def test_anterograde_projections(self):
self.projections.show_anterograde_projections(200)
view = self.view
view.camera.setView([100, 1325, -387], ([0.5, 0.8650, 0.05], 174))
image_compare.capture_and_compare(view, "anterograde_projections.png")
def test_display_simulation_true(self):
view = rtneuron.engine.views[0]
view.attributes.display_simulation = False
rtneuron.engine.frame()
rtneuron.engine.waitFrame()
view.attributes.display_simulation = True
image_compare.capture_and_compare(view, 'view_attributes_with_sim.png')
def test_synaptic_projections(self):
self.projections.show_projections(range(200,310,10), range(400,510,10))
view = self.view
view.camera.setView([146, 1382, -566], ([0.694, 0.718, 0.0552], 175))
image_compare.capture_and_compare(view, "synaptic_projections.png")
def test_retrograde_projections(self):
self.projections.show_retrograde_projections(230)
view = self.view
view.camera.setView([-15, 1664, 381], ([-0.122, -0.114, 0.986], 84.5))
image_compare.capture_and_compare(view, "retrograde_projections.png")
def test_soma_mode(self):
self._handler.attributes.mode = RepresentationMode.SOMA
self._handler.update()
self.engine.frame()
tmp = image_compare.capture_temporary(self.view)
self._handler.apply(NeuronClipping().clipAll(False))
try:
image_compare.capture_and_compare(self.view,
tmp,
prepend_sample_path=False)
finally:
os.remove(tmp)
self._handler.attributes.mode = RepresentationMode.NO_DISPLAY
self._handler.update()
self.engine.frame()
tmp = image_compare.capture_temporary(self.view)
self._handler.apply(NeuronClipping().clipAll(True))
try:
image_compare.capture_and_compare(self.view,
tmp,
prepend_sample_path=False)
finally:
os.remove(tmp)
def test_by_distance_colormaps(self):
view = self.view
neuron = view.scene.objects[0]
neuron.attributes.color_scheme = \
rtneuron.ColorScheme.BY_DISTANCE_TO_SOMA
neuron.update()
image_compare.capture_and_compare(view,
'default_by_distance_coloring.png')
colormap = ColorMap()
colormap.setPoints({0: [0, 0, 1, 1], 100: [1, 0, 0, 1]})
neuron.attributes.colormaps = AttributeMap()
neuron.attributes.colormaps.by_distance_to_soma = colormap
neuron.update()
image_compare.capture_and_compare(view, 'by_distance_colormap1.png')
colormap.setPoints({0: [0, 0, 1, 1], 100: [1, 0, 0, 1],
200: [1, 0.5, 0, 1], 300: [1, 1, 0, 1]})
neuron.update()
image_compare.capture_and_compare(view, 'by_distance_colormap2.png')
colormap.setRange(0, 1000)
neuron.update()
image_compare.capture_and_compare(view, 'by_distance_colormap3.png')
neuron.attributes.colormaps = AttributeMap()
neuron.update()
image_compare.capture_and_compare(view,
'default_by_distance_coloring.png')
def test_set_get_projectionPerspective(self):
# Pre-computed value to adjust the scene content to the view limits
fov = 23.13
self.view.camera.setProjectionPerspective(fov)
image_compare.capture_and_compare(self.view,
'camera_projectionPerspective.png',
threshold=2.0)
def test_set_get_view(self):
position = [30, 600, 300]
orientation = ([0, 0, 1], 0)
assert (self.view.camera.getView() != (position, orientation))
self.view.camera.setView(position, orientation)
assert (self.view.camera.getView() == (position, orientation))
image_compare.capture_and_compare(self.view, "camera_setView.png")
def test_by_width_colormaps(self):
view = self.view
neuron = view.scene.objects[0]
neuron.attributes.color_scheme = rtneuron.ColorScheme.BY_WIDTH
neuron.update()
image_compare.capture_and_compare(view, 'default_by_width_coloring.png')
colormap = ColorMap()
colormap.setPoints({0: [1, 0, 0, 1], 30: [1, 1, 1, 1]})
neuron.attributes.colormaps = AttributeMap()
neuron.attributes.colormaps.by_width = colormap
neuron.update()
image_compare.capture_and_compare(view, 'by_width_colormap1.png')
colormap.setPoints({0: [1, 0, 0, 1], 5: [1, 0.5, 0, 1],
10: [1, 1, 0, 1], 30: [1, 1, 1, 1]})
neuron.update()
image_compare.capture_and_compare(view, 'by_width_colormap2.png')
colormap.setRange(0, 15)
neuron.update()
image_compare.capture_and_compare(view, 'by_width_colormap3.png')
neuron.attributes.colormaps = AttributeMap()
neuron.update()
image_compare.capture_and_compare(view, 'default_by_width_coloring.png')
def test_add_with_color_flat(self):
attributes = AttributeMap()
attributes.color = [1, 0, 0, 1]
attributes.flat = True
self.scene.addModel(cube_path, attributes=attributes)
image_compare.capture_and_compare(self.view, "red_cube.png")
def test_multiple_clip_1(self):
clipping = NeuronClipping()
for i in range(500):
clipping.clip([i], [0.0], [0.5])
self._handler.apply(clipping)
image_compare.capture_and_compare(
self.view, self._prefix + "simple_clip.png")
def test_unclip(self):
self._handler.apply(NeuronClipping().clipAll(True))
self._handler.apply(NeuronClipping().unclip(
range(1, 501), [0.5] * 500, [1.0] * 500))
# This result must match the result from test_clip
image_compare.capture_and_compare(
self.view, self._prefix + "simple_clip.png")
def test_compartment_report_rules2(self):
apply_compartment_report(self.simulation, self.view, "allCompartments")
apply_spike_data(self._spikefile.name, self.view)
self.engine.player.window = [0, 6]
self.switch_mode(RepresentationMode.SOMA)
self.engine.player.timestamp = 5
image_compare.capture_and_compare(
self.view, "compartment_simulation_t5_somas.png")
def test_add_and_change_color(self):
self.scene.addModel(cube_path)
cube = self.scene.objects[0]
cube.attributes.color = [1, 0, 0, 1]
cube.update()
image_compare.capture_and_compare(self.view, "red_cube.png")
def test_set_get_projectionOrtho(self):
left = bottom = -0.5
right = top = 0.5
self.view.camera.setProjectionOrtho(left, right, bottom, top, 1)
assert(self.view.camera.getProjectionOrtho() ==
(left, right, bottom, top))
image_compare.capture_and_compare(
self.view,'camera_projectionOrtho.png', threshold=2.0)
def test_lod_bias_0(self):
view = rtneuron.engine.views[0]
view.attributes.lod_bias = 1
rtneuron.engine.frame()
rtneuron.engine.waitFrame()
view.attributes.lod_bias = 0
image_compare.capture_and_compare(view,
'view_attributes_lod_bias_0.png')
def test_add_modify_clip_plane(self):
view = self.view
view.scene.setClipPlane(0, [0, 0, -1, 0])
view.scene.setClipPlane(1, [-1, 0, 0, 0])
self.engine.frame()
view.scene.setClipPlane(0, [0, 0, -1, 75 + 32.00001])
view.scene.setClipPlane(1, [-1, 0, 0, 74 + 34])
image_compare.capture_and_compare(view, "scene_clipping3.png")
def test_multiple_unclip_2(self):
self._handler.apply(NeuronClipping().clipAll(True))
clipping = NeuronClipping()
for i in range(1, 501):
self._handler.apply(NeuronClipping().unclip([i], [0.5], [1.0]))
self._handler.apply(clipping)
image_compare.capture_and_compare(
self.view, self._prefix + "simple_clip.png")
def test_res_snapshot(self):
# So results are not GPU/drivers dependant
self.view.attributes.idle_AA_steps = 32
snapshot_with_res = self.view_snapshot((512, 512))
neurons = self.scene.objects[0]
neurons.attributes.mode = rtneuron.RepresentationMode.SOMA
image_compare.capture_and_compare(
self.view, 'snapshot_sized.png', 1, snapshot_with_res)
def run_lod_test(self, scene_name):
scene = self.scenes[scene_name]
self.view.scene = scene
self.engine.frame()
scene.highlight([406], True)
file_name = 'lod_' + scene_name + '.png'
image_compare.capture_and_compare(self.view, file_name)
def run_lod_test(self, scene_name):
scene = self.scenes[scene_name]
self.view.scene = scene
apply_compartment_report(self.simulation, self.view, "allCompartments")
self.engine.frame()
scene.highlight([406], True)
file_name = 'lod_' + scene_name + '_with_sim_and_highlight.png'
image_compare.capture_and_compare(self.view, file_name)
def test_subset_attributes1(self):
image_compare.capture_and_compare(self.view,
"spike_simulation_t1_somas.png")
subset = self.scene.objects[0].query(self._gids[0::2])
subset.attributes.color = [1, 0, 0, 1]
subset.update()
image_compare.capture_and_compare(self.view,
"half_red_half_white_somas.png")
def test_add_remove(self):
handler = self.scene.addModel(cube_path)
tmp = image_compare.capture_temporary(self.view)
try:
self.scene.remove(handler)
image_compare.capture_and_compare(self.view, 'empty.png', 1, tmp)
except:
os.remove(tmp)
def test_axon_mode_protected(self):
tmp = image_compare.capture_temporary(self.view)
self._handler.apply(NeuronClipping().unclipAll())
try:
image_compare.capture_and_compare(
self.view, tmp, prepend_sample_path = False)
finally:
os.remove(tmp)
def do_test_color_scheme_change(self, first, second):
self.add_neurons(first)
# Making sure the scene is displayed before the mode is changed
for i in range(2):
self._engine.frame()
self._engine.waitFrame()
self.change_coloring(second)
image_compare.capture_and_compare(
self._view, "coloring_%s.png" % str(second).lower())
def test_set_get_projectionFrustum(self):
left = bottom = -0.5
right = top = 0.5
near = 1
self.view.camera.setProjectionFrustum(left, right, bottom, top, near)
assert(self.view.camera.getProjectionFrustum() ==
(left, right, bottom, top, near))
image_compare.capture_and_compare(
self.view,'camera_projectionFrustum.png', threshold=2.0)
def test_soma_to_detailed(self):
apply_compartment_report(self.simulation, self.view, "allCompartments")
self.engine.player.window = [0, 10]
self.engine.player.timestamp = 5
self.engine.frame()
self.switch_mode(RepresentationMode.WHOLE_NEURON)
image_compare.capture_and_compare(self.view,
"compartment_simulation_t5.png")
def test_clip_chain_1(self):
tmp = image_compare.capture_temporary(self.view)
self._handler.apply(
NeuronClipping().clipAll()
.unclip(range(500), [0] * 500, [1.0] * 500))
try:
image_compare.capture_and_compare(
self.view, tmp, prepend_sample_path = False)
finally:
os.remove(tmp)
def test_clip(self):
self._handler.apply(NeuronClipping().clip(
range(500), [0.0] * 500, [0.5] * 500))
# Rendering at least one frame to make sure the scene is not empty for
# the snapshot.
self.engine.frame()
self.engine.waitFrame()
image_compare.capture_and_compare(
self.view, self._prefix + "simple_clip.png")
def test_axon_spikes(self):
apply_spike_data(self._spikefile.name, self.view)
self.engine.player.window = [0, 10]
self.view.camera.setView([-187, 481, 880], ([0.0, 0.0, 1.0], 0.0))
self.engine.player.timestamp = 4.5
self.view.attributes.spike_tail = 1
image_compare.capture_and_compare(
self.view, "spike_simulation_t4.5_d1_axons.png")
self.view.attributes.spike_tail = 2
image_compare.capture_and_compare(
self.view, "spike_simulation_t4.5_d2_axons.png")
