Source code for tvb.adapters.visualizers.ica
# -*- coding: utf-8 -*-
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"""
A matrix visualizer for the Independent Component Analysis.
It displays the mixing matrix of size n_features x n_components
.. moduleauthor:: Paula Popa <paula.popa@codemart.ro>
.. moduleauthor:: Paula Sanz Leon <Paula@tvb.invalid>
"""
from tvb.adapters.datatypes.db.mode_decompositions import IndependentComponentsIndex
from tvb.adapters.visualizers.matrix_viewer import ABCMappedArraySVGVisualizer
from tvb.basic.neotraits.api import Attr
from tvb.core.adapters.abcadapter import ABCAdapterForm
from tvb.core.adapters.arguments_serialisation import slice_str
from tvb.core.neocom import h5
from tvb.core.neotraits.forms import TraitDataTypeSelectField, IntField
from tvb.core.neotraits.view_model import ViewModel, DataTypeGidAttr
from tvb.datatypes.mode_decompositions import IndependentComponents
[docs]class ICAModel(ViewModel):
datatype = DataTypeGidAttr(
linked_datatype=IndependentComponents,
label='Independent component analysis:'
)
i_svar = Attr(
field_type=int,
default=0,
label='Index of state variable (defaults to first state variable)'
)
i_mode = Attr(
field_type=int,
default=0,
label='Index of mode (defaults to first mode)'
)
[docs]class ICA(ABCMappedArraySVGVisualizer):
_ui_name = "Independent Components Analysis Visualizer"
_ui_subsection = "ica"
[docs] 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)