elecDt
- hsolve.target = '/model/elec/compt'
- moose.reinit()
- moose.reinit()
- """
- print 'pre'
- eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'dend'
- eca = moose.vec( '/model/chem/neuroMesh/DEND/Ca' )
- for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
- print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
-
- print 'PSD'
- eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- print 'spine'
- eca = moose.vec( '/model/chem/spineMesh/SPINE/CaM/Ca' )
- for i in range( 3 ):
- print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
- """
-
- moose.start( 0.5 )
- dumpPlots( plotName )
- print 'All done'
+ elecDt = 50e-6
+ chemDt = 1e-4
+ plotDt = 5e-4
+ plotName = 'x_compt.plot'
+
+ makeNeuroMeshModel()
+ """
+ for i in moose.wildcardFind( '/model/chem/##[ISA=PoolBase]' ):
+ if ( i[0].diffConst > 0 ):
+ grandpaname = i.parent[0].parent.name + '/'
+ paname = i.parent[0].name + '/'
+ print grandpaname + paname + i[0].name, i[0].diffConst
+ """
+ """
+ moose.le( '/model/chem/spineMesh/ksolve' )
+ print 'Neighbors:'
+ for t in moose.element( '/model/chem/spineMesh/ksolve/junction' ).neighbors['masterJunction']:
+ print 'masterJunction <-', t.path
+ for t in moose.wildcardFind( '/model/chem/#Mesh/ksolve' ):
+ k = moose.element( t[0] )
+ print k.path + ' localVoxels=', k.numLocalVoxels, ', allVoxels= ', k.numAllVoxels
+ """
+
+ makeChemPlots()
+ makeElecPlots()
+ moose.setClock( 0, elecDt )
+ moose.setClock( 1, elecDt )
+ moose.setClock( 2, elecDt )
+ moose.setClock( 5, chemDt )
+ moose.setClock( 6, chemDt )
+ moose.setClock( 7, plotDt )
+ moose.setClock( 8, plotDt )
+ moose.useClock( 0, '/model/elec/##[ISA=Compartment]', 'init' )
+ moose.useClock( 1, '/model/elec/##[ISA=SpikeGen]', 'process' )
+ moose.useClock( 2, '/model/elec/##[ISA=ChanBase],/model/##[ISA=SynBase],/model/##[ISA=CaConc]','process')
+ moose.useClock( 5, '/model/chem/##[ISA=PoolBase],/model/##[ISA=ReacBase],/model/##[ISA=EnzBase]', 'process' )
+ moose.useClock( 6, '/model/chem/##[ISA=Adaptor]', 'process' )
+ moose.useClock( 7, '/graphs/#', 'process' )
+ moose.useClock( 8, '/graphs/elec/#', 'process' )
+ moose.useClock( 5, '/model/chem/#Mesh/ksolve', 'init' )
+ moose.useClock( 6, '/model/chem/#Mesh/ksolve', 'process' )
+ hsolve = moose.HSolve( '/model/elec/hsolve' )
+ moose.useClock( 1, '/model/elec/hsolve', 'process' )
+ hsolve.dt = elecDt
+ hsolve.target = '/model/elec/compt'
+ moose.reinit()
+ moose.reinit()
+ """
+ print 'pre'
+ eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'dend'
+ eca = moose.vec( '/model/chem/neuroMesh/DEND/Ca' )
+ for i in ( 0, 1, 2, 30, 60, 90, 120, 144 ):
+ print i, eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+
+ print 'PSD'
+ eca = moose.vec( '/model/chem/psdMesh/PSD/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ print 'spine'
+ eca = moose.vec( '/model/chem/spineMesh/SPINE/CaM/Ca' )
+ for i in range( 3 ):
+ print eca[i].concInit, eca[i].conc, eca[i].nInit, eca[i].n, eca[i].volume
+ """
+
+ moose.start( 0.5 )
+ dumpPlots( plotName )
+ print('All done')
def main():
- testNeuroMeshMultiscale()
+ testNeuroMeshMultiscale()
if __name__ == '__main__':
- main()
+ main()
#
# loadMulti.py ends here.
diff --git a/moose-examples/snippets/RandSpikeStats.py b/moose-examples/snippets/RandSpikeStats.py
index cea9c03244ce1f75f2b4139024a0df08aa8c9b46..9be0ffa812edcde654ac1d639dc0eea4e8bd7498 100644
--- a/moose-examples/snippets/RandSpikeStats.py
+++ b/moose-examples/snippets/RandSpikeStats.py
@@ -102,4 +102,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/STDP.py b/moose-examples/snippets/STDP.py
index dec9be84090458baed4e0e5a653ee6e7832abc35..bd16f32d92b4a6390ad25aa1e52042b358964f27 100644
--- a/moose-examples/snippets/STDP.py
+++ b/moose-examples/snippets/STDP.py
@@ -157,7 +157,7 @@ def main():
t_extent = 20e-3 # s
# dt = tpost - tpre
# negative dt corresponds to post before pre
- print '-----------------------------------------------'
+ print('-----------------------------------------------')
for deltat in arange(t_extent,0.0,-ddt):
reset_settle()
# post neuron spike
@@ -167,9 +167,9 @@ def main():
make_neuron_spike(0)
moose.start(1e-3)
dw = ( syn.synapse[0].weight - weight ) / weight
- print 'post before pre, dt = %1.3f s, dw/w = %1.3f'%(-deltat,dw)
+ print(('post before pre, dt = %1.3f s, dw/w = %1.3f'%(-deltat,dw)))
dwlist_neg.append(dw)
- print '-----------------------------------------------'
+ print('-----------------------------------------------')
# positive dt corresponds to pre before post
dwlist_pos = []
for deltat in arange(ddt,t_extent+ddt,ddt):
@@ -181,9 +181,9 @@ def main():
make_neuron_spike(1)
moose.start(1e-3)
dw = ( syn.synapse[0].weight - weight ) / weight
- print 'pre before post, dt = %1.3f s, dw/w = %1.3f'%(deltat,dw)
+ print(('pre before post, dt = %1.3f s, dw/w = %1.3f'%(deltat,dw)))
dwlist_pos.append(dw)
- print '-----------------------------------------------'
+ print('-----------------------------------------------')
# ###########################################
# Plot the simulated Vm-s and STDP curve
diff --git a/moose-examples/snippets/bidirectionalPlasticity.py b/moose-examples/snippets/bidirectionalPlasticity.py
index 11d6b5eedce56872c657fa13231f4037f3ee48d5..1101807e89bddf151c9a7b60850a52971699a010 100644
--- a/moose-examples/snippets/bidirectionalPlasticity.py
+++ b/moose-examples/snippets/bidirectionalPlasticity.py
@@ -49,13 +49,13 @@ def main():
modelId = moose.loadModel( './stargazin_synapse.g', 'model', method )
moose.start( 1000.0 ) # Run the model for 1000 seconds.
Ca = moose.element( '/model/kinetics/BULK/Ca' )
- Ca.concInit = 2.0e-3 # Calcium stimulus for turnon
+ Ca.concInit = 2.0e-3 # Calcium stimulus for turnon
moose.start( 20.0 ) # Run the model for 100 seconds.
- Ca.concInit = 0.08e-3 # Calcium back to baseline
+ Ca.concInit = 0.08e-3 # Calcium back to baseline
moose.start( 1000.0 ) # Let system settle for 1000 sec
- Ca.concInit = 0.2e-3 # Calcium turnoff stimulus
+ Ca.concInit = 0.2e-3 # Calcium turnoff stimulus
moose.start( 2000.0 ) # Run the model for 1000 seconds for turnoff
- Ca.concInit = 0.08e-3 # Calcium back to baseline
+ Ca.concInit = 0.08e-3 # Calcium back to baseline
moose.start( 2000.0 ) # Let system settle for 2000 sec
displayPlots()
@@ -63,4 +63,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/changeFuncExpression.py b/moose-examples/snippets/changeFuncExpression.py
index 13e9b6cff79f7d278e80871a5e4888758ec651ba..0e6dd09a498a4acf5bc008faf17fb584bd2c0b90 100644
--- a/moose-examples/snippets/changeFuncExpression.py
+++ b/moose-examples/snippets/changeFuncExpression.py
@@ -23,29 +23,29 @@ import moose
useY = False
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compartment = moose.CubeMesh( '/model/compartment' )
- compartment.volume = 1e-15
- # the mesh is created automatically by the compartment
- mesh = moose.element( '/model/compartment/mesh' )
-
- # create molecules and reactions
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compartment = moose.CubeMesh( '/model/compartment' )
+ compartment.volume = 1e-15
+ # the mesh is created automatically by the compartment
+ mesh = moose.element( '/model/compartment/mesh' )
+
+ # create molecules and reactions
# a <----> b
# b + 10c ---func---> d
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- c = moose.Pool( '/model/compartment/c' )
- d = moose.BufPool( '/model/compartment/d' )
- reac = moose.Reac( '/model/compartment/reac' )
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ c = moose.Pool( '/model/compartment/c' )
+ d = moose.BufPool( '/model/compartment/d' )
+ reac = moose.Reac( '/model/compartment/reac' )
func = moose.Function( '/model/compartment/d/func' )
func.numVars = 2
#func.x.num = 2
- # connect them up for reactions
+ # connect them up for reactions
- moose.connect( reac, 'sub', a, 'reac' )
- moose.connect( reac, 'prd', b, 'reac' )
+ moose.connect( reac, 'sub', a, 'reac' )
+ moose.connect( reac, 'prd', b, 'reac' )
if useY:
moose.connect( func, 'requestOut', b, 'getN' )
moose.connect( func, 'requestOut', c, 'getN' )
@@ -59,72 +59,72 @@ def makeModel():
else:
func.expr = "x0 + 10*x1"
- # connect them up to the compartment for volumes
- #for x in ( a, b, c, cplx1, cplx2 ):
- # moose.connect( x, 'mesh', mesh, 'mesh' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 0.5
- c.concInit = 0.1
- reac.Kf = 0.001
- reac.Kb = 0.01
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/concA' )
- outputB = moose.Table2 ( '/model/graphs/concB' )
- outputC = moose.Table2 ( '/model/graphs/concC' )
- outputD = moose.Table2 ( '/model/graphs/concD' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
- moose.connect( outputC, 'requestOut', c, 'getConc' );
- moose.connect( outputD, 'requestOut', d, 'getConc' );
+ # connect them up to the compartment for volumes
+ #for x in ( a, b, c, cplx1, cplx2 ):
+ # moose.connect( x, 'mesh', mesh, 'mesh' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 0.5
+ c.concInit = 0.1
+ reac.Kf = 0.001
+ reac.Kb = 0.01
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/concA' )
+ outputB = moose.Table2 ( '/model/graphs/concB' )
+ outputC = moose.Table2 ( '/model/graphs/concC' )
+ outputD = moose.Table2 ( '/model/graphs/concD' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
+ moose.connect( outputC, 'requestOut', c, 'getConc' );
+ moose.connect( outputD, 'requestOut', d, 'getConc' );
def displayPlots():
- for x in moose.wildcardFind( '/model/graphs/conc#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ for x in moose.wildcardFind( '/model/graphs/conc#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
def main():
- makeModel()
+ makeModel()
'''
'''
- ksolve = moose.Ksolve( '/model/compartment/ksolve' )
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = moose.element( '/model/compartment' )
- stoich.ksolve = ksolve
- stoich.path = "/model/compartment/##"
- #solver.method = "rk5"
- #mesh = moose.element( "/model/compartment/mesh" )
- #moose.connect( mesh, "remesh", solver, "remesh" )
+ ksolve = moose.Ksolve( '/model/compartment/ksolve' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = moose.element( '/model/compartment' )
+ stoich.ksolve = ksolve
+ stoich.path = "/model/compartment/##"
+ #solver.method = "rk5"
+ #mesh = moose.element( "/model/compartment/mesh" )
+ #moose.connect( mesh, "remesh", solver, "remesh" )
'''
- moose.setClock( 5, 1.0 ) # clock for the solver
- moose.useClock( 5, '/model/compartment/ksolve', 'process' )
+ moose.setClock( 5, 1.0 ) # clock for the solver
+ moose.useClock( 5, '/model/compartment/ksolve', 'process' )
'''
- moose.reinit()
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ moose.reinit()
+ moose.start( 100.0 ) # Run the model for 100 seconds.
func = moose.element( '/model/compartment/d/func' )
if useY:
func.expr = "-y0 + 10*y1"
else:
func.expr = "-x0 + 10*x1"
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ moose.start( 100.0 ) # Run the model for 100 seconds.
#moose.showfields( '/model/compartment/d' )
#moose.showfields( '/model/compartment/d/func' )
- print func.x.value
- print moose.element( '/model/compartment/b' ).n
+ print((func.x.value))
+ print((moose.element( '/model/compartment/b' ).n))
- # Iterate through all plots, dump their contents to data.plot.
- displayPlots()
+ # Iterate through all plots, dump their contents to data.plot.
+ displayPlots()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/chemDoseResponse.py b/moose-examples/snippets/chemDoseResponse.py
index c3b7737079be134f3fee8c8bb67796051d94700b..42aa297e8750a8001922a212bfcf002d9b1b9245 100644
--- a/moose-examples/snippets/chemDoseResponse.py
+++ b/moose-examples/snippets/chemDoseResponse.py
@@ -183,4 +183,4 @@ def makeModel():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/compartment_net.py b/moose-examples/snippets/compartment_net.py
index 8d66b30642d3cf695e41e0ffb7833997f4bc5316..58b32e9fa14b3d2deb3ad4791101c5fe5ffd145a 100644
--- a/moose-examples/snippets/compartment_net.py
+++ b/moose-examples/snippets/compartment_net.py
@@ -67,10 +67,10 @@ def create_population(container, size):
"""
path = container.path
- print path, size, type(path)
+ print((path, size, type(path)))
comps = create_1comp_neuron('{}/neuron'.format(path), number=size)
synpath = path+'/synchan'
- print synpath, size, type(size)
+ print((synpath, size, type(size)))
synchan = moose.vec(synpath, n=size, dtype='SynChan')
synchan.Gbar = 1e-8
synchan.tau1 = 2e-3
@@ -109,14 +109,14 @@ def make_synapses(spikegen, synhandler, connprob=1.0, delay=5e-3):
sh.synapse.vec.delay = 5e-3
for ii, syn in enumerate(sh.synapse):
msg = moose.connect(spikegen[ii], 'spikeOut', syn, 'addSpike')
- print 'Connected', spikegen[ii].path, 'to', syn.path, 'on', sh.path
+ print(('Connected', spikegen[ii].path, 'to', syn.path, 'on', sh.path))
def create_network(size=2):
"""Create a network containing two neuronal populations, pop_A and
pop_B and connect them up"""
net = moose.Neutral('network')
pop_a = create_population(moose.Neutral('/network/pop_A'), size)
- print pop_a
+ print(pop_a)
pop_b = create_population(moose.Neutral('/network/pop_B'), size)
make_synapses(pop_a['spikegen'], pop_b['synhandler'])
pulse = moose.PulseGen('pulse')
@@ -156,7 +156,7 @@ if __name__ == '__main__':
moose.start(simtime)
plt.subplot(221)
for oid in vm_a.vec:
- print oid, oid.vector.shape
+ print((oid, oid.vector.shape))
plt.plot(oid.vector, label=oid.path)
plt.legend()
plt.subplot(223)
diff --git a/moose-examples/snippets/compartment_net_no_array.py b/moose-examples/snippets/compartment_net_no_array.py
index a67f271433b31712a770bbb039d843db95b51d7c..47beb305eaeca27293e22322990153e3565645e2 100644
--- a/moose-examples/snippets/compartment_net_no_array.py
+++ b/moose-examples/snippets/compartment_net_no_array.py
@@ -338,14 +338,14 @@ def assign_clocks(model_container_list, simdt, plotdt):
global inited
# `inited` is for avoiding double scheduling of the same object
if not inited:
- print 'SimDt=%g, PlotDt=%g' % (simdt, plotdt)
+ print(('SimDt=%g, PlotDt=%g' % (simdt, plotdt)))
moose.setClock(0, simdt)
moose.setClock(1, simdt)
moose.setClock(2, simdt)
moose.setClock(3, simdt)
moose.setClock(4, plotdt)
for path in model_container_list:
- print 'Scheduling elements under:', path
+ print(('Scheduling elements under:', path))
moose.useClock(0, '%s/##[TYPE=Compartment]' % (path), 'init')
moose.useClock(1, '%s/##[TYPE=Compartment]' % (path), 'process')
moose.useClock(2, '%s/##[TYPE=SynChan],%s/##[TYPE=HHChannel]' % (path, path), 'process')
diff --git a/moose-examples/snippets/compartmental_neuron.py b/moose-examples/snippets/compartmental_neuron.py
index 86ba70fdf101656d78cd7ea3f9d37d531df849ee..33a5db56bbbe9bec7f080bd545f13942f69b13db 100644
--- a/moose-examples/snippets/compartmental_neuron.py
+++ b/moose-examples/snippets/compartmental_neuron.py
@@ -52,7 +52,7 @@ compartment and the membrane voltage in both compartments are recorded
and saved into a csv file.
"""
-from __future__ import print_function
+
import sys
import numpy as np
import moose
diff --git a/moose-examples/snippets/convert_Genesis2Sbml.py b/moose-examples/snippets/convert_Genesis2Sbml.py
index 4fca921289c6affa66ed17194b9221c3139ca519..9366c29367cb6634ab38c05532eb62dcd6f6513b 100644
--- a/moose-examples/snippets/convert_Genesis2Sbml.py
+++ b/moose-examples/snippets/convert_Genesis2Sbml.py
@@ -52,13 +52,12 @@ def main():
into Moose using loadModel function and using writeSBML function
one can save the model into SBML format. \n
libsbml should be installed
-"""
- #This command loads the file into the path '/Kholodenko'
- moose.loadModel('../genesis/Kholodenko.g','/Kholodenko')
-
- #Writes model to xml file
- written = mooseWriteSBML('/Kholodenko','../genesis/Kholodenko_tosbml.xml')
- print written
+ #This command loads the file into the path '/Kholodenko'
+ moose.loadModel('../genesis/Kholodenko.g','/Kholodenko')
+
+ #Writes model to xml file
+ written = mooseWriteSBML('/Kholodenko','../genesis/Kholodenko_tosbml.xml')
+ print(written)
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/crossComptNeuroMesh.py b/moose-examples/snippets/crossComptNeuroMesh.py
index 189cc3bec3ae657d3ace006bd7412c4315fc7b1c..24883b8b07a5548a512241d40fddc0c353b62617 100644
--- a/moose-examples/snippets/crossComptNeuroMesh.py
+++ b/moose-examples/snippets/crossComptNeuroMesh.py
@@ -12,8 +12,11 @@ import math
import pylab
import numpy
import matplotlib.pyplot as plt
+import sys
import moose
+print(( '[INFO] Using moose from %s' % moose.__file__ ))
+
def makeCompt( name, parent, dx, dy, dia ):
RM = 1.0
RA = 1.0
@@ -67,40 +70,40 @@ def makeNeuron( numSeg ):
def makeModel():
numSeg = 5
diffConst = 0.0
- # create container for model
- model = moose.Neutral( 'model' )
- compt0 = moose.NeuroMesh( '/model/compt0' )
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compt0 = moose.NeuroMesh( '/model/compt0' )
compt0.separateSpines = 1
compt0.geometryPolicy = 'cylinder'
- compt1 = moose.SpineMesh( '/model/compt1' )
+ compt1 = moose.SpineMesh( '/model/compt1' )
moose.connect( compt0, 'spineListOut', compt1, 'spineList', 'OneToOne' )
- compt2 = moose.PsdMesh( '/model/compt2' )
+ compt2 = moose.PsdMesh( '/model/compt2' )
moose.connect( compt0, 'psdListOut', compt2, 'psdList', 'OneToOne' )
- # create molecules and reactions
- a = moose.Pool( '/model/compt0/a' )
- b = moose.Pool( '/model/compt1/b' )
- c = moose.Pool( '/model/compt2/c' )
- reac0 = moose.Reac( '/model/compt0/reac0' )
- reac1 = moose.Reac( '/model/compt1/reac1' )
-
- # connect them up for reactions
- moose.connect( reac0, 'sub', a, 'reac' )
- moose.connect( reac0, 'prd', b, 'reac' )
- moose.connect( reac1, 'sub', b, 'reac' )
- moose.connect( reac1, 'prd', c, 'reac' )
-
- # Assign parameters
- a.diffConst = diffConst
- b.diffConst = diffConst
- c.diffConst = diffConst
- a.concInit = 1
- b.concInit = 12.1
- c.concInit = 1
- reac0.Kf = 1
- reac0.Kb = 1
- reac1.Kf = 1
- reac1.Kb = 1
+ # create molecules and reactions
+ a = moose.Pool( '/model/compt0/a' )
+ b = moose.Pool( '/model/compt1/b' )
+ c = moose.Pool( '/model/compt2/c' )
+ reac0 = moose.Reac( '/model/compt0/reac0' )
+ reac1 = moose.Reac( '/model/compt1/reac1' )
+
+ # connect them up for reactions
+ moose.connect( reac0, 'sub', a, 'reac' )
+ moose.connect( reac0, 'prd', b, 'reac' )
+ moose.connect( reac1, 'sub', b, 'reac' )
+ moose.connect( reac1, 'prd', c, 'reac' )
+
+ # Assign parameters
+ a.diffConst = diffConst
+ b.diffConst = diffConst
+ c.diffConst = diffConst
+ a.concInit = 1
+ b.concInit = 12.1
+ c.concInit = 1
+ reac0.Kf = 1
+ reac0.Kb = 1
+ reac1.Kf = 1
+ reac1.Kb = 1
# Create a 'neuron' with a dozen spiny compartments.
elec = makeNeuron( numSeg )
@@ -143,25 +146,25 @@ def makeModel():
stoich2.filterXreacs()
- print a.vec.volume, b.vec.volume, c.vec.volume
- a.vec.concInit = range( numSeg + 1, 0, -1 )
- b.vec.concInit = [5.0 * ( 1 + x ) for x in range( numSeg )]
- c.vec.concInit = range( 1, numSeg + 1 )
- print a.vec.concInit, b.vec.concInit, c.vec.concInit
+ print((a.vec.volume, b.vec.volume, c.vec.volume))
+ a.vec.concInit = list(range( numSeg + 1, 0, -1))
+ b.vec.concInit = [5.0 * ( 1 + x ) for x in range( numSeg )]
+ c.vec.concInit = list(range( 1, numSeg + 1))
+ print((a.vec.concInit, b.vec.concInit, c.vec.concInit))
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/concA' )
- outputB = moose.Table2 ( '/model/graphs/concB' )
- outputC = moose.Table2 ( '/model/graphs/concC' )
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/concA' )
+ outputB = moose.Table2 ( '/model/graphs/concB' )
+ outputC = moose.Table2 ( '/model/graphs/concC' )
- # connect up the tables
+ # connect up the tables
a1 = moose.element( '/model/compt0/a[' + str( numSeg )+ ']')
b1 = moose.element( '/model/compt1/b[' +str(numSeg - 1)+']')
c1 = moose.element( '/model/compt2/c[' +str(numSeg - 1)+']')
- moose.connect( outputA, 'requestOut', a1, 'getConc' );
- moose.connect( outputB, 'requestOut', b1, 'getConc' );
- moose.connect( outputC, 'requestOut', c1, 'getConc' );
+ moose.connect( outputA, 'requestOut', a1, 'getConc' );
+ moose.connect( outputB, 'requestOut', b1, 'getConc' );
+ moose.connect( outputC, 'requestOut', c1, 'getConc' );
def main():
@@ -232,10 +235,13 @@ def display():
line4, = timeseries.plot( t, x.vector, label=x.name )
plt.legend()
fig.canvas.draw()
+ outfile = '%s.png' % sys.argv[0]
+ # print( "Hit 'enter' to exit" )
+ # raw_input()
+ plt.savefig( outfile )
+ print(('[INFO] Results are saved to %s' % outfile ))
- print( "Hit 'enter' to exit" )
- raw_input()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/crossComptOscillator.py b/moose-examples/snippets/crossComptOscillator.py
index cc812bc5b750aff7282620940902fd8e4af199bd..0357c9ccc02bbf92826e957180327e64b7b2d217 100644
--- a/moose-examples/snippets/crossComptOscillator.py
+++ b/moose-examples/snippets/crossComptOscillator.py
@@ -7,6 +7,8 @@
## See the file COPYING.LIB for the full notice.
#########################################################################
+from __future__ import print_function
+
import moose
import pylab
import numpy
@@ -26,10 +28,10 @@ def main():
"""
# the kkit reader doesn't know how to do multicompt solver setup.
solver = "ee"
- mfile = '../genesis/OSC_diff_vols.g'
- runtime = 3000.0
+ mfile = '../genesis/OSC_diff_vols.g'
+ runtime = 3000.0
simDt = 1.0
- modelId = moose.loadModel( mfile, 'model', solver )
+ modelId = moose.loadModel( mfile, 'model', solver )
#moose.delete( '/model/kinetics/A/Stot' )
compt0 = moose.element( '/model/kinetics' )
compt1 = moose.element( '/model/compartment_1' )
@@ -52,37 +54,37 @@ def main():
stoich1.ksolve = ksolve1
stoich1.path = '/model/compartment_1/##'
#stoich0.buildXreacs( stoich1 )
- print ksolve0.numLocalVoxels, ksolve0.numPools, stoich0.numAllPools
+ print(ksolve0.numLocalVoxels, ksolve0.numPools, stoich0.numAllPools)
assert( ksolve0.numLocalVoxels == 1 )
assert( ksolve0.numPools == 7 )
assert( stoich0.numVarPools == 5 )
assert( stoich0.numBufPools == 1 )
assert( stoich0.numProxyPools == 1 )
assert( stoich0.numAllPools == 7 )
- print len( stoich0.proxyPools[stoich1] ),
- print len( stoich1.proxyPools[stoich0] )
+ print(len( stoich0.proxyPools[stoich1] ), end=' ')
+ print(len( stoich1.proxyPools[stoich0] ))
assert( len( stoich0.proxyPools[stoich1] ) == 1 )
assert( len( stoich1.proxyPools[stoich0] ) == 1 )
- print ksolve1.numLocalVoxels, ksolve1.numPools, stoich1.numAllPools
+ print(ksolve1.numLocalVoxels, ksolve1.numPools, stoich1.numAllPools)
assert( ksolve1.numLocalVoxels == 1 )
assert( ksolve1.numPools == 6 )
assert( stoich1.numAllPools == 6 )
stoich0.buildXreacs( stoich1 )
- print moose.element( '/model/kinetics/endo' )
- print moose.element( '/model/compartment_1/exo' )
+ print(moose.element( '/model/kinetics/endo' ))
+ print(moose.element( '/model/compartment_1/exo' ))
moose.le( '/model/compartment_1' )
- moose.reinit()
- moose.start( runtime )
+ moose.reinit()
+ moose.start( runtime )
- # Display all plots.
- for x in moose.wildcardFind( '/model/#graphs/conc#/#' ):
+ # Display all plots.
+ for x in moose.wildcardFind( '/model/#graphs/conc#/#' ):
t = numpy.arange( 0, x.vector.size, 1 ) * simDt
pylab.plot( t, x.vector, label=x.name )
pylab.legend()
pylab.show()
- #quit()
+ #quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/crossComptSimpleReac.py b/moose-examples/snippets/crossComptSimpleReac.py
index 82571b307727dbf6a828be51bae607dcf0415e1c..d76ce9197fade3990f59eeb902afd9cff1c67eed 100644
--- a/moose-examples/snippets/crossComptSimpleReac.py
+++ b/moose-examples/snippets/crossComptSimpleReac.py
@@ -15,14 +15,14 @@ import numpy
import moose
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compt0 = moose.CubeMesh( '/model/compt0' )
- compt0.volume = 1e-15
- compt1 = moose.CubeMesh( '/model/compt1' )
- compt1.volume = 1e-16
- compt2 = moose.CubeMesh( '/model/compt2' )
- compt2.volume = 1e-17
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compt0 = moose.CubeMesh( '/model/compt0' )
+ compt0.volume = 1e-15
+ compt1 = moose.CubeMesh( '/model/compt1' )
+ compt1.volume = 1e-16
+ compt2 = moose.CubeMesh( '/model/compt2' )
+ compt2.volume = 1e-17
# Position containers so that they abut each other, with
# compt1 in the middle.
@@ -31,40 +31,40 @@ def makeModel():
compt0.y0 += side
compt2.x1 += side
compt2.x0 += side
- print('Volumes = ', compt0.volume, compt1.volume, compt2.volume)
-
- # create molecules and reactions
- a = moose.Pool( '/model/compt0/a' )
- b = moose.Pool( '/model/compt1/b' )
- c = moose.Pool( '/model/compt2/c' )
- reac0 = moose.Reac( '/model/compt1/reac0' )
- reac1 = moose.Reac( '/model/compt1/reac1' )
-
- # connect them up for reactions
- moose.connect( reac0, 'sub', a, 'reac' )
- moose.connect( reac0, 'prd', b, 'reac' )
- moose.connect( reac1, 'sub', b, 'reac' )
- moose.connect( reac1, 'prd', c, 'reac' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 12.1
- c.concInit = 1
- reac0.Kf = 0.1
- reac0.Kb = 0.1
- reac1.Kf = 0.1
- reac1.Kb = 0.1
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/concA' )
- outputB = moose.Table2 ( '/model/graphs/concB' )
- outputC = moose.Table2 ( '/model/graphs/concC' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
- moose.connect( outputC, 'requestOut', c, 'getConc' );
+ print(('Volumes = ', compt0.volume, compt1.volume, compt2.volume))
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compt0/a' )
+ b = moose.Pool( '/model/compt1/b' )
+ c = moose.Pool( '/model/compt2/c' )
+ reac0 = moose.Reac( '/model/compt1/reac0' )
+ reac1 = moose.Reac( '/model/compt1/reac1' )
+
+ # connect them up for reactions
+ moose.connect( reac0, 'sub', a, 'reac' )
+ moose.connect( reac0, 'prd', b, 'reac' )
+ moose.connect( reac1, 'sub', b, 'reac' )
+ moose.connect( reac1, 'prd', c, 'reac' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 12.1
+ c.concInit = 1
+ reac0.Kf = 0.1
+ reac0.Kb = 0.1
+ reac1.Kf = 0.1
+ reac1.Kb = 0.1
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/concA' )
+ outputB = moose.Table2 ( '/model/graphs/concB' )
+ outputC = moose.Table2 ( '/model/graphs/concC' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
+ moose.connect( outputC, 'requestOut', c, 'getConc' );
# Build the solvers. No need for diffusion in this version.
ksolve0 = moose.Ksolve( '/model/compt0/ksolve0' )
@@ -138,7 +138,7 @@ def main():
moose.start( runtime ) # Run the model for 100 seconds.
print("All concs should converge to 2.0 even though vols differ:")
for x in moose.wildcardFind( '/model/compt#/#[ISA=PoolBase]' ):
- print(x.name, x.conc)
+ print((x.name, x.conc))
# FIXME: Plotting causes seg-fault.
## Iterate through all plots, dump their contents to data.plot.
@@ -151,4 +151,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/crossComptSimpleReacGSSA.py b/moose-examples/snippets/crossComptSimpleReacGSSA.py
index 879fd90d8bcf3284e2f20e23acf03eccce3ae44e..8723205aed88d4c34241accd054a3f57cf051560 100644
--- a/moose-examples/snippets/crossComptSimpleReacGSSA.py
+++ b/moose-examples/snippets/crossComptSimpleReacGSSA.py
@@ -15,14 +15,14 @@ import numpy
import moose
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compt0 = moose.CubeMesh( '/model/compt0' )
- compt0.volume = 1e-18
- compt1 = moose.CubeMesh( '/model/compt1' )
- compt1.volume = 1e-19
- compt2 = moose.CubeMesh( '/model/compt2' )
- compt2.volume = 1e-20
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compt0 = moose.CubeMesh( '/model/compt0' )
+ compt0.volume = 1e-18
+ compt1 = moose.CubeMesh( '/model/compt1' )
+ compt1.volume = 1e-19
+ compt2 = moose.CubeMesh( '/model/compt2' )
+ compt2.volume = 1e-20
# Position containers so that they abut each other, with
# compt1 in the middle.
@@ -31,40 +31,40 @@ def makeModel():
compt0.y0 += side
compt2.x1 += side
compt2.x0 += side
- print('Volumes = ', compt0.volume, compt1.volume, compt2.volume)
-
- # create molecules and reactions
- a = moose.Pool( '/model/compt0/a' )
- b = moose.Pool( '/model/compt1/b' )
- c = moose.Pool( '/model/compt2/c' )
- reac0 = moose.Reac( '/model/compt1/reac0' )
- reac1 = moose.Reac( '/model/compt1/reac1' )
-
- # connect them up for reactions
- moose.connect( reac0, 'sub', a, 'reac' )
- moose.connect( reac0, 'prd', b, 'reac' )
- moose.connect( reac1, 'sub', b, 'reac' )
- moose.connect( reac1, 'prd', c, 'reac' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 12.1
- c.concInit = 1
- reac0.Kf = 0.1
- reac0.Kb = 0.1
- reac1.Kf = 0.1
- reac1.Kb = 0.1
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/concA' )
- outputB = moose.Table2 ( '/model/graphs/concB' )
- outputC = moose.Table2 ( '/model/graphs/concC' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
- moose.connect( outputC, 'requestOut', c, 'getConc' );
+ print(('Volumes = ', compt0.volume, compt1.volume, compt2.volume))
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compt0/a' )
+ b = moose.Pool( '/model/compt1/b' )
+ c = moose.Pool( '/model/compt2/c' )
+ reac0 = moose.Reac( '/model/compt1/reac0' )
+ reac1 = moose.Reac( '/model/compt1/reac1' )
+
+ # connect them up for reactions
+ moose.connect( reac0, 'sub', a, 'reac' )
+ moose.connect( reac0, 'prd', b, 'reac' )
+ moose.connect( reac1, 'sub', b, 'reac' )
+ moose.connect( reac1, 'prd', c, 'reac' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 12.1
+ c.concInit = 1
+ reac0.Kf = 0.1
+ reac0.Kb = 0.1
+ reac1.Kf = 0.1
+ reac1.Kb = 0.1
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/concA' )
+ outputB = moose.Table2 ( '/model/graphs/concB' )
+ outputC = moose.Table2 ( '/model/graphs/concC' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
+ moose.connect( outputC, 'requestOut', c, 'getConc' );
# Build the solvers. No need for diffusion in this version.
ksolve0 = moose.Gsolve( '/model/compt0/ksolve0' )
@@ -138,7 +138,7 @@ def main():
moose.start( runtime ) # Run the model for 100 seconds.
print("All concs should converge to 2.0 even though vols differ:")
for x in moose.wildcardFind( '/model/compt#/#[ISA=PoolBase]' ):
- print(x.name, x.conc)
+ print((x.name, x.conc))
# Iterate through all plots, dump their contents to data.plot.
for x in moose.wildcardFind( '/model/graphs/conc#' ):
@@ -150,4 +150,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/cspaceSteadyState.py b/moose-examples/snippets/cspaceSteadyState.py
index a21f3bf3eeac93f3770c790fefe066ac9fd33089..06a5f0bc8445df1e4a661528b83729274852f7a4 100644
--- a/moose-examples/snippets/cspaceSteadyState.py
+++ b/moose-examples/snippets/cspaceSteadyState.py
@@ -12,13 +12,13 @@
# It looks for the fixed points 100 times, as follows:
# - Set up the random initial condition that fits the conservation laws
# - Run for 2 seconds. This should not be mathematically necessary, but
-# for obscure numerical reasons it makes it much more likely that the
-# steady state solver will succeed in finding a state.
+# for obscure numerical reasons it makes it much more likely that the
+# steady state solver will succeed in finding a state.
# - Find the fixed point
# - Print out the fixed point vector and various diagnostics.
# - Run for 10 seconds. This is completely unnecessary, and is done here
-# just so that the resultant graph will show what kind of state has been
-# found.
+# just so that the resultant graph will show what kind of state has been
+# found.
# After it does all this, the program runs for 100 more seconds on the last
# found fixed point (which turns out to be a saddle node), then
# is hard-switched in the script to the first attractor basin from which
@@ -27,13 +27,13 @@
# seconds.
# Looking at the output you will see many features of note:
# - the first attractor (stable point) and the saddle point
-# (unstable fixed point) are both found quite often. But the second
-# attractor is found just once. Has a very small basin of attraction.
+# (unstable fixed point) are both found quite often. But the second
+# attractor is found just once. Has a very small basin of attraction.
# - The values found for each of the fixed points match well with the
-# values found by running the system to steady-state at the end.
+# values found by running the system to steady-state at the end.
# - There are a large number of failures to find a fixed point. These are
-# found and reported in the diagnostics. They show up on the plot
-# as cases where the 10-second runs are not flat.
+# found and reported in the diagnostics. They show up on the plot
+# as cases where the 10-second runs are not flat.
#
# If you wanted to find fixed points in a production model, you would
# not need to do the 10-second runs, and you would need to eliminate the
@@ -50,73 +50,73 @@ import numpy
import moose
def displayPlots():
- for x in moose.wildcardFind( '/model/graphs/#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ for x in moose.wildcardFind( '/model/graphs/#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
def getState( ksolve, state ):
- state.randomInit()
- moose.start( 0.1 ) # Run the model for 2 seconds.
- state.settle()
+ state.randomInit()
+ moose.start( 0.1 ) # Run the model for 2 seconds.
+ state.settle()
'''
- scale = 1.0 / ( 1e-15 * 6.022e23 )
- for x in ksolve.nVec[0]:
- print x * scale,
- # print ksolve.nVec[0]
- print state.nIter, state.status, state.stateType, state.nNegEigenvalues, state.nPosEigenvalues, state.solutionStatus
+ scale = 1.0 / ( 1e-15 * 6.022e23 )
+ for x in ksolve.nVec[0]:
+ print x * scale,
+ # print ksolve.nVec[0]
+ print state.nIter, state.status, state.stateType, state.nNegEigenvalues, state.nPosEigenvalues, state.solutionStatus
'''
- moose.start( 20.0 ) # Run model for 10 seconds, just for display
+ moose.start( 20.0 ) # Run model for 10 seconds, just for display
def main():
- # The wildcard uses # for single level, and ## for recursive.
- #compartment = makeModel()
+ # The wildcard uses # for single level, and ## for recursive.
+ #compartment = makeModel()
moose.loadModel( '../genesis/M1719.cspace', '/model', 'ee' )
compartment = moose.element( 'model/kinetics' )
compartment.name = 'compartment'
- ksolve = moose.Ksolve( '/model/compartment/ksolve' )
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = compartment
- stoich.ksolve = ksolve
- #ksolve.stoich = stoich
- stoich.path = "/model/compartment/##"
- state = moose.SteadyState( '/model/compartment/state' )
+ ksolve = moose.Ksolve( '/model/compartment/ksolve' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = compartment
+ stoich.ksolve = ksolve
+ #ksolve.stoich = stoich
+ stoich.path = "/model/compartment/##"
+ state = moose.SteadyState( '/model/compartment/state' )
- moose.reinit()
- state.stoich = stoich
- #state.showMatrices()
- state.convergenceCriterion = 1e-7
+ moose.reinit()
+ state.stoich = stoich
+ #state.showMatrices()
+ state.convergenceCriterion = 1e-7
moose.le( '/model/graphs' )
a = moose.element( '/model/compartment/a' )
b = moose.element( '/model/compartment/b' )
c = moose.element( '/model/compartment/c' )
- for i in range( 0, 100 ):
- getState( ksolve, state )
-
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ for i in range( 0, 100 ):
+ getState( ksolve, state )
+
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- b = moose.element( '/model/compartment/b' )
- c = moose.element( '/model/compartment/c' )
+ b = moose.element( '/model/compartment/b' )
+ c = moose.element( '/model/compartment/c' )
- # move most molecules over to b
- b.conc = b.conc + c.conc * 0.95
- c.conc = c.conc * 0.05
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules over to b
+ b.conc = b.conc + c.conc * 0.95
+ c.conc = c.conc * 0.05
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # move most molecules back to a
- c.conc = c.conc + b.conc * 0.95
- b.conc = b.conc * 0.05
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules back to a
+ c.conc = c.conc + b.conc * 0.95
+ b.conc = b.conc * 0.05
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # Iterate through all plots, dump their contents to data.plot.
- displayPlots()
+ # Iterate through all plots, dump their contents to data.plot.
+ displayPlots()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/cubeMeshSigNeur.py b/moose-examples/snippets/cubeMeshSigNeur.py
index 4669db48eb8e2d11ac150f6cc155acd5722b0383..355ff27b330c1f579b180c30a2db2d017c6fa1da 100644
--- a/moose-examples/snippets/cubeMeshSigNeur.py
+++ b/moose-examples/snippets/cubeMeshSigNeur.py
@@ -155,9 +155,9 @@ def createPool( compt, name, concInit ):
# This is a Ca-activated enzyme that phosphorylates and inactivates kChan
# as per the following scheme:
-# Ca + inact_kinase <===> Ca.kinase
-# kChan ----- Ca.kinase -----> kChan_p
-# kChan_p -------> kChan
+# Ca + inact_kinase <===> Ca.kinase
+# kChan ----- Ca.kinase -----> kChan_p
+# kChan_p -------> kChan
def createChemModel( neuroCompt ):
dendCa = createPool( neuroCompt, 'Ca', 1e-4 )
dendKinaseInact = createPool( neuroCompt, 'inact_kinase', 1e-4 )
diff --git a/moose-examples/snippets/cylinderDiffusion.py b/moose-examples/snippets/cylinderDiffusion.py
index 0b4d8665a5f181f04c997301f8e343cc65b42cd8..a4ff666cc60581f99598771f9a1fad02aed308e7 100644
--- a/moose-examples/snippets/cylinderDiffusion.py
+++ b/moose-examples/snippets/cylinderDiffusion.py
@@ -57,11 +57,11 @@ def makeModel():
The concentrations of all molecules are displayed in an animation.
"""
# create container for model
- r0 = 2e-6 # m
- r1 = 1e-6 # m
+ r0 = 2e-6 # m
+ r1 = 1e-6 # m
num = 100
diffLength = 1e-6 # m
- len = num * diffLength # m
+ len = num * diffLength # m
diffConst = 10e-12 # m^2/sec
motorRate = 10e-6 # m/sec
concA = 1 # millimolar
@@ -106,7 +106,7 @@ def makeModel():
os.kill( PID, signal.SIGUSR1 )
stoich.path = "/model/compartment/##"
- print dsolve.numPools
+ print((dsolve.numPools))
assert( dsolve.numPools == 3 )
a.vec[0].concInit = concA
b.vec[0].concInit = concA
@@ -180,15 +180,15 @@ def main():
ctot2 = sum( c.vec.n )
dtot2 = sum( d.vec.n )
- print 'Ratio of initial to final total numbers of of a, b, c, d = '
- print atot2/atot, btot2/btot, ctot2/ctot, dtot2/dtot
- print 'Initial to final (b+c)=', (btot2 + ctot2) / (btot + ctot )
- print "\nHit 'enter' to exit"
- raw_input()
+ print('Ratio of initial to final total numbers of of a, b, c, d = ')
+ print((atot2/atot, btot2/btot, ctot2/ctot, dtot2/dtot))
+ print(('Initial to final (b+c)=', (btot2 + ctot2) / (btot + ctot )))
+ print("\nHit 'enter' to exit")
+ eval(input())
quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/cylinderMotor.py b/moose-examples/snippets/cylinderMotor.py
index 91257b95d51c071f88ecaa4966e66aeb26c5337b..b9b96ad612e522ce5c61b3305e633288efbfcc4d 100644
--- a/moose-examples/snippets/cylinderMotor.py
+++ b/moose-examples/snippets/cylinderMotor.py
@@ -30,36 +30,36 @@ import signal
PID = os.getpid()
def doNothing( *args ):
- pass
+ pass
signal.signal( signal.SIGUSR1, doNothing )
def makeModel():
- # create container for model
- r0 = 1e-6 # m
- r1 = 1e-6 # m
- num = 25
- diffLength = 1e-6 # m
- len = num * diffLength # m
- diffConst = 1e-12 # m^2/sec
- motorConst = 1e-6 # m/sec
- concA = 1 # millimolar
-
- model = moose.Neutral( 'model' )
- compartment = moose.CylMesh( '/model/compartment' )
- compartment.r0 = r0
- compartment.r1 = r1
- compartment.x0 = 0
- compartment.x1 = len
- compartment.diffLength = diffLength
-
- assert( compartment.numDiffCompts == num )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- c = moose.Pool( '/model/compartment/c' )
- d = moose.Pool( '/model/compartment/d' )
+ # create container for model
+ r0 = 1e-6 # m
+ r1 = 1e-6 # m
+ num = 25
+ diffLength = 1e-6 # m
+ len = num * diffLength # m
+ diffConst = 1e-12 # m^2/sec
+ motorConst = 1e-6 # m/sec
+ concA = 1 # millimolar
+
+ model = moose.Neutral( 'model' )
+ compartment = moose.CylMesh( '/model/compartment' )
+ compartment.r0 = r0
+ compartment.r1 = r1
+ compartment.x0 = 0
+ compartment.x1 = len
+ compartment.diffLength = diffLength
+
+ assert( compartment.numDiffCompts == num )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ c = moose.Pool( '/model/compartment/c' )
+ d = moose.Pool( '/model/compartment/d' )
"""
r1 = moose.Reac( '/model/compartment/r1' )
moose.connect( r1, 'sub', b, 'reac' )
@@ -69,39 +69,39 @@ def makeModel():
r1.Kb = 0.01 # 1/sec
"""
- # Assign parameters
- a.diffConst = 0.0;
- b.diffConst = 0.0;
- #b.motorRate = motorRate
- c.diffConst = 0.0;
- d.diffConst = 0.0;
- #d.diffConst = diffConst;
- os.kill( PID, signal.SIGUSR1 )
+ # Assign parameters
+ a.diffConst = 0.0;
+ b.diffConst = 0.0;
+ #b.motorRate = motorRate
+ c.diffConst = 0.0;
+ d.diffConst = 0.0;
+ #d.diffConst = diffConst;
+ os.kill( PID, signal.SIGUSR1 )
a.motorConst = motorConst
b.motorConst = motorConst
c.motorConst = -motorConst
d.motorConst = -motorConst
- # Make solvers
- ksolve = moose.Ksolve( '/model/compartment/ksolve' )
- dsolve = moose.Dsolve( '/model/compartment/dsolve' )
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = compartment
- stoich.ksolve = ksolve
- stoich.dsolve = dsolve
- stoich.path = "/model/compartment/##"
+ # Make solvers
+ ksolve = moose.Ksolve( '/model/compartment/ksolve' )
+ dsolve = moose.Dsolve( '/model/compartment/dsolve' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = compartment
+ stoich.ksolve = ksolve
+ stoich.dsolve = dsolve
+ stoich.path = "/model/compartment/##"
assert( dsolve.numPools == 4 )
- a.vec[0].concInit = concA * 1
- b.vec[num-1].concInit = concA * 2
- c.vec[0].concInit = concA * 3
- d.vec[num-1].concInit = concA * 4
+ a.vec[0].concInit = concA * 1
+ b.vec[num-1].concInit = concA * 2
+ c.vec[0].concInit = concA * 3
+ d.vec[num-1].concInit = concA * 4
def displayPlots():
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
- c = moose.element( '/model/compartment/c' )
- d = moose.element( '/model/compartment/d' )
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
+ c = moose.element( '/model/compartment/c' )
+ d = moose.element( '/model/compartment/d' )
pos = numpy.arange( 0, a.vec.conc.size, 1 )
pylab.plot( pos, a.vec.conc, label='a' )
pylab.plot( pos, b.vec.conc, label='b' )
@@ -111,44 +111,44 @@ def displayPlots():
pylab.show()
def main():
- dt4 = 0.01
- dt5 = 0.01
+ dt4 = 0.01
+ dt5 = 0.01
runtime = 10.0 # seconds
# Set up clocks. The dsolver to know before assigning stoich
- moose.setClock( 4, dt4 )
- moose.setClock( 5, dt5 )
+ moose.setClock( 4, dt4 )
+ moose.setClock( 5, dt5 )
- makeModel()
- moose.useClock( 4, '/model/compartment/dsolve', 'process' )
+ makeModel()
+ moose.useClock( 4, '/model/compartment/dsolve', 'process' )
# Ksolve must be scheduled after dsolve.
- moose.useClock( 5, '/model/compartment/ksolve', 'process' )
+ moose.useClock( 5, '/model/compartment/ksolve', 'process' )
- moose.reinit()
- moose.start( runtime ) # Run the model
+ moose.reinit()
+ moose.start( runtime ) # Run the model
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
- c = moose.element( '/model/compartment/c' )
- d = moose.element( '/model/compartment/d' )
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
+ c = moose.element( '/model/compartment/c' )
+ d = moose.element( '/model/compartment/d' )
atot = sum( a.vec.conc )
btot = sum( b.vec.conc )
ctot = sum( c.vec.conc )
dtot = sum( d.vec.conc )
- print 'tot = ', atot, btot, ctot, dtot, ' (b+c)=', btot+ctot
+ print(('tot = ', atot, btot, ctot, dtot, ' (b+c)=', btot+ctot))
displayPlots()
- moose.start( runtime ) # Run the model
+ moose.start( runtime ) # Run the model
atot = sum( a.vec.conc )
btot = sum( b.vec.conc )
ctot = sum( c.vec.conc )
dtot = sum( d.vec.conc )
- print 'tot = ', atot, btot, ctot, dtot, ' (b+c)=', btot+ctot
+ print(('tot = ', atot, btot, ctot, dtot, ' (b+c)=', btot+ctot))
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/diffSpinyNeuron.py b/moose-examples/snippets/diffSpinyNeuron.py
index af7f457acbd578ec6130baee50c51545ec9ca355..169848731123e9e9272d52a1595fa4427dbed520 100644
--- a/moose-examples/snippets/diffSpinyNeuron.py
+++ b/moose-examples/snippets/diffSpinyNeuron.py
@@ -102,12 +102,12 @@ def makeModel():
stoich2.filterXreacs()
Ca_input_dend = moose.vec( '/model/chem/compt0/Ca_input' )
- print len( Ca_input_dend )
+ print((len( Ca_input_dend )))
for i in range( 60 ):
Ca_input_dend[ 3 + i * 3 ].conc = 2.0
Ca_input_PSD = moose.vec( '/model/chem/compt2/Ca_input' )
- print len( Ca_input_PSD )
+ print((len( Ca_input_PSD )))
for i in range( 5 ):
Ca_input_PSD[ 2 + i * 2].conc = 1.0
@@ -157,36 +157,36 @@ def makeDisplay():
plt.xlabel( 'time (seconds)' )
plt.legend()
- Ca = moose.vec( '/model/chem/compt0/Ca' )
- Ca_input = moose.vec( '/model/chem/compt0/Ca_input' )
- line1, = dend.plot( range( len( Ca ) ), Ca.conc, label='Ca' )
- line2, = dend.plot( range( len( Ca_input ) ), Ca_input.conc, label='Ca_input' )
+ Ca = moose.vec( '/model/chem/compt0/Ca' )
+ Ca_input = moose.vec( '/model/chem/compt0/Ca_input' )
+ line1, = dend.plot( list(range( len( Ca ))), Ca.conc, label='Ca' )
+ line2, = dend.plot( list(range( len( Ca_input ))), Ca_input.conc, label='Ca_input' )
dend.set_ylim( 0, 2 )
- Ca = moose.vec( '/model/chem/compt1/Ca' )
- line3, = spine.plot( range( len( Ca ) ), Ca.conc, label='Ca' )
+ Ca = moose.vec( '/model/chem/compt1/Ca' )
+ line3, = spine.plot( list(range( len( Ca ))), Ca.conc, label='Ca' )
spine.set_ylim( 0, 1 )
- Ca = moose.vec( '/model/chem/compt2/Ca' )
- Ca_input = moose.vec( '/model/chem/compt2/Ca_input' )
- line4, = psd.plot( range( len( Ca ) ), Ca.conc, label='Ca' )
- line5, = psd.plot( range( len( Ca_input ) ), Ca_input.conc, label='Ca_input' )
+ Ca = moose.vec( '/model/chem/compt2/Ca' )
+ Ca_input = moose.vec( '/model/chem/compt2/Ca_input' )
+ line4, = psd.plot( list(range( len( Ca ))), Ca.conc, label='Ca' )
+ line5, = psd.plot( list(range( len( Ca_input ))), Ca_input.conc, label='Ca_input' )
psd.set_ylim( 0, 1 )
fig.canvas.draw()
return ( timeSeries, dend, spine, psd, fig, line1, line2, line3, line4, line5, timeLabel )
def updateDisplay( plotlist ):
- Ca = moose.vec( '/model/chem/compt0/Ca' )
- Ca_input = moose.vec( '/model/chem/compt0/Ca_input' )
+ Ca = moose.vec( '/model/chem/compt0/Ca' )
+ Ca_input = moose.vec( '/model/chem/compt0/Ca_input' )
plotlist[5].set_ydata( Ca.conc )
plotlist[6].set_ydata( Ca_input.conc )
- Ca = moose.vec( '/model/chem/compt1/Ca' )
+ Ca = moose.vec( '/model/chem/compt1/Ca' )
plotlist[7].set_ydata( Ca.conc )
- Ca = moose.vec( '/model/chem/compt2/Ca' )
- Ca_input = moose.vec( '/model/chem/compt2/Ca_input' )
+ Ca = moose.vec( '/model/chem/compt2/Ca' )
+ Ca_input = moose.vec( '/model/chem/compt2/Ca_input' )
plotlist[8].set_ydata( Ca.conc )
plotlist[9].set_ydata( Ca_input.conc )
plotlist[4].canvas.draw()
@@ -198,7 +198,7 @@ def finalizeDisplay( plotlist, cPlotDt ):
line1, = plotlist[0].plot( pos, x.vector, label=x.name )
plotlist[4].canvas.draw()
print( "Hit 'enter' to exit" )
- raw_input()
+ eval(input())
def makeChemModel( compt, doInput ):
"""
@@ -279,4 +279,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/fieldelement.py b/moose-examples/snippets/fieldelement.py
index 53835f9d0a061ab4a88d744bb626462f6c39238e..ee456c715fe3bd2457ea6ff6212ab8f59ca0e5c6 100644
--- a/moose-examples/snippets/fieldelement.py
+++ b/moose-examples/snippets/fieldelement.py
@@ -92,7 +92,7 @@ import moose
# Create an IntFire vec containing 10 elements, a refers to alpha[0]
a = moose.IntFire('alpha', 10)
-print 'a=', a
+print(('a=', a))
for i in range( 10 ):
syn = moose.SimpleSynHandler( 'alpha[' + str(i) + ']/sh' )
moose.connect( syn, 'activationOut', a.vec[i], 'activation' )
@@ -103,49 +103,49 @@ moose.connect( syn, 'activationOut', a, 'activation', 'OneToOne' )
# FieldElement identity
###############################
x = syn.synapse # x is an ElementField alpha[0].synapse
-print 'x=',x
-print 'x.num=', x.num # Initially there are no synapses, so this will be 0
+print(('x=',x))
+print(('x.num=', x.num)) # Initially there are no synapses, so this will be 0
syn.synapse.num = 3 # We set number of field elements to 3
-print 'x.num=', x.num # x refers to a.synapse, so this should be 3
+print(('x.num=', x.num)) # x refers to a.synapse, so this should be 3
b = moose.element('alpha[0]/sh/synapse[1]') # We access x[1]
-print 'b=',b
-print 'x[1]=', x[1]
-print 'b==x[1]?', b == x[1]
+print(('b=',b))
+print(('x[1]=', x[1]))
+print(('b==x[1]?', b == x[1]))
###############################
# Check fieldIndex and dataId
###############################
-print 'syn.synapse[0]=', syn.synapse[0]
-print 'syn.synapse[1]=', syn.synapse[1] # The fieldIndex should change, not dataId
+print(('syn.synapse[0]=', syn.synapse[0]))
+print(('syn.synapse[1]=', syn.synapse[1])) # The fieldIndex should change, not dataId
#########################
# setVec call example
#########################
-print 'alpha[0].synapse.delay=', x.delay
+print(('alpha[0].synapse.delay=', x.delay))
x.delay = [1.0, 2.0, 3.0] # This sets `delay` field in all elements via setVec call
-print 'alpha[0].synapse.delay=', x.delay
+print(('alpha[0].synapse.delay=', x.delay))
x.delay = [1.141592] * len(x) # This is a Pythonic way of replicating the values in a list - ensures same length
-print 'alpha[0].synapse.delay=', x.delay
+print(('alpha[0].synapse.delay=', x.delay))
#####################################################
# Play a little more with ObjId, FieldElement, Id
#####################################################
-print 'Length of alpha[1]/synapse=', len(moose.element('/alpha[1]/sh').synapse)
+print(('Length of alpha[1]/synapse=', len(moose.element('/alpha[1]/sh').synapse)))
c = moose.element('alpha[1]/sh/synapse[2]') # This should throw an error - alpha[1] does not have 3 synapses.
-print 'b=', b, 'numData=', b.numData
-print 'c=', c, 'numData=', c.numData
+print(('b=', b, 'numData=', b.numData))
+print(('c=', c, 'numData=', c.numData))
try:
- print 'len(c)=', len(c)
-except TypeError, e:
- print e
+ print(('len(c)=', len(c)))
+except TypeError as e:
+ print(e)
d = moose.element('/alpha[1]/sh')
try:
- print d.synapse[1]
-except IndexError, e:
- print e
+ print((d.synapse[1]))
+except IndexError as e:
+ print(e)
else:
- print 'Expected an IndexError. Length of synapse=', len(d.synapse)
+ print(('Expected an IndexError. Length of synapse=', len(d.synapse)))
# The fieldIndex should change, not dataId
x = moose.element(a.vec, 0, 1)
y = moose.element(a.vec, 1, 2)
-print x, y
+print((x, y))
diff --git a/moose-examples/snippets/findChemSteadyState.py b/moose-examples/snippets/findChemSteadyState.py
index 6f928d139e86252127cad63da0b1e3279cf62afb..85783ced1b7ae91cfa1245f3df5421dd0204e514 100644
--- a/moose-examples/snippets/findChemSteadyState.py
+++ b/moose-examples/snippets/findChemSteadyState.py
@@ -7,6 +7,8 @@
## See the file COPYING.LIB for the full notice.
#########################################################################
+from __future__ import print_function
+
import math
import pylab
import numpy
@@ -180,11 +182,12 @@ def getState( ksolve, state ):
moose.start( 2.0 ) # Run the model for 2 seconds.
state.settle() # This function finds the steady states.
for x in ksolve.nVec[0]:
- print x * scale,
- print state.nIter, state.status, state.stateType, state.nNegEigenvalues, state.nPosEigenvalues, state.solutionStatus
+ print(x * scale, end=' ')
+
+ print(state.nIter, state.status, state.stateType, state.nNegEigenvalues, state.nPosEigenvalues, state.solutionStatus)
moose.start( 10.0 ) # Run model for 10 seconds, just for display
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/func.py b/moose-examples/snippets/func.py
index d5bfc7d24ed50373b445f96deb87ad32f29df07e..b521fe5948ad008afc34576eb09a24c529602587 100644
--- a/moose-examples/snippets/func.py
+++ b/moose-examples/snippets/func.py
@@ -62,17 +62,17 @@ def test_func_nosim():
for ii in range(num-1):
expr += 'x_%d, ' % (ii)
expr += 'x_%d)' % (num-1)
- print 'Expression:', expr
+ print(('Expression:', expr))
func_0.expr = expr
for ii in range(num):
var = 'x_%d' % (ii)
- print 'Setting:', var, '=', func_0.var[var]
+ print(('Setting:', var, '=', func_0.var[var]))
func_0.var[var] = float(ii)
- print 'Expression:', func_0.expr
- print 'Variables after assignment:'
+ print(('Expression:', func_0.expr))
+ print('Variables after assignment:')
for v in func_0.vars:
- print ' %s = %g' % (v, func_0.var[v])
- print 'value %g\n' % (func_0.value)
+ print((' %s = %g' % (v, func_0.var[v])))
+ print(('value %g\n' % (func_0.value)))
def test_func():
"""This function creates a Func object evaluating a function of a
@@ -106,7 +106,7 @@ def test_func():
input.startTime = 0.0
input.stepPosition = xarr[0]
input.stopTime = xarr[-1] - xarr[0]
- print input.startTime, input.stopTime
+ print((input.startTime, input.stopTime))
moose.connect(input, 'output', func_1, 'xIn')
@@ -129,7 +129,7 @@ def test_func():
moose.useClock(3, '%s/##' % (data.path), 'process')
moose.reinit()
t = xarr[-1] - xarr[0]
- print 'Run for', t
+ print(('Run for', t))
moose.start(t)
y = np.asarray(y_tab.vector)
yp = np.asarray(yprime_tab.vector)
diff --git a/moose-examples/snippets/funcInputToPools.py b/moose-examples/snippets/funcInputToPools.py
index 12939853cf77644251ed93cb68ddc3455fdf7d8f..b047738117d832bdae020c8df789aef191257be5 100644
--- a/moose-examples/snippets/funcInputToPools.py
+++ b/moose-examples/snippets/funcInputToPools.py
@@ -39,46 +39,46 @@ import moose
import sys
def makeModel():
- if len( sys.argv ) == 1:
- useGsolve = True
+ if len( sys.argv ) == 1:
+ useGsolve = True
else:
- useGsolve = ( sys.argv[1] == 'True' )
- # create container for model
- model = moose.Neutral( 'model' )
- compartment = moose.CubeMesh( '/model/compartment' )
- compartment.volume = 1e-22
- # the mesh is created automatically by the compartment
- moose.le( '/model/compartment' )
- mesh = moose.element( '/model/compartment/mesh' )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
-
- # create functions of time
+ useGsolve = ( sys.argv[1] == 'True' )
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compartment = moose.CubeMesh( '/model/compartment' )
+ compartment.volume = 1e-22
+ # the mesh is created automatically by the compartment
+ moose.le( '/model/compartment' )
+ mesh = moose.element( '/model/compartment/mesh' )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+
+ # create functions of time
f1 = moose.Function( '/model/compartment/f1' )
f2 = moose.Function( '/model/compartment/f2' )
- # connect them up for reactions
- moose.connect( f1, 'valueOut', a, 'setConc' )
- moose.connect( f2, 'valueOut', b, 'increment' )
+ # connect them up for reactions
+ moose.connect( f1, 'valueOut', a, 'setConc' )
+ moose.connect( f2, 'valueOut', b, 'increment' )
- # Assign parameters
- a.concInit = 0
- b.concInit = 1
+ # Assign parameters
+ a.concInit = 0
+ b.concInit = 1
#f1.numVars = 1
#f2.numVars = 1
f1.expr = '1 + sin(t)'
f2.expr = '10 * cos(t)'
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/nA' )
- outputB = moose.Table2 ( '/model/graphs/nB' )
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/nA' )
+ outputB = moose.Table2 ( '/model/graphs/nB' )
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getN' );
- moose.connect( outputB, 'requestOut', b, 'getN' );
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getN' );
+ moose.connect( outputB, 'requestOut', b, 'getN' );
# Set up the solvers
if useGsolve:
@@ -93,31 +93,31 @@ def makeModel():
'''
'''
- # We need a finer timestep than the default 0.1 seconds,
+ # We need a finer timestep than the default 0.1 seconds,
# in order to get numerical accuracy.
for i in range (10, 19 ):
- moose.setClock( i, 0.1 ) # for computational objects
+ moose.setClock( i, 0.1 ) # for computational objects
def main():
- makeModel()
+ makeModel()
moose.seed()
- moose.reinit()
- moose.start( 50.0 ) # Run the model for 100 seconds.
+ moose.reinit()
+ moose.start( 50.0 ) # Run the model for 100 seconds.
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
- # Iterate through all plots, dump their contents to data.plot.
- for x in moose.wildcardFind( '/model/graphs/n#' ):
- #x.xplot( 'scriptKineticModel.plot', x.name )
- t = numpy.arange( 0, x.vector.size, 1 ) * x.dt # sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ # Iterate through all plots, dump their contents to data.plot.
+ for x in moose.wildcardFind( '/model/graphs/n#' ):
+ #x.xplot( 'scriptKineticModel.plot', x.name )
+ t = numpy.arange( 0, x.vector.size, 1 ) * x.dt # sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/funcRateHarmonicOsc.py b/moose-examples/snippets/funcRateHarmonicOsc.py
index 029f49f0a781c7ae02503e4ea96e93aee1f1921e..6fbd0af96a8e6b60171863d425376f68dde4ff4b 100644
--- a/moose-examples/snippets/funcRateHarmonicOsc.py
+++ b/moose-examples/snippets/funcRateHarmonicOsc.py
@@ -14,18 +14,18 @@ import moose
runtime = 120.0
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- harmonic = moose.CubeMesh( '/model/harmonic' )
- harmonic.volume = 1e-15
- lotka = moose.CubeMesh( '/model/lotka' )
- lotka.volume = 1e-15
-
- # create molecules and reactions
- p = moose.Pool( '/model/harmonic/p' )
- v = moose.Pool( '/model/harmonic/v' )
- pdot = moose.Function( '/model/harmonic/p/func' )
- vdot = moose.Function( '/model/harmonic/v/func' )
+ # create container for model
+ model = moose.Neutral( 'model' )
+ harmonic = moose.CubeMesh( '/model/harmonic' )
+ harmonic.volume = 1e-15
+ lotka = moose.CubeMesh( '/model/lotka' )
+ lotka.volume = 1e-15
+
+ # create molecules and reactions
+ p = moose.Pool( '/model/harmonic/p' )
+ v = moose.Pool( '/model/harmonic/v' )
+ pdot = moose.Function( '/model/harmonic/p/func' )
+ vdot = moose.Function( '/model/harmonic/v/func' )
# Parameters
offset1 = 1.0
@@ -38,25 +38,25 @@ def makeModel():
pdot.expr = "x0 - " + str( offset1 )
vdot.expr = "-" + str( k ) + " * (x0 - " + str( offset2 ) + ")"
- # connect them up for reactions
- moose.connect( p, 'nOut', vdot.x[0], 'input' )
- moose.connect( v, 'nOut', pdot.x[0], 'input' )
+ # connect them up for reactions
+ moose.connect( p, 'nOut', vdot.x[0], 'input' )
+ moose.connect( v, 'nOut', pdot.x[0], 'input' )
moose.connect( vdot, 'valueOut', v, 'increment' )
moose.connect( pdot, 'valueOut', p, 'increment' )
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- pplot = moose.Table2 ( '/model/graphs/p' )
- vplot = moose.Table2 ( '/model/graphs/v' )
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ pplot = moose.Table2 ( '/model/graphs/p' )
+ vplot = moose.Table2 ( '/model/graphs/v' )
- # connect up the tables
- moose.connect( pplot, 'requestOut', p, 'getN' );
- moose.connect( vplot, 'requestOut', v, 'getN' );
+ # connect up the tables
+ moose.connect( pplot, 'requestOut', p, 'getN' );
+ moose.connect( vplot, 'requestOut', v, 'getN' );
def main():
- """
- funcRateHarmonicOsc illustrates the use of function objects to
+ """
+ funcRateHarmonicOsc illustrates the use of function objects to
directly define the rates of change of pool concentration. This
example shows how to set up a simple harmonic oscillator system
of differential equations using the script. In normal use one would
@@ -64,31 +64,31 @@ def main():
The equations are ::
- p' = v - offset1
- v' = -k(p - offset2)
+ p' = v - offset1
+ v' = -k(p - offset2)
- where the rates for Pools p and v are computed using Functions.
- Note the use of offsets. This is because MOOSE chemical
- systems cannot have negative concentrations.
-
- The model is set up to run using default Exponential Euler
- integration, and then using the GSL deterministic solver.
- """
- makeModel()
+ where the rates for Pools p and v are computed using Functions.
+ Note the use of offsets. This is because MOOSE chemical
+ systems cannot have negative concentrations.
+
+ The model is set up to run using default Exponential Euler
+ integration, and then using the GSL deterministic solver.
+ """
+ makeModel()
for i in range( 11, 18 ):
moose.setClock( i, 0.01 )
moose.setClock( 18, 0.1 )
- moose.reinit()
- moose.start( runtime ) # Run the model
-
- # Iterate through all plots, dump their contents to data.plot.
- for x in moose.wildcardFind( '/model/graphs/#' ):
- #x.xplot( 'scriptKineticModel.plot', x.name )
- t = numpy.arange( 0, x.vector.size, 1 ) * x.dt # sec
- pylab.plot( t, x.vector, label=x.name )
+ moose.reinit()
+ moose.start( runtime ) # Run the model
+
+ # Iterate through all plots, dump their contents to data.plot.
+ for x in moose.wildcardFind( '/model/graphs/#' ):
+ #x.xplot( 'scriptKineticModel.plot', x.name )
+ t = numpy.arange( 0, x.vector.size, 1 ) * x.dt # sec
+ pylab.plot( t, x.vector, label=x.name )
pylab.suptitle( "Integration using ee" )
- pylab.legend()
+ pylab.legend()
pylab.figure()
compt = moose.element( '/model/harmonic' )
@@ -99,18 +99,18 @@ def main():
stoich.path = '/model/harmonic/##'
for i in range( 11, 18 ):
moose.setClock( i, 0.1 )
- moose.reinit()
- moose.start( runtime ) # Run the model
+ moose.reinit()
+ moose.start( runtime ) # Run the model
- for x in moose.wildcardFind( '/model/graphs/#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) * x.dt # sec
- pylab.plot( t, x.vector, label=x.name )
+ for x in moose.wildcardFind( '/model/graphs/#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) * x.dt # sec
+ pylab.plot( t, x.vector, label=x.name )
pylab.suptitle( "Integration using gsl" )
- pylab.legend()
- pylab.show()
+ pylab.legend()
+ pylab.show()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/funcReacLotkaVolterra.py b/moose-examples/snippets/funcReacLotkaVolterra.py
index a19223929f32623f6bef44e1e3bba45924568aef..13a90119e3efa1aef762ebbd1ac1cbb301db3ced 100644
--- a/moose-examples/snippets/funcReacLotkaVolterra.py
+++ b/moose-examples/snippets/funcReacLotkaVolterra.py
@@ -15,21 +15,21 @@ import moose
runtime = 50.0
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- harmonic = moose.CubeMesh( '/model/harmonic' )
- harmonic.volume = 1e-15
- lotka = moose.CubeMesh( '/model/lotka' )
- lotka.volume = 1e-15
-
- # create molecules and reactions
- x = moose.Pool( '/model/lotka/x' )
- y = moose.Pool( '/model/lotka/y' )
+ # create container for model
+ model = moose.Neutral( 'model' )
+ harmonic = moose.CubeMesh( '/model/harmonic' )
+ harmonic.volume = 1e-15
+ lotka = moose.CubeMesh( '/model/lotka' )
+ lotka.volume = 1e-15
+
+ # create molecules and reactions
+ x = moose.Pool( '/model/lotka/x' )
+ y = moose.Pool( '/model/lotka/y' )
z = moose.BufPool( '/model/lotka/z' ) # Dummy molecule.
xreac = moose.Reac( '/model/lotka/xreac' )
yreac = moose.Reac( '/model/lotka/yreac' )
- xrate = moose.Function( '/model/lotka/xreac/func' )
- yrate = moose.Function( '/model/lotka/yreac/func' )
+ xrate = moose.Function( '/model/lotka/xreac/func' )
+ yrate = moose.Function( '/model/lotka/yreac/func' )
# Parameters
alpha = 1.0
@@ -49,9 +49,9 @@ def makeModel():
xreac.Kb = 0
yreac.Kb = 0
- # connect them up for reactions
- moose.connect( y, 'nOut', xrate.x[0], 'input' )
- moose.connect( x, 'nOut', yrate.x[0], 'input' )
+ # connect them up for reactions
+ moose.connect( y, 'nOut', xrate.x[0], 'input' )
+ moose.connect( x, 'nOut', yrate.x[0], 'input' )
moose.connect( xrate, 'valueOut', xreac, 'setNumKf' )
moose.connect( yrate, 'valueOut', yreac, 'setNumKf' )
moose.connect( xreac, 'sub', x, 'reac' )
@@ -59,14 +59,14 @@ def makeModel():
moose.connect( yreac, 'sub', y, 'reac' )
moose.connect( yreac, 'prd', z, 'reac' )
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- xplot = moose.Table2 ( '/model/graphs/x' )
- yplot = moose.Table2 ( '/model/graphs/y' )
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ xplot = moose.Table2 ( '/model/graphs/x' )
+ yplot = moose.Table2 ( '/model/graphs/y' )
- # connect up the tables
- moose.connect( xplot, 'requestOut', x, 'getN' );
- moose.connect( yplot, 'requestOut', y, 'getN' );
+ # connect up the tables
+ moose.connect( xplot, 'requestOut', x, 'getN' );
+ moose.connect( yplot, 'requestOut', y, 'getN' );
def main():
"""
diff --git a/moose-examples/snippets/gssaCylinderDiffusion.py b/moose-examples/snippets/gssaCylinderDiffusion.py
index 57033a4267c77d0408f54a55e5df004d0759507d..932c4aa23319d27fd6d73326df7482d0c4c23607 100644
--- a/moose-examples/snippets/gssaCylinderDiffusion.py
+++ b/moose-examples/snippets/gssaCylinderDiffusion.py
@@ -9,12 +9,12 @@
import sys
-sys.path.append('../../python')
import math
import pylab
import numpy
import matplotlib.pyplot as plt
import moose
+print(('[INFO] Using moose from %s' % moose.__file__ ))
import os
import signal
@@ -58,11 +58,11 @@ def makeModel():
The concentrations of all molecules are displayed in an animation.
"""
# create container for model
- r0 = 2e-6 # m
- r1 = 1e-6 # m
+ r0 = 2e-6 # m
+ r1 = 1e-6 # m
num = 100
diffLength = 1e-6 # m
- len = num * diffLength # m
+ len = num * diffLength # m
diffConst = 10e-12
#motorRate = 1e-6
#diffConst = 0
@@ -108,7 +108,7 @@ def makeModel():
os.kill( PID, signal.SIGUSR1 )
stoich.path = "/model/compartment/##"
- print dsolve.numPools
+ print((dsolve.numPools))
assert( dsolve.numPools == 4 )
a.vec.concInit = concA
b.vec.concInit = concA / 5.0
@@ -178,22 +178,24 @@ def main():
for t in numpy.arange( 0, runtime, plotdt ):
moose.start( plotdt )
updatePlots( plotlist, t )
- # moose.start( runtime ) # Run the model
+
+ # save the final result to a file.
+ outfile = '%s.png' % sys.argv[0]
+ plt.savefig( outfile )
+ print(( '[INFO] Saved results to %s' % outfile ))
atot2 = sum( a.vec.n )
btot2 = sum( b.vec.n )
ctot2 = sum( c.vec.n )
dtot2 = sum( d.vec.n )
- print 'Ratio of initial to final total numbers of of a, b, c, d = '
- print atot2/atot, btot2/btot, ctot2/ctot, dtot2/dtot
- print 'Initial to final (b+c)=', (btot2 + ctot2) / (btot + ctot )
- print "\nHit 'enter' to exit"
- #raw_input()
-
+ msg = 'Ratio of initial to final total numbers of '
+ msg += 'a=%f b=%f, c=%f, d=%f'% (atot2/atot, btot2/btot, ctot2/ctot, dtot2/dtot)
+ print(msg)
+ print(('Initial to final (b+c)=%f' % (float(btot2 + ctot2) / (btot + ctot ))))
quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/gssaRDspiny.py b/moose-examples/snippets/gssaRDspiny.py
index 46beebcd6ea0be27d0148b3f2023c10734863755..5e95febee536c861a86992cfd74dd36ba52017f5 100644
--- a/moose-examples/snippets/gssaRDspiny.py
+++ b/moose-examples/snippets/gssaRDspiny.py
@@ -133,46 +133,46 @@ def makeDisplay():
plt.xlabel( 'time (seconds)' )
plt.legend()
- a = moose.vec( '/model/chem/compt0/a' )
- b = moose.vec( '/model/chem/compt0/b' )
- line1, = dend.plot( range( len( a ) ), a.conc, label='a' )
- line2, = dend.plot( range( len( b ) ), b.conc, label='b' )
+ a = moose.vec( '/model/chem/compt0/a' )
+ b = moose.vec( '/model/chem/compt0/b' )
+ line1, = dend.plot( list(range( len( a ))), a.conc, label='a' )
+ line2, = dend.plot( list(range( len( b ))), b.conc, label='b' )
dend.set_ylim( 0, 0.6 )
- a = moose.vec( '/model/chem/compt1/a' )
- b = moose.vec( '/model/chem/compt1/b' )
- line3, = spine.plot( range( len( a ) ), a.conc, label='a' )
- line4, = spine.plot( range( len( b ) ), b.conc, label='b' )
+ a = moose.vec( '/model/chem/compt1/a' )
+ b = moose.vec( '/model/chem/compt1/b' )
+ line3, = spine.plot( list(range( len( a ))), a.conc, label='a' )
+ line4, = spine.plot( list(range( len( b ))), b.conc, label='b' )
spine.set_ylim( 0, 0.6 )
- a = moose.vec( '/model/chem/compt2/a' )
- b = moose.vec( '/model/chem/compt2/b' )
- line5, = psd.plot( range( len( a ) ), a.conc, label='a' )
- line6, = psd.plot( range( len( b ) ), b.conc, label='b' )
+ a = moose.vec( '/model/chem/compt2/a' )
+ b = moose.vec( '/model/chem/compt2/b' )
+ line5, = psd.plot( list(range( len( a ))), a.conc, label='a' )
+ line6, = psd.plot( list(range( len( b ))), b.conc, label='b' )
psd.set_ylim( 0, 0.6 )
fig.canvas.draw()
return ( timeSeries, dend, spine, psd, fig, line1, line2, line3, line4, line5, line6, timeLabel )
def updateDisplay( plotlist ):
- a = moose.vec( '/model/chem/compt0/a' )
- b = moose.vec( '/model/chem/compt0/b' )
+ a = moose.vec( '/model/chem/compt0/a' )
+ b = moose.vec( '/model/chem/compt0/b' )
plotlist[5].set_ydata( a.conc )
plotlist[6].set_ydata( b.conc )
- print 'compt0:', min(a.n), max(a.n), min(b.n), max(b.n)
+ print(('compt0:', min(a.n), max(a.n), min(b.n), max(b.n)))
- a = moose.vec( '/model/chem/compt1/a' )
- b = moose.vec( '/model/chem/compt1/b' )
+ a = moose.vec( '/model/chem/compt1/a' )
+ b = moose.vec( '/model/chem/compt1/b' )
plotlist[7].set_ydata( a.conc )
plotlist[8].set_ydata( b.conc )
- print 'compt1:', min(a.n), max(a.n), min(b.n), max(b.n)
+ print(('compt1:', min(a.n), max(a.n), min(b.n), max(b.n)))
- a = moose.vec( '/model/chem/compt2/a' )
- b = moose.vec( '/model/chem/compt2/b' )
+ a = moose.vec( '/model/chem/compt2/a' )
+ b = moose.vec( '/model/chem/compt2/b' )
plotlist[9].set_ydata( a.conc )
plotlist[10].set_ydata( b.conc )
plotlist[4].canvas.draw()
- print 'compt2:', min(a.n), max(a.n), min(b.n), max(b.n)
+ print(('compt2:', min(a.n), max(a.n), min(b.n), max(b.n)))
def finalizeDisplay( plotlist, cPlotDt ):
@@ -181,7 +181,7 @@ def finalizeDisplay( plotlist, cPlotDt ):
line1, = plotlist[0].plot( pos, x.vector, label=x.name )
plotlist[4].canvas.draw()
print( "Hit 'enter' to exit" )
- raw_input()
+ eval(input())
def makeChemModel( compt ):
"""
@@ -293,4 +293,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/hdfdemo.py b/moose-examples/snippets/hdfdemo.py
index f1fdc2e7f9f3c8098c2b3f0662e768ebb98e2de7..081b2c1feea0bf491127584e5c3004b308952299 100644
--- a/moose-examples/snippets/hdfdemo.py
+++ b/moose-examples/snippets/hdfdemo.py
@@ -92,7 +92,7 @@ def example():
moose.start(30.0)
hdfwriter.close()
vm_tab.plainPlot('hdfdemo_Vm.csv')
- print 'Finished simulation. Data was saved in', hdfwriter.filename
+ print(('Finished simulation. Data was saved in', hdfwriter.filename))
if __name__ == '__main__':
diff --git a/moose-examples/snippets/helloMoose.py b/moose-examples/snippets/helloMoose.py
index 1db5f60ec3ea91ffcd07f79b63024d60fa8d3585..c9fe293384d0e1a9cf1d5094edce92b841e71286 100644
--- a/moose-examples/snippets/helloMoose.py
+++ b/moose-examples/snippets/helloMoose.py
@@ -36,4 +36,4 @@ def main():
pylab.show()
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/hhcomp.py b/moose-examples/snippets/hhcomp.py
index 7115a57a6a55b2136fb9209ce3080f1d91e77524..3a7e46fda4a78a60ef4b5da022641ffbabb703c3 100644
--- a/moose-examples/snippets/hhcomp.py
+++ b/moose-examples/snippets/hhcomp.py
@@ -205,7 +205,7 @@ def test_hhcomp():
model = moose.Neutral('/model')
data = moose.Neutral('/data')
comp, na, k = create_hhcomp(parent=model.path)
- print comp.Rm, comp.Cm, na.Ek, na.Gbar, k.Ek, k.Gbar
+ print((comp.Rm, comp.Cm, na.Ek, na.Gbar, k.Ek, k.Gbar))
pg = moose.PulseGen('%s/pg' % (model.path))
pg.firstDelay = 20e-3
pg.firstWidth = 40e-3
diff --git a/moose-examples/snippets/insertSpines.py b/moose-examples/snippets/insertSpines.py
index 024e8aa332f0a3c38bcfc958257e35b9b3684b43..5d8a31c80811067201dc0d5bc4b025b3ab7c0fc1 100644
--- a/moose-examples/snippets/insertSpines.py
+++ b/moose-examples/snippets/insertSpines.py
@@ -56,7 +56,7 @@ def main():
# Now we set up the display
compts = moose.wildcardFind( "/model/elec/#[ISA=CompartmentBase]" )
compts[0].inject = inject
- ecomptPath = map( lambda x : x.path, compts )
+ ecomptPath = [x.path for x in compts]
morphology = moogli.read_morphology_from_moose(name = "", path = "/model/elec")
#morphology.create_group( "group_all", ecomptPath, -0.08, 0.02, \
# [0.0, 0.5, 1.0, 1.0], [1.0, 0.0, 0.0, 0.9] )
@@ -67,7 +67,7 @@ def main():
viewer.set_background_color( 1.0, 1.0, 1.0, 1.0 )
def callback( morphology, viewer ):
moose.start( frameRunTime )
- Vm = map( lambda x: moose.element( x ).Vm, compts )
+ Vm = [moose.element( x ).Vm for x in compts]
morphology.set_color( "group_all", Vm )
currTime = moose.element( '/clock' ).currentTime
#print currTime, compts[0].Vm
diff --git a/moose-examples/snippets/insertSpinesWithoutRdesigneur.py b/moose-examples/snippets/insertSpinesWithoutRdesigneur.py
index 48ae40e3f863203785c21a11568c91a6039e1a46..484653e2293d9dfee566035a1e48f8d15d5bf3ab 100644
--- a/moose-examples/snippets/insertSpinesWithoutRdesigneur.py
+++ b/moose-examples/snippets/insertSpinesWithoutRdesigneur.py
@@ -84,7 +84,7 @@ def main():
# Now we set up the display
compts = moose.wildcardFind( "/model/#[ISA=CompartmentBase]" )
compts[0].inject = inject
- ecomptPath = map( lambda x : x.path, compts )
+ ecomptPath = [x.path for x in compts]
morphology = moogli.read_morphology_from_moose(name = "", path = "/model")
morphology.create_group( "group_all", ecomptPath, -0.08, 0.02, \
[0.0, 0.5, 1.0, 1.0], [1.0, 0.0, 0.0, 0.9] )
@@ -92,7 +92,7 @@ def main():
viewer = moogli.DynamicMorphologyViewerWidget(morphology)
def callback( morphology, viewer ):
moose.start( frameRunTime )
- Vm = map( lambda x: moose.element( x ).Vm, compts )
+ Vm = [moose.element( x ).Vm for x in compts]
morphology.set_color( "group_all", Vm )
currTime = moose.element( '/clock' ).currentTime
#print currTime, compts[0].Vm
diff --git a/moose-examples/snippets/interpol.py b/moose-examples/snippets/interpol.py
index 61193c64f04a9bb21fc8da8c44e70dae94bd1c26..a2f031f00acb8fae09d8fff257218650d9fab024 100644
--- a/moose-examples/snippets/interpol.py
+++ b/moose-examples/snippets/interpol.py
@@ -72,8 +72,8 @@ stimtab.stepSize = 0.0
# stimtab.startTime = 0.0
# stimtab.stopTime = simtime
stimtab.vector = np.linspace(-4, 4, 1000)
-print stimtab.vector
-print interpol.vector
+print((stimtab.vector))
+print((interpol.vector))
moose.connect(stimtab, 'output', interpol, 'input')
diff --git a/moose-examples/snippets/interpol2d.py b/moose-examples/snippets/interpol2d.py
index 46a3041f6c2565d6998267de16ee9d302b6f2069..a6ccef2e09e4b0f807f7544b750beb66a3251e38 100644
--- a/moose-examples/snippets/interpol2d.py
+++ b/moose-examples/snippets/interpol2d.py
@@ -61,18 +61,18 @@ def interpolation_demo():
# Make a 50 element array with entries at equal distance from
# [0,1) and reshape it into a 10x5 matrix and assign to table.
matrix = np.linspace(0, 1.0, 50).reshape(10, 5)
- print 'Setting table to'
- print matrix
+ print('Setting table to')
+ print(matrix)
interpol.tableVector2D = matrix
# interpolating beyond top left corner.
# value should be
pos = (0.8, 0.3)
- print 'Interpolated value at', pos
- print interpol.z[pos[0], pos[1]]
+ print(('Interpolated value at', pos))
+ print((interpol.z[pos[0], pos[1]]))
- print 'Point going out of bound on both x and y', interpol.z[1.1, 1.1]
- print 'Point going out of bound on both x and y', interpol.z[0.5, 1.1]
+ print(('Point going out of bound on both x and y', interpol.z[1.1, 1.1]))
+ print(('Point going out of bound on both x and y', interpol.z[0.5, 1.1]))
if __name__ == '__main__':
interpolation_demo()
diff --git a/moose-examples/snippets/loadCspaceModel.py b/moose-examples/snippets/loadCspaceModel.py
index 561f4199e912a1d77823e47aebb45486325c2d28..a5956fbabdc8907727773a5379c0bbc8eaf53963 100644
--- a/moose-examples/snippets/loadCspaceModel.py
+++ b/moose-examples/snippets/loadCspaceModel.py
@@ -49,26 +49,26 @@ import pylab
import numpy
import moose
def main():
- """ This example illustrates loading and running, a kinetic model
- defined in cspace format. We use the gsl solver here. The model already
- defines a couple of plots and sets the runtime to 3000 seconds.
- """
- # This command loads the file into the path '/model', and tells
- # the system to use the gsl solver.
- modelId = moose.loadModel( 'Osc.cspace', 'model', 'gsl' )
- moose.reinit()
- moose.start( 3000.0 ) # Run the model for 300 seconds.
+ """ This example illustrates loading and running, a kinetic model
+ defined in cspace format. We use the gsl solver here. The model already
+ defines a couple of plots and sets the runtime to 3000 seconds.
+ """
+ # This command loads the file into the path '/model', and tells
+ # the system to use the gsl solver.
+ modelId = moose.loadModel( 'Osc.cspace', 'model', 'gsl' )
+ moose.reinit()
+ moose.start( 3000.0 ) # Run the model for 300 seconds.
- # display all plots
- for x in moose.wildcardFind( '/model/graphs/#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ # display all plots
+ for x in moose.wildcardFind( '/model/graphs/#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
- # moose.saveModel( modelId, 'saveReaction.g' )
- quit()
+ # moose.saveModel( modelId, 'saveReaction.g' )
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/loadKineticModel.py b/moose-examples/snippets/loadKineticModel.py
index 49206ad8b570d215a042d010ee39964de0e451ae..c31d4619f646ca772259dcd3d15230ed126075fe 100644
--- a/moose-examples/snippets/loadKineticModel.py
+++ b/moose-examples/snippets/loadKineticModel.py
@@ -51,47 +51,47 @@ import sys
def main():
""" This example illustrates loading, running, and saving a kinetic model
- defined in kkit format. It uses a default kkit model but you can specify another using the command line ``python filename runtime solver``. We use the gsl solver here. The model already defines a couple of plots and sets the runtime to 20 seconds.
- """
- solver = "gsl" # Pick any of gsl, gssa, ee..
- mfile = '../genesis/kkit_objects_example.g'
- runtime = 20.0
- if ( len( sys.argv ) >= 3 ):
+ defined in kkit format. It uses a default kkit model but you can specify another using the command line ``python filename runtime solver``. We use the gsl solver here. The model already defines a couple of plots and sets the runtime to 20 seconds.
+ """
+ solver = "gsl" # Pick any of gsl, gssa, ee..
+ mfile = '../genesis/kkit_objects_example.g'
+ runtime = 20.0
+ if ( len( sys.argv ) >= 3 ):
if sys.argv[1][0] == '/':
- mfile = sys.argv[1]
+ mfile = sys.argv[1]
else:
- mfile = '../genesis/' + sys.argv[1]
- runtime = float( sys.argv[2] )
- if ( len( sys.argv ) == 4 ):
+ mfile = '../genesis/' + sys.argv[1]
+ runtime = float( sys.argv[2] )
+ if ( len( sys.argv ) == 4 ):
solver = sys.argv[3]
- modelId = moose.loadModel( mfile, 'model', solver )
+ modelId = moose.loadModel( mfile, 'model', solver )
# Increase volume so that the stochastic solver gssa
# gives an interesting output
#compt = moose.element( '/model/kinetics' )
#compt.volume = 1e-19
- moose.reinit()
- moose.start( runtime )
+ moose.reinit()
+ moose.start( runtime )
# Report parameters
'''
- for x in moose.wildcardFind( '/model/kinetics/##[ISA=PoolBase]' ):
- print x.name, x.nInit, x.concInit
- for x in moose.wildcardFind( '/model/kinetics/##[ISA=ReacBase]' ):
- print x.name, 'num: (', x.numKf, ', ', x.numKb, '), conc: (', x.Kf, ', ', x.Kb, ')'
- for x in moose.wildcardFind('/model/kinetics/##[ISA=EnzBase]'):
- print x.name, '(', x.Km, ', ', x.numKm, ', ', x.kcat, ')'
+ for x in moose.wildcardFind( '/model/kinetics/##[ISA=PoolBase]' ):
+ print x.name, x.nInit, x.concInit
+ for x in moose.wildcardFind( '/model/kinetics/##[ISA=ReacBase]' ):
+ print x.name, 'num: (', x.numKf, ', ', x.numKb, '), conc: (', x.Kf, ', ', x.Kb, ')'
+ for x in moose.wildcardFind('/model/kinetics/##[ISA=EnzBase]'):
+ print x.name, '(', x.Km, ', ', x.numKm, ', ', x.kcat, ')'
'''
- # Display all plots.
- for x in moose.wildcardFind( '/model/#graphs/conc#/#' ):
+ # Display all plots.
+ for x in moose.wildcardFind( '/model/#graphs/conc#/#' ):
t = numpy.arange( 0, x.vector.size, 1 ) * x.dt
pylab.plot( t, x.vector, label=x.name )
pylab.legend()
pylab.show()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/loadMorphology.py b/moose-examples/snippets/loadMorphology.py
index 99cbc62a6beb8f2b6629858eef3459b7714105f8..a721544915e1a617443e51d29b88e7a6d70bb198 100644
--- a/moose-examples/snippets/loadMorphology.py
+++ b/moose-examples/snippets/loadMorphology.py
@@ -27,7 +27,7 @@ def main():
# Now we set up the display
compts = moose.wildcardFind( "/model/testSwc/#[ISA=CompartmentBase]" )
compts[0].inject = inject
- ecomptPath = map( lambda x : x.path, compts )
+ ecomptPath = [x.path for x in compts]
morphology = moogli.read_morphology_from_moose(name = "", path = "/model/testSwc")
morphology.create_group( "group_all", ecomptPath, -0.08, 0.02, \
[0.0, 0.5, 1.0, 1.0], [1.0, 0.0, 0.0, 0.9] )
@@ -35,7 +35,7 @@ def main():
viewer = moogli.DynamicMorphologyViewerWidget(morphology)
def callback( morphology, viewer ):
moose.start( frameRunTime )
- Vm = map( lambda x: moose.element( x ).Vm, compts )
+ Vm = [moose.element( x ).Vm for x in compts]
morphology.set_color( "group_all", Vm )
currTime = moose.element( '/clock' ).currentTime
#print currTime, compts[0].Vm
diff --git a/moose-examples/snippets/loadSbmlmodel.py b/moose-examples/snippets/loadSbmlmodel.py
index 9323a467ff664bc068fa695dc75fe57aebd4023f..1a717245c46aa94048d709e5127f8fd344373574 100644
--- a/moose-examples/snippets/loadSbmlmodel.py
+++ b/moose-examples/snippets/loadSbmlmodel.py
@@ -35,22 +35,22 @@
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
+import sys
+import os.path
-import moose
-import matplotlib
import numpy as np
-import matplotlib.pyplot as plt
-import sys
import pylab
+
+import moose
from moose.SBML import *
-import os.path
+from moose.chemUtil.add_Delete_ChemicalSolver import *
def main():
""" This example illustrates loading, running of an SBML model defined in XML format.\n
- The model 00001-sbml-l3v1.xml is taken from l3v1 SBML testcase.\n
- Plots are setup.\n
- Model is run for 20sec.\n
- As a general rule we created model under '/path/model' and plots under '/path/graphs'.\n
+ The model 00001-sbml-l3v1.xml is taken from l3v1 SBML testcase.\n
+ Plots are setup.\n
+ Model is run for 20sec.\n
+ As a general rule we created model under '/path/model' and plots under '/path/graphs'.\n
"""
mfile = "../genesis/00001-sbml-l3v1.xml"
@@ -67,11 +67,14 @@ def main():
runtime = 20.0
else:
runtime = float(sys.argv[2])
+
+ # Loading the sbml file into MOOSE, models are loaded in path/model
+ sbmlId = moose.SBML.readSBML.mooseReadSBML(mfile,'sbml')
# Loading the sbml file into MOOSE, models are loaded in path/model
sbmlId = mooseReadSBML(mfile,'/sbml')
if isinstance(sbmlId, (list, tuple)):
- print sbmlId
+ print(sbmlId)
elif sbmlId.path != '/':
s1 = moose.element('/sbml/model/compartment/S1')
@@ -86,7 +89,9 @@ def main():
moose.connect( outputs1,'requestOut', s1, 'getConc' );
moose.connect( outputs2,'requestOut', s2, 'getConc' );
-
+ # gsl solver is added, default is ee
+ mooseaddChemSolver(sbmlId.path,"ee")
+
# Reset and Run
moose.reinit()
moose.start(runtime)
@@ -97,7 +102,7 @@ def displayPlots():
# Display all plots.
for x in moose.wildcardFind( '/sbml/graphs/#[TYPE=Table2]' ):
t = np.arange( 0, x.vector.size, 1 ) #sec
- plt.plot( t, x.vector, label=x.name )
+ pylab.plot( t, x.vector, label=x.name )
pylab.legend()
pylab.show()
diff --git a/moose-examples/snippets/mgblock.py b/moose-examples/snippets/mgblock.py
index 2ad8741b7368447a95a60ed223f9de4781f5e9dc..0c66ec532393641cffb858b74cd668ff5ed2d224 100644
--- a/moose-examples/snippets/mgblock.py
+++ b/moose-examples/snippets/mgblock.py
@@ -133,7 +133,7 @@ def test_mgblock():
for i in range( 10 ):
moose.setClock( i, simdt )
moose.setClock( Gnmda.tick, plotdt )
- print spikegen.dt, Gnmda.dt
+ print((spikegen.dt, Gnmda.dt))
moose.reinit()
moose.start( simtime )
t = pylab.linspace(0, simtime*1e3, len(Vm.vector))
diff --git a/moose-examples/snippets/multiscaleOneCompt.py b/moose-examples/snippets/multiscaleOneCompt.py
index 19202121376195176205d693af225d166705aad4..2ab9541672617b237a27e8b0b6c688ae916a1caa 100644
--- a/moose-examples/snippets/multiscaleOneCompt.py
+++ b/moose-examples/snippets/multiscaleOneCompt.py
@@ -8,8 +8,9 @@
## See the file COPYING.LIB for the full notice.
#########################################################################
+from __future__ import print_function
+
import sys
-sys.path.append('../../python')
import os
os.environ['NUMPTHREADS'] = '1'
import math
@@ -19,6 +20,7 @@ import matplotlib.pyplot as plt
import moose
import proto18
+scriptDir = os.path.dirname( os.path.realpath( __file__ ) )
#EREST_ACT = -70e-3
def loadElec():
@@ -33,19 +35,19 @@ def loadElec():
for x in moose.wildcardFind( "/library/##" ):
x.tick = -1
model = moose.Neutral( '/model' )
- cellId = moose.loadModel( 'soma.p', '/model/elec', "Neutral" )
+ cellId = moose.loadModel(
+ os.path.join( scriptDir, 'soma.p')
+ , '/model/elec', "Neutral"
+ )
moose.setCwe( '/' )
- '''
- hsolve = moose.HSolve( '/model/elec/hsolve' )
- hsolve.dt = 50.0e-6
- hsolve.target = '/model/elec/soma'
- moose.reinit()
- '''
return cellId
def loadChem():
chem = moose.Neutral( '/model/chem' )
- modelId = moose.loadModel( '../genesis/chanPhosphByCaMKII.g', '/model/chem', 'gsl' )
+ modelId = moose.loadModel(
+ os.path.join( scriptDir, '..', 'genesis', 'chanPhosphByCaMKII.g' )
+ , '/model/chem', 'gsl'
+ )
nmstoich = moose.element( '/model/chem/kinetics/stoich' )
def makeModel():
@@ -87,7 +89,7 @@ def addPlot( objpath, field, plot, tick ):
tab.tick = tick
return tab
else:
- print "failed in addPlot(", objpath, field, plot, tick, ")"
+ print(("failed in addPlot(", objpath, field, plot, tick, ")"))
return 0
def main():
@@ -177,4 +179,4 @@ def main():
quit()
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/neuronFromDotp.py b/moose-examples/snippets/neuronFromDotp.py
index 8b8702c588987274b21ce3790a50a1a3c47dac1b..e7008c03ecada0e6fc0e5ef59e5edd079975dcf5 100644
--- a/moose-examples/snippets/neuronFromDotp.py
+++ b/moose-examples/snippets/neuronFromDotp.py
@@ -78,80 +78,80 @@ VMAX = 120e-3 + EREST_ACT
VDIVS = 3000
def makeChannelPrototypes():
- """Create channel prototypes for readcell."""
- library = moose.Neutral( '/library' )
- moose.setCwe( '/library' )
- compt = moose.SymCompartment( '/library/symcompartment' )
- Em = EREST_ACT + 10.613e-3
- compt.Em = Em
- compt.initVm = EREST_ACT
- compt.Cm = 7.85e-9 * 0.5
- compt.Rm = 4.2e5 * 5.0
- compt.Ra = 7639.44e3
- nachan = moose.HHChannel( '/library/Na' )
- nachan.Xpower = 3
- xGate = moose.HHGate(nachan.path + '/gateX')
- xGate.setupAlpha(Na_m_params + [VDIVS, VMIN, VMAX])
- xGate.useInterpolation = 1
- nachan.Ypower = 1
- yGate = moose.HHGate(nachan.path + '/gateY')
- yGate.setupAlpha(Na_h_params + [VDIVS, VMIN, VMAX])
- yGate.useInterpolation = 1
- nachan.Gbar = 0.942e-3
- nachan.Ek = 115e-3+EREST_ACT
-
- kchan = moose.HHChannel( '/library/K' )
- kchan.Xpower = 4.0
- xGate = moose.HHGate(kchan.path + '/gateX')
- xGate.setupAlpha(K_n_params + [VDIVS, VMIN, VMAX])
- xGate.useInterpolation = 1
- kchan.Gbar = 0.2836e-3
- kchan.Ek = -12e-3+EREST_ACT
+ """Create channel prototypes for readcell."""
+ library = moose.Neutral( '/library' )
+ moose.setCwe( '/library' )
+ compt = moose.SymCompartment( '/library/symcompartment' )
+ Em = EREST_ACT + 10.613e-3
+ compt.Em = Em
+ compt.initVm = EREST_ACT
+ compt.Cm = 7.85e-9 * 0.5
+ compt.Rm = 4.2e5 * 5.0
+ compt.Ra = 7639.44e3
+ nachan = moose.HHChannel( '/library/Na' )
+ nachan.Xpower = 3
+ xGate = moose.HHGate(nachan.path + '/gateX')
+ xGate.setupAlpha(Na_m_params + [VDIVS, VMIN, VMAX])
+ xGate.useInterpolation = 1
+ nachan.Ypower = 1
+ yGate = moose.HHGate(nachan.path + '/gateY')
+ yGate.setupAlpha(Na_h_params + [VDIVS, VMIN, VMAX])
+ yGate.useInterpolation = 1
+ nachan.Gbar = 0.942e-3
+ nachan.Ek = 115e-3+EREST_ACT
+
+ kchan = moose.HHChannel( '/library/K' )
+ kchan.Xpower = 4.0
+ xGate = moose.HHGate(kchan.path + '/gateX')
+ xGate.setupAlpha(K_n_params + [VDIVS, VMIN, VMAX])
+ xGate.useInterpolation = 1
+ kchan.Gbar = 0.2836e-3
+ kchan.Ek = -12e-3+EREST_ACT
def addPlot( objpath, field, plot ):
- assert moose.exists( objpath )
- tab = moose.Table( '/graphs/' + plot )
- obj = moose.element( objpath )
- moose.connect( tab, 'requestOut', obj, field )
- return tab
+ assert moose.exists( objpath )
+ tab = moose.Table( '/graphs/' + plot )
+ obj = moose.element( objpath )
+ moose.connect( tab, 'requestOut', obj, field )
+ return tab
def dumpPlots():
- plots = moose.wildcardFind( '/graphs/##[ISA=Table]' )
- for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
- t = numpy.arange( 0, x.size ) * x.dt # msec
- pylab.plot( t, x.vector, label=x.name)
+ plots = moose.wildcardFind( '/graphs/##[ISA=Table]' )
+ for x in moose.wildcardFind( '/graphs/##[ISA=Table]' ):
+ t = numpy.arange( 0, x.size ) * x.dt # msec
+ pylab.plot( t, x.vector, label=x.name)
- pylab.legend()
- pylab.show()
+ pylab.legend()
+ pylab.show()
def makeModel():
- makeChannelPrototypes()
- cellId = moose.loadModel( 'dotp.p', '/model', 'Neutral' )
- moose.element( '/model/soma' ).inject = 1.7e-9
- graphs = moose.Neutral( '/graphs' )
- addPlot( '/model/soma', 'getVm', 'somaVm' )
- addPlot( '/model/apical_14', 'getVm', 'midVm' )
- addPlot( '/model/lat_15_2', 'getVm', 'latVm' )
- addPlot( '/model/apical_19', 'getVm', 'tipVm' )
+ makeChannelPrototypes()
+ cellId = moose.loadModel( 'dotp.p', '/model', 'Neutral' )
+ moose.element( '/model/soma' ).inject = 1.7e-9
+ graphs = moose.Neutral( '/graphs' )
+ addPlot( '/model/soma', 'getVm', 'somaVm' )
+ addPlot( '/model/apical_14', 'getVm', 'midVm' )
+ addPlot( '/model/lat_15_2', 'getVm', 'latVm' )
+ addPlot( '/model/apical_19', 'getVm', 'tipVm' )
def testModel( useSolver ):
- plotDt = 2e-4
- if ( useSolver ):
- elecDt = 50e-6
- chemDt = 2e-3
+ plotDt = 2e-4
+ if ( useSolver ):
+ elecDt = 50e-6
+ chemDt = 2e-3
- makeModel()
- moose.setClock( 18, plotDt )
+ makeModel()
+ moose.setClock( 18, plotDt )
- moose.reinit()
- moose.start( 0.1 )
- dumpPlots()
+ moose.reinit()
+ moose.start( 0.1 )
+ dumpPlots()
def main():
- testModel( 1 )
+ testModel( 1 )
if __name__ == '__main__':
- main()
+ main()
#
# neuronFromDotp.py ends here
diff --git a/moose-examples/snippets/nsdf.py b/moose-examples/snippets/nsdf.py
index 93db9164ee322ddaa65969362c0b735132391479..fc6d20070ee061ebd17ff2db310ce63b432caaea 100644
--- a/moose-examples/snippets/nsdf.py
+++ b/moose-examples/snippets/nsdf.py
@@ -125,12 +125,12 @@ def setup_model():
nsdf.mode = 2 #overwrite existing file
nsdf.flushLimit = 100
moose.connect(nsdf, 'requestOut', pulse, 'getOutputValue')
- print 'event input', nsdf.eventInput, nsdf.eventInput.num
- print nsdf
+ print(('event input', nsdf.eventInput, nsdf.eventInput.num))
+ print(nsdf)
nsdf.eventInput.num = 1
ei = nsdf.eventInput[0]
- print ei.path
+ print((ei.path))
moose.connect(t_lead, 'spikeOut', nsdf.eventInput[0], 'input')
tab = moose.Table('spiketab')
tab.threshold = t_lead.threshold
@@ -138,10 +138,10 @@ def setup_model():
for ii in range(32):
moose.setClock(ii, dt)
moose.connect(pulse, 'output', tab, 'spike')
- print 'Starting simulation at:', datetime.now().isoformat()
+ print(('Starting simulation at:', datetime.now().isoformat()))
moose.reinit()
moose.start(simtime)
- print 'Finished simulation at:', datetime.now().isoformat()
+ print(('Finished simulation at:', datetime.now().isoformat()))
np.savetxt('nsdf.txt', tab.vector)
###################################
# Set the environment attributes
diff --git a/moose-examples/snippets/nsdf_vec.py b/moose-examples/snippets/nsdf_vec.py
index 879c26d08ea1e03d96ed57448bbf0daadc934e55..7a35586db66bbe3996921a65447b7db64f08418c 100644
--- a/moose-examples/snippets/nsdf_vec.py
+++ b/moose-examples/snippets/nsdf_vec.py
@@ -66,7 +66,7 @@ nsdf.py
"""
-from __future__ import print_function
+
import numpy as np
from datetime import datetime
import getpass
@@ -110,10 +110,10 @@ def write_nsdf():
clock = moose.element('/clock')
for ii in range(32):
moose.setClock(ii, dt)
- print('Starting simulation at:', datetime.now().isoformat())
+ print(('Starting simulation at:', datetime.now().isoformat()))
moose.reinit()
moose.start(simtime)
- print('Finished simulation at:', datetime.now().isoformat())
+ print(('Finished simulation at:', datetime.now().isoformat()))
###################################
# Set the environment attributes
###################################
diff --git a/moose-examples/snippets/proto18.py b/moose-examples/snippets/proto18.py
index 83448ef7e89ab3e274f9dbcfd79ccd7056b90110..b2fecbb3aa0ee275de072b61752e9087f8c1f511 100644
--- a/moose-examples/snippets/proto18.py
+++ b/moose-examples/snippets/proto18.py
@@ -4,7 +4,7 @@
#** The 1991 Traub set of voltage and concentration dependent channels
#** Implemented as tabchannels by : Dave Beeman
#** R.D.Traub, R. K. S. Wong, R. Miles, and H. Michelson
-#** Journal of Neurophysiology, Vol. 66, p. 635 (1991)
+#** Journal of Neurophysiology, Vol. 66, p. 635 (1991)
#**
#** This file depends on functions and constants defined in defaults.g
#** As it is also intended as an example of the use of the tabchannel
@@ -52,61 +52,61 @@ SOMA_A = 3.320e-9 #// soma area in square meters
#//========================================================================
def make_Ca():
- if moose.exists( 'Ca' ):
- return
- Ca = moose.HHChannel( 'Ca' )
- Ca.Ek = ECA
- Ca.Gbar = 40 * SOMA_A
- Ca.Gk = 0
- Ca.Xpower = 2
- Ca.Ypower = 1
- Ca.Zpower = 0
-
- xgate = moose.element( 'Ca/gateX' )
- xA = numpy.array( [ 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389, -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3, 3000, -0.1, 0.05 ] )
-# xgate.min = -0.1
-# xgate.max = 0.05
-# xgate.divs = 3000
+ if moose.exists( 'Ca' ):
+ return
+ Ca = moose.HHChannel( 'Ca' )
+ Ca.Ek = ECA
+ Ca.Gbar = 40 * SOMA_A
+ Ca.Gk = 0
+ Ca.Xpower = 2
+ Ca.Ypower = 1
+ Ca.Zpower = 0
+
+ xgate = moose.element( 'Ca/gateX' )
+ xA = numpy.array( [ 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389, -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3, 3000, -0.1, 0.05 ] )
+# xgate.min = -0.1
+# xgate.max = 0.05
+# xgate.divs = 3000
#// Converting Traub's expressions for the gCa/s alpha and beta functions
#// to SI units and entering the A, B, C, D and F parameters, we get:
-# xgate.alpha( 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389 )
-# xgate.beta( -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3 )
- #xgate.setupAlpha( xA )
- xgate.alphaParms = xA
+# xgate.alpha( 1.6e3, 0, 1.0, -1.0 * (0.065 + EREST_ACT), -0.01389 )
+# xgate.beta( -20e3 * (0.0511 + EREST_ACT), 20e3, -1.0, -1.0 * (0.0511 + EREST_ACT), 5.0e-3 )
+ #xgate.setupAlpha( xA )
+ xgate.alphaParms = xA
# The Y gate (gCa/r) is not quite of this form. For V > EREST_ACT, alpha =
# 5*{exp({-50*(V - EREST_ACT)})}. Otherwise, alpha = 5. Over the entire
# range, alpha + beta = 5. To create the Y_A and Y_B tables, we use some
# of the pieces of the setupalpha function.
- ygate = moose.element( 'Ca/gateY' )
- ygate.min = -0.1
- ygate.max = 0.05
- ygate.divs = 3000
- yA = numpy.zeros( (ygate.divs + 1), dtype=float)
- yB = numpy.zeros( (ygate.divs + 1), dtype=float)
+ ygate = moose.element( 'Ca/gateY' )
+ ygate.min = -0.1
+ ygate.max = 0.05
+ ygate.divs = 3000
+ yA = numpy.zeros( (ygate.divs + 1), dtype=float)
+ yB = numpy.zeros( (ygate.divs + 1), dtype=float)
#Fill the Y_A table with alpha values and the Y_B table with (alpha+beta)
- dx = (ygate.max - ygate.min)/ygate.divs
- x = ygate.min
- for i in range( ygate.divs + 1 ):
- if ( x > EREST_ACT):
- yA[i] = 5.0 * math.exp( -50 * (x - EREST_ACT) )
- else:
- yA[i] = 5.0
- yB[i] = 5.0
- x += dx
- ygate.tableA = yA
- ygate.tableB = yB
+ dx = (ygate.max - ygate.min)/ygate.divs
+ x = ygate.min
+ for i in range( ygate.divs + 1 ):
+ if ( x > EREST_ACT):
+ yA[i] = 5.0 * math.exp( -50 * (x - EREST_ACT) )
+ else:
+ yA[i] = 5.0
+ yB[i] = 5.0
+ x += dx
+ ygate.tableA = yA
+ ygate.tableB = yB
# Tell the cell reader that the current from this channel must be fed into
# the Ca_conc pool of calcium.
- addmsg1 = moose.Mstring( '/library/Ca/addmsg1' )
- addmsg1.value = '. IkOut ../Ca_conc current'
+ addmsg1 = moose.Mstring( '/library/Ca/addmsg1' )
+ addmsg1.value = '. IkOut ../Ca_conc current'
# in some compartments, whe have an NMDA_Ca_conc object to put the current
# into.
- addmsg2 = moose.Mstring( '/library/Ca/addmsg2' )
- addmsg2.value = '. IkOut ../NMDA_Ca_conc current'
+ addmsg2 = moose.Mstring( '/library/Ca/addmsg2' )
+ addmsg2.value = '. IkOut ../NMDA_Ca_conc current'
# As we typically use the cell reader to create copies of these prototype
#elements in one or more compartments, we need some way to be sure that the
#needed messages are established. Although the cell reader has enough
@@ -153,12 +153,12 @@ def make_Ca():
#//========================================================================
def make_Ca_conc():
- if moose.exists( 'Ca_conc' ):
- return
- conc = moose.CaConc( 'Ca_conc' )
- conc.tau = 0.013333 # sec
- conc.B = 17.402e12 # Curr to conc conversion for soma
- conc.Ca_base = 0.0
+ if moose.exists( 'Ca_conc' ):
+ return
+ conc = moose.CaConc( 'Ca_conc' )
+ conc.tau = 0.013333 # sec
+ conc.B = 17.402e12 # Curr to conc conversion for soma
+ conc.Ca_base = 0.0
#This Ca_concen element should receive a message from any calcium channels
# with the current going through the channel. Here we have this specified
@@ -176,38 +176,38 @@ def make_Ca_conc():
# functions of concentration, instead of voltage.
def make_K_AHP():
- if moose.exists( 'K_AHP' ):
- return
-
- K_AHP = moose.HHChannel( 'K_AHP' )
- K_AHP.Ek = EK # V
- K_AHP.Gbar = 8 * SOMA_A # S
- K_AHP.Gk = 0 # S
- K_AHP.Xpower = 0
- K_AHP.Ypower = 0
- K_AHP.Zpower = 1
-
- zgate = moose.element( 'K_AHP/gateZ' )
- xmax = 500.0
- zgate.min = 0
- zgate.max = xmax
- zgate.divs = 3000
- zA = numpy.zeros( (zgate.divs + 1), dtype=float)
- zB = numpy.zeros( (zgate.divs + 1), dtype=float)
- dx = (zgate.max - zgate.min)/zgate.divs
- x = zgate.min
- for i in range( zgate.divs + 1 ):
- if (x < (xmax / 2.0 )):
- zA[i] = 0.02*x
- else:
- zA[i] = 10.0
- zB[i] = zA[i] + 1.0
- x = x + dx
-
- zgate.tableA = zA
- zgate.tableB = zB
- addmsg1 = moose.Mstring( '/library/K_AHP/addmsg1' )
- addmsg1.value = '../Ca_conc concOut . concen'
+ if moose.exists( 'K_AHP' ):
+ return
+
+ K_AHP = moose.HHChannel( 'K_AHP' )
+ K_AHP.Ek = EK # V
+ K_AHP.Gbar = 8 * SOMA_A # S
+ K_AHP.Gk = 0 # S
+ K_AHP.Xpower = 0
+ K_AHP.Ypower = 0
+ K_AHP.Zpower = 1
+
+ zgate = moose.element( 'K_AHP/gateZ' )
+ xmax = 500.0
+ zgate.min = 0
+ zgate.max = xmax
+ zgate.divs = 3000
+ zA = numpy.zeros( (zgate.divs + 1), dtype=float)
+ zB = numpy.zeros( (zgate.divs + 1), dtype=float)
+ dx = (zgate.max - zgate.min)/zgate.divs
+ x = zgate.min
+ for i in range( zgate.divs + 1 ):
+ if (x < (xmax / 2.0 )):
+ zA[i] = 0.02*x
+ else:
+ zA[i] = 10.0
+ zB[i] = zA[i] + 1.0
+ x = x + dx
+
+ zgate.tableA = zA
+ zgate.tableB = zB
+ addmsg1 = moose.Mstring( '/library/K_AHP/addmsg1' )
+ addmsg1.value = '../Ca_conc concOut . concen'
# Use an added field to tell the cell reader to set up a message from the
# Ca_Conc with concentration info, to the current K_AHP object.
@@ -228,71 +228,71 @@ def make_K_AHP():
#the multiplicative Ca-dependent factor in the conductance.
def make_K_C():
- if moose.exists( 'K_C'):
- return
-
- K_C = moose.HHChannel( 'K_C' )
- K_C.Ek = EK # V
- K_C.Gbar = 100.0 * SOMA_A # S
- K_C.Gk = 0 # S
- K_C.Xpower = 1
- K_C.Zpower = 1
- K_C.instant = 4 # Flag: 0x100 means Z gate is instant.
-
- # Now make a X-table for the voltage-dependent activation parameter.
- xgate = moose.element( 'K_C/gateX' )
- xgate.min = -0.1
- xgate.max = 0.05
- xgate.divs = 3000
- xA = numpy.zeros( (xgate.divs + 1), dtype=float)
- xB = numpy.zeros( (xgate.divs + 1), dtype=float)
- dx = (xgate.max - xgate.min)/xgate.divs
- x = xgate.min
- for i in range( xgate.divs + 1 ):
- alpha = 0.0
- beta = 0.0
- if (x < EREST_ACT + 0.05):
- alpha = math.exp( 53.872 * (x - EREST_ACT) - 0.66835 ) / 0.018975
- beta = 2000* (math.exp ( (EREST_ACT + 0.0065 - x)/0.027)) - alpha
- else:
- alpha = 2000 * math.exp( ( EREST_ACT + 0.0065 - x)/0.027 )
- beta = 0.0
- xA[i] = alpha
- xB[i] = alpha + beta
- x = x + dx
- xgate.tableA = xA
- xgate.tableB = xB
+ if moose.exists( 'K_C'):
+ return
+
+ K_C = moose.HHChannel( 'K_C' )
+ K_C.Ek = EK # V
+ K_C.Gbar = 100.0 * SOMA_A # S
+ K_C.Gk = 0 # S
+ K_C.Xpower = 1
+ K_C.Zpower = 1
+ K_C.instant = 4 # Flag: 0x100 means Z gate is instant.
+
+ # Now make a X-table for the voltage-dependent activation parameter.
+ xgate = moose.element( 'K_C/gateX' )
+ xgate.min = -0.1
+ xgate.max = 0.05
+ xgate.divs = 3000
+ xA = numpy.zeros( (xgate.divs + 1), dtype=float)
+ xB = numpy.zeros( (xgate.divs + 1), dtype=float)
+ dx = (xgate.max - xgate.min)/xgate.divs
+ x = xgate.min
+ for i in range( xgate.divs + 1 ):
+ alpha = 0.0
+ beta = 0.0
+ if (x < EREST_ACT + 0.05):
+ alpha = math.exp( 53.872 * (x - EREST_ACT) - 0.66835 ) / 0.018975
+ beta = 2000* (math.exp ( (EREST_ACT + 0.0065 - x)/0.027)) - alpha
+ else:
+ alpha = 2000 * math.exp( ( EREST_ACT + 0.0065 - x)/0.027 )
+ beta = 0.0
+ xA[i] = alpha
+ xB[i] = alpha + beta
+ x = x + dx
+ xgate.tableA = xA
+ xgate.tableB = xB
# Create a table for the function of concentration, allowing a
# concentration range of 0 to 1000, with 50 divisions. This is done
# using the Z gate, which can receive a CONCEN message. By using
# the "instant" flag, the A and B tables are evaluated as lookup tables,
# rather than being used in a differential equation.
- zgate = moose.element( 'K_C/gateZ' )
- zgate.min = 0.0
- xmax = 500.0
- zgate.max = xmax
- zgate.divs = 3000
- zA = numpy.zeros( (zgate.divs + 1), dtype=float)
- zB = numpy.zeros( (zgate.divs + 1), dtype=float)
- dx = ( zgate.max - zgate.min)/ zgate.divs
- x = zgate.min
- for i in range( xgate.divs + 1 ):
- if ( x < ( xmax / 4.0 ) ):
- zA[i] = x * 4.0 / xmax
- else:
- zA[i] = 1.0
- zB[i] = 1.0
- x += dx
- zgate.tableA = zA
- zgate.tableB = zB
+ zgate = moose.element( 'K_C/gateZ' )
+ zgate.min = 0.0
+ xmax = 500.0
+ zgate.max = xmax
+ zgate.divs = 3000
+ zA = numpy.zeros( (zgate.divs + 1), dtype=float)
+ zB = numpy.zeros( (zgate.divs + 1), dtype=float)
+ dx = ( zgate.max - zgate.min)/ zgate.divs
+ x = zgate.min
+ for i in range( xgate.divs + 1 ):
+ if ( x < ( xmax / 4.0 ) ):
+ zA[i] = x * 4.0 / xmax
+ else:
+ zA[i] = 1.0
+ zB[i] = 1.0
+ x += dx
+ zgate.tableA = zA
+ zgate.tableB = zB
# Now we need to provide for messages that link to external elements.
# The message that sends the Ca concentration to the Z gate tables is stored
# in an added field of the channel, so that it may be found by the cell
# reader.
- addmsg1 = moose.Mstring( '/library/K_C/addmsg1' )
- addmsg1.value = '../Ca_conc concOut . concen'
+ addmsg1 = moose.Mstring( '/library/K_C/addmsg1' )
+ addmsg1.value = '../Ca_conc concOut . concen'
# The remaining channels are straightforward tabchannel implementations
@@ -301,103 +301,103 @@ def make_K_C():
#/ Tabchannel Na Hippocampal cell channel
#/========================================================================
def make_Na():
- if moose.exists( 'Na' ):
- return
- Na = moose.HHChannel( 'Na' )
- Na.Ek = ENA # V
- Na.Gbar = 300 * SOMA_A # S
- Na.Gk = 0 # S
- Na.Xpower = 2
- Na.Ypower = 1
- Na.Zpower = 0
-
- xgate = moose.element( 'Na/gateX' )
- xA = numpy.array( [ 320e3 * (0.0131 + EREST_ACT),
- -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004,
- -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0,
- -1.0 * (0.0401 + EREST_ACT), 5.0e-3,
- 3000, -0.1, 0.05 ] )
- xgate.alphaParms = xA
-
-
- #xgate.alpha( 320e3 * (0.0131 + EREST_ACT), -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004 )
- #xgate.beta( -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 5.0e-3 )
-
- ygate = moose.element( 'Na/gateY' )
- yA = numpy.array( [ 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018,
- 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3,
- 3000, -0.1, 0.05 ] )
- ygate.alphaParms = yA
-
- #ygate.alpha( 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018 )
- #ygate.beta( 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3 )
+ if moose.exists( 'Na' ):
+ return
+ Na = moose.HHChannel( 'Na' )
+ Na.Ek = ENA # V
+ Na.Gbar = 300 * SOMA_A # S
+ Na.Gk = 0 # S
+ Na.Xpower = 2
+ Na.Ypower = 1
+ Na.Zpower = 0
+
+ xgate = moose.element( 'Na/gateX' )
+ xA = numpy.array( [ 320e3 * (0.0131 + EREST_ACT),
+ -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004,
+ -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0,
+ -1.0 * (0.0401 + EREST_ACT), 5.0e-3,
+ 3000, -0.1, 0.05 ] )
+ xgate.alphaParms = xA
+
+
+ #xgate.alpha( 320e3 * (0.0131 + EREST_ACT), -320e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.004 )
+ #xgate.beta( -280e3 * (0.0401 + EREST_ACT), 280e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 5.0e-3 )
+
+ ygate = moose.element( 'Na/gateY' )
+ yA = numpy.array( [ 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018,
+ 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3,
+ 3000, -0.1, 0.05 ] )
+ ygate.alphaParms = yA
+
+ #ygate.alpha( 128.0, 0.0, 0.0, -1.0 * (0.017 + EREST_ACT), 0.018 )
+ #ygate.beta( 4.0e3, 0.0, 1.0, -1.0 * (0.040 + EREST_ACT), -5.0e-3 )
#========================================================================
# Tabchannel K(DR) Hippocampal cell channel
#========================================================================
def make_K_DR():
- if moose.exists( 'K_DR' ):
- return
- K_DR = moose.HHChannel( 'K_DR' )
- K_DR.Ek = EK # V
- K_DR.Gbar = 150 * SOMA_A # S
- K_DR.Gk = 0 # S
- K_DR.Xpower = 1
- K_DR.Ypower = 0
- K_DR.Zpower = 0
-
- xgate = moose.element( 'K_DR/gateX' )
- xA = numpy.array( [ 16e3 * (0.0351 + EREST_ACT),
- -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005,
- 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04,
- 3000, -0.1, 0.05 ] )
- xgate.alphaParms = xA
- #xgate.alpha( 16e3 * (0.0351 + EREST_ACT), -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005 )
- #xgate.beta( 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04 )
+ if moose.exists( 'K_DR' ):
+ return
+ K_DR = moose.HHChannel( 'K_DR' )
+ K_DR.Ek = EK # V
+ K_DR.Gbar = 150 * SOMA_A # S
+ K_DR.Gk = 0 # S
+ K_DR.Xpower = 1
+ K_DR.Ypower = 0
+ K_DR.Zpower = 0
+
+ xgate = moose.element( 'K_DR/gateX' )
+ xA = numpy.array( [ 16e3 * (0.0351 + EREST_ACT),
+ -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005,
+ 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04,
+ 3000, -0.1, 0.05 ] )
+ xgate.alphaParms = xA
+ #xgate.alpha( 16e3 * (0.0351 + EREST_ACT), -16e3, -1.0, -1.0 * (0.0351 + EREST_ACT), -0.005 )
+ #xgate.beta( 250, 0.0, 0.0, -1.0 * (0.02 + EREST_ACT), 0.04 )
#========================================================================
# Tabchannel K(A) Hippocampal cell channel
#========================================================================
def make_K_A():
- if moose.exists( 'K_A' ):
- return
- K_A = moose.HHChannel( 'K_A' )
- K_A.Ek = EK # V
- K_A.Gbar = 50 * SOMA_A # S
- K_A.Gk = 0 # S
- K_A.Xpower = 1
- K_A.Ypower = 1
- K_A.Zpower = 0
-
- xgate = moose.element( 'K_A/gateX' )
- xA = numpy.array( [ 20e3 * (0.0131 + EREST_ACT),
- -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01,
- -17.5e3 * (0.0401 + EREST_ACT),
- 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01,
- 3000, -0.1, 0.05 ] )
- xgate.alphaParms = xA
- # xgate.alpha( 20e3 * (0.0131 + EREST_ACT), -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01 )
- # xgate.beta( -17.5e3 * (0.0401 + EREST_ACT), 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01 )
-
- ygate = moose.element( 'K_A/gateY' )
- yA = numpy.array( [ 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018,
- 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005,
- 3000, -0.1, 0.05 ] )
- ygate.alphaParms = yA
- # ygate.alpha( 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018 )
- # ygate.beta( 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005 )
+ if moose.exists( 'K_A' ):
+ return
+ K_A = moose.HHChannel( 'K_A' )
+ K_A.Ek = EK # V
+ K_A.Gbar = 50 * SOMA_A # S
+ K_A.Gk = 0 # S
+ K_A.Xpower = 1
+ K_A.Ypower = 1
+ K_A.Zpower = 0
+
+ xgate = moose.element( 'K_A/gateX' )
+ xA = numpy.array( [ 20e3 * (0.0131 + EREST_ACT),
+ -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01,
+ -17.5e3 * (0.0401 + EREST_ACT),
+ 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01,
+ 3000, -0.1, 0.05 ] )
+ xgate.alphaParms = xA
+ # xgate.alpha( 20e3 * (0.0131 + EREST_ACT), -20e3, -1.0, -1.0 * (0.0131 + EREST_ACT), -0.01 )
+ # xgate.beta( -17.5e3 * (0.0401 + EREST_ACT), 17.5e3, -1.0, -1.0 * (0.0401 + EREST_ACT), 0.01 )
+
+ ygate = moose.element( 'K_A/gateY' )
+ yA = numpy.array( [ 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018,
+ 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005,
+ 3000, -0.1, 0.05 ] )
+ ygate.alphaParms = yA
+ # ygate.alpha( 1.6, 0.0, 0.0, 0.013 - EREST_ACT, 0.018 )
+ # ygate.beta( 50.0, 0.0, 1.0, -1.0 * (0.0101 + EREST_ACT), -0.005 )
#========================================================================
# SynChan: Glu receptor
#========================================================================
def make_glu():
- if moose.exists( 'glu' ):
- return
- glu = moose.SynChan( 'glu' )
- glu.Ek = 0.0
- glu.tau1 = 2.0e-3
- glu.tau2 = 9.0e-3
- glu.Gbar = 40 * SOMA_A
+ if moose.exists( 'glu' ):
+ return
+ glu = moose.SynChan( 'glu' )
+ glu.Ek = 0.0
+ glu.tau1 = 2.0e-3
+ glu.tau2 = 9.0e-3
+ glu.Gbar = 40 * SOMA_A
sh = moose.SimpleSynHandler( 'glu/sh' )
moose.connect( sh, 'activationOut', glu, 'activation' )
sh.numSynapses = 1
@@ -409,39 +409,39 @@ def make_glu():
#========================================================================
def make_NMDA():
- if moose.exists( 'NMDA' ):
- return
- NMDA = moose.SynChan( 'NMDA' )
- NMDA.Ek = 0.0
- NMDA.tau1 = 20.0e-3
- NMDA.tau2 = 20.0e-3
- NMDA.Gbar = 5 * SOMA_A
-
- block = moose.MgBlock( '/library/NMDA/block' )
- block.CMg = 1.2 # [Mg] in mM
- block.Zk = 2
- block.KMg_A = 1.0/0.28
- block.KMg_B = 1.0/62
-
- moose.connect( NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
- addmsg1 = moose.Mstring( '/library/NMDA/addmsg1' )
- addmsg1.value = '.. channel ./block channel'
- #Here we want to also tell the cell reader to _remove_ the original
- #Gk, Ek term going from the channel to the compartment, as this is
- # now handled by the MgBlock.
- #addmsg2 = moose.Mstring( 'NMDA/addmsg2'
- #addmsg2.value = 'DropMsg .. channel'
- addmsg1 = moose.Mstring( '/library/NMDA/addmsg1' )
- addmsg1.value = '.. VmOut ./block Vm'
- addmsg2 = moose.Mstring( '/library/NMDA/addmsg2' )
- addmsg2.value = './block IkOut ../Ca_conc current'
- addmsg3 = moose.Mstring( '/library/NMDA/addmsg3' )
- addmsg3.value = '.. VmOut . Vm'
-
- sh = moose.SimpleSynHandler( 'NMDA/sh' )
- moose.connect( sh, 'activationOut', NMDA, 'activation' )
- sh.numSynapses = 1
- sh.synapse[0].weight = 1
+ if moose.exists( 'NMDA' ):
+ return
+ NMDA = moose.SynChan( 'NMDA' )
+ NMDA.Ek = 0.0
+ NMDA.tau1 = 20.0e-3
+ NMDA.tau2 = 20.0e-3
+ NMDA.Gbar = 5 * SOMA_A
+
+ block = moose.MgBlock( '/library/NMDA/block' )
+ block.CMg = 1.2 # [Mg] in mM
+ block.Zk = 2
+ block.KMg_A = 1.0/0.28
+ block.KMg_B = 1.0/62
+
+ moose.connect( NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
+ addmsg1 = moose.Mstring( '/library/NMDA/addmsg1' )
+ addmsg1.value = '.. channel ./block channel'
+ #Here we want to also tell the cell reader to _remove_ the original
+ #Gk, Ek term going from the channel to the compartment, as this is
+ # now handled by the MgBlock.
+ #addmsg2 = moose.Mstring( 'NMDA/addmsg2'
+ #addmsg2.value = 'DropMsg .. channel'
+ addmsg1 = moose.Mstring( '/library/NMDA/addmsg1' )
+ addmsg1.value = '.. VmOut ./block Vm'
+ addmsg2 = moose.Mstring( '/library/NMDA/addmsg2' )
+ addmsg2.value = './block IkOut ../Ca_conc current'
+ addmsg3 = moose.Mstring( '/library/NMDA/addmsg3' )
+ addmsg3.value = '.. VmOut . Vm'
+
+ sh = moose.SimpleSynHandler( 'NMDA/sh' )
+ moose.connect( sh, 'activationOut', NMDA, 'activation' )
+ sh.numSynapses = 1
+ sh.synapse[0].weight = 1
#addfield NMDA addmsg1
#setfield NMDA addmsg1 ".. ./block VOLTAGE Vm"
@@ -461,37 +461,37 @@ def make_NMDA():
#========================================================================
def make_Ca_NMDA():
- if moose.exists( 'Ca_NMDA' ):
- return
- Ca_NMDA = moose.SynChan( 'Ca_NMDA' )
- Ca_NMDA.Ek = ECA
- Ca_NMDA.tau1 = 20.0e-3
- Ca_NMDA.tau2 = 20.0e-3
- Ca_NMDA.Gbar = 5 * SOMA_A
-
- block = moose.MgBlock( '/library/Ca_NMDA/block' )
- block.CMg = 1.2 # [Mg] in mM
- block.Zk = 2
- block.KMg_A = 1.0/0.28
- block.KMg_B = 1.0/62
-
- moose.connect( Ca_NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
- addmsg1 = moose.Mstring( '/library/Ca_NMDA/addmsg1' )
- addmsg1.value = '.. VmOut ./block Vm'
- addmsg2 = moose.Mstring( '/library/Ca_NMDA/addmsg2' )
- addmsg2.value = './block IkOut ../NMDA_Ca_conc current'
- # The original model has the Ca current also coming here.
+ if moose.exists( 'Ca_NMDA' ):
+ return
+ Ca_NMDA = moose.SynChan( 'Ca_NMDA' )
+ Ca_NMDA.Ek = ECA
+ Ca_NMDA.tau1 = 20.0e-3
+ Ca_NMDA.tau2 = 20.0e-3
+ Ca_NMDA.Gbar = 5 * SOMA_A
+
+ block = moose.MgBlock( '/library/Ca_NMDA/block' )
+ block.CMg = 1.2 # [Mg] in mM
+ block.Zk = 2
+ block.KMg_A = 1.0/0.28
+ block.KMg_B = 1.0/62
+
+ moose.connect( Ca_NMDA, 'channelOut', block, 'origChannel', 'OneToOne' )
+ addmsg1 = moose.Mstring( '/library/Ca_NMDA/addmsg1' )
+ addmsg1.value = '.. VmOut ./block Vm'
+ addmsg2 = moose.Mstring( '/library/Ca_NMDA/addmsg2' )
+ addmsg2.value = './block IkOut ../NMDA_Ca_conc current'
+ # The original model has the Ca current also coming here.
#========================================================================
# Ca pool for influx through Ca_NMDA
#========================================================================
def make_NMDA_Ca_conc():
- if moose.exists( 'NMDA_Ca_conc' ):
- return
- NMDA_Ca_conc = moose.CaConc( 'NMDA_Ca_conc' )
- NMDA_Ca_conc.tau = 0.004 # sec. Faster in spine than dend
- NMDA_Ca_conc.B = 17.402e12 # overridden by cellreader.
- NMDA_Ca_conc.Ca_base = 0.0
+ if moose.exists( 'NMDA_Ca_conc' ):
+ return
+ NMDA_Ca_conc = moose.CaConc( 'NMDA_Ca_conc' )
+ NMDA_Ca_conc.tau = 0.004 # sec. Faster in spine than dend
+ NMDA_Ca_conc.B = 17.402e12 # overridden by cellreader.
+ NMDA_Ca_conc.Ca_base = 0.0
# This pool used to set up Ca info coming to it. Now we insist that the
# originating channel should specify the deferred message.
@@ -502,9 +502,9 @@ def make_NMDA_Ca_conc():
#//addmsg axon/spike axon BUFFER name
def make_axon():
- if moose.exists( 'axon' ):
- return
- axon = moose.SpikeGen( 'axon' )
- axon.threshold = -40e-3 # V
- axon.abs_refract = 10e-3 # sec
+ if moose.exists( 'axon' ):
+ return
+ axon = moose.SpikeGen( 'axon' )
+ axon.threshold = -40e-3 # V
+ axon.abs_refract = 10e-3 # sec
diff --git a/moose-examples/snippets/pulsegen2.py b/moose-examples/snippets/pulsegen2.py
index 812e63027100b728cca92fa88a7880e74a9263ed..b5c9f0ca90de3064a5090a3e8ee1bd6a120257ca 100644
--- a/moose-examples/snippets/pulsegen2.py
+++ b/moose-examples/snippets/pulsegen2.py
@@ -164,7 +164,7 @@ pylab.plot(plotGate.vector)
pylab.title('Free Running Gate')
pylab.tight_layout()
pylab.show()
-print "pulsegen.py: finished simulation"
+print("pulsegen.py: finished simulation")
#
# pulsegen2.py ends here
diff --git a/moose-examples/snippets/reacDiffBranchingNeuron.py b/moose-examples/snippets/reacDiffBranchingNeuron.py
index fa4864eb01ca15cb0d5784d32aeb00af3a285bc0..c76a32066c6675922f1100e147130087531a8d85 100644
--- a/moose-examples/snippets/reacDiffBranchingNeuron.py
+++ b/moose-examples/snippets/reacDiffBranchingNeuron.py
@@ -99,8 +99,8 @@ def makeDisplay():
return ( timeSeries, fig, line, timeLabel, yp )
def updateDisplay( plotlist ):
- a = moose.vec( '/model/chem/compt0/a' )
- b = moose.vec( '/model/chem/compt0/b' )
+ a = moose.vec( '/model/chem/compt0/a' )
+ b = moose.vec( '/model/chem/compt0/b' )
plotlist[2].set_ydata( a.conc * 10 + plotlist[4] )
plotlist[1].canvas.draw()
@@ -113,7 +113,7 @@ def finalizeDisplay( plotlist, cPlotDt ):
plt.legend()
plotlist[1].canvas.draw()
print( "Hit 'enter' to exit" )
- raw_input()
+ eval(input())
def makeChemModel( compt ):
"""
@@ -232,4 +232,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/reacDiffConcGradient.py b/moose-examples/snippets/reacDiffConcGradient.py
index 80cf4637c401889326d5bc51572a75ffacffd0fa..67f002095d40ffeb2ce9ab4e5810bcc923da5fdf 100644
--- a/moose-examples/snippets/reacDiffConcGradient.py
+++ b/moose-examples/snippets/reacDiffConcGradient.py
@@ -17,7 +17,7 @@ import moose
diffConst = 1e-12
def makeCyl( num, concInit, radius, x0, x1 ):
- compt = moose.CylMesh( '/model/compt' + num )
+ compt = moose.CylMesh( '/model/compt' + num )
compt.x0 = x0
compt.x1 = x1
compt.y0 = 0
@@ -29,14 +29,14 @@ def makeCyl( num, concInit, radius, x0, x1 ):
compt.diffLength = x1-x0
a = moose.Pool( compt.path + '/a' )
b = moose.Pool( compt.path + '/b' + num )
- reac = moose.Reac( compt.path + '/reac' )
- moose.connect( reac, 'sub', a, 'reac' )
- moose.connect( reac, 'prd', b, 'reac' )
+ reac = moose.Reac( compt.path + '/reac' )
+ moose.connect( reac, 'sub', a, 'reac' )
+ moose.connect( reac, 'prd', b, 'reac' )
a.diffConst = diffConst
a.concInit = concInit
b.concInit = concInit
- reac.Kf = 0.1
- reac.Kb = 0.1
+ reac.Kf = 0.1
+ reac.Kb = 0.1
return a, b, compt
def makeModel():
@@ -44,40 +44,40 @@ def makeModel():
len0 = 4e-6
len1 = 2e-6
len2 = 1e-6
- # create container for model
- model = moose.Neutral( 'model' )
+ # create container for model
+ model = moose.Neutral( 'model' )
a0, b0, compt0 = makeCyl( '0', 1, radius, -len0, 0 )
a1, b1, compt1 = makeCyl( '1', 2, radius, 0, len1 )
a2, b2, compt2 = makeCyl( '2', 6, radius, len1, len1 + len2 )
- print('Volumes = ', compt0.volume, compt1.volume, compt2.volume)
+ print(('Volumes = ', compt0.volume, compt1.volume, compt2.volume))
- # create molecules and reactions
- reac0 = moose.Reac( '/model/compt1/reac0' )
- reac1 = moose.Reac( '/model/compt1/reac1' )
+ # create molecules and reactions
+ reac0 = moose.Reac( '/model/compt1/reac0' )
+ reac1 = moose.Reac( '/model/compt1/reac1' )
- # connect them up for reactions
- moose.connect( reac0, 'sub', b0, 'reac' )
- moose.connect( reac0, 'prd', b1, 'reac' )
- moose.connect( reac1, 'sub', b1, 'reac' )
- moose.connect( reac1, 'prd', b2, 'reac' )
+ # connect them up for reactions
+ moose.connect( reac0, 'sub', b0, 'reac' )
+ moose.connect( reac0, 'prd', b1, 'reac' )
+ moose.connect( reac1, 'sub', b1, 'reac' )
+ moose.connect( reac1, 'prd', b2, 'reac' )
- # Assign parameters
- reac0.Kf = 0.5
- reac0.Kb = 0.05
- reac1.Kf = 0.5
- reac1.Kb = 0.05
+ # Assign parameters
+ reac0.Kf = 0.5
+ reac0.Kb = 0.05
+ reac1.Kf = 0.5
+ reac1.Kb = 0.05
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA0 = moose.Table2 ( '/model/graphs/concA0' )
- outputA1 = moose.Table2 ( '/model/graphs/concA1' )
- outputA2 = moose.Table2 ( '/model/graphs/concA2' )
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA0 = moose.Table2 ( '/model/graphs/concA0' )
+ outputA1 = moose.Table2 ( '/model/graphs/concA1' )
+ outputA2 = moose.Table2 ( '/model/graphs/concA2' )
- # connect up the tables
- moose.connect( outputA0, 'requestOut', a0, 'getConc' );
- moose.connect( outputA1, 'requestOut', a1, 'getConc' );
- moose.connect( outputA2, 'requestOut', a2, 'getConc' );
+ # connect up the tables
+ moose.connect( outputA0, 'requestOut', a0, 'getConc' );
+ moose.connect( outputA1, 'requestOut', a1, 'getConc' );
+ moose.connect( outputA2, 'requestOut', a2, 'getConc' );
# Build the solvers. No need for diffusion in this version.
ksolve0 = moose.Ksolve( '/model/compt0/ksolve0' )
@@ -143,10 +143,10 @@ def main():
initTot = 0
tot = 0
for x in moose.wildcardFind( '/model/compt#/#[ISA=PoolBase]' ):
- print(x.name, x.conc)
+ print((x.name, x.conc))
tot += x.n
initTot += x.nInit
- print("Totals: expected = ", initTot, ", got: ", tot)
+ print(("Totals: expected = ", initTot, ", got: ", tot))
# Iterate through all plots, dump their contents to data.plot.
for x in moose.wildcardFind( '/model/graphs/conc#' ):
@@ -158,4 +158,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/reacDiffSpinyNeuron.py b/moose-examples/snippets/reacDiffSpinyNeuron.py
index 2edb86b99b86f76523258a1772db777f3dc1e708..067147f004f59d62721451aa199d4d3e2f358415 100644
--- a/moose-examples/snippets/reacDiffSpinyNeuron.py
+++ b/moose-examples/snippets/reacDiffSpinyNeuron.py
@@ -93,7 +93,7 @@ def makeModel():
graphs = moose.Neutral( '/model/graphs' )
moose.le( '/model/chem/compt1' )
a = moose.element( '/model/chem/compt1' )
- print a.voxelVolume
+ print((a.voxelVolume))
makeTab( 'a_soma', '/model/chem/compt0/a[0]' )
makeTab( 'b_soma', '/model/chem/compt0/b[0]' )
makeTab( 'a_apical', '/model/chem/compt0/a[' + str( num ) + ']' )
@@ -135,40 +135,40 @@ def makeDisplay():
plt.xlabel( 'time (seconds)' )
plt.legend()
- a = moose.vec( '/model/chem/compt0/a' )
- b = moose.vec( '/model/chem/compt0/b' )
- line1, = dend.plot( range( len( a ) ), a.conc, label='a' )
- line2, = dend.plot( range( len( b ) ), b.conc, label='b' )
+ a = moose.vec( '/model/chem/compt0/a' )
+ b = moose.vec( '/model/chem/compt0/b' )
+ line1, = dend.plot( list(range( len( a ))), a.conc, label='a' )
+ line2, = dend.plot( list(range( len( b ))), b.conc, label='b' )
dend.set_ylim( 0, 0.6 )
- a = moose.vec( '/model/chem/compt1/a' )
- b = moose.vec( '/model/chem/compt1/b' )
- line3, = spine.plot( range( len( a ) ), a.conc, label='a' )
- line4, = spine.plot( range( len( b ) ), b.conc, label='b' )
+ a = moose.vec( '/model/chem/compt1/a' )
+ b = moose.vec( '/model/chem/compt1/b' )
+ line3, = spine.plot( list(range( len( a ))), a.conc, label='a' )
+ line4, = spine.plot( list(range( len( b ))), b.conc, label='b' )
spine.set_ylim( 0, 0.6 )
- a = moose.vec( '/model/chem/compt2/a' )
- b = moose.vec( '/model/chem/compt2/b' )
- line5, = psd.plot( range( len( a ) ), a.conc, label='a' )
- line6, = psd.plot( range( len( b ) ), b.conc, label='b' )
+ a = moose.vec( '/model/chem/compt2/a' )
+ b = moose.vec( '/model/chem/compt2/b' )
+ line5, = psd.plot( list(range( len( a ))), a.conc, label='a' )
+ line6, = psd.plot( list(range( len( b ))), b.conc, label='b' )
psd.set_ylim( 0, 0.6 )
fig.canvas.draw()
return ( timeSeries, dend, spine, psd, fig, line1, line2, line3, line4, line5, line6, timeLabel )
def updateDisplay( plotlist ):
- a = moose.vec( '/model/chem/compt0/a' )
- b = moose.vec( '/model/chem/compt0/b' )
+ a = moose.vec( '/model/chem/compt0/a' )
+ b = moose.vec( '/model/chem/compt0/b' )
plotlist[5].set_ydata( a.conc )
plotlist[6].set_ydata( b.conc )
- a = moose.vec( '/model/chem/compt1/a' )
- b = moose.vec( '/model/chem/compt1/b' )
+ a = moose.vec( '/model/chem/compt1/a' )
+ b = moose.vec( '/model/chem/compt1/b' )
plotlist[7].set_ydata( a.conc )
plotlist[8].set_ydata( b.conc )
- a = moose.vec( '/model/chem/compt2/a' )
- b = moose.vec( '/model/chem/compt2/b' )
+ a = moose.vec( '/model/chem/compt2/a' )
+ b = moose.vec( '/model/chem/compt2/b' )
plotlist[9].set_ydata( a.conc )
plotlist[10].set_ydata( b.conc )
plotlist[4].canvas.draw()
@@ -180,7 +180,7 @@ def finalizeDisplay( plotlist, cPlotDt ):
line1, = plotlist[0].plot( pos, x.vector, label=x.name )
plotlist[4].canvas.draw()
print( "Hit 'enter' to exit" )
- raw_input()
+ eval(input())
def makeChemModel( compt ):
"""
@@ -294,4 +294,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/recurrentIntFire.py b/moose-examples/snippets/recurrentIntFire.py
index 6a480cc4941b55ec56013b400504771f9441f014..1e291e1eefe77daa941084cb2d1c96f3afa4186b 100644
--- a/moose-examples/snippets/recurrentIntFire.py
+++ b/moose-examples/snippets/recurrentIntFire.py
@@ -22,49 +22,49 @@ sys.path.append('/home/subha/src/moose_async13/python')
import moose
def make_network():
- size = 1024
- dt = 0.2
- runsteps = 50
- delayMin = 0
- delayMax = 4
- weightMax = 1
- Vmax = 1.0
- thresh = 0.4
- refractoryPeriod = 0.4
+ size = 1024
+ dt = 0.2
+ runsteps = 50
+ delayMin = 0
+ delayMax = 4
+ weightMax = 1
+ Vmax = 1.0
+ thresh = 0.4
+ refractoryPeriod = 0.4
tau = 0.5
- connectionProbability = 0.01
- random.seed( 123 )
- nprand.seed( 456 )
- t0 = time.time()
+ connectionProbability = 0.01
+ random.seed( 123 )
+ nprand.seed( 456 )
+ t0 = time.time()
- network = moose.IntFire( 'network', size );
- syns = moose.SimpleSynHandler( '/network/syns', size );
+ network = moose.IntFire( 'network', size );
+ syns = moose.SimpleSynHandler( '/network/syns', size );
moose.connect( syns, 'activationOut', network, 'activation', 'OneToOne' )
- moose.le( '/network' )
- syns.vec.numSynapses = [1] * size
- sv = moose.vec( '/network/syns/synapse' )
- print 'before connect t = ', time.time() - t0
- mid = moose.connect( network, 'spikeOut', sv, 'addSpike', 'Sparse')
- print 'after connect t = ', time.time() - t0
- #print mid.destFields
- m2 = moose.element( mid )
- m2.setRandomConnectivity( connectionProbability, 5489 )
- print 'after setting connectivity, t = ', time.time() - t0
- #network.vec.Vm = [(Vmax*random.random()) for r in range(size)]
- network.vec.Vm = nprand.rand( size ) * Vmax
- network.vec.thresh = thresh
- network.vec.refractoryPeriod = refractoryPeriod
- network.vec.tau = tau
- numSynVec = syns.vec.numSynapses
- print 'Middle of setup, t = ', time.time() - t0
- numTotSyn = sum( numSynVec )
- print numSynVec.size, ', tot = ', numTotSyn, ', numSynVec = ', numSynVec
- for item in syns.vec:
- sh = moose.element( item )
+ moose.le( '/network' )
+ syns.vec.numSynapses = [1] * size
+ sv = moose.vec( '/network/syns/synapse' )
+ print(('before connect t = ', time.time() - t0))
+ mid = moose.connect( network, 'spikeOut', sv, 'addSpike', 'Sparse')
+ print(('after connect t = ', time.time() - t0))
+ #print mid.destFields
+ m2 = moose.element( mid )
+ m2.setRandomConnectivity( connectionProbability, 5489 )
+ print(('after setting connectivity, t = ', time.time() - t0))
+ #network.vec.Vm = [(Vmax*random.random()) for r in range(size)]
+ network.vec.Vm = nprand.rand( size ) * Vmax
+ network.vec.thresh = thresh
+ network.vec.refractoryPeriod = refractoryPeriod
+ network.vec.tau = tau
+ numSynVec = syns.vec.numSynapses
+ print(('Middle of setup, t = ', time.time() - t0))
+ numTotSyn = sum( numSynVec )
+ print((numSynVec.size, ', tot = ', numTotSyn, ', numSynVec = ', numSynVec))
+ for item in syns.vec:
+ sh = moose.element( item )
sh.synapse.delay = delayMin + (delayMax - delayMin ) * nprand.rand( len( sh.synapse ) )
- #sh.synapse.delay = [ (delayMin + random.random() * (delayMax - delayMin ) for r in range( len( sh.synapse ) ) ]
- sh.synapse.weight = nprand.rand( len( sh.synapse ) ) * weightMax
- print 'after setup, t = ', time.time() - t0
+ #sh.synapse.delay = [ (delayMin + random.random() * (delayMax - delayMin ) for r in range( len( sh.synapse ) ) ]
+ sh.synapse.weight = nprand.rand( len( sh.synapse ) ) * weightMax
+ print(('after setup, t = ', time.time() - t0))
numStats = 100
stats = moose.SpikeStats( '/stats', numStats )
@@ -77,26 +77,26 @@ def make_network():
moose.connect( network.vec[k], 'spikeOut', stats.vec[i], 'addSpike' )
moose.connect( plots, 'requestOut', stats, 'getMean', 'OneToOne' )
- #moose.useClock( 0, '/network/syns,/network', 'process' )
- moose.useClock( 0, '/network/syns', 'process' )
- moose.useClock( 1, '/network', 'process' )
- moose.useClock( 2, '/stats', 'process' )
- moose.useClock( 3, '/plot', 'process' )
- moose.setClock( 0, dt )
- moose.setClock( 1, dt )
- moose.setClock( 2, dt )
- moose.setClock( 3, dt )
- moose.setClock( 9, dt )
- t1 = time.time()
- moose.reinit()
- print 'reinit time t = ', time.time() - t1
- network.vec.Vm = nprand.rand( size ) * Vmax
- print 'setting Vm , t = ', time.time() - t1
- t1 = time.time()
- print 'starting'
- moose.start(runsteps * dt)
- print 'runtime, t = ', time.time() - t1
- print network.vec.Vm[99:103], network.vec.Vm[900:903]
+ #moose.useClock( 0, '/network/syns,/network', 'process' )
+ moose.useClock( 0, '/network/syns', 'process' )
+ moose.useClock( 1, '/network', 'process' )
+ moose.useClock( 2, '/stats', 'process' )
+ moose.useClock( 3, '/plot', 'process' )
+ moose.setClock( 0, dt )
+ moose.setClock( 1, dt )
+ moose.setClock( 2, dt )
+ moose.setClock( 3, dt )
+ moose.setClock( 9, dt )
+ t1 = time.time()
+ moose.reinit()
+ print(('reinit time t = ', time.time() - t1))
+ network.vec.Vm = nprand.rand( size ) * Vmax
+ print(('setting Vm , t = ', time.time() - t1))
+ t1 = time.time()
+ print('starting')
+ moose.start(runsteps * dt)
+ print(('runtime, t = ', time.time() - t1))
+ print((network.vec.Vm[99:103], network.vec.Vm[900:903]))
t = [i * dt for i in range( plots.vec[0].vector.size )]
i = 0
for p in plots.vec:
diff --git a/moose-examples/snippets/recurrentLIF.py b/moose-examples/snippets/recurrentLIF.py
index 6f00fdfae9c696bb305aafd8f9c3a35662a4fb32..0bb5249fe2b542ebac140e22658393886ca72cc2 100644
--- a/moose-examples/snippets/recurrentLIF.py
+++ b/moose-examples/snippets/recurrentLIF.py
@@ -22,50 +22,50 @@ sys.path.append('/home/subha/src/moose_async13/python')
import moose
def make_network():
- size = 1024
- dt = 0.2
- runsteps = 50
- delayMin = 0
- delayMax = 4
- weightMax = 1
- Vmax = 1.0
- thresh = 0.4
- refractoryPeriod = 0.4
+ size = 1024
+ dt = 0.2
+ runsteps = 50
+ delayMin = 0
+ delayMax = 4
+ weightMax = 1
+ Vmax = 1.0
+ thresh = 0.4
+ refractoryPeriod = 0.4
tau = 0.5
- connectionProbability = 0.01
- random.seed( 123 )
- nprand.seed( 456 )
- t0 = time.time()
+ connectionProbability = 0.01
+ random.seed( 123 )
+ nprand.seed( 456 )
+ t0 = time.time()
- network = moose.LIF( 'network', size );
- syns = moose.SimpleSynHandler( '/network/syns', size );
+ network = moose.LIF( 'network', size );
+ syns = moose.SimpleSynHandler( '/network/syns', size );
moose.connect( syns, 'activationOut', network, 'activation', 'OneToOne' )
- moose.le( '/network' )
- syns.vec.numSynapses = [1] * size
- sv = moose.vec( '/network/syns/synapse' )
- print 'before connect t = ', time.time() - t0
- mid = moose.connect( network, 'spikeOut', sv, 'addSpike', 'Sparse')
- print 'after connect t = ', time.time() - t0
- #print mid.destFields
- m2 = moose.element( mid )
- m2.setRandomConnectivity( connectionProbability, 5489 )
- print 'after setting connectivity, t = ', time.time() - t0
- #network.vec.Vm = [(Vmax*random.random()) for r in range(size)]
- network.vec.Vm = nprand.rand( size ) * Vmax
- network.vec.thresh = thresh
- network.vec.refractoryPeriod = refractoryPeriod
- network.vec.Rm = 1e10
- network.vec.Cm = 5e-9
- numSynVec = syns.vec.numSynapses
- print 'Middle of setup, t = ', time.time() - t0
- numTotSyn = sum( numSynVec )
- print numSynVec.size, ', tot = ', numTotSyn, ', numSynVec = ', numSynVec
- for item in syns.vec:
- sh = moose.element( item )
+ moose.le( '/network' )
+ syns.vec.numSynapses = [1] * size
+ sv = moose.vec( '/network/syns/synapse' )
+ print(('before connect t = ', time.time() - t0))
+ mid = moose.connect( network, 'spikeOut', sv, 'addSpike', 'Sparse')
+ print(('after connect t = ', time.time() - t0))
+ #print mid.destFields
+ m2 = moose.element( mid )
+ m2.setRandomConnectivity( connectionProbability, 5489 )
+ print(('after setting connectivity, t = ', time.time() - t0))
+ #network.vec.Vm = [(Vmax*random.random()) for r in range(size)]
+ network.vec.Vm = nprand.rand( size ) * Vmax
+ network.vec.thresh = thresh
+ network.vec.refractoryPeriod = refractoryPeriod
+ network.vec.Rm = 1e10
+ network.vec.Cm = 5e-9
+ numSynVec = syns.vec.numSynapses
+ print(('Middle of setup, t = ', time.time() - t0))
+ numTotSyn = sum( numSynVec )
+ print((numSynVec.size, ', tot = ', numTotSyn, ', numSynVec = ', numSynVec))
+ for item in syns.vec:
+ sh = moose.element( item )
sh.synapse.delay = delayMin + (delayMax - delayMin ) * nprand.rand( len( sh.synapse ) )
- #sh.synapse.delay = [ (delayMin + random.random() * (delayMax - delayMin ) for r in range( len( sh.synapse ) ) ]
- sh.synapse.weight = nprand.rand( len( sh.synapse ) ) * weightMax
- print 'after setup, t = ', time.time() - t0
+ #sh.synapse.delay = [ (delayMin + random.random() * (delayMax - delayMin ) for r in range( len( sh.synapse ) ) ]
+ sh.synapse.weight = nprand.rand( len( sh.synapse ) ) * weightMax
+ print(('after setup, t = ', time.time() - t0))
numStats = 100
stats = moose.SpikeStats( '/stats', numStats )
@@ -78,26 +78,26 @@ def make_network():
moose.connect( network.vec[k], 'spikeOut', stats.vec[i], 'addSpike' )
moose.connect( plots, 'requestOut', stats, 'getMean', 'OneToOne' )
- #moose.useClock( 0, '/network/syns,/network', 'process' )
- moose.useClock( 0, '/network/syns', 'process' )
- moose.useClock( 1, '/network', 'process' )
- moose.useClock( 2, '/stats', 'process' )
- moose.useClock( 3, '/plot', 'process' )
- moose.setClock( 0, dt )
- moose.setClock( 1, dt )
- moose.setClock( 2, dt )
- moose.setClock( 3, dt )
- moose.setClock( 9, dt )
- t1 = time.time()
- moose.reinit()
- print 'reinit time t = ', time.time() - t1
- network.vec.Vm = nprand.rand( size ) * Vmax
- print 'setting Vm , t = ', time.time() - t1
- t1 = time.time()
- print 'starting'
- moose.start(runsteps * dt)
- print 'runtime, t = ', time.time() - t1
- print network.vec.Vm[99:103], network.vec.Vm[900:903]
+ #moose.useClock( 0, '/network/syns,/network', 'process' )
+ moose.useClock( 0, '/network/syns', 'process' )
+ moose.useClock( 1, '/network', 'process' )
+ moose.useClock( 2, '/stats', 'process' )
+ moose.useClock( 3, '/plot', 'process' )
+ moose.setClock( 0, dt )
+ moose.setClock( 1, dt )
+ moose.setClock( 2, dt )
+ moose.setClock( 3, dt )
+ moose.setClock( 9, dt )
+ t1 = time.time()
+ moose.reinit()
+ print(('reinit time t = ', time.time() - t1))
+ network.vec.Vm = nprand.rand( size ) * Vmax
+ print(('setting Vm , t = ', time.time() - t1))
+ t1 = time.time()
+ print('starting')
+ moose.start(runsteps * dt)
+ print(('runtime, t = ', time.time() - t1))
+ print((network.vec.Vm[99:103], network.vec.Vm[900:903]))
t = [i * dt for i in range( plots.vec[0].vector.size )]
i = 0
for p in plots.vec:
diff --git a/moose-examples/snippets/rxdFuncDiffusion.py b/moose-examples/snippets/rxdFuncDiffusion.py
index 142341dc321d79d7f99efd199643d38337b47629..b33983677d70756d28539bab3e3590e83c8f90b7 100644
--- a/moose-examples/snippets/rxdFuncDiffusion.py
+++ b/moose-examples/snippets/rxdFuncDiffusion.py
@@ -1,9 +1,12 @@
+import sys
import numpy
import pylab
import moose
import time
import sys
+print(('[DEBUG] Using moose from %s' % moose.__file__))
+
'''
This example implements a reaction-diffusion like system which is
bistable and propagates losslessly. It is based on the NEURON example
@@ -58,8 +61,9 @@ t1 = time.time()
for t in range( 0, runtime-1, updateDt ):
moose.start( updateDt )
plt = pylab.plot( x, c.vec.n, label='t = '+str(t + updateDt) )
+print(("Time = %f " % (time.time() - t1)))
-print("Time = %s " % ( time.time() - t1) )
+print(("Time = %s " % ( time.time() - t1) ))
pylab.ylim( 0, 1.05 )
pylab.legend()
pylab.show( )
diff --git a/moose-examples/snippets/rxdFuncDiffusionStoch.py b/moose-examples/snippets/rxdFuncDiffusionStoch.py
index 64883f0c05646623e9a9c6f1a8af049bcc8ff1df..7b2894759267a5252ca7c981c6a1449fb0ffb323 100644
--- a/moose-examples/snippets/rxdFuncDiffusionStoch.py
+++ b/moose-examples/snippets/rxdFuncDiffusionStoch.py
@@ -55,7 +55,7 @@ c.vec.nInit = [ 100 for q in x ]
# Run and plot it.
moose.reinit()
-print dir(compt)
+print((dir(compt)))
updateDt = 50
runtime = updateDt * 4
plt = pylab.plot( x, c.vec.n, label='t = 0 ')
@@ -63,7 +63,7 @@ t1 = time.time()
for t in range( 0, runtime-1, updateDt ):
moose.start( updateDt )
plt = pylab.plot( x, c.vec.n, label='t = '+str(t + updateDt) )
-print "Time = ", time.time() - t1
+print(("Time = ", time.time() - t1))
pylab.ylim( 0, 105 )
pylab.legend()
diff --git a/moose-examples/snippets/rxdReacDiffusion.py b/moose-examples/snippets/rxdReacDiffusion.py
index b6b1adaf167f0e4ef07c00264dc186a67ff493e3..d462b768796533216394738315ab20213dfe306b 100644
--- a/moose-examples/snippets/rxdReacDiffusion.py
+++ b/moose-examples/snippets/rxdReacDiffusion.py
@@ -71,7 +71,7 @@ t1 = time.time()
for t in range( 0, runtime-1, updateDt ):
moose.start( updateDt )
plt = pylab.plot( x, c.vec.n, label='t = '+str(t + updateDt) )
-print "Time = ", time.time() - t1
+print(("Time = ", time.time() - t1))
pylab.ylim( 0, 1.05 )
pylab.legend()
diff --git a/moose-examples/snippets/rxdSpineSize.py b/moose-examples/snippets/rxdSpineSize.py
index 1d071aba3aceba2f52303e4404d90aea61aaf852..544adc56cca8b4a302b2457358323c1e384fac28 100644
--- a/moose-examples/snippets/rxdSpineSize.py
+++ b/moose-examples/snippets/rxdSpineSize.py
@@ -54,7 +54,7 @@ def makeChemProto( name ):
chem = moose.Neutral( '/library/' + name )
comptVol = diffLen * dendDia * dendDia * PI / 4.0
for i in ( ['dend', comptVol], ['spine', 1e-19], ['psd', 1e-20] ):
- print 'making ', i
+ print(('making ', i))
compt = moose.CubeMesh( chem.path + '/' + i[0] )
compt.volume = i[1]
#x = moose.Pool( compt.path + '/x' )
@@ -72,7 +72,7 @@ def makeChemProto( name ):
x.diffConst = diffConst
func = moose.Function( x.path + '/func' )
func.expr = "-x0 * (0.3 - " + nstr + " * x0) * ( 1 - " + nstr + " * x0)"
- print func.expr
+ print((func.expr))
func.x.num = 1
moose.connect( x, 'nOut', func.x[0], 'input' )
moose.connect( func, 'valueOut', x, 'increment' )
@@ -264,9 +264,9 @@ def create_viewer(path, moose_dendrite, dendZ, diaTab, psdZ):
view.stop()
viewer = moogli.Viewer("Viewer")
- viewer.attach_shapes(network.shapes.values())
+ viewer.attach_shapes(list(network.shapes.values()))
viewer.detach_shape(dendrite)
- viewer.attach_shapes(chem_compt_group.shapes.values())
+ viewer.attach_shapes(list(chem_compt_group.shapes.values()))
view = moogli.View("main-view",
prelude=prelude,
diff --git a/moose-examples/snippets/savemodel.py b/moose-examples/snippets/savemodel.py
index bf29b914d6a3c8f7c2cdcd7f4929e9b7f21f9ef3..3c296bba76a7407a356b3c4ec5489ce1027bf102 100644
--- a/moose-examples/snippets/savemodel.py
+++ b/moose-examples/snippets/savemodel.py
@@ -49,13 +49,20 @@ into Moose using "loadModel" function and using "saveModel" function one can
save the model back to Genesis format
"""
+import os
import sys
-#sys.path.append('../../python')
import moose
from moose.genesis import *
+cwd = os.path.dirname( os.path.realpath( __file__ ) )
+
if __name__ == '__main__':
- """ The script demonstates to convert Chemical (Genesis) file back to Genesis file using moose """
- model = moose.loadModel('../genesis/reaction.g', '/model')
- written = write('/model', 'testsave.g')
- print written
+ """
+ The script demonstates to convert Chemical (Genesis) file back to Genesis
+ file using moose
+ """
+ model = moose.loadModel(
+ os.path.join( cwd, '../genesis/reaction.g' ), '/model'
+ )
+ written = mooseWriteKkit('/model', 'testsave.g')
+ print( written )
diff --git a/moose-examples/snippets/scaleVolumes.py b/moose-examples/snippets/scaleVolumes.py
index 6a69da65d8c56332801060119e56aac0b08740af..5591d205abc6983de1fe543cdbf65426db78480b 100644
--- a/moose-examples/snippets/scaleVolumes.py
+++ b/moose-examples/snippets/scaleVolumes.py
@@ -13,74 +13,74 @@ import numpy
import moose
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compartment = moose.CubeMesh( '/model/compartment' )
- compartment.volume = 1e-20
- # the mesh is created automatically by the compartment
- mesh = moose.element( '/model/compartment/mesh' )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- c = moose.Pool( '/model/compartment/c' )
- enz1 = moose.Enz( '/model/compartment/b/enz1' )
- enz2 = moose.Enz( '/model/compartment/c/enz2' )
- cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
- cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
- reac = moose.Reac( '/model/compartment/reac' )
-
- # connect them up for reactions
- moose.connect( enz1, 'sub', a, 'reac' )
- moose.connect( enz1, 'prd', b, 'reac' )
- moose.connect( enz1, 'enz', b, 'reac' )
- moose.connect( enz1, 'cplx', cplx1, 'reac' )
-
- moose.connect( enz2, 'sub', b, 'reac' )
- moose.connect( enz2, 'prd', a, 'reac' )
- moose.connect( enz2, 'enz', c, 'reac' )
- moose.connect( enz2, 'cplx', cplx2, 'reac' )
-
- moose.connect( reac, 'sub', a, 'reac' )
- moose.connect( reac, 'prd', b, 'reac' )
-
- # connect them up to the compartment for volumes
- #for x in ( a, b, c, cplx1, cplx2 ):
- # moose.connect( x, 'mesh', mesh, 'mesh' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 0
- c.concInit = 0.01
- enz1.kcat = 0.4
- enz1.Km = 4
- enz2.kcat = 0.6
- enz2.Km = 0.01
- reac.Kf = 0.001
- reac.Kb = 0.01
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2( '/model/graphs/concA' )
- outputB = moose.Table2( '/model/graphs/concB' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compartment = moose.CubeMesh( '/model/compartment' )
+ compartment.volume = 1e-20
+ # the mesh is created automatically by the compartment
+ mesh = moose.element( '/model/compartment/mesh' )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ c = moose.Pool( '/model/compartment/c' )
+ enz1 = moose.Enz( '/model/compartment/b/enz1' )
+ enz2 = moose.Enz( '/model/compartment/c/enz2' )
+ cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
+ cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
+ reac = moose.Reac( '/model/compartment/reac' )
+
+ # connect them up for reactions
+ moose.connect( enz1, 'sub', a, 'reac' )
+ moose.connect( enz1, 'prd', b, 'reac' )
+ moose.connect( enz1, 'enz', b, 'reac' )
+ moose.connect( enz1, 'cplx', cplx1, 'reac' )
+
+ moose.connect( enz2, 'sub', b, 'reac' )
+ moose.connect( enz2, 'prd', a, 'reac' )
+ moose.connect( enz2, 'enz', c, 'reac' )
+ moose.connect( enz2, 'cplx', cplx2, 'reac' )
+
+ moose.connect( reac, 'sub', a, 'reac' )
+ moose.connect( reac, 'prd', b, 'reac' )
+
+ # connect them up to the compartment for volumes
+ #for x in ( a, b, c, cplx1, cplx2 ):
+ # moose.connect( x, 'mesh', mesh, 'mesh' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 0
+ c.concInit = 0.01
+ enz1.kcat = 0.4
+ enz1.Km = 4
+ enz2.kcat = 0.6
+ enz2.Km = 0.01
+ reac.Kf = 0.001
+ reac.Kb = 0.01
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2( '/model/graphs/concA' )
+ outputB = moose.Table2( '/model/graphs/concB' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
'''
- # Schedule the whole lot
- moose.setClock( 4, 0.01 ) # for the computational objects
- moose.setClock( 8, 1.0 ) # for the plots
- # The wildcard uses # for single level, and ## for recursive.
- moose.useClock( 4, '/model/compartment/##', 'process' )
- moose.useClock( 8, '/model/graphs/#', 'process' )
+ # Schedule the whole lot
+ moose.setClock( 4, 0.01 ) # for the computational objects
+ moose.setClock( 8, 1.0 ) # for the plots
+ # The wildcard uses # for single level, and ## for recursive.
+ moose.useClock( 4, '/model/compartment/##', 'process' )
+ moose.useClock( 8, '/model/graphs/#', 'process' )
'''
def displayPlots():
- for x in moose.wildcardFind( '/model/graphs/conc#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
+ for x in moose.wildcardFind( '/model/graphs/conc#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
def main():
@@ -128,7 +128,7 @@ def main():
for vol in ( 1e-19, 1e-20, 1e-21, 3e-22, 1e-22, 3e-23, 1e-23 ):
# Set the volume
compt.volume = vol
- print 'vol = ', vol, ', a.concInit = ', a.concInit, ', a.nInit = ', a.nInit
+ print(('vol = ', vol, ', a.concInit = ', a.concInit, ', a.nInit = ', a.nInit))
moose.reinit()
moose.start( 100.0 ) # Run the model for 100 seconds.
@@ -149,11 +149,11 @@ def main():
# Iterate through all plots, dump their contents to data.plot.
displayPlots()
pylab.show( block=False )
- print 'vol = ', vol, 'hit enter to go to next plot'
- raw_input()
+ print(('vol = ', vol, 'hit enter to go to next plot'))
+ eval(input())
quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/scriptGssaSolver.py b/moose-examples/snippets/scriptGssaSolver.py
index 94f10aed79b95463a7f9e8889294727b6765b6d2..0bf5c4c09ee36b88c612ffca23946d905446fcc7 100644
--- a/moose-examples/snippets/scriptGssaSolver.py
+++ b/moose-examples/snippets/scriptGssaSolver.py
@@ -21,103 +21,103 @@ import numpy
import moose
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compartment = moose.CubeMesh( '/model/compartment' )
- compartment.volume = 1e-20
- # the mesh is created automatically by the compartment
- mesh = moose.element( '/model/compartment/mesh' )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- c = moose.Pool( '/model/compartment/c' )
- enz1 = moose.Enz( '/model/compartment/b/enz1' )
- enz2 = moose.Enz( '/model/compartment/c/enz2' )
- cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
- cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
- reac = moose.Reac( '/model/compartment/reac' )
-
- # connect them up for reactions
- moose.connect( enz1, 'sub', a, 'reac' )
- moose.connect( enz1, 'prd', b, 'reac' )
- moose.connect( enz1, 'enz', b, 'reac' )
- moose.connect( enz1, 'cplx', cplx1, 'reac' )
-
- moose.connect( enz2, 'sub', b, 'reac' )
- moose.connect( enz2, 'prd', a, 'reac' )
- moose.connect( enz2, 'enz', c, 'reac' )
- moose.connect( enz2, 'cplx', cplx2, 'reac' )
-
- moose.connect( reac, 'sub', a, 'reac' )
- moose.connect( reac, 'prd', b, 'reac' )
-
- # connect them up to the compartment for volumes
- #for x in ( a, b, c, cplx1, cplx2 ):
- # moose.connect( x, 'mesh', mesh, 'mesh' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 0
- c.concInit = 0.01
- enz1.kcat = 0.4
- enz1.Km = 4
- enz2.kcat = 0.6
- enz2.Km = 0.01
- reac.Kf = 0.001
- reac.Kb = 0.01
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/concA' )
- outputB = moose.Table2 ( '/model/graphs/concB' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compartment = moose.CubeMesh( '/model/compartment' )
+ compartment.volume = 1e-20
+ # the mesh is created automatically by the compartment
+ mesh = moose.element( '/model/compartment/mesh' )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ c = moose.Pool( '/model/compartment/c' )
+ enz1 = moose.Enz( '/model/compartment/b/enz1' )
+ enz2 = moose.Enz( '/model/compartment/c/enz2' )
+ cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
+ cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
+ reac = moose.Reac( '/model/compartment/reac' )
+
+ # connect them up for reactions
+ moose.connect( enz1, 'sub', a, 'reac' )
+ moose.connect( enz1, 'prd', b, 'reac' )
+ moose.connect( enz1, 'enz', b, 'reac' )
+ moose.connect( enz1, 'cplx', cplx1, 'reac' )
+
+ moose.connect( enz2, 'sub', b, 'reac' )
+ moose.connect( enz2, 'prd', a, 'reac' )
+ moose.connect( enz2, 'enz', c, 'reac' )
+ moose.connect( enz2, 'cplx', cplx2, 'reac' )
+
+ moose.connect( reac, 'sub', a, 'reac' )
+ moose.connect( reac, 'prd', b, 'reac' )
+
+ # connect them up to the compartment for volumes
+ #for x in ( a, b, c, cplx1, cplx2 ):
+ # moose.connect( x, 'mesh', mesh, 'mesh' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 0
+ c.concInit = 0.01
+ enz1.kcat = 0.4
+ enz1.Km = 4
+ enz2.kcat = 0.6
+ enz2.Km = 0.01
+ reac.Kf = 0.001
+ reac.Kb = 0.01
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/concA' )
+ outputB = moose.Table2 ( '/model/graphs/concB' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
def displayPlots():
- for x in moose.wildcardFind( '/model/graphs/conc#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ for x in moose.wildcardFind( '/model/graphs/conc#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
def main():
- makeModel()
- gsolve = moose.Gsolve( '/model/compartment/gsolve' )
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = moose.element( '/model/compartment' )
- stoich.ksolve = gsolve
- stoich.path = "/model/compartment/##"
- #solver.method = "rk5"
- #mesh = moose.element( "/model/compartment/mesh" )
- #moose.connect( mesh, "remesh", solver, "remesh" )
- moose.setClock( 5, 1.0 ) # clock for the solver
- moose.useClock( 5, '/model/compartment/gsolve', 'process' )
-
- moose.reinit()
- moose.start( 100.0 ) # Run the model for 100 seconds.
-
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
-
- # move most molecules over to bgsolve
- b.conc = b.conc + a.conc * 0.9
- a.conc = a.conc * 0.1
- moose.start( 100.0 ) # Run the model for 100 seconds.
-
- # move most molecules back to a
- a.conc = a.conc + b.conc * 0.99
- b.conc = b.conc * 0.01
- moose.start( 100.0 ) # Run the model for 100 seconds.
-
- # Iterate through all plots, dump their contents to data.plot.
- displayPlots()
-
- quit()
+ makeModel()
+ gsolve = moose.Gsolve( '/model/compartment/gsolve' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = moose.element( '/model/compartment' )
+ stoich.ksolve = gsolve
+ stoich.path = "/model/compartment/##"
+ #solver.method = "rk5"
+ #mesh = moose.element( "/model/compartment/mesh" )
+ #moose.connect( mesh, "remesh", solver, "remesh" )
+ moose.setClock( 5, 1.0 ) # clock for the solver
+ moose.useClock( 5, '/model/compartment/gsolve', 'process' )
+
+ moose.reinit()
+ moose.start( 100.0 ) # Run the model for 100 seconds.
+
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
+
+ # move most molecules over to bgsolve
+ b.conc = b.conc + a.conc * 0.9
+ a.conc = a.conc * 0.1
+ moose.start( 100.0 ) # Run the model for 100 seconds.
+
+ # move most molecules back to a
+ a.conc = a.conc + b.conc * 0.99
+ b.conc = b.conc * 0.01
+ moose.start( 100.0 ) # Run the model for 100 seconds.
+
+ # Iterate through all plots, dump their contents to data.plot.
+ displayPlots()
+
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/scriptKineticModel.py b/moose-examples/snippets/scriptKineticModel.py
index 453e446ff6a66342212495aa688fdc05e22123a4..392027155e7ebc37730c4364b4a14844493534a9 100644
--- a/moose-examples/snippets/scriptKineticModel.py
+++ b/moose-examples/snippets/scriptKineticModel.py
@@ -6,115 +6,112 @@
## GNU Lesser General Public License version 2.1
## See the file COPYING.LIB for the full notice.
#########################################################################
-
-"""
-This example illustrates how to define a kinetic model using the
-scripting interface. Normally one uses standard model formats like
-SBML or kkit to concisely define kinetic models, but in some cases one
-would like to modify the model through the script.
-This example creates a bistable model having two enzymes and a reaction.
-One of the enzymes is autocatalytic.
-The model is set up to run using default Exponential Euler integration.
-The snippet scriptKineticSolver.py uses the much better GSL
-Runge-Kutta-Fehlberg integration scheme on this same model.
-"""
-
import math
import pylab
import numpy
import moose
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compartment = moose.CubeMesh( '/model/compartment' )
- compartment.volume = 1e-15
- # the mesh is created automatically by the compartment
- moose.le( '/model/compartment' )
- mesh = moose.element( '/model/compartment/mesh' )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- c = moose.Pool( '/model/compartment/c' )
- enz1 = moose.Enz( '/model/compartment/b/enz1' )
- enz2 = moose.Enz( '/model/compartment/c/enz2' )
- cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
- cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
- reac = moose.Reac( '/model/compartment/reac' )
-
- # connect them up for reactions
- moose.connect( enz1, 'sub', a, 'reac' )
- moose.connect( enz1, 'prd', b, 'reac' )
- moose.connect( enz1, 'enz', b, 'reac' )
- moose.connect( enz1, 'cplx', cplx1, 'reac' )
-
- moose.connect( enz2, 'sub', b, 'reac' )
- moose.connect( enz2, 'prd', a, 'reac' )
- moose.connect( enz2, 'enz', c, 'reac' )
- moose.connect( enz2, 'cplx', cplx2, 'reac' )
-
- moose.connect( reac, 'sub', a, 'reac' )
- moose.connect( reac, 'prd', b, 'reac' )
-
- # connect them up to the compartment for volumes
- #for x in ( a, b, c, cplx1, cplx2 ):
- # moose.connect( x, 'mesh', mesh, 'mesh' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 0
- c.concInit = 0.01
- enz1.kcat = 0.4
- enz1.Km = 4
- enz2.kcat = 0.6
- enz2.Km = 0.01
- reac.Kf = 0.001
- reac.Kb = 0.01
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/concA' )
- outputB = moose.Table2 ( '/model/graphs/concB' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
-
- # We need a finer timestep than the default 0.1 seconds,
- # in order to get numerical accuracy.
- for i in range (11, 15 ):
- moose.setClock( i, 0.001 ) # for computational objects
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compartment = moose.CubeMesh( '/model/compartment' )
+ compartment.volume = 1e-15
+ # the mesh is created automatically by the compartment
+ moose.le( '/model/compartment' )
+ mesh = moose.element( '/model/compartment/mesh' )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ c = moose.Pool( '/model/compartment/c' )
+ enz1 = moose.Enz( '/model/compartment/b/enz1' )
+ enz2 = moose.Enz( '/model/compartment/c/enz2' )
+ cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
+ cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
+ reac = moose.Reac( '/model/compartment/reac' )
+
+ # connect them up for reactions
+ moose.connect( enz1, 'sub', a, 'reac' )
+ moose.connect( enz1, 'prd', b, 'reac' )
+ moose.connect( enz1, 'enz', b, 'reac' )
+ moose.connect( enz1, 'cplx', cplx1, 'reac' )
+
+ moose.connect( enz2, 'sub', b, 'reac' )
+ moose.connect( enz2, 'prd', a, 'reac' )
+ moose.connect( enz2, 'enz', c, 'reac' )
+ moose.connect( enz2, 'cplx', cplx2, 'reac' )
+
+ moose.connect( reac, 'sub', a, 'reac' )
+ moose.connect( reac, 'prd', b, 'reac' )
+
+ # connect them up to the compartment for volumes
+ #for x in ( a, b, c, cplx1, cplx2 ):
+ # moose.connect( x, 'mesh', mesh, 'mesh' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 0
+ c.concInit = 0.01
+ enz1.kcat = 0.4
+ enz1.Km = 4
+ enz2.kcat = 0.6
+ enz2.Km = 0.01
+ reac.Kf = 0.001
+ reac.Kb = 0.01
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/concA' )
+ outputB = moose.Table2 ( '/model/graphs/concB' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
+
+ # We need a finer timestep than the default 0.1 seconds,
+ # in order to get numerical accuracy.
+ for i in range (11, 15 ):
+ moose.setClock( i, 0.001 ) # for computational objects
def main():
- makeModel()
-
- moose.reinit()
- moose.start( 100.0 ) # Run the model for 100 seconds.
-
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
-
- # move most molecules over to b
- b.conc = b.conc + a.conc * 0.9
- a.conc = a.conc * 0.1
- moose.start( 100.0 ) # Run the model for 100 seconds.
-
- # move most molecules back to a
- a.conc = a.conc + b.conc * 0.99
- b.conc = b.conc * 0.01
- moose.start( 100.0 ) # Run the model for 100 seconds.
-
- # Iterate through all plots, dump their contents to data.plot.
- for x in moose.wildcardFind( '/model/graphs/conc#' ):
- #x.xplot( 'scriptKineticModel.plot', x.name )
- t = numpy.arange( 0, x.vector.size, 1 ) # sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
-
- quit()
+ """
+ This example illustrates how to define a kinetic model using the
+ scripting interface. Normally one uses standard model formats like
+ SBML or kkit to concisely define kinetic models, but in some cases one
+ would like to modify the model through the script.
+ This example creates a bistable model having two enzymes and a reaction.
+ One of the enzymes is autocatalytic.
+ The model is set up to run using default Exponential Euler integration.
+ The snippet scriptKineticSolver.py uses the much better GSL
+ Runge-Kutta-Fehlberg integration scheme on this same model.
+ """
+ makeModel()
+ moose.reinit()
+ moose.start( 100.0 ) # Run the model for 100 seconds.
+
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
+
+ # move most molecules over to b
+ b.conc = b.conc + a.conc * 0.9
+ a.conc = a.conc * 0.1
+ moose.start( 100.0 ) # Run the model for 100 seconds.
+
+ # move most molecules back to a
+ a.conc = a.conc + b.conc * 0.99
+ b.conc = b.conc * 0.01
+ moose.start( 100.0 ) # Run the model for 100 seconds.
+
+ # Iterate through all plots, dump their contents to data.plot.
+ for x in moose.wildcardFind( '/model/graphs/conc#' ):
+ #x.xplot( 'scriptKineticModel.plot', x.name )
+ t = numpy.arange( 0, x.vector.size, 1 ) # sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
+
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/scriptKineticSolver.py b/moose-examples/snippets/scriptKineticSolver.py
index 977a099fb359c00df20b2b83d54c656dcf5446f0..3660afea87cad8e11b62ec4c53ad19ad70fca89b 100644
--- a/moose-examples/snippets/scriptKineticSolver.py
+++ b/moose-examples/snippets/scriptKineticSolver.py
@@ -21,104 +21,104 @@ import numpy
import moose
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compartment = moose.CubeMesh( '/model/compartment' )
- compartment.volume = 1e-15
- # the mesh is created automatically by the compartment
- mesh = moose.element( '/model/compartment/mesh' )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- c = moose.Pool( '/model/compartment/c' )
- enz1 = moose.Enz( '/model/compartment/b/enz1' )
- enz2 = moose.Enz( '/model/compartment/c/enz2' )
- cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
- cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
- reac = moose.Reac( '/model/compartment/reac' )
-
- # connect them up for reactions
- moose.connect( enz1, 'sub', a, 'reac' )
- moose.connect( enz1, 'prd', b, 'reac' )
- moose.connect( enz1, 'enz', b, 'reac' )
- moose.connect( enz1, 'cplx', cplx1, 'reac' )
-
- moose.connect( enz2, 'sub', b, 'reac' )
- moose.connect( enz2, 'prd', a, 'reac' )
- moose.connect( enz2, 'enz', c, 'reac' )
- moose.connect( enz2, 'cplx', cplx2, 'reac' )
-
- moose.connect( reac, 'sub', a, 'reac' )
- moose.connect( reac, 'prd', b, 'reac' )
-
- # connect them up to the compartment for volumes
- #for x in ( a, b, c, cplx1, cplx2 ):
- # moose.connect( x, 'mesh', mesh, 'mesh' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 0
- c.concInit = 0.01
- enz1.kcat = 0.4
- enz1.Km = 4
- enz2.kcat = 0.6
- enz2.Km = 0.01
- reac.Kf = 0.001
- reac.Kb = 0.01
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table2 ( '/model/graphs/concA' )
- outputB = moose.Table2 ( '/model/graphs/concB' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compartment = moose.CubeMesh( '/model/compartment' )
+ compartment.volume = 1e-15
+ # the mesh is created automatically by the compartment
+ mesh = moose.element( '/model/compartment/mesh' )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ c = moose.Pool( '/model/compartment/c' )
+ enz1 = moose.Enz( '/model/compartment/b/enz1' )
+ enz2 = moose.Enz( '/model/compartment/c/enz2' )
+ cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
+ cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
+ reac = moose.Reac( '/model/compartment/reac' )
+
+ # connect them up for reactions
+ moose.connect( enz1, 'sub', a, 'reac' )
+ moose.connect( enz1, 'prd', b, 'reac' )
+ moose.connect( enz1, 'enz', b, 'reac' )
+ moose.connect( enz1, 'cplx', cplx1, 'reac' )
+
+ moose.connect( enz2, 'sub', b, 'reac' )
+ moose.connect( enz2, 'prd', a, 'reac' )
+ moose.connect( enz2, 'enz', c, 'reac' )
+ moose.connect( enz2, 'cplx', cplx2, 'reac' )
+
+ moose.connect( reac, 'sub', a, 'reac' )
+ moose.connect( reac, 'prd', b, 'reac' )
+
+ # connect them up to the compartment for volumes
+ #for x in ( a, b, c, cplx1, cplx2 ):
+ # moose.connect( x, 'mesh', mesh, 'mesh' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 0
+ c.concInit = 0.01
+ enz1.kcat = 0.4
+ enz1.Km = 4
+ enz2.kcat = 0.6
+ enz2.Km = 0.01
+ reac.Kf = 0.001
+ reac.Kb = 0.01
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table2 ( '/model/graphs/concA' )
+ outputB = moose.Table2 ( '/model/graphs/concB' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
def displayPlots():
- for x in moose.wildcardFind( '/model/graphs/conc#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ for x in moose.wildcardFind( '/model/graphs/conc#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
def main():
- makeModel()
- ksolve = moose.Ksolve( '/model/compartment/ksolve' )
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = moose.element( '/model/compartment' )
- stoich.ksolve = ksolve
- stoich.path = "/model/compartment/##"
- #solver.method = "rk5"
- #mesh = moose.element( "/model/compartment/mesh" )
- #moose.connect( mesh, "remesh", solver, "remesh" )
+ makeModel()
+ ksolve = moose.Ksolve( '/model/compartment/ksolve' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = moose.element( '/model/compartment' )
+ stoich.ksolve = ksolve
+ stoich.path = "/model/compartment/##"
+ #solver.method = "rk5"
+ #mesh = moose.element( "/model/compartment/mesh" )
+ #moose.connect( mesh, "remesh", solver, "remesh" )
'''
- moose.setClock( 5, 1.0 ) # clock for the solver
- moose.useClock( 5, '/model/compartment/ksolve', 'process' )
+ moose.setClock( 5, 1.0 ) # clock for the solver
+ moose.useClock( 5, '/model/compartment/ksolve', 'process' )
'''
- moose.reinit()
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ moose.reinit()
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
- # move most molecules over to b
- b.conc = b.conc + a.conc * 0.9
- a.conc = a.conc * 0.1
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules over to b
+ b.conc = b.conc + a.conc * 0.9
+ a.conc = a.conc * 0.1
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # move most molecules back to a
- a.conc = a.conc + b.conc * 0.99
- b.conc = b.conc * 0.01
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules back to a
+ a.conc = a.conc + b.conc * 0.99
+ b.conc = b.conc * 0.01
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # Iterate through all plots, dump their contents to data.plot.
- displayPlots()
+ # Iterate through all plots, dump their contents to data.plot.
+ displayPlots()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/showclocks.py b/moose-examples/snippets/showclocks.py
index 3ebb3f7cfe860fb6d2139112fe71cbcfa55319ab..1bcd23ee77622767621f836ff562df790406d7e3 100644
--- a/moose-examples/snippets/showclocks.py
+++ b/moose-examples/snippets/showclocks.py
@@ -35,37 +35,37 @@ moose.useClock(0, '/##[ISA=Compartment]', 'init')
moose.useClock(1, '/##[ISA=Compartment]', 'process')
# List the ticks connected to an element.
-print 'Ticks connected to `process` method of', comp.path
+print(('Ticks connected to `process` method of', comp.path))
for tick in comp.neighbors['process']:
- print ' ->',tick.path
+ print((' ->',tick.path))
# Different ticks can be connected to different fields.
-print 'Ticks connected to `init` method of', comp.path
+print(('Ticks connected to `init` method of', comp.path))
for tick in comp.neighbors['init']:
- print ' ->',tick.path
+ print((' ->',tick.path))
# View the scheduled elements using the tick nos.
t = moose.element('/clock')
-print 'Elements on tick 0'
+print('Elements on tick 0')
for e in t.neighbors['proc0']:
- print ' ->', e.path
-print 'Elements on tick 1'
+ print((' ->', e.path))
+print('Elements on tick 1')
for e in t.neighbors['proc1']:
- print ' ->', e.path
+ print((' ->', e.path))
ch = moose.HHChannel('/comp/chan')
moose.useClock(1, ch.path, 'process')
-print ch.path, 'has been scheduled'
-print 'Elements on tick 1'
+print((ch.path, 'has been scheduled'))
+print('Elements on tick 1')
for e in t.neighbors['proc1']:
- print ' ->', e.path
+ print((' ->', e.path))
# Go through elements by wildcard search and list the ticks connected.
# This can be slow when the model is too big.
for el in moose.wildcardFind('/##[ISA=Compartment]'):
- print 'Ticks connected to `process` method of', el.path
+ print(('Ticks connected to `process` method of', el.path))
for t in moose.element(el).neighbors['process']:
- print ' ->', t.path
+ print((' ->', t.path))
# <codecell>
diff --git a/moose-examples/snippets/showmsg.py b/moose-examples/snippets/showmsg.py
index 38535e69d499f8bcf0c3ffa088571258332e6a44..f981956acf360eeca4f73fbdaeb45561f640323f 100644
--- a/moose-examples/snippets/showmsg.py
+++ b/moose-examples/snippets/showmsg.py
@@ -14,9 +14,9 @@ mid = moose.connect(net, 'spikeOut', synapse, 'addSpike', 'Sparse') # This creat
msg = moose.element(mid)
msg.setRandomConnectivity(connectionProbability, 5)
for n in net.vec:
- print 'Messages from %s.spikeOut' % (n.path)
+ print(('Messages from %s.spikeOut' % (n.path)))
node = moose.element(n)
for dest, df in zip(node.msgDests['spikeOut'], node.msgDestFunctions['spikeOut']):
- print '\t--> %s.%s' % (dest.path, df)
+ print(('\t--> %s.%s' % (dest.path, df)))
diff --git a/moose-examples/snippets/singlemsgcross.py b/moose-examples/snippets/singlemsgcross.py
index 7a589294f13c28c6f36afa6fc44da15593c34dfd..ee0a67a1795fdefe4b75fa7ab62b672b45168691 100644
--- a/moose-examples/snippets/singlemsgcross.py
+++ b/moose-examples/snippets/singlemsgcross.py
@@ -74,17 +74,17 @@ def test_crossing_single():
tab = moose.Table('table', size)
moose.connect(tab.vec[0], 'requestOut', pg.vec[1], 'getOutputValue', 'Single')
moose.connect(tab.vec[1], 'requestOut', pg.vec[0], 'getOutputValue', 'Single')
- print 'Neighbors:'
+ print('Neighbors:')
for t in tab.vec:
- print t.path
+ print((t.path))
for n in moose.element(t).neighbors['requestOut']:
- print 'requestOut <-', n.path
+ print(('requestOut <-', n.path))
moose.setClock(0, 0.1)
moose.useClock(0, '/##', 'process')
moose.start(5)
for ii in tab.vec:
t = moose.Table(ii).vector
- print len(t)
+ print((len(t)))
pylab.plot(t)
pylab.show()
diff --git a/moose-examples/snippets/startstop.py b/moose-examples/snippets/startstop.py
index 11d98ea2d5cb00af3bead961e3a055f01106619a..fd66b4f904fedbb07dd357b94a1c020bc8f1b76f 100644
--- a/moose-examples/snippets/startstop.py
+++ b/moose-examples/snippets/startstop.py
@@ -77,11 +77,11 @@ def main():
moose.setClock( table.tick, dt )
moose.reinit()
clock = moose.element('/clock')
- print dt
- print 'dt = ', dt, ', Total simulation time = ', simtime
- print 'Running simulation for', simtime, 'seconds'
+ print(dt)
+ print(('dt = ', dt, ', Total simulation time = ', simtime))
+ print(('Running simulation for', simtime, 'seconds'))
moose.start( simtime )
- print 'Simulator time:', clock.currentTime
+ print(('Simulator time:', clock.currentTime))
# Here we change the pulse delay and then run again.
pulse.delay[0] = 1.0
moose.start( simtime )
@@ -93,13 +93,13 @@ def main():
# Here is yet another way to change clocks used by the table
moose.useClock( 9, '/model/pulse/tab', 'process' )
- print table.tick
+ print((table.tick))
moose.setClock( 9, dt / 2.0 )
moose.start( simtime )
# Finally, here we change the pulse delay to 1 second and run again.
- print 'Simulator time at end of simulation', clock.currentTime
+ print(('Simulator time at end of simulation', clock.currentTime))
pylab.plot(pylab.linspace(0, clock.currentTime, len(table.vector)), table.vector)
pylab.show()
diff --git a/moose-examples/snippets/stochasticLotkaVolterra.py b/moose-examples/snippets/stochasticLotkaVolterra.py
index 59864005e6ff7720bd514d6e7fb14ebdab97fc35..e7bec53bea2a818ca8fa3571956026ee1a9b44fc 100644
--- a/moose-examples/snippets/stochasticLotkaVolterra.py
+++ b/moose-examples/snippets/stochasticLotkaVolterra.py
@@ -15,21 +15,21 @@ import moose
runtime = 138.0
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- harmonic = moose.CubeMesh( '/model/harmonic' )
- harmonic.volume = 1e-15
- lotka = moose.CubeMesh( '/model/lotka' )
- lotka.volume = 1e-15
-
- # create molecules and reactions
- x = moose.Pool( '/model/lotka/x' )
- y = moose.Pool( '/model/lotka/y' )
+ # create container for model
+ model = moose.Neutral( 'model' )
+ harmonic = moose.CubeMesh( '/model/harmonic' )
+ harmonic.volume = 1e-15
+ lotka = moose.CubeMesh( '/model/lotka' )
+ lotka.volume = 1e-15
+
+ # create molecules and reactions
+ x = moose.Pool( '/model/lotka/x' )
+ y = moose.Pool( '/model/lotka/y' )
z = moose.BufPool( '/model/lotka/z' ) # Dummy molecule.
xreac = moose.Reac( '/model/lotka/xreac' )
yreac = moose.Reac( '/model/lotka/yreac' )
- xrate = moose.Function( '/model/lotka/xreac/func' )
- yrate = moose.Function( '/model/lotka/yreac/func' )
+ xrate = moose.Function( '/model/lotka/xreac/func' )
+ yrate = moose.Function( '/model/lotka/yreac/func' )
# Parameters
alpha = 1.0
@@ -49,9 +49,9 @@ def makeModel():
xreac.Kb = 0
yreac.Kb = 0
- # connect them up for reactions
- moose.connect( y, 'nOut', xrate.x[0], 'input' )
- moose.connect( x, 'nOut', yrate.x[0], 'input' )
+ # connect them up for reactions
+ moose.connect( y, 'nOut', xrate.x[0], 'input' )
+ moose.connect( x, 'nOut', yrate.x[0], 'input' )
moose.connect( xrate, 'valueOut', xreac, 'setNumKf' )
moose.connect( yrate, 'valueOut', yreac, 'setNumKf' )
moose.connect( xreac, 'sub', x, 'reac' )
@@ -59,14 +59,14 @@ def makeModel():
moose.connect( yreac, 'sub', y, 'reac' )
moose.connect( yreac, 'prd', z, 'reac' )
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- xplot = moose.Table2 ( '/model/graphs/x' )
- yplot = moose.Table2 ( '/model/graphs/y' )
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ xplot = moose.Table2 ( '/model/graphs/x' )
+ yplot = moose.Table2 ( '/model/graphs/y' )
- # connect up the tables
- moose.connect( xplot, 'requestOut', x, 'getN' );
- moose.connect( yplot, 'requestOut', y, 'getN' );
+ # connect up the tables
+ moose.connect( xplot, 'requestOut', x, 'getN' );
+ moose.connect( yplot, 'requestOut', y, 'getN' );
def main():
"""
diff --git a/moose-examples/snippets/switchKineticSolvers.py b/moose-examples/snippets/switchKineticSolvers.py
index 5ef2c1d217e9db6984908853ff36d5ad5c33a6a4..4859293457e6bf6dbfda7e48620ff6bd939448ea 100644
--- a/moose-examples/snippets/switchKineticSolvers.py
+++ b/moose-examples/snippets/switchKineticSolvers.py
@@ -134,4 +134,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/synapse.py b/moose-examples/snippets/synapse.py
index aea6f372b2c2c8b19bdd7270ec60ad50cdb60a45..fb061e7e9b401c03335f337cd01f38cbcb74c156 100644
--- a/moose-examples/snippets/synapse.py
+++ b/moose-examples/snippets/synapse.py
@@ -43,6 +43,10 @@
#
# Code:
+
+from __future__ import print_function
+
+
import moose
def many_ematrix_to_one_element():
@@ -73,9 +77,9 @@ def many_ematrix_to_one_element():
# synchan.synapse[ii].delay = ii * 1e-3
# synchan.synapse[ii].weight = (ii+1) * 0.1
for sg in spikegens:
- print sg.path, '-->',
+ print(sg.path, '-->', end=' ')
for m in sg.msgOut:
- print moose.element(m).adjacent[sg].path
+ print(moose.element(m).adjacent[sg].path)
if __name__ == '__main__':
many_ematrix_to_one_element()
diff --git a/moose-examples/snippets/synapse_tutorial.py b/moose-examples/snippets/synapse_tutorial.py
index 98b6c02d15aefae0586e5996611f8fa75e6bb10e..b6e574b8c2687215d7f79575dd657587f56dd175 100644
--- a/moose-examples/snippets/synapse_tutorial.py
+++ b/moose-examples/snippets/synapse_tutorial.py
@@ -108,7 +108,7 @@ net.vec.Vm = [thresh / 2.0] * size
-print net.vec[1].Vm
+print((net.vec[1].Vm))
@@ -116,7 +116,7 @@ print net.vec[1].Vm
-print len(synh.synapse)
+print((len(synh.synapse)))
@@ -125,12 +125,12 @@ print len(synh.synapse)
synh.numSynapses = 3
-print len(synh.synapse)
+print((len(synh.synapse)))
synh.synapse.num = 4
-print len(synh.synapse)
+print((len(synh.synapse)))
@@ -138,9 +138,9 @@ print len(synh.synapse)
-print 'Before:', synh.synapse[0].delay
+print(('Before:', synh.synapse[0].delay))
synh.synapse[0].delay = 1.0
-print 'After:', synh.synapse[0].delay
+print(('After:', synh.synapse[0].delay))
@@ -149,7 +149,7 @@ print 'After:', synh.synapse[0].delay
synh.synapse.weight = [0.2] * len(synh.synapse)
-print synh.synapse.weight
+print((synh.synapse.weight))
@@ -177,8 +177,8 @@ for syn in synh.vec:
for syn in synh.vec[:5]:
- print 'Delays for synapses on ', syn.path, ':', syn.synapse.delay
- print 'Weights for synapses on ', syn.path, ':', syn.synapse.weight
+ print(('Delays for synapses on ', syn.path, ':', syn.synapse.delay))
+ print(('Weights for synapses on ', syn.path, ':', syn.synapse.weight))
diff --git a/moose-examples/snippets/testHsolve.py b/moose-examples/snippets/testHsolve.py
index 7eba6625d1073df02a960ccea335a1bfff8b6ec3..9f06c4cd75785f4d717741c90baa90f72d6a387b 100644
--- a/moose-examples/snippets/testHsolve.py
+++ b/moose-examples/snippets/testHsolve.py
@@ -103,7 +103,7 @@ def create_squid():
nachan.Xpower = 3
xGate = moose.HHGate(nachan.path + '/gateX')
xGate.setupAlpha(Na_m_params + [VDIVS, VMIN, VMAX])
- #This is important: one can run without it but the output will diverge.
+ #This is important: one can run without it but the output will diverge.
xGate.useInterpolation = 1
nachan.Ypower = 1
yGate = moose.HHGate(nachan.path + '/gateY')
@@ -295,7 +295,7 @@ def test_elec_alone():
hsolve.target = '/n/compt'
moose.le( '/n' )
for dt in ( 20e-6, 50e-6, 100e-6 ):
- print 'running at dt =', dt
+ print(('running at dt =', dt))
moose.setClock( 0, dt )
moose.setClock( 1, dt )
moose.setClock( 2, dt )
diff --git a/moose-examples/snippets/testRdesigneur.py b/moose-examples/snippets/testRdesigneur.py
index c77648137e1b4c552f2db70d656ead50986173b0..b38e0ccdaec6ab97c9747065b81d65ff6f280d7c 100644
--- a/moose-examples/snippets/testRdesigneur.py
+++ b/moose-examples/snippets/testRdesigneur.py
@@ -40,7 +40,7 @@ spineAngleDistrib = 2*numpy.pi
# Here we define a function that is used to make a cell prototype. Normally
# it would load in a model from a file.
def makeCellProto( name ):
- print 'IN: makeCellProto( ', name, ')'
+ print(('IN: makeCellProto( ', name, ')'))
elec = moose.Neuron( '/library/' + name )
ecompt = []
for i in range( numDendSegments ):
@@ -63,7 +63,7 @@ rd.makeCellProto = makeCellProto
def makeChemProto( name ):
chem = moose.Neutral( '/library/' + name )
for i in ( 'dend', 'spine', 'psd' ):
- print 'making ', i
+ print(('making ', i))
compt = moose.CubeMesh( chem.path + '/' + i )
compt.volume = 1e-18
ca = moose.Pool( compt.path + '/Ca' )
@@ -109,7 +109,7 @@ def addPlot( objpath, field, plot, tick ):
tab.tick = tick
return tab
else:
- print "failed in addPlot(", objpath, field, plot, tick, ")"
+ print(("failed in addPlot(", objpath, field, plot, tick, ")"))
return 0
def plotVm( plot, name ):
@@ -202,4 +202,4 @@ def getMidpts( compt ):
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/testSigNeur.py b/moose-examples/snippets/testSigNeur.py
index 679bb3123702c3d1869a3d25afad8967b2c6690e..b6695b7550ac3cdd7e85e430775c0144274a4a5c 100644
--- a/moose-examples/snippets/testSigNeur.py
+++ b/moose-examples/snippets/testSigNeur.py
@@ -404,8 +404,8 @@ def makeNeuroMeshModel():
assert( pdc == 5 )
#
# We need to use the spine solver as the master for the purposes of
- # these calculations. This will handle the diffusion calculations
- # between head and dendrite, and between head and PSD.
+ # these calculations. This will handle the diffusion calculations
+ # between head and dendrite, and between head and PSD.
smksolve.addJunction( nmksolve )
#print "spine: nv=", smksolve.numLocalVoxels, ", nav=", smksolve.numAllVoxels, smksolve.numVarPools, smksolve.numAllPools
smksolve.addJunction( pmksolve )
@@ -442,7 +442,7 @@ def makeNeuroMeshModel():
elecR = moose.element( path )
moose.connect( adaptGluR[i], 'outputSrc', elecR, 'setGbar', 'Single' )
#moose.connect( chemR, 'nOut', adaptGluR, 'input', 'OneToOne' )
- # Ksolve isn't sending nOut. Not good. So have to use requestOut.
+ # Ksolve isn't sending nOut. Not good. So have to use requestOut.
moose.connect( adaptGluR, 'requestOut', chemR, 'getN', 'OneToOne' )
adaptGluR.outputOffset = 1e-7 # pS
adaptGluR.scale = 1e-6 / 100 # from n to pS
diff --git a/moose-examples/snippets/testWigglySpines.py b/moose-examples/snippets/testWigglySpines.py
index 36a8294c14fb882e05b8553c3c9b9b643132c796..5adb7746ce5a1df5c76b23d11bde06026616139a 100644
--- a/moose-examples/snippets/testWigglySpines.py
+++ b/moose-examples/snippets/testWigglySpines.py
@@ -10,17 +10,22 @@
## a molecule that diffuses.
##################################################################
+from __future__ import print_function
+
import math
import pylab
import numpy
import matplotlib.pyplot as plt
import moose
import sys
-sys.path.append( '../util' )
import rdesigneur as rd
from PyQt4 import QtGui
import moogli
+import os
+scriptDir = os.path.dirname( os.path.realpath( __file__ ) )
+sys.path.append( os.path.join( scriptDir, '../util' ) )
+
PI = 3.141592653
ScalingForTesting = 10
RM = 1.0 / ScalingForTesting
@@ -46,7 +51,7 @@ def makeCellProto( name ):
def makeChemProto( name ):
chem = moose.Neutral( '/library/' + name )
for i in ( ['dend', 1e-18], ['spine', 1e-19], ['psd', 1e-20] ):
- print 'making ', i
+ print('making ', i)
compt = moose.CubeMesh( chem.path + '/' + i[0] )
compt.volume = i[1]
Ca = moose.Pool( compt.path + '/Ca' )
@@ -93,12 +98,12 @@ def p2(x):
'''
Print to 2 sig fig
'''
- print round(x, 1-int(numpy.floor(numpy.log10(x)))),
+ print(round(x, 1-int(numpy.floor(numpy.log10(x)))), end=' ')
def assertEq( a, b ):
- print '.',
+ print('.', end=' ')
if not( numpy.fabs( a-b) / (a+b) < 1e-10 ):
- print 'a!=b:', a, b
+ print('a!=b:', a, b)
assert(False)
def main():
@@ -151,8 +156,8 @@ def main():
head2 = moose.element( '/model/elec/head2' )
# Here we scale the spine head length while keeping all vols constt.
- print "Spine 0: longer head, same vol\nSpine 1: longer shaft"
- print "Spine 2: Bigger head, same diffScale\n"
+ print("Spine 0: longer head, same vol\nSpine 1: longer shaft")
+ print("Spine 2: Bigger head, same diffScale\n")
elecParms = [ (i.Rm, i.Cm, i.Ra) for i in ( head0, shaft1, head2) ]
chemParms = [ i.volume for i in ( caHead[0], caPsd[0], caHead[1], caPsd[1], caHead[2], caPsd[2] ) ]
@@ -170,7 +175,7 @@ def main():
elec.spine[2].headDiameter *= numpy.sqrt(2) # sqrt(2) x dia
hdia = elec.spine[2].headDiameter
- print "Checking scaling assertions: "
+ print("Checking scaling assertions: ")
assertEq( elecParms[0][0] * 0.5 , head0.Rm )
assertEq( elecParms[0][1] * 2 , head0.Cm )
assertEq( elecParms[0][2] * 16 , head0.Ra )
@@ -189,7 +194,7 @@ def main():
assertEq( elecParms[2][2] , head2.Ra )
assertEq( chemParms[4] * 4 , caHead[2].volume )
assertEq( chemParms[5] * 2 , caPsd[2].volume )
- print "\nAll assertions cleared"
+ print("\nAll assertions cleared")
moose.start( 2 )
for i in range( len( psdTab ) ):
@@ -220,4 +225,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/threading_demo.py b/moose-examples/snippets/threading_demo.py
index a9fd15caf417a49a6df2b09f5be8bf8300e9792c..ca04091109021ac602e44d259b5456a19dfd534b 100644
--- a/moose-examples/snippets/threading_demo.py
+++ b/moose-examples/snippets/threading_demo.py
@@ -30,15 +30,20 @@
# Code:
import sys
-from datetime import datetime
import threading
-import Queue
-import time
+# Python3 and python2.
+try:
+ import queue
+except ImportError as e:
+ import Queue as queue
+
+import time
+from datetime import datetime
import moose
-worker_queue = Queue.Queue()
-status_queue = Queue.Queue()
+worker_queue = queue.Queue()
+status_queue = queue.Queue()
class WorkerThread(threading.Thread):
"""This thread initializes the simulation (reinit) and then runs
@@ -49,16 +54,16 @@ class WorkerThread(threading.Thread):
def __init__(self, runtime):
threading.Thread.__init__(self)
self.runtime = runtime
- print 'Created WorkerThread of name', self.name
+ print(('Created WorkerThread of name', self.name))
def run(self):
- print self.name, 'Starting run for', self.runtime, ' seconds'
+ print((self.name, 'Starting run for', self.runtime, ' seconds'))
moose.reinit()
moose.start(self.runtime)
while moose.isRunning():
time.sleep(1.0)
- print self.name, 'Table length', len(moose.Table('/tab').vector)
- print self.name, 'Finishing simulation'
+ print((self.name, 'Table length', len(moose.Table('/tab').vector)))
+ print((self.name, 'Finishing simulation'))
worker_queue.put(self.name)
class StatusThread(threading.Thread):
@@ -71,18 +76,23 @@ class StatusThread(threading.Thread):
def __init__(self, tab):
threading.Thread.__init__(self)
self.table = tab
- print 'Created StatusThread of name', self.name
+ print(('Created StatusThread of name', self.name))
def run(self):
while True:
try:
value = worker_queue.get(False)
- print self.name, 'Received queue entry: ', value, '. Final table length:', len(self.table.vector), ' ... now Finishing'
+ print((self.name, 'Received queue entry: ', value
+ , '. Final table length:', len(self.table.vector)
+ , ' ... now Finishing'
+ ))
status_queue.put(self.name)
return
- except Queue.Empty:
+ except queue.Empty:
time.sleep(1.0)
- print self.name, 'Queue is empty. Current table length:', len(self.table.vector)
+ print((self.name, 'Queue is empty. Current table length:'
+ , len(self.table.vector)
+ ))
if __name__ == '__main__':
pg = moose.PulseGen('pg')
@@ -99,7 +109,7 @@ if __name__ == '__main__':
t1.start()
status_queue.get(True)
tab.xplot('threading_demo.dat', 'pulsegen_output')
- print 'Ending threading_demo: final length of table', len(tab.vector)
+ print(('Ending threading_demo: final length of table', len(tab.vector)))
#
# threading_demo.py ends here
diff --git a/moose-examples/snippets/transportBranchingNeuron.py b/moose-examples/snippets/transportBranchingNeuron.py
index b8616b5885bbddaba30df7dff6695e140f2a241e..c15ab0d126a52786b244c8cbd3837649afad7cb7 100644
--- a/moose-examples/snippets/transportBranchingNeuron.py
+++ b/moose-examples/snippets/transportBranchingNeuron.py
@@ -73,7 +73,7 @@ def makeModel():
moose.element( '/model/chem/compt0/a[0]' ).concInit = aConcInit
twigs = findTwigs( compt0 )
- print 'twigs = ', twigs
+ print(('twigs = ', twigs))
for i in twigs:
e = moose.element( '/model/chem/compt0/b[' + str(i) + ']' )
e.concInit = bConcInit
@@ -126,8 +126,8 @@ def makeDisplay():
return ( timeSeries, fig, aline, bline, timeLabel, yp )
def updateDisplay( plotlist ):
- a = moose.vec( '/model/chem/compt0/a' )
- b = moose.vec( '/model/chem/compt0/b' )
+ a = moose.vec( '/model/chem/compt0/a' )
+ b = moose.vec( '/model/chem/compt0/b' )
plotlist[2].set_ydata( a.conc * plotScale + plotlist[5] )
plotlist[3].set_ydata( b.conc * plotScale + plotlist[5] )
plotlist[1].canvas.draw()
@@ -140,7 +140,7 @@ def finalizeDisplay( plotlist, cPlotDt ):
plt.legend()
plotlist[1].canvas.draw()
print( "Hit 'enter' to exit" )
- raw_input()
+ eval(input())
def makeChemModel( compt ):
@@ -208,10 +208,10 @@ def main():
plotlist[4].set_text( "time = %d" % i )
updateDisplay( plotlist )
- print 'mass consv a = ', a0, sum( a.n ), ', b = ', b0, sum( b.n )
+ print(('mass consv a = ', a0, sum( a.n ), ', b = ', b0, sum( b.n )))
finalizeDisplay( plotlist, plotdt )
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/traub_naf.py b/moose-examples/snippets/traub_naf.py
index cb124e4456eae73dfeebbce68887049ce7dd28c6..db83c41f20233a3e85d4c1a3f117a4e0b99e6dc5 100644
--- a/moose-examples/snippets/traub_naf.py
+++ b/moose-examples/snippets/traub_naf.py
@@ -254,7 +254,7 @@ def run_clamp(model_dict, clamp, levels, holding=0.0, simtime=100e-3):
for level in levels:
model_dict['command'].level[0] = level
model_dict['command'].baseLevel = holding
- print 'Running %s with holding=%g, level=%g' % (clamp, holding, model_dict['command'].level[0])
+ print(('Running %s with holding=%g, level=%g' % (clamp, holding, model_dict['command'].level[0])))
run_sim(model_dict['model'], model_dict['data'], simtime)
ivec.append(np.asarray(model_dict['inject_tab'].vector))
cvec.append(np.asarray(model_dict['command_tab'].vector))
diff --git a/moose-examples/snippets/tweakingParameters.py b/moose-examples/snippets/tweakingParameters.py
index 2f7a2a58f70e7a1cfa8e5e11e2f5fcfc8fa299e2..7c962ea1315bf66f9cffa56d0ec67c7f2a42098c 100644
--- a/moose-examples/snippets/tweakingParameters.py
+++ b/moose-examples/snippets/tweakingParameters.py
@@ -72,4 +72,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/snippets/vclamp.py b/moose-examples/snippets/vclamp.py
index 71f6067955469686bb55f1722fb5695c88449e9d..edad646021020ea1b6c2fa986232bde914759c9f 100644
--- a/moose-examples/snippets/vclamp.py
+++ b/moose-examples/snippets/vclamp.py
@@ -101,10 +101,10 @@ def vclamp_demo(simtime=50.0, dt=1e-2):
moose.useClock(2, '%s/##[TYPE=VClamp]' % (container.path), 'process')
moose.useClock(3, '%s/##[TYPE=Table]' % (container.path), 'process')
moose.reinit()
- print 'RC filter in VClamp:: tau:', clamp.tau
- print 'PID controller in VClamp:: ti:', clamp.ti, 'td:', clamp.td, 'gain:', clamp.gain
+ print(('RC filter in VClamp:: tau:', clamp.tau))
+ print(('PID controller in VClamp:: ti:', clamp.ti, 'td:', clamp.td, 'gain:', clamp.gain))
moose.start(simtime)
- print 'Finished simulation for %g seconds' % (simtime)
+ print(('Finished simulation for %g seconds' % (simtime)))
tseries = linspace(0, simtime, len(vmtab.vector))
subplot(211)
title('Membrane potential and clamp voltage')
diff --git a/moose-examples/snippets/wildcard.py b/moose-examples/snippets/wildcard.py
index 6db9225cd81d7c8a96d5cfe7f367c8326ca3bee2..97cf2dacfcb4374c02392e769b1e1d73472157ec 100644
--- a/moose-examples/snippets/wildcard.py
+++ b/moose-examples/snippets/wildcard.py
@@ -71,84 +71,84 @@ def wildcard_setup():
def wildcard_test():
# TYPE matches the type of the object
wildcard = '/alfa/bravo/#[TYPE=HHChannel2D]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# ISA matches elements of specified type or its subclasses
wildcard = '/alfa/bravo/#[ISA=HHChannel]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# HHChannel and HHChannel2D are subclasses of ChanBase
wildcard = '/alfa/bravo/#[ISA=ChanBase]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# HHChannel and HHChannel2D are subclasses of ChanBase
wildcard = '/alfa/bravo/#[TYPE=ChanBase]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# `#` can be used only once and matches all subsequent characters in name
wildcard = '/alfa/bravo/charl?e'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# `?` can be used any number of times but substitutes a single character
wildcard = '/alfa/bravo/fox#'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# Specify `##` to search through all levels below the path prefixing it
wildcard = '/##[ISA=ChanBase]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# You can even select by field - but if the field does not exist,
# this will produce a lot of harmless error messages in debug
# builds.
wildcard = '/##[FIELD(name)=echo]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# == and = are same
wildcard = '/##[FIELD(name)==echo]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path
+ print(('\t', element.path))
# Comparison operators other than == are allowed for floating point number fields
wildcard = '/alfa/##[FIELD(Gbar)<1e-6]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path, moose.element(element).Gbar
+ print(('\t', element.path, moose.element(element).Gbar))
# Equality is not defined for floating point fields
wildcard = '/alfa/##[FIELD(Gbar)=1e-6]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path, moose.element(element).Gbar
+ print(('\t', element.path, moose.element(element).Gbar))
# Another operator is !=
wildcard = '/alfa/bravo/#[TYPE!=HHChannel]'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path, ', class:', element.className
+ print(('\t', element.path, ', class:', element.className))
# With `##` you can get a listing of all elements under a path if
# you don't use a condition
wildcard = '/alfa/##'
- print '\nElements Matching:', wildcard
+ print(('\nElements Matching:', wildcard))
for element in moose.wildcardFind(wildcard):
- print '\t', element.path, ', class:', element.className
+ print(('\t', element.path, ', class:', element.className))
if __name__ == '__main__':
diff --git a/moose-examples/squid/channeleditor.py b/moose-examples/squid/channeleditor.py
index ead90412ff75a4940e8c8bfeb49e77657d21bca7..23f8973e757db4d91aecf3059ef8f4ae7b8fb570 100644
--- a/moose-examples/squid/channeleditor.py
+++ b/moose-examples/squid/channeleditor.py
@@ -59,17 +59,17 @@ class GateEditor(QtGui.QWidget):
self.maxVEdit = QtGui.QLineEdit(self)
self.divsVEdit = QtGui.QLineEdit(self)
self.equation = '(A + B * V) / (C + exp((V + D)/F))'
- self.alphaText = u'Equation for forward rate \u03B1 '
- self.betaText = u'Equation for backward rate \u03B2 '
- self.minfText = u'Equation for m\u221E '
- self.taumText = u'Equation for \u03C4m '
+ self.alphaText = 'Equation for forward rate \\u03B1 '
+ self.betaText = 'Equation for backward rate \\u03B2 '
+ self.minfText = 'Equation for m\\u221E '
+ self.taumText = 'Equation for \\u03C4m '
self.alphaLabel = QtGui.QLabel(self.minfText, self)
self.betaLabel = QtGui.QLabel(self.taumText, self)
self.alphaEdit = QtGui.QLineEdit(self)
self.betaEdit = QtGui.QLineEdit(self)
self.formCombo = QtGui.QComboBox(self)
- self.formCombo.addItem(u'm\u221E - \u03C4m')
- self.formCombo.addItem(u'\u03B1 - \u03B2')
+ self.formCombo.addItem('m\\u221E - \\u03C4m')
+ self.formCombo.addItem('\\u03B1 - \\u03B2')
self.okButton = QtGui.QPushButton('OK', self)
layout = QtGui.QGridLayout(self.inputPanel)
layout.addWidget(self.minVLabel, 0, 0)
@@ -125,10 +125,10 @@ class GateEditor(QtGui.QWidget):
a[ii] = %s
b[ii] = %s
""" % (symbol, a_expr, b_expr)
- print code
+ print(code)
tree = compile(code, '<string>', 'exec')
exec(tree)
- print a, b
+ print((a, b))
return {'min': vmin,
'max': vmax,
'divs': vdivs,
diff --git a/moose-examples/squid/squid.py b/moose-examples/squid/squid.py
index b7c2727e57836056696eeab62ecadb8f8baacab0..dae8ff9dc5e83e37bd6249a074965f140900cdc7 100644
--- a/moose-examples/squid/squid.py
+++ b/moose-examples/squid/squid.py
@@ -303,7 +303,7 @@ class SquidAxon(moose.Compartment):
self.temperature = celsius + CELSIUS_TO_KELVIN
def use_defaults(self):
- for field, value in SquidAxon.defaults.items():
+ for field, value in list(SquidAxon.defaults.items()):
setattr(self, field, value)
class SquidModel(moose.Neutral):
@@ -311,13 +311,13 @@ class SquidModel(moose.Neutral):
def __init__(self, path):
moose.Neutral.__init__(self, path)
self.squid_axon = SquidAxon(path+'/squid_axon')
- print self.squid_axon.Na_channel.Gbar, self.squid_axon.K_channel.Gbar
+ print((self.squid_axon.Na_channel.Gbar, self.squid_axon.K_channel.Gbar))
self.current_clamp = moose.PulseGen(path+'/pulsegen')
self.current_clamp.firstDelay = 5.0 # ms
self.current_clamp.firstWidth = 40 # ms
self.current_clamp.firstLevel = 0.1 # uA
self.current_clamp.secondDelay = 1e9
- print 'Current clamp connected:', moose.connect(self.current_clamp, 'output', self.squid_axon, 'injectMsg')
+ print(('Current clamp connected:', moose.connect(self.current_clamp, 'output', self.squid_axon, 'injectMsg')))
self.Vm_table = moose.Table('%s/Vm' % (self.path))
moose.connect(self.Vm_table, 'requestOut', self.squid_axon, 'getVm')
@@ -345,19 +345,19 @@ class SquidModel(moose.Neutral):
def save_data(self):
self.Vm_table.xplot('Vm.dat', 'Vm')
- print 'Vm saved to Vm.dat'
+ print('Vm saved to Vm.dat')
if hasattr(self, 'gK_table'):
self.gK_table.xplot('gK.dat', 'gK')
numpy.savetxt('K_alpha_n.dat', self.squid_axon.K_channel.alpha_m)
numpy.savetxt('K_beta_n.dat', self.squid_axon.K_channel.beta_m)
- print 'K conductance saved to gK.dat'
+ print('K conductance saved to gK.dat')
if hasattr(self, 'gNa_table'):
self.gNa_table.xplot('gNa.dat', 'gNa')
numpy.savetxt('Na_alpha_m.dat', self.squid_axon.Na_channel.alpha_m)
numpy.savetxt('Na_beta_m.dat', self.squid_axon.Na_channel.beta_m)
numpy.savetxt('Na_alpha_h.dat', self.squid_axon.Na_channel.alpha_h)
numpy.savetxt('Na_beta_h.dat', self.squid_axon.Na_channel.beta_h)
- print 'Na conductance saved to gNa.dat'
+ print('Na conductance saved to gNa.dat')
diff --git a/moose-examples/squid/squid_demo.py b/moose-examples/squid/squid_demo.py
index 85a351867a7d0285cbe874e4aa02a86b699f02b4..d243b0f5b03c88b0b84d20029cae8999008702c1 100644
--- a/moose-examples/squid/squid_demo.py
+++ b/moose-examples/squid/squid_demo.py
@@ -95,7 +95,7 @@ where P<sub>C</sub> is the permeability of the membrane to ion C.
"""
-tooltip_NaChan = u"""<h3>Na+ channel conductance</h3>
+tooltip_NaChan = """<h3>Na+ channel conductance</h3>
<p/>
The Na<sup>+</sup> channel conductance in squid giant axon is given by:
@@ -120,7 +120,7 @@ and time constant for steady state is:
and similarly for h.
"""
-tooltip_KChan = u"""<h3>K+ channel conductance</h3>
+tooltip_KChan = """<h3>K+ channel conductance</h3>
<p/>The K+ channel conductance in squid giant axon is given by:
<p> G<sub>K</sub> = GÌ„<sub>K</sub> * n<sup>4</sup></p>
@@ -634,7 +634,7 @@ class SquidGui(QtGui.QMainWindow):
def _runSlot(self):
if moose.isRunning():
- print 'Stopping simulation in progress ...'
+ print('Stopping simulation in progress ...')
moose.stop()
self._runtime = self.getFloatInput(self._runTimeEdit, self._runTimeLabel.text())
self._overlayPlots(self._overlayAction.isChecked())
@@ -892,7 +892,7 @@ if __name__ == '__main__':
QtGui.qApp = app
squid_gui = SquidGui()
squid_gui.show()
- print squid_gui.size()
+ print((squid_gui.size()))
sys.exit(app.exec_())
#
diff --git a/moose-examples/traub_2005/py/cell_test_util.py b/moose-examples/traub_2005/py/cell_test_util.py
index d0ba68e43263fec3b64ca4406f50d71bac9b4f4e..6e7d29c45154644a890382e2996ee5871b3683c1 100644
--- a/moose-examples/traub_2005/py/cell_test_util.py
+++ b/moose-examples/traub_2005/py/cell_test_util.py
@@ -28,7 +28,7 @@
#
# Code:
-from __future__ import print_function
+
from datetime import datetime
import time
diff --git a/moose-examples/traub_2005/py/cells.py b/moose-examples/traub_2005/py/cells.py
index 530029c8007334e8d4719e3462879bb86e544480..ab10380b714b2b8e3617dc1d3036372553afdf7f 100644
--- a/moose-examples/traub_2005/py/cells.py
+++ b/moose-examples/traub_2005/py/cells.py
@@ -28,7 +28,7 @@
#
# Code:
-from __future__ import print_function
+
import csv
import numpy as np
from collections import defaultdict
@@ -101,7 +101,7 @@ def adjust_chanlib(cdict):
"""Update the revarsal potentials for channels. Set the initial X
value for AR channel. Set the tau for Ca pool."""
channel_dict = init_chanlib()
- for ch in channel_dict.values():
+ for ch in list(channel_dict.values()):
config.logger.info('adjusting properties of %s' % (ch.path))
if isinstance(ch, kchans.KChannel):
ch.Ek = cdict['EK']
@@ -142,7 +142,7 @@ def read_prototype(celltype, cdict):
leveldict = read_keyvals('%s/%s.levels' % (config.modelSettings.protodir, celltype))
depths = read_keyvals('%s/%s.depths' % (config.modelSettings.protodir, celltype))
depthdict = {}
- for level, depthset in depths.items():
+ for level, depthset in list(depths.items()):
if len(depthset) != 1:
raise Exception('Depth set must have only one entry.')
depthdict[level] = depthset.pop()
@@ -165,7 +165,7 @@ def assign_depths(cell, depthdict, leveldict):
"""
if not depthdict:
return
- for level, depth in depthdict.items():
+ for level, depth in list(depthdict.items()):
z = float(depth)
complist = leveldict[level]
for comp_number in complist:
@@ -187,15 +187,14 @@ class CellMeta(type):
break
if annotation is not None:
info = moose.Annotator('%s/info' % (proto.path))
- info.notes = '\n'.join('"%s": "%s"' % kv for kv in annotation.items())
+ info.notes = '\n'.join('"%s": "%s"' % kv for kv in list(annotation.items()))
if 'soma_tauCa' in cdict:
moose.element(proto.path + '/comp_1/CaPool').tau = cdict['soma_tauCa']
cdict['prototype'] = proto
return type.__new__(cls, name, bases, cdict)
-class CellBase(moose.Neuron):
- __metaclass__ = CellMeta
+class CellBase(moose.Neuron, CellMeta):
annotation = {'cno': 'cno_0000020'}
def __init__(self, path):
if not moose.exists(path):
diff --git a/moose-examples/traub_2005/py/channel_test_util.py b/moose-examples/traub_2005/py/channel_test_util.py
index 29f70c383b0869b3f60241345fae687a29cd0350..95a0049b6ad46db0cb1333055d7cb0bc0d24f8de 100644
--- a/moose-examples/traub_2005/py/channel_test_util.py
+++ b/moose-examples/traub_2005/py/channel_test_util.py
@@ -27,7 +27,7 @@
#
# Code:
-from __future__ import print_function
+
import uuid
import unittest
@@ -57,15 +57,15 @@ def run_single_channel(channelname, Gbar, simtime, simdt=testutils.SIMDT, plotdt
vm_file = 'data/%s_Vm.dat' % (channelname)
gk_file = 'data/%s_Gk.dat' % (channelname)
ik_file = 'data/%s_Ik.dat' % (channelname)
- tseries = np.array(range(len(vm_data.vector))) * simdt
- print('Vm:', len(vm_data.vector), 'Gk', len(gk_data.vector), 'Ik', len(ik_data.vector))
+ tseries = np.array(list(range(len(vm_data.vector)))) * simdt
+ print(('Vm:', len(vm_data.vector), 'Gk', len(gk_data.vector), 'Ik', len(ik_data.vector)))
data = np.c_[tseries, vm_data.vector]
np.savetxt(vm_file, data)
- print('Saved Vm in', vm_file)
- print(len(gk_data.vector), len(vm_data.vector))
+ print(('Saved Vm in', vm_file))
+ print((len(gk_data.vector), len(vm_data.vector)))
data = np.c_[tseries, gk_data.vector]
np.savetxt(gk_file, data)
- print('Saved Gk in', gk_file)
+ print(('Saved Gk in', gk_file))
data = np.c_[tseries, ik_data.vector]
np.savetxt(ik_file, data)
print('Saved Gk in', ik_file)
@@ -80,7 +80,7 @@ def compare_channel_data(series, channelname, param, simulator, x_range=None, pl
raise ValueError('Unrecognised simulator: %s' % (simulator))
try:
ref_series = np.loadtxt(ref_file)
- except IOError, e:
+ except IOError as e:
print(e)
return -1.0
if plot:
diff --git a/moose-examples/traub_2005/py/channelbase.py b/moose-examples/traub_2005/py/channelbase.py
index a013558a7657b9bea9e1b4254ebcc25c184c4d6a..20ba21c5b8276830bc45f08668830ffed6614dde 100644
--- a/moose-examples/traub_2005/py/channelbase.py
+++ b/moose-examples/traub_2005/py/channelbase.py
@@ -154,7 +154,7 @@ class ChannelMeta(type):
mstring.value = mstring_field[1]
if 'annotation' in cdict:
info = moose.Annotator('%s/info' % (proto.path))
- info.notes = '\n'.join('%s: %s' % kv for kv in cdict['annotation'].items())
+ info.notes = '\n'.join('%s: %s' % kv for kv in list(cdict['annotation'].items()))
# print proto.path, info.notes
cdict['prototype'] = proto
prototypes[name] = proto
@@ -162,10 +162,9 @@ class ChannelMeta(type):
return type.__new__(cls, name, bases, cdict)
-class ChannelBase(moose.HHChannel):
+class ChannelBase(moose.HHChannel, ChannelMeta):
annotation = {'cno': 'cno_0000047'}
abstract = True
- __metaclass__ = ChannelMeta
def __init__(self, path, xpower=1, ypower=0, Ek=0.0):
moose.HHChannel.__init__(self, path)
diff --git a/moose-examples/traub_2005/py/config.py b/moose-examples/traub_2005/py/config.py
index 7569af2d3e61545d38f5ac6edb9682df3eec4377..02fd52b975adbc76c489ab4b4ac7e986032d1f6a 100644
--- a/moose-examples/traub_2005/py/config.py
+++ b/moose-examples/traub_2005/py/config.py
@@ -29,7 +29,7 @@
# Code:
-from __future__ import print_function
+
import settings
import os
diff --git a/moose-examples/traub_2005/py/deadlock_bug.py b/moose-examples/traub_2005/py/deadlock_bug.py
index d876cd7da438208f490f2c6fed70495d24970b95..760a6cefbda9aa18ddda0cc0e1f4d1dd555f68cc 100644
--- a/moose-examples/traub_2005/py/deadlock_bug.py
+++ b/moose-examples/traub_2005/py/deadlock_bug.py
@@ -28,7 +28,7 @@
#
# Code:
-from __future__ import print_function
+
from collections import defaultdict
import moose
@@ -68,7 +68,7 @@ def adjust_chanlib(cdict):
"""Update the revarsal potentials for channels. Set the initial X
value for AR channel. Set the tau for Ca pool."""
channel_dict = init_chanlib()
- for ch in channel_dict.values():
+ for ch in list(channel_dict.values()):
if isinstance(ch, kchans.KChannel):
ch.Ek = cdict['EK']
elif isinstance(ch, nachans.NaChannel):
@@ -106,7 +106,7 @@ def read_prototype(celltype, cdict):
leveldict = read_keyvals('%s/%s.levels' % (config.modelSettings.protodir, celltype))
depths = read_keyvals('%s/%s.depths' % (config.modelSettings.protodir, celltype))
depthdict = {}
- for level, depthset in depths.items():
+ for level, depthset in list(depths.items()):
if len(depthset) != 1:
raise Exception('Depth set must have only one entry.')
depthdict[level] = depthset.pop()
@@ -128,7 +128,7 @@ def assign_depths(cell, depthdict, leveldict):
"""
if not depthdict:
return
- for level, depth in depthdict.items():
+ for level, depth in list(depthdict.items()):
z = float(depth)
complist = leveldict[level]
for comp_number in complist:
@@ -146,8 +146,7 @@ class CellMeta(type):
return type.__new__(cls, name, bases, cdict)
-class CellBase(moose.Neutral):
- __metaclass__ = CellMeta
+class CellBase(moose.Neutral, CellMeta):
def __init__(self, path):
if not moose.exists(path):
path_tokens = path.rpartition('/')
diff --git a/moose-examples/traub_2005/py/display_morphology.py b/moose-examples/traub_2005/py/display_morphology.py
index 7722b23f563a00f02d2d1bed637be4822a5d0e7c..72cdbbbbd893c16e56966277739138041c27e505 100644
--- a/moose-examples/traub_2005/py/display_morphology.py
+++ b/moose-examples/traub_2005/py/display_morphology.py
@@ -28,19 +28,24 @@
#
# Code:
-from __future__ import print_function
+
"""
+
Display/save the topology of one or all cells in traub_2005 demo.
command line options (all are optional):
--c celltype : display topology of cell type 'celltype'. If unspecified, all cell types are displayed
--p filename : save output to fiel specified by 'filename'
--l : show labels of the compartments
--h,--help : show this help
+
+ -c celltype : display topology of cell type 'celltype'. If unspecified,
+ all cell types are displayed
+ -p filename : save output to fiel specified by 'filename'
+ -l : show labels of the compartments
+ -h,--help : show this help
+
"""
+from __future__ import print_function
+
import sys
-sys.path.append('../../../python')
import os
import numpy as np
import matplotlib.pyplot as plt
@@ -117,7 +122,7 @@ def plot_cell_topology(cell, label=False):
nx.draw_networkx_edges(g, pos, width=10*weights/max(weights), edge_color='gray', alpha=0.8)
nx.draw_networkx_nodes(g, pos, with_labels=False,
nnode_size=node_size * 500,
- node_color=map(lambda x: 'k' if x in axon else 'gray', g.nodes()),
+ node_color=['k' if x in axon else 'gray' for x in g.nodes()],
linewidths=[1 if n.endswith('comp_1') else 0 for n in g.nodes()],
alpha=0.8)
if label:
@@ -131,6 +136,7 @@ import sys
from getopt import getopt
if __name__ == '__main__':
+ print(sys.argv)
optlist, args = getopt(sys.argv[1:], 'lhp:c:', ['help'])
celltype = ''
pdf = ''
@@ -151,6 +157,7 @@ if __name__ == '__main__':
print('-p filename (optional) save outputin a pdf file named "filename".')
print('-h,--help print this help')
sys.exit(0)
+ print('args', optlist, args)
figures = []
if len(celltype) > 0:
try:
@@ -160,12 +167,13 @@ if __name__ == '__main__':
# print 'Label', label
plot_cell_topology(cell, label=label)
except KeyError:
- print( '%s: no such cell type. Available are:' % (celltype))
- for ii in cells.init_prototypes().keys():
- print( ii)
+ print('%s: no such cell type. Available are:' % (celltype))
+ for ii in list(cells.init_prototypes().keys()):
+ print(ii, end=' ')
+ print()
sys.exit(1)
else:
- for cell, proto in cells.init_prototypes().items():
+ for cell, proto in list(cells.init_prototypes().items()):
figures.append(plt.figure())
plot_cell_topology(proto, label=label)
plt.axis('off')
diff --git a/moose-examples/traub_2005/py/dump_f_i_curves.py b/moose-examples/traub_2005/py/dump_f_i_curves.py
index 7135a4d871b7a8cdce3d621eabc2416270f2f103..bc9e77e3005f2978b77d6dcae764b4b2fe645d9e 100644
--- a/moose-examples/traub_2005/py/dump_f_i_curves.py
+++ b/moose-examples/traub_2005/py/dump_f_i_curves.py
@@ -1,112 +1,112 @@
-# dump_f_i_curves.py ---
-#
-# Filename: dump_f_i_curves.py
-# Description:
-# Author: Subhasis Ray
-# Maintainer:
-# Created: Tue Dec 8 13:11:01 2015 (-0500)
-# Version:
-# Package-Requires: ()
-# Last-Updated: Wed Dec 9 12:28:06 2015 (-0500)
-# By: Subhasis Ray
-# Update #: 79
-# URL:
-# Doc URL:
-# Keywords:
-# Compatibility:
-#
-#
-
-# Commentary:
-#
-#
-#
-#
-
-# Change Log:
-#
-#
-#
-#
-# This program is free software: you can redistribute it and/or modify
-# it under the terms of the GNU General Public License as published by
-# the Free Software Foundation, either version 3 of the License, or (at
-# your option) any later version.
-#
-# This program is distributed in the hope that it will be useful, but
-# WITHOUT ANY WARRANTY; without even the implied warranty of
-# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
-# General Public License for more details.
-#
-# You should have received a copy of the GNU General Public License
-# along with GNU Emacs. If not, see <http://www.gnu.org/licenses/>.
-#
-#
-
-# Code:
-
-"""Do a series of current steps on each celltype"""
-from __future__ import print_function
-import numpy as np
-import h5py as h5
-from collections import defaultdict
-
-import moose
-from moose import utils as mutils
-
-from cells import SpinyStellate
-from cells import DeepBasket
-from cells import DeepLTS
-
-
-simdt = 2.5e-6
-plotdt = 1e-4
-
-amps = np.array([-0.1, 0.1, 0.5, 1.0, 1.5])*1e-9
-
-def run_current_pulse(amps, delay=100e-3, dur=100e-3, trail=100e-3, outfile='f_i_curves_data.h5'):
- models = []
- model = moose.Neutral('/model')
- data = moose.Neutral('/data')
- ddict = defaultdict(list)
- for ii, amp in enumerate(amps):
- mc = moose.Neutral('{}/mc_{}'.format(model.path, ii))
- models.append(mc)
- stim = moose.PulseGen('{}/stim_{}'.format(mc.path, ii))
- stim.delay[0] = delay
- stim.width[0] = dur
- stim.level[0] = amp
- stim.delay[1] = 1e9 # make delay so large that it does not activate again
- for celltype in [SpinyStellate, DeepBasket, DeepLTS]:
- cell = celltype('{}/{}_{}'.format(mc.path, celltype.__name__, ii))
- solver = moose.HSolve('{}/solver'.format(cell.path))
- solver.dt = simdt
- solver.target = cell.path
- stim.connect('output', cell.soma, 'injectMsg')
- tab = moose.Table('/data/Vm_{}'.format(cell.name))
- ddict[ii].append(tab)
- tab.connect('requestOut', cell.soma, 'getVm')
- mutils.setDefaultDt(elecdt=simdt, plotdt2=plotdt)
- mutils.assignDefaultTicks(modelRoot='/model', dataRoot='/data', solver='hsolve')
- moose.reinit()
- print('Finished scheduling')
- moose.start(delay + dur + trail)
- print('Finished simulation')
- # Save data
- fd = h5.File(outfile, 'w')
- for ii, tabs in ddict.items():
- for tab in tabs:
- print('Table', tab.name)
- node = fd.create_dataset(tab.name, data=tab.vector)
- node.attrs['current'] = amps[ii]
- node.attrs['delay'] = delay
- node.attrs['width'] = dur
- fd.close()
- print('Finished saving data in file', outfile)
-
-
-if __name__ == '__main__':
- run_current_pulse(amps)
-
-#
-# dump_f_i_curves.py ends here
+# dump_f_i_curves.py ---
+#
+# Filename: dump_f_i_curves.py
+# Description:
+# Author: Subhasis Ray
+# Maintainer:
+# Created: Tue Dec 8 13:11:01 2015 (-0500)
+# Version:
+# Package-Requires: ()
+# Last-Updated: Wed Dec 9 12:28:06 2015 (-0500)
+# By: Subhasis Ray
+# Update #: 79
+# URL:
+# Doc URL:
+# Keywords:
+# Compatibility:
+#
+#
+
+# Commentary:
+#
+#
+#
+#
+
+# Change Log:
+#
+#
+#
+#
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or (at
+# your option) any later version.
+#
+# This program is distributed in the hope that it will be useful, but
+# WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+# General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with GNU Emacs. If not, see <http://www.gnu.org/licenses/>.
+#
+#
+
+# Code:
+
+"""Do a series of current steps on each celltype"""
+
+import numpy as np
+import h5py as h5
+from collections import defaultdict
+
+import moose
+from moose import utils as mutils
+
+from cells import SpinyStellate
+from cells import DeepBasket
+from cells import DeepLTS
+
+
+simdt = 2.5e-6
+plotdt = 1e-4
+
+amps = np.array([-0.1, 0.1, 0.5, 1.0, 1.5])*1e-9
+
+def run_current_pulse(amps, delay=100e-3, dur=100e-3, trail=100e-3, outfile='f_i_curves_data.h5'):
+ models = []
+ model = moose.Neutral('/model')
+ data = moose.Neutral('/data')
+ ddict = defaultdict(list)
+ for ii, amp in enumerate(amps):
+ mc = moose.Neutral('{}/mc_{}'.format(model.path, ii))
+ models.append(mc)
+ stim = moose.PulseGen('{}/stim_{}'.format(mc.path, ii))
+ stim.delay[0] = delay
+ stim.width[0] = dur
+ stim.level[0] = amp
+ stim.delay[1] = 1e9 # make delay so large that it does not activate again
+ for celltype in [SpinyStellate, DeepBasket, DeepLTS]:
+ cell = celltype('{}/{}_{}'.format(mc.path, celltype.__name__, ii))
+ solver = moose.HSolve('{}/solver'.format(cell.path))
+ solver.dt = simdt
+ solver.target = cell.path
+ stim.connect('output', cell.soma, 'injectMsg')
+ tab = moose.Table('/data/Vm_{}'.format(cell.name))
+ ddict[ii].append(tab)
+ tab.connect('requestOut', cell.soma, 'getVm')
+ mutils.setDefaultDt(elecdt=simdt, plotdt2=plotdt)
+ mutils.assignDefaultTicks(modelRoot='/model', dataRoot='/data', solver='hsolve')
+ moose.reinit()
+ print('Finished scheduling')
+ moose.start(delay + dur + trail)
+ print('Finished simulation')
+ # Save data
+ fd = h5.File(outfile, 'w')
+ for ii, tabs in list(ddict.items()):
+ for tab in tabs:
+ print(('Table', tab.name))
+ node = fd.create_dataset(tab.name, data=tab.vector)
+ node.attrs['current'] = amps[ii]
+ node.attrs['delay'] = delay
+ node.attrs['width'] = dur
+ fd.close()
+ print(('Finished saving data in file', outfile))
+
+
+if __name__ == '__main__':
+ run_current_pulse(amps)
+
+#
+# dump_f_i_curves.py ends here
diff --git a/moose-examples/traub_2005/py/fig_a2_fs.py b/moose-examples/traub_2005/py/fig_a2_fs.py
index 625a6228b2be9f3407aa335dacbd75aa1ce4ae0f..db7bd2223baceced6698e141ef514b2239fb9178 100644
--- a/moose-examples/traub_2005/py/fig_a2_fs.py
+++ b/moose-examples/traub_2005/py/fig_a2_fs.py
@@ -49,7 +49,7 @@ Reproduce the experiment for Fig A2 in Traub et al 2005.
FS (deep basket cell) with 0.5 nA current pusle simulated for 1 s
"""
-from __future__ import print_function
+
import numpy as np
import pylab
diff --git a/moose-examples/traub_2005/py/fig_a3.py b/moose-examples/traub_2005/py/fig_a3.py
index 393ecaf1fd77a86305cc47d1a36bb411b647657b..dfeecea8f793f25d8372b53a2ebb6c7a501e59b7 100644
--- a/moose-examples/traub_2005/py/fig_a3.py
+++ b/moose-examples/traub_2005/py/fig_a3.py
@@ -105,7 +105,7 @@ def main():
np.vstack((t, inject, vm)).transpose())
msg = 'Saved data for %g A current pulse in %s' % (a, fname)
config.logger.info(msg)
- print( msg)
+ print(msg)
pylab.subplot(3,1,ii+1)
pylab.title('%g nA' % (a*1e9))
pylab.plot(t, vm, label='soma-Vm (mV)')
diff --git a/moose-examples/traub_2005/py/gui.py b/moose-examples/traub_2005/py/gui.py
index c77e68007780b82204cfe308a1185eab910b2cac..9241c11f3c36615885459b81d1160e4c93bcd2e0 100644
--- a/moose-examples/traub_2005/py/gui.py
+++ b/moose-examples/traub_2005/py/gui.py
@@ -48,7 +48,7 @@
"""
Display channel properties graphically
"""
-from __future__ import print_function
+
from datetime import datetime
from PyQt4 import QtCore, QtGui
from matplotlib import mlab
@@ -115,7 +115,7 @@ class HHChanView(QtGui.QWidget):
self.channelListWidget = QtGui.QListWidget(self)
self.channelListWidget.setSelectionMode( QtGui.QAbstractItemView.ExtendedSelection)
root = str(self.rootEdit.text())
- for chan in self.getChannels(root).values():
+ for chan in list(self.getChannels(root).values()):
self.channelListWidget.addItem(chan.name)
self.update()
return self.channelListWidget
@@ -154,7 +154,9 @@ class HHChanView(QtGui.QWidget):
self.mhaxes.set_title('Activation/Inactivation')
self.tauaxes = self.figure.add_subplot(2, 1, 2)
self.tauaxes.set_title('Tau')
+ print((self.channels))
for item in self.getChannelListWidget().selectedItems():
+ print((item.text()))
chan = self.channels[str(item.text())]
if chan.Xpower > 0:
path = '{}/gateX'.format(chan.path)
@@ -194,6 +196,19 @@ class NetworkXWidget(QtGui.QWidget):
if len(sizes) == 0:
print('Empty graph for cell. Make sure proto file has `*asymmetric` on top. I cannot handle symmetric compartmental connections')
return
+ weights = np.array([g.edge[e[0]][e[1]]['weight'] for e in g.edges()])
+ pos = nx.graphviz_layout(g, prog='twopi')
+ xmin, ymin, xmax, ymax = 1e9, 1e9, -1e9, -1e9
+ for p in list(pos.values()):
+ if xmin > p[0]:
+ xmin = p[0]
+ if xmax < p[0]:
+ xmax = p[0]
+ if ymin > p[1]:
+ ymin = p[1]
+ if ymax < p[1]:
+ ymax = p[1]
+ edge_widths = 10.0 * weights / max(weights)
node_colors = ['k' if x in axon else 'gray' for x in g.nodes()]
lw = [1 if n.endswith('comp_1') else 0 for n in g.nodes()]
self.axes.clear()
@@ -300,6 +315,7 @@ class CellView(QtGui.QWidget):
def displayCellMorphology(self, cellpath):
cell = moose.element(cellpath)
+ print('HERE')
graph = cell_to_graph(cell)
self.getCellMorphologyWidget().displayGraph(graph)
@@ -319,8 +335,11 @@ class CellView(QtGui.QWidget):
[1e9, 0, 0]])
# moose.le(model_container)
# moose.le(data_container)
+ print('11111')
+ print((model_container.path, data_container.path))
params['modelRoot'] = model_container.path
params['dataRoot'] = data_container.path
+ print('here')
return params
def displaySelected(self):
@@ -386,7 +405,7 @@ class CellView(QtGui.QWidget):
self.vmAxes.legend()
self.plotCanvas.draw()
td = np.mean(tdlist)
- print('Simulating %g s took %g s of computer time' % (simtime, td))
+ print(('Simulating %g s took %g s of computer time' % (simtime, td)))
# self.plotFigure.tight_layout()
def getPlotWidget(self):
diff --git a/moose-examples/traub_2005/py/test_capool.py b/moose-examples/traub_2005/py/test_capool.py
index eee8ce6cce0d16ee9e0a03e2ab99a3c377f7d5ef..672b243f248d7122005866bb80c84356281fec91 100644
--- a/moose-examples/traub_2005/py/test_capool.py
+++ b/moose-examples/traub_2005/py/test_capool.py
@@ -28,7 +28,7 @@
#
# Code:
-from __future__ import print_function
+
import uuid
import numpy as np
@@ -78,21 +78,21 @@ def run_capool(poolname, Gbar, simtime):
gk_file = 'data/%s_Gk.dat' % (poolname)
ik_file = 'data/%s_Ik.dat' % (poolname)
ca_file = 'data/%s_Ca.dat' % (poolname)
- tseries = np.array(range(len(vm_data.vector))) * simdt
- print('Vm:', len(vm_data.vector), 'Gk', len(gk_data.vector), 'Ik', len(ik_data.vector))
+ tseries = np.array(list(range(len(vm_data.vector)))) * simdt
+ print(('Vm:', len(vm_data.vector), 'Gk', len(gk_data.vector), 'Ik', len(ik_data.vector)))
data = np.c_[tseries, vm_data.vector]
np.savetxt(vm_file, data)
- print('Saved Vm in', vm_file)
+ print(('Saved Vm in', vm_file))
data = np.c_[tseries, gk_data.vector]
np.savetxt(gk_file, data)
- print('Saved Gk in', gk_file)
+ print(('Saved Gk in', gk_file))
data = np.c_[tseries, ik_data.vector]
np.savetxt(ik_file, data)
- print('Saved Ik in', ik_file)
- print('>>', len(ca_data.vector))
+ print(('Saved Ik in', ik_file))
+ print(('>>', len(ca_data.vector)))
data = np.c_[tseries, ca_data.vector]
np.savetxt(ca_file, data)
- print('Saved [Ca2+] in', ca_file)
+ print(('Saved [Ca2+] in', ca_file))
return params
@@ -103,7 +103,7 @@ class TestCaPool(ChannelTestBase):
vm = np.array(params['Vm'].vector)
gk = np.array(params['Gk'].vector)
ca = np.array(params['Ca'].vector)
- print(len(ca))
+ print(le(ca))
tseries = np.arange(0, len(vm), 1.0) * simdt
def testCaPool_Vm_Neuron(self):
diff --git a/moose-examples/traub_2005/py/test_kchans.py b/moose-examples/traub_2005/py/test_kchans.py
index 0eb5eddb456f8185dff97ec08269196ddbe2b6f4..416e4a83961b3914fa9adbb8fd42e7a48981f0e2 100644
--- a/moose-examples/traub_2005/py/test_kchans.py
+++ b/moose-examples/traub_2005/py/test_kchans.py
@@ -27,7 +27,7 @@
#
# Code:
-from __future__ import print_function
+
import uuid
import unittest
@@ -196,19 +196,19 @@ def run_cadep_channel(channelname, Gbar, simtime):
gk_file = 'data/%s_Gk.dat' % (channelname)
ik_file = 'data/%s_Ik.dat' % (channelname)
ca_file = 'data/%s_Ca.dat' % (channelname)
- tseries = np.array(range(len(vm_data.vector))) * simdt
- print('Vm:', len(vm_data.vector), 'Gk', len(gk_data.vector), 'Ik', len(ik_data.vector))
+ tseries = np.array(list(range(len(vm_data.vector)))) * simdt
+ print(('Vm:', len(vm_data.vector), 'Gk', len(gk_data.vector), 'Ik', len(ik_data.vector)))
data = np.c_[tseries, vm_data.vector]
np.savetxt(vm_file, data)
- print('Saved Vm in', vm_file)
+ print(('Saved Vm in', vm_file))
data = np.c_[tseries, gk_data.vector]
np.savetxt(gk_file, data)
- print('Saved Gk in', gk_file)
+ print(('Saved Gk in', gk_file))
data = np.c_[tseries, ik_data.vector]
np.savetxt(ik_file, data)
- print('Saved Ik in', ik_file)
+ print(('Saved Ik in', ik_file))
np.savetxt(ca_file, data)
- print('Saved [Ca2+] in', ca_file)
+ print(('Saved [Ca2+] in', ca_file))
return params
diff --git a/moose-examples/traub_2005/py/test_nachans.py b/moose-examples/traub_2005/py/test_nachans.py
index b96eb1b652e7d47e1e1d0faaf73f4a742ee0b113..e2c91e50e87460820ba96926ada2c66c5a571cec 100644
--- a/moose-examples/traub_2005/py/test_nachans.py
+++ b/moose-examples/traub_2005/py/test_nachans.py
@@ -28,12 +28,12 @@
#
# Code:
+
from __future__ import print_function
import os
os.environ['NUMPTHREADS'] = '1'
import sys
-sys.path.append('../../../python')
import numpy as np
import testutils
from testutils import *
@@ -50,7 +50,7 @@ class TestNaF(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaF_Vm_Moose(self):
print('Testing MOOSE Vm ...',)
@@ -65,7 +65,7 @@ class TestNaF(ChannelTestBase):
print('OK')
def testNaF_Vm_Neuron(self):
- print('Testing NEURON Vm ...', end='')
+ print('Testing NEURON Vm ...', end=' ')
data = np.c_[self.tseries, self.vm]
err = compare_channel_data(data, self.channelname, 'Vm', 'neuron', x_range=(simtime/10.0, simtime))
self.assertLess(err, 0.01)
@@ -83,7 +83,7 @@ class TestNaF_TCR(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaF_TCR_Vm_Moose(self):
print('Testing MOOSE Vm ...', end='')
err = compare_channel_data(self.vm, TestNaF_TCR.channelname, 'Vm', 'moose', x_range=(simtime/10.0, simtime))
@@ -116,15 +116,15 @@ class TestNaF2(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaF2_Vm_Moose(self):
- print('Testing MOOSE Vm ...', end='')
+ print('Testing MOOSE Vm ...', end=' ')
err = compare_channel_data(self.vm, TestNaF2.channelname, 'Vm', 'moose', x_range=(simtime/10.0, simtime))
self.assertLess(err, 0.01)
- print('OK', end='')
+ print('OK')
def testNaF2_Gk_Moose(self):
- print('Testing MOOSE Gk ...', end='')
+ print('Testing MOOSE Gk ...', end=' ')
err = compare_channel_data(self.gk, TestNaF2.channelname, 'Gk', 'moose', x_range=(simtime/10.0, simtime))
self.assertLess(err, 0.05)
print('OK')
@@ -149,7 +149,7 @@ class TestNaF2_nRT(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaF2_nRT_Vm_Moose(self):
print('Testing MOOSE Vm ...', end='')
err = compare_channel_data(self.vm, TestNaF2_nRT.channelname, 'Vm', 'moose', x_range=(simtime/10.0, simtime))
@@ -181,7 +181,7 @@ class TestNaP(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaP_Vm_Moose(self):
print('Testing MOOSE Vm ...', end='')
err = compare_channel_data(self.vm, TestNaP.channelname, 'Vm', 'moose', x_range=(simtime/10.0, simtime))
@@ -214,7 +214,7 @@ class TestNaPF(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaPF_Vm_Moose(self):
print('Testing MOOSE Vm ...', end='')
err = compare_channel_data(self.vm, TestNaPF.channelname, 'Vm', 'moose', x_range=(simtime/10.0, simtime))
@@ -247,7 +247,7 @@ class TestNaPF_SS(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaPF_SS_Vm_Moose(self):
print('Testing MOOSE Vm ...', end='')
err = compare_channel_data(self.vm, TestNaPF_SS.channelname, 'Vm', 'moose', x_range=(simtime/10.0, simtime))
@@ -280,7 +280,7 @@ class TestNaPF_TCR(ChannelTestBase):
params = run_single_channel(channelname, 1e-9, simtime)
vm = np.asarray(params['Vm'].vector)
gk = np.asarray(params['Gk'].vector)
- tseries = np.array(range(0, len(params['Vm'].vector))) * simdt
+ tseries = np.array(list(range(0, len(params['Vm'].vector)))) * simdt
def testNaPF_TCR_Vm_Moose(self):
print('Testing MOOSE Vm ...', end='')
err = compare_channel_data(self.vm, TestNaPF_TCR.channelname, 'Vm', 'moose', x_range=(simtime/10.0, simtime))
@@ -288,7 +288,7 @@ class TestNaPF_TCR(ChannelTestBase):
print('OK')
def testNaPF_TCR_Gk_Moose(self):
- print('Testing MOOSE Gk ...', end='')
+ print('Testing MOOSE Gk ...', end=' ')
err = compare_channel_data(self.gk, TestNaPF_TCR.channelname, 'Gk', 'moose', x_range=(simtime/10.0, simtime))
self.assertLess(err, 0.05)
print('OK')
diff --git a/moose-examples/traub_2005/py/test_singlecomp.py b/moose-examples/traub_2005/py/test_singlecomp.py
index decd56dd20c7eb8a614389f7c7521ab649fd9999..3412806ced9ff7f67154fae3e6e0befcb703f1ed 100644
--- a/moose-examples/traub_2005/py/test_singlecomp.py
+++ b/moose-examples/traub_2005/py/test_singlecomp.py
@@ -29,7 +29,7 @@
#
# Code:
-from __future__ import print_function
+
import os
os.environ['NUMPTHREADS'] = '1'
@@ -142,7 +142,7 @@ class TestSingleComp(unittest.TestCase):
tab = moose.Table('%s/Vm' % (self.data.path))
self.tables['Vm'] = tab
moose.connect(tab, 'requestOut', self.soma, 'getVm')
- for channelname, conductance in channel_density.items():
+ for channelname, conductance in list(channel_density.items()):
chanclass = eval(channelname)
channel = insert_channel(self.soma, chanclass, conductance, density=True)
if issubclass(chanclass, KChannel):
@@ -189,8 +189,8 @@ class TestSingleComp(unittest.TestCase):
nrndata = np.loadtxt('../nrn/data/singlecomp_Vm.dat')
vm_axis.plot(nrndata[:,0], nrndata[:,1], label='Vm (mV) - nrn')
ca_axis.plot(nrndata[:,0], nrndata[:,2], label='Ca (mM) - nrn')
- except IOError, e:
- print( e)
+ except IOError as e:
+ print(e)
tseries = np.linspace(0, simtime, len(self.tables['Vm'].vector)) * 1e3
# plotcount = len(channel_density) + 1
# rows = int(np.sqrt(plotcount) + 0.5)
diff --git a/moose-examples/traub_2005/py/test_tcr.py b/moose-examples/traub_2005/py/test_tcr.py
index b148bf69dfc563a4fb112fd3bba0a6b5d1f15902..c6d1c4999b93e0b7bf9bd2799520e4e0ad5d98d7 100644
--- a/moose-examples/traub_2005/py/test_tcr.py
+++ b/moose-examples/traub_2005/py/test_tcr.py
@@ -28,7 +28,7 @@
#
# Code:
-from __future__ import print_function
+
import unittest
from cell_test_util import setup_current_step_model, SingleCellCurrentStepTest
import testutils
@@ -80,9 +80,9 @@ class TestTCR(SingleCellCurrentStepTest):
tab = moose.Table('%s/command' % (self.data_container.path))
moose.connect(tab, 'requestOut', clamp, 'getCommand')
for ii in moose.wildcardFind('/##[TYPE=VClamp]'):
- print(ii.path)
+ print((ii.path))
self.runsim(simtime)
- print(tab, len(tab.vector))
+ print((tab, len(tab.vector)))
pylab.plot(pylab.linspace(0, simtime, len(tab.vector)), tab.vector, 'kx')
self.plot_vm()
diff --git a/moose-examples/traub_2005/py/testutils.py b/moose-examples/traub_2005/py/testutils.py
index b3d6b68e2622687fad31a046cbce826f527c015f..d6dff4546cb3b8cbac5e1c2582eac9e2a9431947 100644
--- a/moose-examples/traub_2005/py/testutils.py
+++ b/moose-examples/traub_2005/py/testutils.py
@@ -28,7 +28,7 @@
#
# Code:
-from __future__ import print_function
+
import os
os.environ['NUMPTHREADS'] = '1'
@@ -335,11 +335,11 @@ def compare_cell_dump(left, right, rtol=1e-3, atol=1e-8, row_header=True, col_he
right_end = False
while True:
try:
- left_row = left_reader.next()
+ left_row = next(left_reader)
except StopIteration:
left_end = True
try:
- right_row = right_reader.next()
+ right_row = next(right_reader)
except StopIteration:
right_end = True
if left_end and not right_end:
@@ -359,11 +359,11 @@ def compare_cell_dump(left, right, rtol=1e-3, atol=1e-8, row_header=True, col_he
left = float(left_row[key])
right = float(right_row[key])
if not np.allclose(float(left), float(right), rtol=rtol, atol=atol):
- print( 'Mismatch in row:%s, column:%s. Values: %g <> %g' % (index, key, left, right))
+ print(('Mismatch in row:%s, column:%s. Values: %g <> %g' % (index, key, left, right)))
ret = False
- except ValueError, e:
- print( e)
- print( 'Row:', index, 'Key:', key, left_row[key], right_row[key])
+ except ValueError as e:
+ print(e)
+ print(('Row:', index, 'Key:', key, left_row[key], right_row[key]))
index = index + 1
return ret
diff --git a/moose-examples/traub_2005/py/trbconfig.py b/moose-examples/traub_2005/py/trbconfig.py
index 63814c316debdb3f2e379f09870f4b786804f29c..134537e7ed6c0b9e4426c1058445ad10c6ab6f69 100644
--- a/moose-examples/traub_2005/py/trbconfig.py
+++ b/moose-examples/traub_2005/py/trbconfig.py
@@ -29,7 +29,7 @@
# Code:
from datetime import datetime
-import ConfigParser as configparser
+import configparser as configparser
import logging
import numpy
import os
diff --git a/moose-examples/tutorials/ChemicalBistables/findSteadyState.py b/moose-examples/tutorials/ChemicalBistables/findSteadyState.py
index b53c94bd9cf8277670bb7c74d95642af1bd3355f..21c545cee6cbe641fad0e2cc30dbc8ba65c1ed2f 100644
--- a/moose-examples/tutorials/ChemicalBistables/findSteadyState.py
+++ b/moose-examples/tutorials/ChemicalBistables/findSteadyState.py
@@ -50,73 +50,74 @@ import numpy
import moose
def displayPlots():
- for x in moose.wildcardFind( '/model/graphs/conc#/#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ for x in moose.wildcardFind( '/model/graphs/conc#/#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
def getState( ksolve, state ):
- state.randomInit()
- moose.start( 0.1 ) # Run the model for 2 seconds.
- state.settle()
- '''
- scale = 1.0 / ( 1e-15 * 6.022e23 )
- for x in ksolve.nVec[0]:
- print x * scale,
- # print ksolve.nVec[0]
- print state.nIter, state.status, state.stateType, state.nNegEigenvalues, state.nPosEigenvalues, state.solutionStatus
- '''
- moose.start( 20.0 ) # Run model for 10 seconds, just for display
+ state.randomInit()
+ moose.start( 0.1 ) # Run the model for 2 seconds.
+ state.settle()
+
+ '''
+ scale = 1.0 / ( 1e-15 * 6.022e23 )
+ for x in ksolve.nVec[0]:
+ print x * scale,
+ # print ksolve.nVec[0]
+ print state.nIter, state.status, state.stateType, state.nNegEigenvalues, state.nPosEigenvalues, state.solutionStatus
+ '''
+ moose.start( 20.0 ) # Run model for 10 seconds, just for display
def main():
- # Schedule the whole lot
- moose.setClock( 4, 0.1 ) # for the computational objects
- moose.setClock( 5, 0.2 ) # clock for the solver
- moose.setClock( 8, 1.0 ) # for the plots
- # The wildcard uses # for single level, and ## for recursive.
- #compartment = makeModel()
- moose.loadModel( '../../genesis/M1719.g', '/model', 'ee' )
- compartment = moose.element( 'model/kinetics' )
- compartment.name = 'compartment'
- ksolve = moose.Ksolve( '/model/compartment/ksolve' )
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = compartment
- stoich.ksolve = ksolve
- #ksolve.stoich = stoich
- stoich.path = "/model/compartment/##"
- state = moose.SteadyState( '/model/compartment/state' )
- moose.useClock( 5, '/model/compartment/ksolve', 'process' )
- moose.useClock( 8, '/model/graphs/#', 'process' )
+ # Schedule the whole lot
+ moose.setClock( 4, 0.1 ) # for the computational objects
+ moose.setClock( 5, 0.2 ) # clock for the solver
+ moose.setClock( 8, 1.0 ) # for the plots
+ # The wildcard uses # for single level, and ## for recursive.
+ #compartment = makeModel()
+ moose.loadModel( '../../genesis/M1719.g', '/model', 'ee' )
+ compartment = moose.element( 'model/kinetics' )
+ compartment.name = 'compartment'
+ ksolve = moose.Ksolve( '/model/compartment/ksolve' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = compartment
+ stoich.ksolve = ksolve
+ #ksolve.stoich = stoich
+ stoich.path = "/model/compartment/##"
+ state = moose.SteadyState( '/model/compartment/state' )
+ moose.useClock( 5, '/model/compartment/ksolve', 'process' )
+ moose.useClock( 8, '/model/graphs/#', 'process' )
- moose.reinit()
- state.stoich = stoich
- #state.showMatrices()
- state.convergenceCriterion = 1e-7
+ moose.reinit()
+ state.stoich = stoich
+ #state.showMatrices()
+ state.convergenceCriterion = 1e-7
- for i in range( 0, 50 ):
- getState( ksolve, state )
-
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ for i in range( 0, 50 ):
+ getState( ksolve, state )
+
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- b = moose.element( '/model/compartment/b' )
- c = moose.element( '/model/compartment/c' )
+ b = moose.element( '/model/compartment/b' )
+ c = moose.element( '/model/compartment/c' )
- # move most molecules over to b
- b.conc = b.conc + c.conc * 0.95
- c.conc = c.conc * 0.05
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules over to b
+ b.conc = b.conc + c.conc * 0.95
+ c.conc = c.conc * 0.05
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # move most molecules back to a
- c.conc = c.conc + b.conc * 0.95
- b.conc = b.conc * 0.05
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules back to a
+ c.conc = c.conc + b.conc * 0.95
+ b.conc = b.conc * 0.05
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # Iterate through all plots, dump their contents to data.plot.
- displayPlots()
+ # Iterate through all plots, dump their contents to data.plot.
+ displayPlots()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
diff --git a/moose-examples/tutorials/ChemicalBistables/mapkFB.py b/moose-examples/tutorials/ChemicalBistables/mapkFB.py
index 7770f407a7743337c739246f4287909c9677b741..36c3d0d485af70f791fc354cda01e8c15176c1eb 100644
--- a/moose-examples/tutorials/ChemicalBistables/mapkFB.py
+++ b/moose-examples/tutorials/ChemicalBistables/mapkFB.py
@@ -13,6 +13,9 @@ import matplotlib.image as mpimg
import pylab
import numpy
import sys
+import os
+
+scriptDir = os.path.dirname( os.path.realpath( __file__ ) )
def main():
"""
@@ -34,37 +37,39 @@ def main():
'turn off'
by setting the system calcium levels to zero for a while. This
is a somewhat unphysiological manipulation!
+
"""
+
solver = "gsl" # Pick any of gsl, gssa, ee..
#solver = "gssa" # Pick any of gsl, gssa, ee..
- mfile = '../../genesis/acc35.g'
- runtime = 2000.0
- if ( len( sys.argv ) == 2 ):
- solver = sys.argv[1]
- modelId = moose.loadModel( mfile, 'model', solver )
+ mfile = os.path.join( scriptDir, '..', '..', 'genesis' , 'acc35.g' )
+ runtime = 2000.0
+ if ( len( sys.argv ) == 2 ):
+ solver = sys.argv[1]
+ modelId = moose.loadModel( mfile, 'model', solver )
# Increase volume so that the stochastic solver gssa
# gives an interesting output
compt = moose.element( '/model/kinetics' )
compt.volume = 5e-19
- moose.reinit()
- moose.start( 500 )
+ moose.reinit()
+ moose.start( 500 )
moose.element( '/model/kinetics/PDGFR/PDGF' ).concInit = 0.0001
- moose.start( 400 )
+ moose.start( 400 )
moose.element( '/model/kinetics/PDGFR/PDGF' ).concInit = 0.0
- moose.start( 2000 )
+ moose.start( 2000 )
moose.element( '/model/kinetics/Ca' ).concInit = 0.0
- moose.start( 500 )
+ moose.start( 500 )
moose.element( '/model/kinetics/Ca' ).concInit = 0.00008
- moose.start( 2000 )
+ moose.start( 2000 )
- # Display all plots.
+ # Display all plots.
img = mpimg.imread( 'mapkFB.png' )
fig = plt.figure( figsize=(12, 10 ) )
png = fig.add_subplot( 211 )
imgplot = plt.imshow( img )
ax = fig.add_subplot( 212 )
- x = moose.wildcardFind( '/model/#graphs/conc#/#' )
+ x = moose.wildcardFind( '/model/#graphs/conc#/#' )
t = numpy.arange( 0, x[0].vector.size, 1 ) * x[0].dt
ax.plot( t, x[0].vector, 'b-', label=x[0].name )
ax.plot( t, x[1].vector, 'c-', label=x[1].name )
@@ -77,4 +82,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/tutorials/ChemicalBistables/propagationBis.py b/moose-examples/tutorials/ChemicalBistables/propagationBis.py
index a4a5f9c67df13a0be87fed7bd1c961b7edee14a3..add79df3e7f84303055ecbb9ec778b3514e625ef 100644
--- a/moose-examples/tutorials/ChemicalBistables/propagationBis.py
+++ b/moose-examples/tutorials/ChemicalBistables/propagationBis.py
@@ -50,70 +50,70 @@ import matplotlib.image as mpimg
import moose
def makeModel():
- # create container for model
- r0 = 1e-6 # m
- r1 = 0.5e-6 # m. Note taper.
- num = 200
- diffLength = 1e-6 # m
- comptLength = num * diffLength # m
- diffConst = 20e-12 # m^2/sec
- concA = 1 # millimolar
- diffDt = 0.02 # for the diffusion
- chemDt = 0.2 # for the reaction
+ # create container for model
+ r0 = 1e-6 # m
+ r1 = 0.5e-6 # m. Note taper.
+ num = 200
+ diffLength = 1e-6 # m
+ comptLength = num * diffLength # m
+ diffConst = 20e-12 # m^2/sec
+ concA = 1 # millimolar
+ diffDt = 0.02 # for the diffusion
+ chemDt = 0.2 # for the reaction
mfile = '../../genesis/M1719.g'
- model = moose.Neutral( 'model' )
- compartment = moose.CylMesh( '/model/kinetics' )
+ model = moose.Neutral( 'model' )
+ compartment = moose.CylMesh( '/model/kinetics' )
- # load in model
+ # load in model
modelId = moose.loadModel( mfile, '/model', 'ee' )
- a = moose.element( '/model/kinetics/a' )
- b = moose.element( '/model/kinetics/b' )
- c = moose.element( '/model/kinetics/c' )
+ a = moose.element( '/model/kinetics/a' )
+ b = moose.element( '/model/kinetics/b' )
+ c = moose.element( '/model/kinetics/c' )
ac = a.concInit
bc = b.concInit
cc = c.concInit
- compartment.r0 = r0
- compartment.r1 = r1
- compartment.x0 = 0
- compartment.x1 = comptLength
- compartment.diffLength = diffLength
- assert( compartment.numDiffCompts == num )
+ compartment.r0 = r0
+ compartment.r1 = r1
+ compartment.x0 = 0
+ compartment.x1 = comptLength
+ compartment.diffLength = diffLength
+ assert( compartment.numDiffCompts == num )
- # Assign parameters
+ # Assign parameters
for x in moose.wildcardFind( '/model/kinetics/##[ISA=PoolBase]' ):
#print 'pools: ', x, x.name
x.diffConst = diffConst
- # Make solvers
- ksolve = moose.Ksolve( '/model/kinetics/ksolve' )
- dsolve = moose.Dsolve( '/model/dsolve' )
+ # Make solvers
+ ksolve = moose.Ksolve( '/model/kinetics/ksolve' )
+ dsolve = moose.Dsolve( '/model/dsolve' )
# Set up clocks.
- moose.setClock( 10, diffDt )
+ moose.setClock( 10, diffDt )
for i in range( 11, 17 ):
- moose.setClock( i, chemDt )
-
- stoich = moose.Stoich( '/model/kinetics/stoich' )
- stoich.compartment = compartment
- stoich.ksolve = ksolve
- stoich.dsolve = dsolve
- stoich.path = "/model/kinetics/##"
- print 'dsolve.numPools, num = ', dsolve.numPools, num
+ moose.setClock( i, chemDt )
+
+ stoich = moose.Stoich( '/model/kinetics/stoich' )
+ stoich.compartment = compartment
+ stoich.ksolve = ksolve
+ stoich.dsolve = dsolve
+ stoich.path = "/model/kinetics/##"
+ print(('dsolve.numPools, num = ', dsolve.numPools, num))
b.vec[num-1].concInit *= 1.01 # Break symmetry.
def main():
runtime = 100
displayInterval = 2
- makeModel()
- dsolve = moose.element( '/model/dsolve' )
- moose.reinit()
- #moose.start( runtime ) # Run the model for 10 seconds.
+ makeModel()
+ dsolve = moose.element( '/model/dsolve' )
+ moose.reinit()
+ #moose.start( runtime ) # Run the model for 10 seconds.
- a = moose.element( '/model/kinetics/a' )
- b = moose.element( '/model/kinetics/b' )
- c = moose.element( '/model/kinetics/c' )
+ a = moose.element( '/model/kinetics/a' )
+ b = moose.element( '/model/kinetics/b' )
+ c = moose.element( '/model/kinetics/c' )
img = mpimg.imread( 'propBis.png' )
#imgplot = plt.imshow( img )
@@ -143,7 +143,7 @@ def main():
timeLabel.set_text( "time = %d" % t )
fig.canvas.draw()
- print 'Swapping concs of b and c in half the cylinder'
+ print('Swapping concs of b and c in half the cylinder')
for i in range( b.numData/2 ):
temp = b.vec[i].conc
b.vec[i].conc = c.vec[i].conc
@@ -159,10 +159,10 @@ def main():
fig.canvas.draw()
print( "Hit 'enter' to exit" )
- raw_input()
+ eval(input())
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/tutorials/ChemicalBistables/scaleVolumes.py b/moose-examples/tutorials/ChemicalBistables/scaleVolumes.py
index dec2124712267cbaed24413008e7c9ed2079e357..ca9e8ce6b6ebe492c0a026f26797d19bd5757fb4 100644
--- a/moose-examples/tutorials/ChemicalBistables/scaleVolumes.py
+++ b/moose-examples/tutorials/ChemicalBistables/scaleVolumes.py
@@ -126,7 +126,7 @@ def main():
for vol in ( 1e-19, 1e-20, 1e-21, 3e-22, 1e-22, 3e-23, 1e-23 ):
# Set the volume
compt.volume = vol
- print 'vol = ', vol, ', a.concInit = ', a.concInit, ', a.nInit = ', a.nInit
+ print(('vol = ', vol, ', a.concInit = ', a.concInit, ', a.nInit = ', a.nInit))
moose.reinit()
moose.start( 100.0 ) # Run the model for 100 seconds.
@@ -147,8 +147,8 @@ def main():
# Iterate through all plots, dump their contents to data.plot.
displayPlots()
pylab.show( block=False )
- print 'vol = ', vol, 'hit enter to go to next plot'
- raw_input()
+ print(('vol = ', vol, 'hit enter to go to next plot'))
+ eval(input())
quit()
diff --git a/moose-examples/tutorials/ChemicalBistables/simpleBis.py b/moose-examples/tutorials/ChemicalBistables/simpleBis.py
index 346f0a4bc230c396eb42f03236d8b7909b7fc847..34e2510a463b894925ff8a0799b9c0d1814f7bc8 100644
--- a/moose-examples/tutorials/ChemicalBistables/simpleBis.py
+++ b/moose-examples/tutorials/ChemicalBistables/simpleBis.py
@@ -25,116 +25,116 @@ import moose
import sys
def makeModel():
- # create container for model
- model = moose.Neutral( 'model' )
- compartment = moose.CubeMesh( '/model/compartment' )
- compartment.volume = 1e-21
- # the mesh is created automatically by the compartment
- mesh = moose.element( '/model/compartment/mesh' )
-
- # create molecules and reactions
- a = moose.Pool( '/model/compartment/a' )
- b = moose.Pool( '/model/compartment/b' )
- c = moose.Pool( '/model/compartment/c' )
- enz1 = moose.Enz( '/model/compartment/b/enz1' )
- enz2 = moose.Enz( '/model/compartment/c/enz2' )
- cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
- cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
- reac = moose.Reac( '/model/compartment/reac' )
-
- # connect them up for reactions
- moose.connect( enz1, 'sub', a, 'reac' )
- moose.connect( enz1, 'prd', b, 'reac' )
- moose.connect( enz1, 'enz', b, 'reac' )
- moose.connect( enz1, 'cplx', cplx1, 'reac' )
-
- moose.connect( enz2, 'sub', b, 'reac' )
- moose.connect( enz2, 'prd', a, 'reac' )
- moose.connect( enz2, 'enz', c, 'reac' )
- moose.connect( enz2, 'cplx', cplx2, 'reac' )
-
- moose.connect( reac, 'sub', a, 'reac' )
- moose.connect( reac, 'prd', b, 'reac' )
-
- # connect them up to the compartment for volumes
- #for x in ( a, b, c, cplx1, cplx2 ):
- # moose.connect( x, 'mesh', mesh, 'mesh' )
-
- # Assign parameters
- a.concInit = 1
- b.concInit = 0
- c.concInit = 0.01
- enz1.kcat = 0.4
- enz1.Km = 4
- enz2.kcat = 0.6
- enz2.Km = 0.01
- reac.Kf = 0.001
- reac.Kb = 0.01
-
- # Create the output tables
- graphs = moose.Neutral( '/model/graphs' )
- outputA = moose.Table ( '/model/graphs/concA' )
- outputB = moose.Table ( '/model/graphs/concB' )
-
- # connect up the tables
- moose.connect( outputA, 'requestOut', a, 'getConc' );
- moose.connect( outputB, 'requestOut', b, 'getConc' );
-
- # Schedule the whole lot
- moose.setClock( 4, 0.01 ) # for the computational objects
- moose.setClock( 8, 1.0 ) # for the plots
- # The wildcard uses # for single level, and ## for recursive.
- moose.useClock( 4, '/model/compartment/##', 'process' )
- moose.useClock( 8, '/model/graphs/#', 'process' )
+ # create container for model
+ model = moose.Neutral( 'model' )
+ compartment = moose.CubeMesh( '/model/compartment' )
+ compartment.volume = 1e-21
+ # the mesh is created automatically by the compartment
+ mesh = moose.element( '/model/compartment/mesh' )
+
+ # create molecules and reactions
+ a = moose.Pool( '/model/compartment/a' )
+ b = moose.Pool( '/model/compartment/b' )
+ c = moose.Pool( '/model/compartment/c' )
+ enz1 = moose.Enz( '/model/compartment/b/enz1' )
+ enz2 = moose.Enz( '/model/compartment/c/enz2' )
+ cplx1 = moose.Pool( '/model/compartment/b/enz1/cplx' )
+ cplx2 = moose.Pool( '/model/compartment/c/enz2/cplx' )
+ reac = moose.Reac( '/model/compartment/reac' )
+
+ # connect them up for reactions
+ moose.connect( enz1, 'sub', a, 'reac' )
+ moose.connect( enz1, 'prd', b, 'reac' )
+ moose.connect( enz1, 'enz', b, 'reac' )
+ moose.connect( enz1, 'cplx', cplx1, 'reac' )
+
+ moose.connect( enz2, 'sub', b, 'reac' )
+ moose.connect( enz2, 'prd', a, 'reac' )
+ moose.connect( enz2, 'enz', c, 'reac' )
+ moose.connect( enz2, 'cplx', cplx2, 'reac' )
+
+ moose.connect( reac, 'sub', a, 'reac' )
+ moose.connect( reac, 'prd', b, 'reac' )
+
+ # connect them up to the compartment for volumes
+ #for x in ( a, b, c, cplx1, cplx2 ):
+ # moose.connect( x, 'mesh', mesh, 'mesh' )
+
+ # Assign parameters
+ a.concInit = 1
+ b.concInit = 0
+ c.concInit = 0.01
+ enz1.kcat = 0.4
+ enz1.Km = 4
+ enz2.kcat = 0.6
+ enz2.Km = 0.01
+ reac.Kf = 0.001
+ reac.Kb = 0.01
+
+ # Create the output tables
+ graphs = moose.Neutral( '/model/graphs' )
+ outputA = moose.Table ( '/model/graphs/concA' )
+ outputB = moose.Table ( '/model/graphs/concB' )
+
+ # connect up the tables
+ moose.connect( outputA, 'requestOut', a, 'getConc' );
+ moose.connect( outputB, 'requestOut', b, 'getConc' );
+
+ # Schedule the whole lot
+ moose.setClock( 4, 0.01 ) # for the computational objects
+ moose.setClock( 8, 1.0 ) # for the plots
+ # The wildcard uses # for single level, and ## for recursive.
+ moose.useClock( 4, '/model/compartment/##', 'process' )
+ moose.useClock( 8, '/model/graphs/#', 'process' )
def displayPlots():
- for x in moose.wildcardFind( '/model/graphs/conc#' ):
- t = numpy.arange( 0, x.vector.size, 1 ) #sec
- pylab.plot( t, x.vector, label=x.name )
- pylab.legend()
- pylab.show()
+ for x in moose.wildcardFind( '/model/graphs/conc#' ):
+ t = numpy.arange( 0, x.vector.size, 1 ) #sec
+ pylab.plot( t, x.vector, label=x.name )
+ pylab.legend()
+ pylab.show()
def main():
solver = "gsl"
- makeModel()
+ makeModel()
if ( len ( sys.argv ) == 2 ):
solver = sys.argv[1]
- stoich = moose.Stoich( '/model/compartment/stoich' )
- stoich.compartment = moose.element( '/model/compartment' )
+ stoich = moose.Stoich( '/model/compartment/stoich' )
+ stoich.compartment = moose.element( '/model/compartment' )
if ( solver == 'gssa' ):
- gsolve = moose.Gsolve( '/model/compartment/ksolve' )
- stoich.ksolve = gsolve
+ gsolve = moose.Gsolve( '/model/compartment/ksolve' )
+ stoich.ksolve = gsolve
else:
- ksolve = moose.Ksolve( '/model/compartment/ksolve' )
- stoich.ksolve = ksolve
- stoich.path = "/model/compartment/##"
- #solver.method = "rk5"
- #mesh = moose.element( "/model/compartment/mesh" )
- #moose.connect( mesh, "remesh", solver, "remesh" )
- moose.setClock( 5, 1.0 ) # clock for the solver
- moose.useClock( 5, '/model/compartment/ksolve', 'process' )
+ ksolve = moose.Ksolve( '/model/compartment/ksolve' )
+ stoich.ksolve = ksolve
+ stoich.path = "/model/compartment/##"
+ #solver.method = "rk5"
+ #mesh = moose.element( "/model/compartment/mesh" )
+ #moose.connect( mesh, "remesh", solver, "remesh" )
+ moose.setClock( 5, 1.0 ) # clock for the solver
+ moose.useClock( 5, '/model/compartment/ksolve', 'process' )
- moose.reinit()
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ moose.reinit()
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- a = moose.element( '/model/compartment/a' )
- b = moose.element( '/model/compartment/b' )
+ a = moose.element( '/model/compartment/a' )
+ b = moose.element( '/model/compartment/b' )
- # move most molecules over to b
- b.conc = b.conc + a.conc * 0.9
- a.conc = a.conc * 0.1
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules over to b
+ b.conc = b.conc + a.conc * 0.9
+ a.conc = a.conc * 0.1
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # move most molecules back to a
- a.conc = a.conc + b.conc * 0.99
- b.conc = b.conc * 0.01
- moose.start( 100.0 ) # Run the model for 100 seconds.
+ # move most molecules back to a
+ a.conc = a.conc + b.conc * 0.99
+ b.conc = b.conc * 0.01
+ moose.start( 100.0 ) # Run the model for 100 seconds.
- # Iterate through all plots, dump their contents to data.plot.
- displayPlots()
+ # Iterate through all plots, dump their contents to data.plot.
+ displayPlots()
- quit()
+ quit()
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/tutorials/ChemicalBistables/strongBis.py b/moose-examples/tutorials/ChemicalBistables/strongBis.py
index db7299f764d1e740743a30e9f893cf482957564d..04d234bb8f49ba47ccd6287c24319423c92e49b7 100644
--- a/moose-examples/tutorials/ChemicalBistables/strongBis.py
+++ b/moose-examples/tutorials/ChemicalBistables/strongBis.py
@@ -15,66 +15,66 @@ import numpy
import sys
def main():
- """
- This example illustrates loading, and running a kinetic model
- for a bistable system, defined in kkit format.
- Defaults to the deterministic gsl method, you can pick the
- stochastic one by
+ """
+ This example illustrates loading, and running a kinetic model
+ for a bistable system, defined in kkit format.
+ Defaults to the deterministic gsl method, you can pick the
+ stochastic one by
- ``python filename gssa``
+ ``python filename gssa``
- The model starts out equally poised between sides **b** and **c**.
- Then there is a small molecular 'tap' to push it over to **b**.
- Then we apply a moderate push to show that it is now very stably in
- this state. it takes a strong push to take it over to **c**.
- Then it takes a strong push to take it back to **b**.
- This is a good model to use as the basis for running stochastically
- and examining how state stability is affected by changing volume.
- """
+ The model starts out equally poised between sides **b** and **c**.
+ Then there is a small molecular 'tap' to push it over to **b**.
+ Then we apply a moderate push to show that it is now very stably in
+ this state. it takes a strong push to take it over to **c**.
+ Then it takes a strong push to take it back to **b**.
+ This is a good model to use as the basis for running stochastically
+ and examining how state stability is affected by changing volume.
+ """
- solver = "gsl" # Pick any of gsl, gssa, ee..
- #solver = "gssa" # Pick any of gsl, gssa, ee..
- #moose.seed( 1234 ) # Needed if stochastic.
- mfile = '../../genesis/M1719.g'
- runtime = 100.0
- if ( len( sys.argv ) >= 2 ):
+ solver = "gsl" # Pick any of gsl, gssa, ee..
+ #solver = "gssa" # Pick any of gsl, gssa, ee..
+ #moose.seed( 1234 ) # Needed if stochastic.
+ mfile = '../../genesis/M1719.g'
+ runtime = 100.0
+ if ( len( sys.argv ) >= 2 ):
solver = sys.argv[1]
- modelId = moose.loadModel( mfile, 'model', solver )
+ modelId = moose.loadModel( mfile, 'model', solver )
# Increase volume so that the stochastic solver gssa
# gives an interesting output
compt = moose.element( '/model/kinetics' )
compt.volume = 0.2e-19
r = moose.element( '/model/kinetics/equil' )
- moose.reinit()
- moose.start( runtime )
+ moose.reinit()
+ moose.start( runtime )
r.Kf *= 1.1 # small tap to break symmetry
- moose.start( runtime/10 )
+ moose.start( runtime/10 )
r.Kf = r.Kb
- moose.start( runtime )
+ moose.start( runtime )
r.Kb *= 2.0 # Moderate push does not tip it back.
- moose.start( runtime/10 )
+ moose.start( runtime/10 )
r.Kb = r.Kf
- moose.start( runtime )
+ moose.start( runtime )
r.Kb *= 5.0 # Strong push does tip it over
- moose.start( runtime/10 )
+ moose.start( runtime/10 )
r.Kb = r.Kf
- moose.start( runtime )
+ moose.start( runtime )
r.Kf *= 5.0 # Strong push tips it back.
- moose.start( runtime/10 )
+ moose.start( runtime/10 )
r.Kf = r.Kb
- moose.start( runtime )
+ moose.start( runtime )
- # Display all plots.
+ # Display all plots.
img = mpimg.imread( 'strongBis.png' )
fig = plt.figure( figsize=(12, 10 ) )
png = fig.add_subplot( 211 )
imgplot = plt.imshow( img )
ax = fig.add_subplot( 212 )
- x = moose.wildcardFind( '/model/#graphs/conc#/#' )
+ x = moose.wildcardFind( '/model/#graphs/conc#/#' )
dt = moose.element( '/clock' ).tickDt[18]
t = numpy.arange( 0, x[0].vector.size, 1 ) * dt
ax.plot( t, x[0].vector, 'r-', label=x[0].name )
@@ -87,4 +87,4 @@ def main():
# Run the 'main' if this script is executed standalone.
if __name__ == '__main__':
- main()
+ main()
diff --git a/moose-examples/tutorials/ChemicalOscillators/TuringOneDim.py b/moose-examples/tutorials/ChemicalOscillators/TuringOneDim.py
index 1860ceea32ee61e89b659f0359285c436032c006..4a202a639b7559e62af661627c3bbb1b3c46487f 100644
--- a/moose-examples/tutorials/ChemicalOscillators/TuringOneDim.py
+++ b/moose-examples/tutorials/ChemicalOscillators/TuringOneDim.py
@@ -160,7 +160,7 @@ def main():
fig.canvas.draw()
print( "Hit 'enter' to exit" )
- raw_input()
+ eval(input())
diff --git a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000.py b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000.py
index aa35d46965f8163d2866fdaaf758c067e8b6862b..14a205589352511411a89f10e9b14652f532fa08 100644
--- a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000.py
+++ b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000.py
@@ -159,11 +159,11 @@ class ExcInhNetBase:
t1 = time.time()
print('reinit MOOSE')
moose.reinit()
- print('reinit time t = ', time.time() - t1)
+ print(('reinit time t = ', time.time() - t1))
t1 = time.time()
print('starting')
moose.start(self.simtime)
- print('runtime, t = ', time.time() - t1)
+ print(('runtime, t = ', time.time() - t1))
if plotif:
self._plot()
diff --git a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian.py b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian.py
index 2c9859b3d3f4dd0c6e95a49a2d1aa8e95e7d454d..c67de7b37732cc84dad5799ef8f98810a34333d3 100644
--- a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian.py
+++ b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian.py
@@ -107,12 +107,12 @@ con_i = Synapses(Pi,neurons,'',pre='v_post+=-g*J',clock=clocksyn)
random.seed(100) # set seed for reproducibility of simulations
for i in range(0,N):
## draw excC number of neuron indices out of NmaxExc neurons
- preIdxs = random.sample(range(NE),excC)
+ preIdxs = random.sample(list(range(NE)),excC)
## connect these presynaptically to i-th post-synaptic neuron
for synnum,preIdx in enumerate(preIdxs):
con_e[preIdx,i]=True
## draw inhC=C-excC number of neuron indices out of inhibitory neurons
- preIdxs = random.sample(range(N-NE),C-excC)
+ preIdxs = random.sample(list(range(N-NE)),C-excC)
## connect these presynaptically to i-th post-synaptic neuron
for synnum,preIdx in enumerate(preIdxs):
con_i[preIdx,i]=True
@@ -135,21 +135,21 @@ popm_e = PopulationRateMonitor(Pe,bin=1.*ms)
popm_i = PopulationRateMonitor(Pi,bin=1.*ms)
# voltage monitor
-sm_e_vm = StateMonitor(Pe,'v',record=range(10),clock=clocknrn)
+sm_e_vm = StateMonitor(Pe,'v',record=list(range(10)),clock=clocknrn)
# ###########################################
# Simulate
# ###########################################
-print "Setup complete, running for",simtime,"at dt =",dt,"s."
+print(("Setup complete, running for",simtime,"at dt =",dt,"s."))
t1 = time.time()
run(simtime,report='text')
-print 'inittime + runtime, t = ', time.time() - t1
+print(('inittime + runtime, t = ', time.time() - t1))
-print "For g,J =",g,J,"mean exc rate =",\
- sm_e.nspikes/float(Nmon_exc)/(simtime/second),'Hz.'
-print "For g,J =",g,J,"mean inh rate =",\
- sm_i.nspikes/float(Nmon-Nmon_exc)/(simtime/second),'Hz.'
+print(("For g,J =",g,J,"mean exc rate =",\
+ sm_e.nspikes/float(Nmon_exc)/(simtime/second),'Hz.'))
+print(("For g,J =",g,J,"mean inh rate =",\
+ sm_i.nspikes/float(Nmon-Nmon_exc)/(simtime/second),'Hz.'))
# ###########################################
# Analysis functions
diff --git a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2.py b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2.py
index c4c777014ad8b966e5ff57a9c3754b68c809441c..8f854a6d746f9e42e394fd83ae86adb96da72204 100644
--- a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2.py
+++ b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2.py
@@ -107,9 +107,9 @@ conn_i = []
conn_j = []
for j in range(0,N):
## draw excC number of neuron indices out of NmaxExc neurons
- preIdxsE = random.sample(range(NE),excC)
+ preIdxsE = random.sample(list(range(NE)),excC)
## draw inhC=C-excC number of neuron indices out of inhibitory neurons
- preIdxsI = random.sample(range(NE,N),C-excC)
+ preIdxsI = random.sample(list(range(NE,N)),C-excC)
## connect these presynaptically to i-th post-synaptic neuron
## choose the synapses object based on whether post-syn nrn is exc or inh
conn_i += preIdxsE
@@ -132,17 +132,17 @@ sm = SpikeMonitor(P)
popm = PopulationRateMonitor(P)
# voltage monitor
-sm_vm = StateMonitor(P,'v',record=range(10)+range(NE,NE+10))
+sm_vm = StateMonitor(P,'v',record=list(range(10))+list(range(NE,NE+10)))
# ###########################################
# Simulate
# ###########################################
-print "Setup complete, running for",simtime,"at dt =",dt,"s."
+print(("Setup complete, running for",simtime,"at dt =",dt,"s."))
t1 = time.time()
run(simtime,report='text')
device.build(directory='output', compile=True, run=True, debug=False)
-print 'inittime + runtime, t = ', time.time() - t1
+print(('inittime + runtime, t = ', time.time() - t1))
#print "For g,J =",g,J,"mean exc rate =",\
# sm_e.num_spikes/float(NE)/(simtime/second),'Hz.'
@@ -201,7 +201,7 @@ title(str(N)+" exc & inh neurons")
xlim([0,simtime/second])
xlabel("")
-print "plotting firing rates"
+print("plotting firing rates")
subplot(232)
# firing rates
timeseries = arange(0,simtime/second+dt,dt)
@@ -227,7 +227,7 @@ ylim(0,300)
xlabel("Time (s)")
ylabel("Hz")
-print "plotting pop firing rates"
+print("plotting pop firing rates")
# Population firing rates
subplot(233)
timeseries = arange(0,simtime/second,dt)
diff --git a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2_slow_2pops_4syns.py b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2_slow_2pops_4syns.py
index 92b8f12230f9cad88e38809d3431f4d621b98411..dccfd6f51a594981566dd6a51ee5a6dc6fc51bea 100644
--- a/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2_slow_2pops_4syns.py
+++ b/moose-examples/tutorials/ExcInhNet/ExcInhNet_Ostojic2014_Brunel2000_brian2_slow_2pops_4syns.py
@@ -108,13 +108,13 @@ con_ii = Synapses(Pi,Pi,'',pre='v_post+=-g*J')
#con_i.connect_random(sparseness=sparseness_i)
## Connections from some Exc/Inh neurons to each neuron
random.seed(100) # set seed for reproducibility of simulations
-print "Creating connections (very slow, use the optimized script)"
+print("Creating connections (very slow, use the optimized script)")
for i in range(0,N):
- if i%100==0: print "Connecting post syn nrn",i
+ if i%100==0: print(("Connecting post syn nrn",i))
## draw excC number of neuron indices out of NmaxExc neurons
- preIdxsE = random.sample(range(NE),excC)
+ preIdxsE = random.sample(list(range(NE)),excC)
## draw inhC=C-excC number of neuron indices out of inhibitory neurons
- preIdxsI = random.sample(range(N-NE),C-excC)
+ preIdxsI = random.sample(list(range(N-NE)),C-excC)
## connect these presynaptically to i-th post-synaptic neuron
## choose the synapses object based on whether post-syn nrn is exc or inh
if i<NE:
@@ -141,21 +141,21 @@ popm_e = PopulationRateMonitor(Pe)
popm_i = PopulationRateMonitor(Pi)
# voltage monitor
-sm_e_vm = StateMonitor(Pe,'v',record=range(10))
+sm_e_vm = StateMonitor(Pe,'v',record=list(range(10)))
# ###########################################
# Simulate
# ###########################################
-print "Setup complete, running for",simtime,"at dt =",dt,"s."
+print(("Setup complete, running for",simtime,"at dt =",dt,"s."))
t1 = time.time()
run(simtime,report='text')
-print 'inittime + runtime, t = ', time.time() - t1
+print(('inittime + runtime, t = ', time.time() - t1))
-print "For g,J =",g,J,"mean exc rate =",\
- sm_e.num_spikes/float(NE)/(simtime/second),'Hz.'
-print "For g,J =",g,J,"mean inh rate =",\
- sm_i.num_spikes/float(NI)/(simtime/second),'Hz.'
+print(("For g,J =",g,J,"mean exc rate =",\
+ sm_e.num_spikes/float(NE)/(simtime/second),'Hz.'))
+print(("For g,J =",g,J,"mean inh rate =",\
+ sm_i.num_spikes/float(NI)/(simtime/second),'Hz.'))
# ###########################################
# Analysis functions
@@ -214,7 +214,7 @@ xlim([0,simtime/second])
title(str(NI)+" inh neurons")
subplot(232)
-print "plotting firing rates"
+print("plotting firing rates")
# firing rates
timeseries = arange(0,simtime/second+dt,dt)
num_to_plot = 10
@@ -239,7 +239,7 @@ ylim(0,300)
xlabel("Time (s)")
ylabel("Hz")
-print "plotting pop firing rates"
+print("plotting pop firing rates")
# Population firing rates
subplot(233)
timeseries = arange(0,simtime/second,dt)
diff --git a/moose-examples/tutorials/ExcInhNetCaPlasticity/ExcInhNet_HigginsGraupnerBrunel2014.py b/moose-examples/tutorials/ExcInhNetCaPlasticity/ExcInhNet_HigginsGraupnerBrunel2014.py
index 28f7cac23bafba27e0ec18d39dbc0d59d424ffa6..1340067d89d02122cc3d333469cdb6fbbaabc5c4 100644
--- a/moose-examples/tutorials/ExcInhNetCaPlasticity/ExcInhNet_HigginsGraupnerBrunel2014.py
+++ b/moose-examples/tutorials/ExcInhNetCaPlasticity/ExcInhNet_HigginsGraupnerBrunel2014.py
@@ -241,11 +241,11 @@ class ExcInhNetBase:
t1 = time.time()
print('reinit MOOSE -- takes a while ~20s.')
moose.reinit()
- print('reinit time t = ', time.time() - t1)
+ print(('reinit time t = ', time.time() - t1))
t1 = time.time()
print('starting run ...')
moose.start(self.simtime)
- print('runtime, t = ', time.time() - t1)
+ print(('runtime, t = ', time.time() - t1))
if plotif:
self._plot()
diff --git a/moose-examples/tutorials/Rdesigneur/rdes_ex3.2.py b/moose-examples/tutorials/Rdesigneur/rdes_ex3.2.py
index fc453ebdbbc876ca1d00253b8dfccbf9a76e6e95..e91f7898249c78688016dcb98c0e547b7101b430 100644
--- a/moose-examples/tutorials/Rdesigneur/rdes_ex3.2.py
+++ b/moose-examples/tutorials/Rdesigneur/rdes_ex3.2.py
@@ -62,7 +62,7 @@ rdes = rd.rdesigneur(
rdes.buildModel()
for i in moose.wildcardFind( "/model/elec/#/Na" ):
- print i.parent.name, i.Gbar
+ print(i.parent.name, i.Gbar)
moose.reinit()
diff --git a/moose-examples/unsorted/ksolve_with_heavy_load.py b/moose-examples/unsorted/ksolve_with_heavy_load.py
index f7bbd62cfcf3c47c32aedbb28e21189a4081ac39..5eff870ecfa2b0101517e130666d41e586a6a3d7 100644
--- a/moose-examples/unsorted/ksolve_with_heavy_load.py
+++ b/moose-examples/unsorted/ksolve_with_heavy_load.py
@@ -35,7 +35,7 @@ def add_table(elem):
def plot( numPlots ):
global records_
- toPlots = records_.keys()[0:numPlots]
+ toPlots = list(records_.keys())[0:numPlots]
newPlots = {}
for i in toPlots:
newPlots[i] = records_[i]
diff --git a/moose-examples/util/moogli_viewer.py b/moose-examples/util/moogli_viewer.py
index f48330c8746c84372641de5998d3b9c071f1fb99..ec1b71ccf7e77abb9e7920d2b4542d445098d5f9 100644
--- a/moose-examples/util/moogli_viewer.py
+++ b/moose-examples/util/moogli_viewer.py
@@ -38,12 +38,12 @@ class MorphologyEditor(moogli.MorphologyViewer):
self._timer = QtCore.QTimer(self)
def start(self):
- self._timer.timeout.connect(self.next)
+ self._timer.timeout.connect(self.__next__)
self._timer.start(0)
@QtCore.pyqtSlot()
def show(self):
- self._timer.timeout.connect(self.next)
+ self._timer.timeout.connect(self.__next__)
super(MorphologyEditor, self).show()
self._timer.start(0)
@@ -52,7 +52,7 @@ class MorphologyEditor(moogli.MorphologyViewer):
self._timer.stop()
super(MorphologyEditor, self).hide()
- def next(self):
+ def __next__(self):
self.frame()
info_id = self.select_info.get_id()
info_event = self.select_info.get_event_type()
@@ -175,7 +175,7 @@ class MoogliViewer(QWidget):
self.morphology = self.createMorphology(self.geometry)
self.morphology.set_compartment_order(
- map(lambda x : x.path, self.compartmentOrder)
+ [x.path for x in self.compartmentOrder]
)
self.vms = np.empty(len(self.compartmentOrder), dtype=np.float, order='C')
diff --git a/moose-examples/util/pymoose.py b/moose-examples/util/pymoose.py
index bea52516c96b6c182cab23989b1beb8db0830823..735883f388657e019553eb66d4014c6cbe0ac93d 100644
--- a/moose-examples/util/pymoose.py
+++ b/moose-examples/util/pymoose.py
@@ -34,12 +34,12 @@ def listmsg(pymoose_object):
"""Print a list of the messages on this object.
"""
- print 'Incoming messages:'
+ print('Incoming messages:')
for msg in pymoose_object.inMessages():
- print msg
- print 'Outgoing messages:'
+ print(msg)
+ print('Outgoing messages:')
for msg in pymoose_object.outMessages():
- print msg
+ print(msg)
#
# pymoose.py ends here