[BT] This is all a really rough kludge to get this working

[github-actions]

[BT] This is all a really rough kludge to get this working

NOW. Need to come back and think how to do this properly.

NorMITs-Demand/normits_demand/models/distribution_model.py

Line 777 in 8efa8da

# BACKLOG(BT): This is all a really rough kludge to get this working

        )

    def _convert_matrix_time_format(
        self,
        import_dir: pathlib.Path,
        export_dir: pathlib.Path,
        from_time_format: nd.core.TimeFormat = None,
        to_time_format: nd.core.TimeFormat = None,
    ) -> None:
        """Converts matrices between time formats"""
        # TODO(BT): This function just assumes there's time periods.
        #  Won't work otherwise
        conversion_factors = from_time_format.get_conversion_factors(to_time_format)

        # Build matrix naming templates
        template = self.running_segmentation.generate_template_file_name(
            file_desc='{matrix_format}',
            trip_origin=self.trip_origin,
            year=str(self.year),
            compressed=True,
        )

        if self.trip_origin == nd.core.TripOrigin.HB.value:
            matrix_formats = ["synthetic_od_from", "synthetic_od_to"]
        elif self.trip_origin == nd.core.TripOrigin.NHB.value:
            matrix_formats = ["synthetic_od"]
        else:
            raise ValueError(f"Trip origin '{self.trip_origin}' not recognised.")

        # Build the multiprocessing kwargs
        kwarg_list = list()

        # BACKLOG(BT): This is all a really rough kludge to get this working
        #  NOW. Need to come back and think how to do this properly.
        if self.running_segmentation.has_time_period_segments():
            iterator = itertools.product(self.running_segmentation, [-1])
            naming_order = self.running_segmentation.naming_order
            segment_types = self.running_segmentation.segment_types
        else:
            tps = [1, 2, 3, 4, 5, 6]
            iterator = itertools.product(self.running_segmentation, tps)
            naming_order = self.running_segmentation.naming_order + ['tp']
            segment_types = self.running_segmentation.segment_types | {"tp": int}

        for segment_params, tp in iterator:
            # Generate filenames
            tp_params = segment_params.copy()
            if "tp" not in tp_params:
                tp_params['tp'] = tp
            segment_str = nd.core.SegmentationLevel.generate_template_segment_str(
                naming_order=naming_order,
                segment_params=tp_params,
                segment_types=segment_types,
            )

            # Build the kwarg list
            for mx_format in matrix_formats:
                fname = template.format(segment_params=segment_str, matrix_format=mx_format)
                kwarg_list.append({
                    "input_path": import_dir / fname,
                    "output_path": export_dir / fname,
                    "factor": conversion_factors[tp_params["tp"]]
                })

        # MP running
        self._logger.info(
            f"Converting OD matrix time format from {from_time_format.value} "
            f"to {to_time_format.value}."
        )
        pbar_kwargs = {'desc': "Converting OD matrix time format"}
        multiprocessing.multiprocess(
            fn=mat_utils.apply_factor,
            kwargs=kwarg_list,
            process_count=self.process_count,
            pbar_kwargs=pbar_kwargs

        )

    def compile_to_assignment_format(
        self,
        from_time_format: nd.core.TimeFormat = None,
        to_time_format: nd.core.TimeFormat = None,
    ):
        """TfN Specific helper function to compile outputs into assignment format

        This should really be the job of NorMITs Matrix tools! Move there

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