diff --git a/.travis.yml b/.travis.yml
index 66ddee2ae3a2afec20a9af28f00c09d7178aa600..7db143a8d465f93dd0da35ad150ed827165e6a01 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -143,6 +143,8 @@ install:
curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
python$PY get-pip.py
pip$PY --version
+ pip$PY install pandas
+ pip$PY install seaborn
fi
- if [[ ( "$WITH_PYTHON" == "true" ) && ( "$TRAVIS_OS_NAME" == "osx" ) ]]; then pip$PY install numpy; fi
- |
diff --git a/python/example/network_ring.py b/python/example/network_ring.py
index b7d2a9bc7bfede9af0b940237ee23bacd2ddef8b..e486c624a71b39f235f4f293743cb4d63d8f274d 100644
--- a/python/example/network_ring.py
+++ b/python/example/network_ring.py
@@ -1,4 +1,3 @@
-import sys
import arbor
import pandas, seaborn
from math import sqrt
@@ -109,9 +108,6 @@ print(f'{recipe}')
meters.checkpoint('recipe-create', context)
-decomp = arbor.partition_load_balance(recipe, context)
-print(f'{decomp}')
-
hint = arbor.partition_hint()
hint.prefer_gpu = True
hint.gpu_group_size = 1000
@@ -148,8 +144,12 @@ for sp in spike_recorder.spikes:
print(' ', sp)
# Plot the recorded voltages over time.
-df = pandas.DataFrame()
+print("Plotting results ...")
+df_list = []
for gid in range(ncells):
- for s in samplers[gid].samples(arbor.cell_member(gid,0)):
- df=df.append({'t/ms': s.time, 'U/mV': s.value, 'Cell': f"cell {gid}"}, ignore_index=True)
+ times = [s.time for s in samplers[gid].samples(arbor.cell_member(gid,0))]
+ volts = [s.value for s in samplers[gid].samples(arbor.cell_member(gid,0))]
+ df_list.append(pandas.DataFrame({'t/ms': times, 'U/mV': volts, 'Cell': f"cell {gid}"}))
+
+df = pandas.concat(df_list)
seaborn.relplot(data=df, kind="line", x="t/ms", y="U/mV",hue="Cell").savefig('network_ring_result.svg')
diff --git a/python/example/single_cell_model.py b/python/example/single_cell_model.py
index 5ef30b3ac4eabbad8568234889d13918a7c125d7..7634541773075f7f0b12cc38c043ebf4e4f184a6 100644
--- a/python/example/single_cell_model.py
+++ b/python/example/single_cell_model.py
@@ -1,4 +1,5 @@
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()
@@ -33,7 +34,7 @@ else:
print('no spikes')
# (8) Plot the recorded voltages over time.
-import pandas, seaborn # You may have to pip install these.
+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").savefig('single_cell_model_result.svg')
diff --git a/python/example/single_cell_multi_branch.py b/python/example/single_cell_multi_branch.py
index 444eb0b3f30d91b5d476a24d20dcd5051e1f8550..6bc6c013fe2e98dcd56f23023a6927a52d197864 100644
--- a/python/example/single_cell_multi_branch.py
+++ b/python/example/single_cell_multi_branch.py
@@ -91,6 +91,7 @@ m.probe('voltage', '"dtips"', 10000) # at the tips of the dendrites.
# Run simulation for 100 ms of simulated activity.
tfinal=100
m.run(tfinal)
+print("Simulation done.")
# Print spike times.
if len(m.spikes)>0:
@@ -101,8 +102,9 @@ else:
print('no spikes')
# Plot the recorded voltages over time.
+print("Plotting results...")
df = pandas.DataFrame()
for t in m.traces:
- df=df.append( pandas.DataFrame({'t/ms': t.time, 'U/mV': t.value, 'Location': t.location, "Variable": t.variable}) )
+ df=df.append(pandas.DataFrame({'t/ms': t.time, 'U/mV': t.value, 'Location': t.location, "Variable": t.variable}) )
seaborn.relplot(data=df, kind="line", x="t/ms", y="U/mV",hue="Location",col="Variable").savefig('single_cell_multi_branch_result.svg')
diff --git a/python/example/single_cell_swc.py b/python/example/single_cell_swc.py
index bb9429d3ca496968e422580e932adfbd53923aed..5136218b6f4982ff872bd92ef2c97d4a081af0fb 100644
--- a/python/example/single_cell_swc.py
+++ b/python/example/single_cell_swc.py
@@ -12,9 +12,16 @@ import arbor
from arbor import mechanism as mech
from arbor import location as loc
import pandas, seaborn
+import sys
# Load a cell morphology from an swc file.
-tree = arbor.load_swc('../../test/unit/swc/pyramidal.swc')
+# Example present here: ../../test/unit/swc/pyramidal.swc
+if len(sys.argv) < 2:
+ print("No SWC file passed to the program")
+ sys.exit(0)
+
+filename = sys.argv[1]
+tree = arbor.load_swc(filename)
# Define the regions and locsets in the model.
defs = {'soma': '(tag 1)', # soma has tag 1 in swc files.
@@ -45,7 +52,7 @@ cell.paint('"dend"', rL=500)
cell.place('"stim_site"', arbor.iclamp(3, 1, current=2))
cell.place('"stim_site"', arbor.iclamp(8, 1, current=4))
# Detect spikes at the soma with a voltage threshold of -10 mV.
-cell.place('"root"', arbor.spike_detector(-10))
+cell.place('"axon_end"', arbor.spike_detector(-10))
# Have one compartment between each sample point.
cell.compartments_on_segments()
@@ -62,6 +69,7 @@ m.probe('voltage', where='"axon_end"', frequency=50000)
# Simulate the cell for 15 ms.
tfinal=15
m.run(tfinal)
+print("Simulation done.")
# Print spike times.
if len(m.spikes)>0:
@@ -72,8 +80,11 @@ else:
print('no spikes')
# Plot the recorded voltages over time.
-df = pandas.DataFrame()
+print("Plotting results ...")
+df_list = []
for t in m.traces:
- df=df.append( pandas.DataFrame({'t/ms': t.time, 'U/mV': t.value, 'Location': t.location, "Variable": t.variable}) )
+ df_list.append(pandas.DataFrame({'t/ms': t.time, 'U/mV': t.value, 'Location': t.location, "Variable": t.variable}))
+
+df = pandas.concat(df_list)
seaborn.relplot(data=df, kind="line", x="t/ms", y="U/mV",hue="Location",col="Variable").savefig('single_cell_swc.svg')
diff --git a/scripts/travis/build.sh b/scripts/travis/build.sh
index b81f3ae6659164b242012675e136a40618531f09..8875dfca32364e16e55d5bff756bb0036a14f1aa 100755
--- a/scripts/travis/build.sh
+++ b/scripts/travis/build.sh
@@ -107,9 +107,14 @@ fi
if [[ "${WITH_PYTHON}" == "true" ]]; then
progress "Building python module"
- make pyarb -j4 || error "building pyarb"
+ make pyarb -j4 || error "building pyarb"
progress "Python unit tests"
- python$PY $python_path/test/unit/runner.py -v2 || error "running python unit tests (serial)"
+ python$PY $python_path/test/unit/runner.py -v2 || error "running python unit tests (serial)"
+ progress "Python examples"
+ python$PY $python_path/example/network_ring.py || error "running python network_ring example"
+ python$PY $python_path/example/single_cell_model.py || error "running python single_cell_model example"
+ python$PY $python_path/example/single_cell_multi_branch.py || error "running python single_cell_multi_branch example"
+ python$PY $python_path/example/single_cell_swc.py $base_path/test/unit/swc/pyramidal.swc || error "running python single_cell_swc example"
if [[ "${WITH_DISTRIBUTED}" = "mpi" ]]; then
if [[ "$TRAVIS_OS_NAME" = "osx" ]]; then
progress "Python distributed unit tests (MPI)"