The Virtual Brain Project

Source code for tvb.adapters.visualizers.time_series_volume

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Backend-side for TS Visualizer of TS Volume DataTypes.

.. moduleauthor:: Robert Parcus <>
.. moduleauthor:: Lia Domide <>
.. moduleauthor:: Ciprian Tomoiaga <>


import json
from tvb.adapters.visualizers.region_volume_mapping import _MappedArrayVolumeBase
from tvb.basic.filters.chain import FilterChain
from tvb.core.adapters.abcdisplayer import ABCDisplayer
from import dao
from tvb.datatypes.structural import StructuralMRI
from tvb.datatypes.time_series import TimeSeries, TimeSeriesVolume

[docs]class TimeSeriesVolumeVisualiser(ABCDisplayer): _ui_name = "Time Series Volume Visualizer" _ui_subsection = "volume"
[docs] def get_input_tree(self): return [{'name': 'time_series', 'label': 'Time Series', 'type': TimeSeries, 'required': True, 'conditions': FilterChain(fields=[FilterChain.datatype + '._has_volume_mapping'], operations=["=="], values=[True])}, _MappedArrayVolumeBase.get_background_input_tree()]
[docs] def get_required_memory_size(self, **kwargs): """Return required memory.""" return -1
[docs] def launch(self, time_series, background=None): min_value, max_value = time_series.get_min_max_values() url_volume_data = self.paths2url(time_series, "get_volume_view", parameter="") url_timeseries_data = self.paths2url(time_series, "get_voxel_time_series", parameter="") if isinstance(time_series, TimeSeriesVolume): volume = time_series.volume volume_shape = time_series.read_data_shape() else: volume = time_series.region_mapping_volume.volume volume_shape = [time_series.read_data_shape()[0]] volume_shape.extend(time_series.region_mapping_volume.shape) params = dict(title="Volumetric Time Series", ts_title=time_series.title, labelsStateVar=time_series.labels_dimensions.get(time_series.labels_ordering[1], []), labelsModes=range(time_series.read_data_shape()[3]), minValue=min_value, maxValue=max_value, urlVolumeData=url_volume_data, urlTimeSeriesData=url_timeseries_data, samplePeriod=time_series.sample_period, samplePeriodUnit=time_series.sample_period_unit, volumeShape=json.dumps(volume_shape), volumeOrigin=json.dumps(volume.origin.tolist()), voxelUnit=volume.voxel_unit, voxelSize=json.dumps(volume.voxel_size.tolist())) if background is None: background = dao.try_load_last_entity_of_type(self.current_project_id, StructuralMRI) params.update(_MappedArrayVolumeBase._compute_background(background)) return self.build_display_result("time_series_volume/view", params, pages=dict(controlPage="time_series_volume/controls"))