def _create_volume(self):
     volume = Volume(storage_path=self.storage_path)
     volume.set_operation_id(self.operation_id)
     volume.origin = [[0.0, 0.0, 0.0]]
     volume.voxel_size = [self.parser.zooms[0], self.parser.zooms[1], self.parser.zooms[2]]
     if self.parser.units is not None and len(self.parser.units) > 0:
         volume.voxel_unit = self.parser.units[0]
     return volume
    def launch(self, data_file, apply_corrections=False, connectivity=None):
        """
        Execute import operations:
        """

        try:
            parser = NIFTIParser(data_file)

            # Create volume DT
            volume = Volume(storage_path=self.storage_path)
            volume.set_operation_id(self.operation_id)
            volume.origin = [[0.0, 0.0, 0.0]]
            volume.voxel_size = [
                parser.zooms[0], parser.zooms[1], parser.zooms[2]
            ]
            if parser.units is not None and len(parser.units) > 0:
                volume.voxel_unit = parser.units[0]

            if parser.has_time_dimension or not connectivity:
                # Now create TimeSeries and fill it with data from NIFTI image
                time_series = TimeSeriesVolume(storage_path=self.storage_path)
                time_series.set_operation_id(self.operation_id)
                time_series.volume = volume
                time_series.title = "NIFTI Import - " + os.path.split(
                    data_file)[1]
                time_series.labels_ordering = ["Time", "X", "Y", "Z"]
                time_series.start_time = 0.0

                if len(parser.zooms) > 3:
                    time_series.sample_period = float(parser.zooms[3])
                else:
                    # If no time dim, set sampling to 1 sec
                    time_series.sample_period = 1

                if parser.units is not None and len(parser.units) > 1:
                    time_series.sample_period_unit = parser.units[1]

                parser.parse(time_series, True)
                return [volume, time_series]

            else:
                region2volume_mapping = RegionVolumeMapping(
                    storage_path=self.storage_path)
                region2volume_mapping.set_operation_id(self.operation_id)
                region2volume_mapping.volume = volume
                region2volume_mapping.connectivity = connectivity
                region2volume_mapping.title = "NIFTI Import - " + os.path.split(
                    data_file)[1]
                region2volume_mapping.dimensions_labels = ["X", "Y", "Z"]
                region2volume_mapping.apply_corrections = apply_corrections

                parser.parse(region2volume_mapping, False)
                return [volume, region2volume_mapping]

        except ParseException, excep:
            logger = get_logger(__name__)
            logger.exception(excep)
            raise LaunchException(excep)
 def _create_volume(self):
     volume = Volume(storage_path=self.storage_path)
     volume.set_operation_id(self.operation_id)
     volume.origin = [[0.0, 0.0, 0.0]]
     volume.voxel_size = [
         self.parser.zooms[0], self.parser.zooms[1], self.parser.zooms[2]
     ]
     if self.parser.units is not None and len(self.parser.units) > 0:
         volume.voxel_unit = self.parser.units[0]
     return volume
    def launch(self, data_file, apply_corrections=False, connectivity=None):
        """
        Execute import operations:
        """

        try:
            parser = NIFTIParser(data_file)

            # Create volume DT
            volume = Volume(storage_path=self.storage_path)
            volume.set_operation_id(self.operation_id)
            volume.origin = [[0.0, 0.0, 0.0]]
            volume.voxel_size = [parser.zooms[0], parser.zooms[1], parser.zooms[2]]
            if parser.units is not None and len(parser.units) > 0:
                volume.voxel_unit = parser.units[0]

            if parser.has_time_dimension or not connectivity:
                # Now create TimeSeries and fill it with data from NIFTI image
                time_series = TimeSeriesVolume(storage_path=self.storage_path)
                time_series.set_operation_id(self.operation_id)
                time_series.volume = volume
                time_series.title = "NIFTI Import - " + os.path.split(data_file)[1]
                time_series.labels_ordering = ["Time", "X", "Y", "Z"]
                time_series.start_time = 0.0

                if len(parser.zooms) > 3:
                    time_series.sample_period = float(parser.zooms[3])
                else:
                    # If no time dim, set sampling to 1 sec
                    time_series.sample_period = 1

                if parser.units is not None and len(parser.units) > 1:
                    time_series.sample_period_unit = parser.units[1]

                parser.parse(time_series, True)
                return [volume, time_series]

            else:
                region2volume_mapping = RegionVolumeMapping(storage_path=self.storage_path)
                region2volume_mapping.set_operation_id(self.operation_id)
                region2volume_mapping.volume = volume
                region2volume_mapping.connectivity = connectivity
                region2volume_mapping.title = "NIFTI Import - " + os.path.split(data_file)[1]
                region2volume_mapping.dimensions_labels = ["X", "Y", "Z"]
                region2volume_mapping.apply_corrections = apply_corrections

                parser.parse(region2volume_mapping, False)
                return [volume, region2volume_mapping]

        except ParseException, excep:
            logger = get_logger(__name__)
            logger.exception(excep)
            raise LaunchException(excep)