def test_copy_group(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Load TestCell.hoc - create a group
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc1 = h.TestCell();')
# Load cell into first group
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# Create 2nd cell
ncn.client.run_command('tc2 = h.TestCell();')
# Add second group, and shift 2nd cell up by 5 um
bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"bpy.ops.blenderneuron.import_groups();"
"bpy.data.objects['TestCell[1].soma'].location[2] += 5;")
# Test group copying logic
group_int_granularity = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].interaction_granularity = 'Section';"
"bpy.context.scene.BlenderNEURON.groups_index = 1;"
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups[1];"
"group.copy_from_group = 'Group.000';"
"bpy.ops.blenderneuron.copy_from_group();"
"return_value = group.interaction_granularity;")
self.assertEqual(group_int_granularity, 'Section')
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_ugly_render_curves(self):
with NEURON(), CommNode("Control-NEURON", coverage=True) as ncn, \
Blender(), CommNode("Control-Blender", coverage=True) as bcn:
# Load TestCell.hoc
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc = h.TestCell();')
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# Non-smooth curves
bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].interaction_granularity = 'Cell';"
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].smooth_sections = False;"
"bpy.ops.blenderneuron.import_groups();")
# Non-smooth curves
bevel = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].interaction_granularity = 'Cell';"
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].as_lines = True;"
"bpy.ops.blenderneuron.import_groups();"
"return_value = bpy.data.curves['Group.000_bezier.001'].bevel_depth"
)
# Should have no bevel
self.assertEqual(bevel, 0)
def test_remove_cell_from_nrn(self):
with NEURON(), CommNode("Control-NEURON", coverage=True) as ncn, \
Blender(), CommNode("Control-Blender", coverage=True) as bcn:
# Load TestCell.hoc - create a group
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc1 = h.TestCell();')
# Load cell into first group and show it
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();"
"bpy.ops.blenderneuron.import_groups();")
# Create 2nd cell
ncn.client.run_command('tc2 = h.TestCell();')
# Delete the first cell from NRN
ncn.client.run_command('tc1 = None;' 'del tc1;')
# Add second group, check the number of ui cells
ui_cell_count = bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"bpy.ops.blenderneuron.import_groups();"
"return_value = len(bpy.context.scene.BlenderNEURON.groups[0].root_entries);"
)
self.assertEqual(ui_cell_count, 1)
# Get the name of the visible cell of the second group
ui_cell_name = bcn.client.run_command(
"return_value = bpy.context.scene.BlenderNEURON.groups[1].root_entries[0].name;"
)
self.assertEqual(ui_cell_name, "TestCell[1].soma")
def test_glare(self):
with NEURON(), CommNode("Control-NEURON", coverage=True) as ncn, \
Blender(), CommNode("Control-Blender", coverage=True) as bcn:
bcn.client.run_command('bpy.ops.blenderneuron.add_neon_effect();')
# Adding 2nd time should not fail either
bcn.client.run_command('bpy.ops.blenderneuron.add_neon_effect();')
def test_import_remove_import_again(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Load TestCell.hoc - create a group
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc = h.TestCell();')
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# Import the cell and check if created in correct location
x, y, z = bcn.client.run_command(
"bpy.ops.blenderneuron.import_groups();"
"return_value = list(bpy.data.objects['TestCell[0].soma'].location)"
)
self.assertAlmostEqual(x, 150, 1)
self.assertAlmostEqual(y, -176, 1)
self.assertAlmostEqual(z, 0, 1)
# Shift the cell up by 100 um
bcn.client.run_command(
"bpy.data.objects['TestCell[0].soma'].location = [150, -176, 100];"
)
# Re-Import the cell and check if overwrote the shift above
x, y, z = bcn.client.run_command(
"bpy.ops.blenderneuron.import_groups();"
"return_value = list(bpy.data.objects['TestCell[0].soma'].location)"
)
self.assertAlmostEqual(z, 0, 1)
# Shift the cell up again by 100 um
bcn.client.run_command(
"bpy.data.objects['TestCell[0].soma'].location = [150, -176, 100];"
)
# Remove the group, there should be no cell objects
count = bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_remove();"
"return_value = len([ob for ob in bpy.data.objects if 'TestCell[0].soma' in ob.name])"
)
# Add a new group, import it
x, y, z = bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"bpy.ops.blenderneuron.import_groups();"
"return_value = list(bpy.data.objects['TestCell[0].soma'].location)"
)
# The z position should be the original position (not shifted)
self.assertAlmostEqual(z, 0, 1)
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_save_groups(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Load TestCell.hoc - create a group
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc1 = h.TestCell();')
# Load cell into first group
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# Create 2nd cell
ncn.client.run_command('tc2 = h.TestCell();')
# Add second group, and shift 2nd cell up by 5 um
bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"bpy.ops.blenderneuron.import_groups();"
"bpy.data.objects['TestCell[1].soma'].location[2] += 5;")
file1 = 'test_group1.json'
file2 = 'test_group2.json'
try:
# Test group saving
bcn.client.run_command(
"groups = bpy.types.Object.BlenderNEURON_node.groups;"
"groups['Group.000'].to_file('" + file1 + "');"
"groups['Group.001'].to_file('" + file2 + "');")
# Read the saved files
import json
with open(file1) as f1, open(file2) as f2:
json1 = json.load(f1)
json2 = json.load(f2)
# check that correct cells were saved
self.assertEqual(json1['roots'][0]['name'], 'TestCell[0].soma')
self.assertEqual(json2['roots'][0]['name'], 'TestCell[1].soma')
# Check that the z-location was saved correctly
self.assertEqual(json1['roots'][0]['coords'][-1], 0)
# 2nd cell should be shifted up by 5um
self.assertEqual(json2['roots'][0]['coords'][-1], 5)
finally:
os.remove(file1)
os.remove(file2)
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_blender_coverage(self):
with NEURON(), Blender(), \
CommNode('Control-NEURON') as cn, \
CommNode("Control-Blender") as cb:
self.assertEqual(cn.client.ping(), 1)
self.assertEqual(cb.client.ping(), 1)
cn.client.end_code_coverage()
cb.client.end_code_coverage()
def test_simulator_settings_exchange(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# set settings in Blender and send to NEURON
bcn.client.run_command(
"params = bpy.data.scenes['Scene'].BlenderNEURON.simulator_settings;"
"params.neuron_tstop = 1111;"
"params.time_step = 0.002;"
"params.abs_tolerance = 0.005;"
"params.temperature = 44;"
"params.integration_method = '1';"
"bpy.ops.blenderneuron.sim_settings_to_neuron();"
"bpy.ops.blenderneuron.sim_settings_from_neuron();"
)
self.assertEqual(1111, bcn.client.run_command(
"params = bpy.data.scenes['Scene'].BlenderNEURON.simulator_settings;"
"return_value = params.neuron_tstop"
))
self.assertAlmostEqual(0.005, bcn.client.run_command(
"params = bpy.data.scenes['Scene'].BlenderNEURON.simulator_settings;"
"return_value = params.abs_tolerance"
), places=3)
self.assertEqual(44, bcn.client.run_command(
"params = bpy.data.scenes['Scene'].BlenderNEURON.simulator_settings;"
"return_value = params.temperature"
))
self.assertEqual('1', bcn.client.run_command(
"params = bpy.data.scenes['Scene'].BlenderNEURON.simulator_settings;"
"return_value = params.integration_method"
))
# Test fixed step integration
bcn.client.run_command(
"params = bpy.data.scenes['Scene'].BlenderNEURON.simulator_settings;"
"params.time_step = 0.002;"
"params.integration_method = '0';"
"bpy.ops.blenderneuron.sim_settings_to_neuron();"
"bpy.ops.blenderneuron.sim_settings_from_neuron();"
)
self.assertAlmostEqual(0.002, bcn.client.run_command(
"params = bpy.data.scenes['Scene'].BlenderNEURON.simulator_settings;"
"return_value = params.time_step"
), places=3)
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_can_connect_to_neuron(self):
# Start Blender with a running node
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# See if Blender is able to connect to the NEURON process node
result = bcn.client.run_command("return_value = str(bpy.types.Object.BlenderNEURON_node.client)")
self.assertIn("Proxy", result)
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_mpi(self):
with NEURON(), CommNode("Control-NEURON", coverage=True) as ncn, \
Blender(), CommNode("Control-Blender", coverage=True) as bcn:
# Load TestCell.hoc - create a cell name:mpi rank map
ncn.client.run_command(
'h.load_file("tests/TestCell.hoc");'
'tc = h.TestCell();'
'from blenderneuron.neuronstart import BlenderNEURON as bn_node;'
)
# Get section name before MPI map is provided
self.assertEqual(
ncn.client.run_command(
'return_value = bn_node.rank_section_name(tc.soma.name());'
), 'TestCell[0].soma')
# Provide MPI map
ncn.client.run_command(
'pc = h.ParallelContext();'
'single_rank_name = "TestCell[0]";'
'mpi_rank_name = "TestCell[0]";'
'mpimap = {};'
'mpimap[single_rank_name] = { "name": mpi_rank_name, "rank": pc.id() };'
'mpimap["TestCell[1]"] = { "name": mpi_rank_name, "rank": 2 };'
'bn_node.init_mpi(pc, mpimap);')
# Get section name after MPI init
self.assertEqual(
ncn.client.run_command(
'return_value = bn_node.rank_section_name(tc.soma.name());'
), 'TestCell[0].soma')
# Cell without a specific section
self.assertEqual(
ncn.client.run_command(
'return_value = bn_node.rank_section_name("TestCell[0]");'
), 'TestCell[0]')
# Try section that does not exist on the rank
self.assertEqual(
ncn.client.run_command(
'return_value = bn_node.rank_section_name("TestCell[1].soma");'
), None)
def test_error_handling(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
from xmlrpc.client import Fault
try:
bcn.client.run_command('1/0')
except Fault:
pass
try:
ncn.client.run_command('1/0')
except Fault:
pass
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_group_select_all_none_invert(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Create a few named root sections in NEURON
ncn.client.run_command('s1 = h.Section(name="soma1");'
's2 = h.Section(name="soma2");')
# Refresh the default cell group in Blender
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();"
)
# Check the group contains the two root sections
self.assertEqual(2, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = len(group.root_entries);"
))
# Unselect all, Check that no cells are selected
self.assertEqual(True, bcn.client.run_command(
"bpy.ops.blenderneuron.unselect_all_cells();"
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = all(cell.selected == False for cell in group.root_entries)"
))
# Select all, Check that all cells are selected
self.assertEqual(True, bcn.client.run_command(
"bpy.ops.blenderneuron.select_all_cells();"
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = all(cell.selected for cell in group.root_entries)"
))
# Unselect last cell, invert selection, and check that first cell is unselected
self.assertEqual(False, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"group.root_entries[-1].selected = False;"
"bpy.ops.blenderneuron.invert_cell_selection();"
"return_value = group.root_entries[0].selected"
))
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_simulator_run(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Create a root section in NEURON
ncn.client.run_command('s1 = h.Section(name="soma1");'
's1.insert("pas");'
's1.insert("hh");')
# Run the sim
bcn.client.run_command(
"bpy.ops.blenderneuron.init_and_run_neuron()"
)
# Check that sim time is advanced
self.assertAlmostEqual(5.0,
ncn.client.run_command('return_value=h.t'),
places=1)
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_remove_cells_groups(self):
with NEURON(), CommNode("Control-NEURON", coverage=True) as ncn, \
Blender(), CommNode("Control-Blender", coverage=True) as bcn:
# Load TestCell.hoc - create a group
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc1 = h.TestCell();')
# Load cell into first group
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# Create 2nd cell
ncn.client.run_command('tc2 = h.TestCell();')
# Add second group, and shift 2nd cell up by 5 um
group_count = bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"bpy.ops.blenderneuron.import_groups();"
"bpy.data.objects['TestCell[1].soma'].location[2] += 5;"
"return_value = len(bpy.context.scene.BlenderNEURON.groups);")
self.assertEqual(group_count, 2)
# Unselect 2nd cell from 2nd group and remove the empty group
group_count = bcn.client.run_command(
"bpy.context.scene.BlenderNEURON.groups[1].root_entries[1].selected = False;"
"bpy.ops.blenderneuron.cell_group_remove();"
"return_value = len(bpy.context.scene.BlenderNEURON.groups);")
self.assertEqual(group_count, 1)
# Remove the last group
group_count = bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_remove();"
"return_value = len(bpy.context.scene.BlenderNEURON.groups);")
self.assertEqual(group_count, 0)
def test_mpi_synset(self):
with NEURON(), CommNode("Control-NEURON", coverage=True) as ncn, \
Blender(), CommNode("Control-Blender", coverage=True) as bcn:
# Load TestCell.hoc - create a cell name:mpi rank map
ncn.client.run_command(
'h.load_file("tests/TestCell.hoc");'
'tc = h.TestCell();'
'from blenderneuron.neuronstart import BlenderNEURON as bn_node;'
'bn_node.update_section_index();')
# Provide MPI map - first cell on this rank, 2nd cell on another rank
ncn.client.run_command(
'pc = h.ParallelContext();'
'mpimap = {};'
'mpimap["TestCell[0]"] = { "name": "TestCell[0]", "rank": 0 };'
'mpimap["TestCell[1]"] = { "name": "TestCell[1]", "rank": 1 };'
'bn_node.init_mpi(pc, mpimap);')
ncn.client.run_command('from json import load;'
'f = open("tests/test_synset.json");'
'bn_node.create_synapses(load(f));'
'f.close();')
def test_add_remove_group_and_cells(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Create a few named root sections in NEURON
ncn.client.run_command('s1 = h.Section(name="soma1");'
's2 = h.Section(name="soma2");')
# Check that a default group was added
self.assertEqual([1, 0], bcn.client.run_command(
"groups = bpy.data.scenes['Scene'].BlenderNEURON.groups;"
"count = len(groups);"
"index = bpy.data.scenes['Scene'].BlenderNEURON.groups_index;"
"return_value = [count, index];"
))
# Refresh the list after adding the cells - this should not break the later tests
# Check that there are 2 cells within the group
self.assertEqual(2, bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();"
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = len(group.root_entries);"
))
# The last cell listed is the last cell created
self.assertEqual("soma2", bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = group.root_entries[-1].name"
))
# Check that both cells are selected
self.assertEqual(True, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = all(cell.selected for cell in group.root_entries)"
))
# Create a second cell group
# Check that a group was added
self.assertEqual(2, bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"return_value = len(bpy.data.scenes['Scene'].BlenderNEURON.groups)"
))
# Check that there are 2 cells within the 2nd group
self.assertEqual(2, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups[1];"
"return_value = len(group.root_entries)"
))
# Check that NONE of the cells are selected in 2nd group
self.assertEqual(True, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups[1];"
"return_value = all(cell.selected == False for cell in group.root_entries)"
))
# Select the last cell of the *2nd* group
# Check that the last cell of the *1st* group becomes unselected
self.assertEqual(False, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups[1];"
"group.root_entries[-1].selected = True;"
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = group.root_entries[-1].selected"
))
# Now select the first cell of the 2nd group (both cells should be selected)
# Delete the second cell group (this should free the 2nd group's cells)
# Check that a group was removed
self.assertEqual(1, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups[1];"
"group.root_entries[0].selected = True;"
"bpy.ops.blenderneuron.cell_group_remove();"
"return_value = len(bpy.data.scenes['Scene'].BlenderNEURON.groups)"
))
# Add a new cell group (it should now contain the free'd cells)
# Check that a group was added
self.assertEqual(2, bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"return_value = len(bpy.data.scenes['Scene'].BlenderNEURON.groups)"
))
# Check that both cells are selected
self.assertEqual(True, bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups[1];"
"return_value = all(cell.selected for cell in group.root_entries)"
))
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_server_established(self):
# Start Blender with a running node
with Blender(), CommNode("Control-Blender") as bcn:
self.assertEqual(bcn.client.ping(), 1)
bcn.client.end_code_coverage()
def test_find_synapses(self):
with NEURON(), CommNode("Control-NEURON", coverage=True) as ncn, \
Blender(), CommNode("Control-Blender", coverage=True) as bcn:
# Load TestCell.hoc - create a group
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc1 = h.TestCell();')
# Load cell into first group
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# Create 2nd cell
ncn.client.run_command('tc2 = h.TestCell();')
# Add second group, and shift 2nd cell up by 5 um
bcn.client.run_command(
"bpy.ops.blenderneuron.cell_group_add();"
"bpy.ops.blenderneuron.import_groups();"
"bpy.data.objects['TestCell[1].soma'].location[2] += 5;")
# Setup synapse former to look for synapses between the two cells
syn_count = bcn.client.run_command(
"syn_set = bpy.data.scenes['Scene'].BlenderNEURON.synapse_sets[0];"
"syn_set.section_pattern_source = '*dend*';"
"syn_set.group_dest = 'Group.001';"
"syn_set.is_reciprocal = True;"
"syn_set.create_spines = True;"
"syn_set.use_radius = False;"
"syn_set.max_syns_per_pt = 1;"
"bpy.ops.blenderneuron.find_synapse_locations();"
"return_value = len(bpy.data.objects['SynapsePreview'].data.splines)"
)
self.assertEqual(syn_count, 32)
# There should be no synapses when max search distance is very small
syn_count = bcn.client.run_command(
"syn_set = bpy.data.scenes['Scene'].BlenderNEURON.synapse_sets[0];"
"syn_set.max_distance = 1;"
"bpy.ops.blenderneuron.find_synapse_locations();"
"return_value = len(bpy.data.objects['SynapsePreview'].data.splines)"
)
self.assertEqual(syn_count, 0)
# When using radius, it should find the same synapses at a shortened distance
syn_count = bcn.client.run_command(
"syn_set = bpy.data.scenes['Scene'].BlenderNEURON.synapse_sets[0];"
"syn_set.use_radius = True;"
"syn_set.max_distance = 4;"
"bpy.ops.blenderneuron.find_synapse_locations();"
"return_value = len(bpy.data.objects['SynapsePreview'].data.splines)"
)
self.assertEqual(syn_count, 32)
# Sub-divide the cell sections in NEURON
ncn.client.run_command(
"[setattr(sec,'nseg', 10) for sec in h.allsec()];")
# And create the found synapses
bcn.client.run_command("bpy.ops.blenderneuron.create_synapses();")
# check if the syns were created correctly in NEURON
syn1_sec, syn1_x = ncn.client.run_command(
'seg = h.ExpSyn[0].get_segment();'
'return_value = (seg.sec.name(), seg.x);')
self.assertEqual(syn1_sec, 'TestCell[1].dendrites[4]')
self.assertEqual(syn1_x, 0.95) # middle of the 10th segment = 0.95
syn2_sec, syn2_x = ncn.client.run_command(
'seg = h.ExpSyn[1].get_segment();'
'return_value = (seg.sec.name(), seg.x);')
self.assertEqual(syn2_sec, 'SynapseSet_001_Spine[0].head')
self.assertEqual(syn2_x, 0.5) # middle of the spine head
# Save the found synapses into a JSON file
syn_file = 'syn_test.json'
bcn.client.run_command(
"bpy.context.scene.BlenderNEURON.synapse_set.save_synapses('" +
syn_file + "');")
import json
with open(syn_file) as f:
syns = json.load(f)
import os
try:
os.remove(syn_file)
except:
pass
self.assertEqual(syns['entries'][0]['dest_section'],
'TestCell[1].dendrites[4]')
self.assertEqual(syns['entries'][0]['source_section'],
'TestCell[0].dendrites[4]')
self.assertEqual(syns['entries'][0]['dest_x'], 1.0)
self.assertEqual(syns['entries'][0]['source_x'], 1.0)
# Test renaming logic
syn_set_name = bcn.client.run_command(
"syn_set = bpy.data.scenes['Scene'].BlenderNEURON.synapse_sets[0];"
"syn_set.name = 'TEST_NAME';"
"return_value = syn_set.name;")
self.assertEqual(syn_set_name, 'TEST_NAME')
def test_import_export_cell(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Load TestCell.hoc - create a group
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc = h.TestCell();')
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# Check that the cell was loaded
self.assertEqual(
"TestCell[0].soma",
bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups['Group.000'];"
"return_value = group.root_entries[0].name"))
# Import the cell and check if created in correct location
x, y, z = bcn.client.run_command(
"bpy.ops.blenderneuron.import_groups();"
"return_value = list(bpy.data.objects['TestCell[0].soma'].location)"
)
self.assertAlmostEqual(x, 150, 1)
self.assertAlmostEqual(y, -176, 1)
self.assertAlmostEqual(z, 0, 1)
# And cell bounding box dimensions are correct
dim_x, dim_y, dim_z = bcn.client.run_command(
"return_value = list(bpy.data.objects['TestCell[0].soma'].dimensions)"
)
self.assertAlmostEqual(dim_x, 165.45, 1)
self.assertAlmostEqual(dim_y, 165.80, 1)
self.assertAlmostEqual(dim_z, 1, 0)
# Shift the cell up by 100 um, and export to NRN
bcn.client.run_command(
"bpy.data.objects['TestCell[0].soma'].location = [150, -176, 100];"
"bpy.ops.blenderneuron.update_groups_with_view_data();"
"bpy.ops.blenderneuron.export_groups();")
# Test if coordinates in NRN changed by same amount
z_soma, z_dend1, z_dend2 = ncn.client.run_command(
'return_value = [h.z3d(0,sec=tc.soma), h.z3d(0,sec=tc.dendrites[-1]), h.z3d(0,sec=tc.dendrites[15])]'
)
self.assertEqual(z_soma, 100.0)
self.assertEqual(z_soma, z_dend1)
self.assertEqual(z_dend1, z_dend2)
# Re-import the cell and check if change persists
x, y, z = bcn.client.run_command(
"bpy.ops.blenderneuron.import_groups();"
"return_value = list(bpy.data.objects['TestCell[0].soma'].location)"
)
self.assertAlmostEqual(z, 100, 1)
# And that duplicate objects were not created
count = bcn.client.run_command(
"cellObjs = [ob for ob in bpy.data.objects if 'TestCell[0].soma' in ob.name];"
"return_value = len(cellObjs)")
self.assertEqual(count, 1)
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
def test_object_levels(self):
with NEURON(), CommNode("Control-NEURON") as ncn, \
Blender(), CommNode("Control-Blender") as bcn:
# Load TestCell.hoc - and add somatic stimulus
ncn.client.run_command('h.load_file("tests/TestCell.hoc");'
'tc = h.TestCell();'
'ic = h.IClamp(0.5);'
'ic.amp = 1; ic.delay = 1; ic.dur = 10;')
bcn.client.run_command(
"bpy.ops.blenderneuron.get_cell_list_from_neuron();")
# ----------------- Cell level objects --------------- #
soma_object_exists, dendrite_object_exists = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].interaction_granularity = 'Cell';"
"bpy.ops.blenderneuron.import_groups();"
"objs = bpy.data.objects;"
"return_value = ('TestCell[0].soma' in objs, 'TestCell[0].dendrites[0]' in objs);"
)
self.assertTrue(soma_object_exists)
self.assertFalse(dendrite_object_exists)
# Import animation - animate WHOLE CELL
soma_mat_exists, dendrite_mat_exists, = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].record_activity = True;"
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].recording_granularity = 'Cell';"
"bpy.ops.blenderneuron.import_groups();"
"mats = bpy.data.materials;"
"return_value = ('TestCell[0].soma' in mats, 'TestCell[0].dendrites[0]' in mats);"
)
self.assertTrue(soma_mat_exists)
self.assertFalse(dendrite_mat_exists)
soma_emission_start, soma_emission_end, = bcn.client.run_command(
"mats = bpy.data.materials;"
"bpy.context.scene.frame_set(0);"
"start_emit = mats['TestCell[0].soma'].emit;"
"bpy.context.scene.frame_set(5);"
"end_emit = mats['TestCell[0].soma'].emit;"
"return_value = (start_emit, end_emit);")
self.assertGreater(soma_emission_start, 0)
self.assertGreater(soma_emission_end, soma_emission_start)
# Import animation - animate EACH SECTION
soma_mat_exists, dendrite_mat_exists, = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].record_activity = True;"
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].recording_granularity = 'Section';"
"bpy.ops.blenderneuron.import_groups();"
"mats = bpy.data.materials;"
"return_value = ('TestCell[0].soma' in mats, 'TestCell[0].dendrites[0]' in mats);"
)
self.assertTrue(soma_mat_exists)
self.assertTrue(dendrite_mat_exists)
dend_emission_start, dend_emission_end, = bcn.client.run_command(
"mats = bpy.data.materials;"
"bpy.context.scene.frame_set(0);"
"start_emit = mats['TestCell[0].dendrites[0]'].emit;"
"bpy.context.scene.frame_set(5);"
"end_emit = mats['TestCell[0].dendrites[0]'].emit;"
"return_value = (start_emit, end_emit);")
self.assertGreater(dend_emission_start, 0)
self.assertGreater(dend_emission_end, dend_emission_start)
# --------------- Section level objects ------------------- #
soma_object_exists, dendrite_object_exists = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].interaction_granularity = 'Section';"
"bpy.ops.blenderneuron.import_groups();"
"objs = bpy.data.objects;"
"return_value = ('TestCell[0].soma' in objs, 'TestCell[0].dendrites[0]' in objs);"
)
self.assertTrue(soma_object_exists)
self.assertTrue(dendrite_object_exists)
# Import animation - animate WHOLE CELL
soma_mat_exists, dendrite_mat_exists, = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].record_activity = True;"
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].recording_granularity = 'Cell';"
"bpy.ops.blenderneuron.import_groups();"
"mats = bpy.data.materials;"
"return_value = ('TestCell[0].soma' in mats, 'TestCell[0].dendrites[0]' in mats);"
)
self.assertTrue(soma_mat_exists)
self.assertFalse(dendrite_mat_exists)
soma_emission_start, soma_emission_end, = bcn.client.run_command(
"mats = bpy.data.materials;"
"bpy.context.scene.frame_set(0);"
"start_emit = mats['TestCell[0].soma'].emit;"
"bpy.context.scene.frame_set(5);"
"end_emit = mats['TestCell[0].soma'].emit;"
"return_value = (start_emit, end_emit);")
self.assertGreater(soma_emission_start, 0)
self.assertGreater(soma_emission_end, soma_emission_start)
# Import animation - animate EACH SECTION
soma_mat_exists, dendrite_mat_exists, = bcn.client.run_command(
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].record_activity = True;"
"bpy.data.scenes['Scene'].BlenderNEURON.groups[0].recording_granularity = 'Section';"
"bpy.ops.blenderneuron.import_groups();"
"mats = bpy.data.materials;"
"return_value = ('TestCell[0].soma' in mats, 'TestCell[0].dendrites[0]' in mats);"
)
self.assertTrue(soma_mat_exists)
self.assertTrue(dendrite_mat_exists)
dend_emission_start, dend_emission_end, = bcn.client.run_command(
"mats = bpy.data.materials;"
"bpy.context.scene.frame_set(0);"
"start_emit = mats['TestCell[0].dendrites[0]'].emit;"
"bpy.context.scene.frame_set(5);"
"end_emit = mats['TestCell[0].dendrites[0]'].emit;"
"return_value = (start_emit, end_emit);")
self.assertGreater(dend_emission_start, 0)
self.assertGreater(dend_emission_end, dend_emission_start)
# Test group renaming logic
group_name = bcn.client.run_command(
"group = bpy.data.scenes['Scene'].BlenderNEURON.groups[0];"
"group.name = 'TEST_GROUP';"
"return_value = group.name;")
self.assertEqual(group_name, 'TEST_GROUP')
bcn.client.end_code_coverage()
ncn.client.end_code_coverage()
