Source code for tvb.adapters.visualizers.pearson_edge_bundle
# -*- coding: utf-8 -*-
#
#
# TheVirtualBrain-Framework Package. This package holds all Data Management, and
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# documentation-folder for more details. See also http://www.thevirtualbrain.org
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# (c) 2012-2024, Baycrest Centre for Geriatric Care ("Baycrest") and others
#
# This program is free software: you can redistribute it and/or modify it under the
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import json
import numpy
from tvb.adapters.visualizers.pearson_cross_correlation import PearsonCorrelationCoefficientVisualizerForm, \
PearsonCorrelationCoefficientVisualizerModel
from tvb.adapters.visualizers.time_series import ABCSpaceDisplayer
from tvb.core.adapters.abcdisplayer import URLGenerator
from tvb.core.neocom import h5
from tvb.core.utils import TVBJSONEncoder
from tvb.datatypes.graph import CorrelationCoefficients
[docs]
class PearsonEdgeBundle(ABCSpaceDisplayer):
"""
Viewer for Pearson CorrelationCoefficients.
Very similar to the CrossCorrelationVisualizer - this one done with Matplotlib
"""
_ui_name = "Pearson Edge Bundle"
_ui_subsection = "correlation_pearson_edge"
[docs]
def get_required_memory_size(self, view_model):
# type: (PearsonCorrelationCoefficientVisualizerModel) -> numpy.ndarray
"""Return required memory."""
datatype_index = self.load_entity_by_gid(view_model.datatype)
input_size = (datatype_index.data_length_1d, datatype_index.data_length_2d,
datatype_index.data_length_3d, datatype_index.data_length_4d)
return numpy.prod(input_size) * 8.0
[docs]
def launch(self, view_model):
# type: (PearsonCorrelationCoefficientVisualizerModel) -> dict
"""Construct data for visualization and launch it."""
with h5.h5_file_for_gid(view_model.datatype) as datatype_h5:
matrix_shape = datatype_h5.array_data.shape[0:2]
ts_gid = datatype_h5.source.load()
ts_index = self.load_entity_by_gid(ts_gid)
state_list = ts_index.get_labels_for_dimension(1)
mode_list = list(range(ts_index.data_length_4d))
with h5.h5_file_for_index(ts_index) as ts_h5:
labels = self.get_space_labels(ts_h5)
if not labels:
labels = None
pars = dict(matrix_labels=json.dumps(labels, cls=TVBJSONEncoder),
matrix_shape=json.dumps(matrix_shape),
viewer_title='Pearson Edge Bundle',
url_base=URLGenerator.build_h5_url(view_model.datatype.hex, 'get_correlation_data', flatten="True",
parameter=''),
state_variable=0,
mode=mode_list[0],
state_list=state_list,
mode_list=mode_list,
pearson_min=CorrelationCoefficients.PEARSON_MIN,
pearson_max=CorrelationCoefficients.PEARSON_MAX,
thresh=0.5
)
return self.build_display_result("pearson_edge_bundle/view", pars)