def get_spatial_equation_chart(self, **form_data):
"""
Returns the HTML which contains the chart in which is plotted the temporal equation.
"""
try:
min_x, max_x, ui_message = self.get_x_axis_range(
form_data['min_space_x'], form_data['max_space_x'])
surface_stimulus_creator = self.get_creator_and_interface(
SURFACE_STIMULUS_CREATOR_MODULE,
SURFACE_STIMULUS_CREATOR_CLASS, StimuliSurface())[0]
form_data = surface_stimulus_creator.prepare_ui_inputs(
form_data, validation_required=False)
equation = surface_stimulus_creator.get_spatial_equation(form_data)
series_data, display_ui_message = equation.get_series_data(
min_range=min_x, max_range=max_x)
json_data = self.get_series_json(series_data, "Spatial")
all_series = self.build_final_json([json_data])
ui_message = ''
if display_ui_message:
ui_message = self.get_ui_message(["spatial"])
return {
'allSeries': all_series,
'prefix': 'spatial',
'message': ui_message
}
except NameError, ex:
self.logger.exception(ex)
return {
'allSeries': None,
'errorMsg': "Incorrect parameters for equation passed."
}
def get_input_tree(self):
"""
Returns the input interface for this adapter.
"""
stimuli_surface = StimuliSurface()
stimuli_surface.trait.bound = interface.INTERFACE_ATTRIBUTES_ONLY
inputList = stimuli_surface.interface[interface.INTERFACE_ATTRIBUTES]
return inputList
def view_stimulus(self, focal_points):
"""
Just create the stimulus to view the actual data, don't store to db.
Hold the entity in session without the surface, so the next time you need
data just get from that one.
"""
try:
context = common.get_from_session(KEY_SURFACE_CONTEXT)
context.set_focal_points(focal_points)
kwargs = copy.deepcopy(context.equation_kwargs)
surface_stimulus_creator = self.get_creator_and_interface(
SURFACE_STIMULUS_CREATOR_MODULE,
SURFACE_STIMULUS_CREATOR_CLASS, StimuliSurface())[0]
min_time = float(kwargs.get('min_tmp_x', 0))
max_time = float(kwargs.get('max_tmp_x', 100))
kwargs = surface_stimulus_creator.prepare_ui_inputs(kwargs)
stimulus = surface_stimulus_creator.launch(**kwargs)
surface_gid = common.get_from_session(PARAM_SURFACE)
surface = ABCAdapter.load_entity_by_gid(surface_gid)
stimulus.surface = surface
stimulus.configure_space()
time = numpy.arange(min_time, max_time, 1)
time = time[numpy.newaxis, :]
stimulus.configure_time(time)
data = []
max_value = numpy.max(stimulus())
min_value = numpy.min(stimulus())
for i in range(min(CHUNK_SIZE,
stimulus.temporal_pattern.shape[1])):
step_data = stimulus(i).tolist()
data.append(step_data)
stimulus.surface = surface.gid
common.add2session(KEY_STIMULUS, stimulus)
result = {
'status': 'ok',
'max': max_value,
'min': min_value,
'data': data,
"time_min": min_time,
"time_max": max_time,
"chunk_size": CHUNK_SIZE
}
return result
except (NameError, ValueError, SyntaxError):
return {
'status':
'error',
'errorMsg':
"Could not generate stimulus data. Some of the parameters hold invalid characters."
}
except Exception, ex:
return {'allSeries': 'error', 'errorMsg': ex.message}
def _get_stimulus_interface(self):
"""
Returns a dictionary which contains the interface for a surface stimulus.
"""
context = base.get_from_session(KEY_SURFACE_CONTEXT)
input_list = self.get_creator_and_interface(SURFACE_STIMULUS_CREATOR_MODULE,
SURFACE_STIMULUS_CREATOR_CLASS, StimuliSurface(),
lock_midpoint_for_eq=[1])[1]
input_list = ABCAdapter.fill_defaults(input_list, context.equation_kwargs)
input_list, focal_points_list = self._remove_focal_points(input_list)
input_list = self.prepare_entity_interface(input_list)
input_list['selectedFocalPoints'] = focal_points_list
return self._add_extra_fields_to_interface(input_list)
def load_surface_stimulus(self, surface_stimulus_gid, from_step):
"""
Loads the interface for the selected surface stimulus.
"""
context = common.get_from_session(KEY_SURFACE_CONTEXT)
selected_surface_stimulus = ABCAdapter.load_entity_by_gid(
surface_stimulus_gid)
temporal_eq = selected_surface_stimulus.temporal
spatial_eq = selected_surface_stimulus.spatial
surface = selected_surface_stimulus.surface
focal_points_surface = selected_surface_stimulus.focal_points_surface
focal_points_triangles = selected_surface_stimulus.focal_points_triangles
temporal_eq_type = temporal_eq.__class__.__name__
spatial_eq_type = spatial_eq.__class__.__name__
default_dict = {
'temporal': temporal_eq_type,
'spatial': spatial_eq_type,
'surface': surface.gid,
'focal_points_surface': json.dumps(focal_points_surface),
'focal_points_triangles': json.dumps(focal_points_triangles)
}
for param in temporal_eq.parameters:
prepared_name = 'temporal_parameters_option_' + str(
temporal_eq_type)
prepared_name = prepared_name + '_parameters_parameters_' + str(
param)
default_dict[prepared_name] = str(temporal_eq.parameters[param])
for param in spatial_eq.parameters:
prepared_name = 'spatial_parameters_option_' + str(
spatial_eq_type) + '_parameters_parameters_' + str(param)
default_dict[prepared_name] = str(spatial_eq.parameters[param])
default_dict[
DataTypeMetaData.KEY_TAG_1] = selected_surface_stimulus.user_tag_1
input_list = self.get_creator_and_interface(
SURFACE_STIMULUS_CREATOR_MODULE,
SURFACE_STIMULUS_CREATOR_CLASS,
StimuliSurface(),
lock_midpoint_for_eq=[1])[1]
input_list = ABCAdapter.fill_defaults(input_list, default_dict)
context.reset()
context.update_from_interface(input_list)
context.equation_kwargs[
DataTypeMetaData.KEY_TAG_1] = selected_surface_stimulus.user_tag_1
context.set_active_stimulus(surface_stimulus_gid)
return self.do_step(from_step)
def create_stimulus(self):
"""
Creates a stimulus from the given data.
"""
try:
context = common.get_from_session(KEY_SURFACE_CONTEXT)
surface_stimulus_creator = self.get_creator_and_interface(SURFACE_STIMULUS_CREATOR_MODULE,
SURFACE_STIMULUS_CREATOR_CLASS,
StimuliSurface())[0]
self.flow_service.fire_operation(surface_stimulus_creator, common.get_logged_user(),
common.get_current_project().id, **context.equation_kwargs)
common.set_important_message("The operation for creating the stimulus was successfully launched.")
context.selected_stimulus = None
except (NameError, ValueError, SyntaxError), _:
common.set_error_message("The operation failed due to invalid parameter input.")
return False
def prepare_stimuli_surface_from_view_model(view_model, load_full_surface=False):
# type: (SurfaceStimulusCreatorModel, bool) -> StimuliSurface
stimuli_surface = StimuliSurface()
stimuli_surface.focal_points_triangles = view_model.focal_points_triangles
stimuli_surface.spatial = view_model.spatial
stimuli_surface.temporal = view_model.temporal
surface_index = SurfaceStimulusCreator.load_entity_by_gid(view_model.surface.hex)
if load_full_surface:
stimuli_surface.surface = h5.load_from_index(surface_index)
else:
stimuli_surface.surface = CorticalSurface()
stimuli_surface.gid = view_model.surface
surface_h5 = h5.h5_file_for_index(surface_index)
# We need to load surface triangles on stimuli because focal_points_surface property needs to acces them
stimuli_surface.surface.triangles = surface_h5.triangles.load()
surface_h5.close()
return stimuli_surface
def prepare_stimuli_surface_from_view_model(self,
view_model,
load_full_surface=False):
# type: (SurfaceStimulusCreatorModel, bool) -> StimuliSurface
stimuli_surface = StimuliSurface()
stimuli_surface.focal_points_triangles = view_model.focal_points_triangles
stimuli_surface.spatial = view_model.spatial
stimuli_surface.temporal = view_model.temporal
if load_full_surface:
stimuli_surface.surface = self.load_traited_by_gid(
view_model.surface)
else:
stimuli_surface.surface = CorticalSurface()
stimuli_surface.gid = view_model.surface
# We need to load surface triangles on stimuli because focal_points_surface property needs to acces them
with h5.h5_file_for_gid(view_model.surface) as surface_h5:
stimuli_surface.surface.triangles = surface_h5.triangles.load()
return stimuli_surface
def launch(self, **kwargs):
"""
Used for creating a StimuliSurface instance
"""
stimuli_surface = StimuliSurface(storage_path=self.storage_path)
stimuli_surface.surface = kwargs['surface']
triangles_indices = kwargs['focal_points_triangles']
focal_points = []
fp_triangle_indices = []
for triangle_index in triangles_indices:
focal_points.append(int(stimuli_surface.surface.triangles[triangle_index][0]))
fp_triangle_indices.append(int(triangle_index))
stimuli_surface.focal_points_triangles = fp_triangle_indices
stimuli_surface.focal_points_surface = focal_points
stimuli_surface.spatial = self.get_spatial_equation(kwargs)
stimuli_surface.temporal = self.get_temporal_equation(kwargs)
return stimuli_surface
def launch(self, **kwargs):
"""
Used for creating a `StimuliSurface` instance
"""
stimuli_surface = StimuliSurface(storage_path=self.storage_path)
stimuli_surface.surface = kwargs['surface']
triangles_indices = kwargs['focal_points_triangles']
focal_points = []
fp_triangle_indices = []
for triangle_index in triangles_indices:
focal_points.append(int(stimuli_surface.surface.triangles[triangle_index][0]))
fp_triangle_indices.append(int(triangle_index))
stimuli_surface.focal_points_triangles = fp_triangle_indices
stimuli_surface.focal_points_surface = focal_points
stimuli_surface.spatial = self.get_spatial_equation(kwargs)
stimuli_surface.temporal = self.get_temporal_equation(kwargs)
return stimuli_surface