def test():
from blenderneuron.quick import bn
with Blender():
self.assertTrue(bn.run_command("print('Test')") is None)
self.assertTrue(bn.run_command("return_value = 1+3") == 4)
self.assertTrue(
bn.run_command(
"return_value = 'Camera' in bpy.data.objects"))
def test():
from blenderneuron.quick import bn
with Blender():
from neuron import h
soma = h.Section(name="Soma")
soma.L = soma.diam = 10
bn.to_blender()
self.assertTrue(
bn.run_command(
"return_value = 'Soma' in bpy.data.objects"))
self.assertTrue(
bn.run_command(
"return_value = bpy.data.objects['Soma'].dimensions == mathutils.Vector((10.020000457763672, 10.0, 10.0))"
))
def test():
from blenderneuron.quick import bn
with Blender():
from neuron import h
h.load_file(test_hoc_file)
tc = h.TestCell()
bn.to_blender()
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[0].soma' in bpy.data.objects"
))
self.assertTrue(
bn.run_command(
"return_value = len([i for i in bpy.data.objects if 'dendrites' in i.name]) == 31"
))
def test():
from blenderneuron.quick import bn
with Blender():
from neuron import h
soma1 = h.Section(name="Soma1")
soma2 = h.Section(name="Soma2")
soma1.L = soma2.L = soma1.diam = soma2.diam = 5
bn.to_blender()
self.assertTrue(
bn.run_command(
"return_value = 'Soma1' in bpy.data.objects"))
self.assertTrue(
bn.run_command(
"return_value = 'Soma2' in bpy.data.objects"))
def test():
from blenderneuron.quick import bn
with Blender():
from neuron import h
h.load_file(test_hoc_file)
tc1 = h.TestCell()
tc2 = h.TestCell()
bn.to_blender()
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[0].soma' in bpy.data.objects"
))
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[1].soma' in bpy.data.objects"
))
def test():
from blenderneuron.quick import bn
with Blender(keep=False):
from neuron import h
h.load_file(test_hoc_file)
tc1 = h.TestCell()
tc2 = h.TestCell()
ic = h.IClamp(0.5, sec=tc1.soma)
ic.delay = 1
ic.dur = 3
ic.amp = 0.5
bn.prepare_for_collection()
bn.groups["all"]["3d_data"]["interaction_level"] = "Section"
bn.groups["all"]["3d_data"]["color_level"] = "Group"
h.run()
bn.to_blender()
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[0].soma' in bpy.data.objects"
))
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[1].soma' in bpy.data.objects"
))
self.assertTrue(
bn.run_command(
"return_value = 'allGroup' in bpy.data.materials"))
bn.run_command("bpy.data.scenes['Scene'].frame_current = 0")
self.assertEqual(
bn.run_command(
"return_value = bpy.data.materials['allGroup'].emit"),
0.0)
bn.run_command("bpy.data.scenes['Scene'].frame_current = 7")
self.assertEqual(
bn.run_command(
"return_value = bpy.data.materials['allGroup'].emit"),
1.069335699081421)
def test():
from blenderneuron.quick import bn
with Blender(keep=False):
from neuron import h
h.load_file(test_hoc_file)
tc = h.TestCell()
ic = h.IClamp(0.5, sec=tc.soma)
ic.delay = 1
ic.dur = 3
ic.amp = 0.5
bn.prepare_for_collection()
h.run()
bn.to_blender()
bn.run_command("bpy.data.scenes['Scene'].frame_current = 1;")
self.assertTrue(
bn.run_command(
"return_value = bpy.data.materials['TestCell[0].dendrites[9][0]'].emit"
) == 0.0)
bn.run_command("bpy.data.scenes['Scene'].frame_current = 7;")
self.assertTrue(
bn.run_command(
"return_value = bpy.data.materials['TestCell[0].dendrites[9][0]'].emit"
) == 2.0)
def test():
from blenderneuron.quick import bn
with Blender():
from neuron import h
h.load_file(test_hoc_file)
# Add one cell
tc1 = h.TestCell()
bn.to_blender()
# Check if it was exported
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[0].soma' in bpy.data.objects"
))
# Add a second cell
tc2 = h.TestCell()
# Refresh sections
bn.refresh()
bn.to_blender()
# Both cells should be in blender
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[0].soma' in bpy.data.objects"
))
self.assertTrue(
bn.run_command(
"return_value = 'TestCell[1].soma' in bpy.data.objects"
))
self.assertTrue(
bn.run_command(
"return_value = len([i for i in bpy.data.objects if 'soma' in i.name]) == 2"
))
def test():
from blenderneuron.quick import bn
with Blender(keep=False):
from neuron import h
s1 = h.Section(name="Soma1")
s2 = h.Section(name="Soma2")
s1.L = s1.diam = s2.L = s2.diam = 10
syn = h.Exp2Syn(0.5, sec=s2)
syn.g = 10
nc = h.NetCon(s1(0.5)._ref_v, syn, sec=s1)
nc.weight[0] = 1
bn.to_blender()
self.assertTrue(
bn.run_command(
"return_value = bpy.data.objects['SynapsesGroup'].dimensions == mathutils.Vector((4.0, 4.0, 101.02000427246094))"
))
