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Benjamin Cumming authored
Make the `cable_cell` interface read only by passing the decorations to its constructor in a new `decor` type. C++ library * Remove the paint/place/set_default interface from `cable_cell` * Create a `decor` type that: * stores lists of paintings and placings * stores a set of cable cell parameters * uses the `paint`, `place`, `set_default` interface that was deprecated from `cable_cell`. * Create `paintable`, `placeable` and `defaultable` variants that are sum types over the respective types that can be painted, placed and defaulted. * Remove the overloaded `cable_cell::paint`, `cable_cell::place`, `cable_cell::set_default` methods to single methods that consume the sum types. Unit Tests * Many small changes because many many tests use cable cell API. * There were no `cable_cell` unit tests! Not such a big deal, since cable_cell is tested implicitly in so many other tests * but I added cable_cell tests: not much at the moment but will quickly fill ...Unverifiedac63809f
single_cell_model.py 1.59 KiB
#!/usr/bin/env python3
import arbor
import pandas, seaborn # You may have to pip install these.
# (1) Create a morphology with a single (cylindrical) segment of length=diameter=6 μm
tree = arbor.segment_tree()
tree.append(arbor.mnpos, arbor.mpoint(-3, 0, 0, 3), arbor.mpoint(3, 0, 0, 3), tag=1)
# (2) Define the soma and its center
labels = arbor.label_dict({'soma': '(tag 1)',
'center': '(location 0 0.5)'})
# (3) Create cell and set properties
decor = arbor.decor()
decor.set_property(Vm=-40)
decor.paint('"soma"', 'hh')
decor.place('"center"', arbor.iclamp( 10, 2, 0.8))
decor.place('"center"', arbor.spike_detector(-10))
# (4) Create cell and the single cell model based on it
cell = arbor.cable_cell(tree, labels, decor)
# (5) Make single cell model.
m = arbor.single_cell_model(cell)
# (6) Attach voltage probe sampling at 10 kHz (every 0.1 ms).
m.probe('voltage', '"center"', frequency=10000)
# (7) Run simulation for 30 ms of simulated activity.
m.run(tfinal=30)
# (8) Print spike times.
if len(m.spikes)>0:
print('{} spikes:'.format(len(m.spikes)))
for s in m.spikes:
print('{:3.3f}'.format(s))
else:
print('no spikes')
# (8) Plot the recorded voltages over time.
print("Plotting results ...")
seaborn.set_theme() # Apply some styling to the plot
df = pandas.DataFrame({'t/ms': m.traces[0].time, 'U/mV': m.traces[0].value})
seaborn.relplot(data=df, kind="line", x="t/ms", y="U/mV",ci=None).savefig('single_cell_model_result.svg')
# (9) Optionally, you can store your results for later processing.
df.to_csv('single_cell_model_result.csv', float_format='%g')