def launch(self, view_model):
# type: (ICAModel) -> dict
"""Construct data for visualization and launch it."""
ica_gid = view_model.datatype
ica_index = self.load_entity_by_gid(ica_gid)
slice_given = slice_str(
(slice(None), slice(None), slice(view_model.i_svar),
slice(view_model.i_mode)))
if view_model.i_svar < 0 or view_model.i_svar >= ica_index.parsed_shape[
2]:
view_model.i_svar = 0
if view_model.i_mode < 0 or view_model.i_mode >= ica_index.parsed_shape[
3]:
view_model.i_mode = 0
slice_used = slice_str(
(slice(None), slice(None), slice(view_model.i_svar),
slice(view_model.i_mode)))
with h5.h5_file_for_index(ica_index) as h5_file:
unmixing_matrix = h5_file.unmixing_matrix[..., view_model.i_svar,
view_model.i_mode]
prewhitening_matrix = h5_file.prewhitening_matrix[
..., view_model.i_svar, view_model.i_mode]
Cinv = unmixing_matrix.dot(prewhitening_matrix)
title = 'ICA region contribution -- (Ellipsis, %d, 0)' % (
view_model.i_svar)
labels = self.extract_source_labels(ica_index)
pars = self.compute_params(ica_index, Cinv, title, [labels, labels],
slice_given, slice_used,
slice_given != slice_used)
return self.build_display_result("matrix/svg_view", pars)
def compute_2d_view(self, dtm_index, slice_s):
# type: (DataTypeMatrix, str) -> (numpy.array, str, bool)
"""
Create a 2d view of the matrix using the suggested slice
If the given slice is invalid or fails to produce a 2d array the default is used
which selects the first 2 dimensions.
If the matrix is complex the real part is shown
:param dtm_index: main input. It can have more then 2D
:param slice_s: a string representation of a slice
:return: (a 2d array, the slice used to make it, is_default_returned)
"""
default = (slice(None), slice(None)) + tuple(
0 for _ in range(dtm_index.ndim - 2)) # [:,:,0,0,0,0 etc]
slice_used = default
try:
if slice_s is not None and slice_s != "":
slice_used = parse_slice(slice_s)
except ValueError: # if the slice could not be parsed
self.log.warning("failed to parse the slice")
try:
with h5.h5_file_for_index(dtm_index) as h5_file:
result_2d = h5_file.array_data[slice_used]
result_2d = result_2d.astype(float)
if result_2d.ndim > 2: # the slice did not produce a 2d array, treat as error
raise ValueError(str(dtm_index.shape))
except (ValueError, IndexError,
TypeError): # if the slice failed to produce a 2d array
self.log.warning("failed to produce a 2d array")
return self.compute_2d_view(dtm_index, "")
return result_2d, slice_str(slice_used), slice_used == default
def compute_2d_view(matrix, slice_s):
"""
Create a 2d view of the matrix using the suggested slice
If the given slice is invalid or fails to produce a 2d array the default is used
which selects the first 2 dimensions.
If the matrix is complex the real part is shown
:param matrix: main input. It can have more then 2D
:param slice_s: a string representation of a slice
:return: (a 2d array, the slice used to make it, is_default_returned)
"""
default = (slice(None), slice(None)) + tuple(
0 for _ in range(matrix.ndim - 2)) # [:,:,0,0,0,0 etc]
try:
if slice_s is not None:
matrix_slice = parse_slice(slice_s)
else:
matrix_slice = slice(None)
m = matrix[matrix_slice]
if m.ndim > 2: # the slice did not produce a 2d array, treat as error
raise ValueError(str(matrix.shape))
except (
IndexError, ValueError
): # if the slice could not be parsed or it failed to produce a 2d array
matrix_slice = default
slice_used = slice_str(matrix_slice)
return matrix[matrix_slice].astype(
float), slice_used, matrix_slice == default