def launch(self, view_model):
        # type: (ConnectivityMeasureImporterModel) -> [ConnectivityMeasureIndex]
        """
        Execute import operations:
        """
        try:
            data = self.read_matlab_data(view_model.data_file,
                                         view_model.dataset_name)
            measurement_count, node_count = data.shape
            connectivity_index = self.load_entity_by_gid(
                view_model.connectivity.hex)

            if node_count != connectivity_index.number_of_regions:
                raise LaunchException(
                    'The measurements are for %s nodes but the selected connectivity'
                    ' contains %s nodes' %
                    (node_count, connectivity_index.number_of_regions))

            measures = []
            for i in range(measurement_count):
                cm_idx = ConnectivityMeasureIndex()
                cm_idx.type = ConnectivityMeasureIndex.__name__
                cm_idx.connectivity_gid = connectivity_index.gid

                cm_data = data[i, :]
                cm_idx.array_data_ndim = cm_data.ndim
                cm_idx.ndim = cm_data.ndim
                cm_idx.array_data_min, cm_idx.array_data_max, cm_idx.array_data_mean = from_ndarray(
                    cm_data)

                cm_h5_path = h5.path_for(self.storage_path,
                                         ConnectivityMeasureH5, cm_idx.gid)
                with ConnectivityMeasureH5(cm_h5_path) as cm_h5:
                    cm_h5.array_data.store(data[i, :])
                    cm_h5.connectivity.store(uuid.UUID(connectivity_index.gid))
                    cm_h5.gid.store(uuid.UUID(cm_idx.gid))

                cm_idx.user_tag_2 = "nr.-%d" % (i + 1)
                cm_idx.user_tag_3 = "conn_%d" % node_count
                measures.append(cm_idx)
            return measures
        except ParseException as excep:
            logger = get_logger(__name__)
            logger.exception(excep)
            raise LaunchException(excep)
Exemple #2
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    def launch(self, view_model):
        # type: (FCDAdapterModel) -> [FcdIndex]
        """
        Launch algorithm and build results.

        :param time_series: the input time-series index for which fcd matrix should be computed
        :param sw: length of the sliding window
        :param sp: spanning time: distance between two consecutive sliding window
        :returns: the fcd index for the computed fcd matrix on the given time-series, with that sw and that sp
        :rtype: `FcdIndex`,`ConnectivityMeasureIndex`
        """
        with h5.h5_file_for_index(self.input_time_series_index) as ts_h5:
            [fcd, fcd_segmented, eigvect_dict,
             eigval_dict] = self._compute_fcd_matrix(ts_h5)
            connectivity_gid = ts_h5.connectivity.load()

        result = [
        ]  # list to store: fcd index, fcd_segmented index (eventually), and connectivity measure indexes

        # Create an index for the computed fcd.
        fcd_index = FcdIndex()
        fcd_h5_path = h5.path_for(self.storage_path, FcdH5, fcd_index.gid)
        with FcdH5(fcd_h5_path) as fcd_h5:
            fcd_array_metadata = self._populate_fcd_h5(
                fcd_h5, fcd, fcd_index.gid, self.input_time_series_index.gid,
                view_model.sw, view_model.sp)
        self._populate_fcd_index(fcd_index, self.input_time_series_index.gid,
                                 fcd, fcd_array_metadata)
        result.append(fcd_index)

        if np.amax(fcd_segmented) == 1.1:
            result_fcd_segmented_index = FcdIndex()
            result_fcd_segmented_h5_path = h5.path_for(
                self.storage_path, FcdH5, result_fcd_segmented_index.gid)
            with FcdH5(
                    result_fcd_segmented_h5_path) as result_fcd_segmented_h5:
                fcd_segmented_metadata = self._populate_fcd_h5(
                    result_fcd_segmented_h5, fcd_segmented,
                    result_fcd_segmented_index.gid,
                    self.input_time_series_index.gid, view_model.sw,
                    view_model.sp)
            self._populate_fcd_index(result_fcd_segmented_index,
                                     self.input_time_series_index.id,
                                     fcd_segmented, fcd_segmented_metadata)
            result.append(result_fcd_segmented_index)

        for mode in eigvect_dict.keys():
            for var in eigvect_dict[mode].keys():
                for ep in eigvect_dict[mode][var].keys():
                    for eig in range(3):
                        cm_data = eigvect_dict[mode][var][ep][eig]
                        cm_index = ConnectivityMeasureIndex()
                        cm_index.type = ConnectivityMeasure.__name__
                        cm_index.fk_connectivity_gid = connectivity_gid.hex
                        cm_index.title = "Epoch # %d, \n eigenvalue = %s,\n variable = %s,\n " \
                                         "mode = %s." % (ep, eigval_dict[mode][var][ep][eig], var, mode)

                        storage_path = h5.path_for(self.storage_path,
                                                   ConnectivityMeasureH5,
                                                   cm_index.gid)
                        with ConnectivityMeasureH5(storage_path) as f:
                            f.array_data.store(cm_data)
                            f.connectivity.store(connectivity_gid)
                            f.title.store(cm_index.title)
                            cm_array_metadata = f.array_data.get_cached_metadata(
                            )

                        cm_index.array_data_min = cm_array_metadata.min
                        cm_index.array_data_max = cm_array_metadata.max
                        cm_index.array_data_mean = cm_array_metadata.mean
                        result.append(cm_index)
        return result
 def test_happy_flow(self):
     assert 0 == TestFactory.get_entity_count(self.test_project,
                                              ConnectivityMeasureIndex())
     self._import('mantini_networks.mat')
     assert 6 == TestFactory.get_entity_count(self.test_project,
                                              ConnectivityMeasureIndex())