How to use the scenedetect.stats_manager.StatsFileCorrupt function in scenedetect

[some_frame_key, some_frame_timecode.get_timecode(), some_metric_value])

        # File 3: Wrong Header Names [StatsFileCorrupt]
        stats_writers[3].writerow([COLUMN_NAME_FPS, '%.10f' % base_timecode.get_framerate()])
        stats_writers[3].writerow(
            [COLUMN_NAME_TIMECODE, COLUMN_NAME_FRAME_NUMBER, some_metric_key])
        stats_writers[3].writerow(
            [some_frame_key, some_frame_timecode.get_timecode(), some_metric_value])

        for stats_file in stats_files: stats_file.close()

        stats_files = [open(stats_file, 'rt') for stats_file in TEST_STATS_FILES]

        with pytest.raises(StatsFileCorrupt):
            stats_manager.load_from_csv(stats_files[0], base_timecode)
        with pytest.raises(StatsFileCorrupt):
            stats_manager.load_from_csv(stats_files[1], base_timecode)
        with pytest.raises(StatsFileFramerateMismatch):
            stats_manager.load_from_csv(stats_files[2], base_timecode)
        with pytest.raises(StatsFileCorrupt):
            stats_manager.load_from_csv(stats_files[3], base_timecode)

    finally:
        for stats_file in stats_files: stats_file.close()
        for stats_file in TEST_STATS_FILES: os.remove(stats_file)

[COLUMN_NAME_FRAME_NUMBER, COLUMN_NAME_TIMECODE, some_metric_key])
        stats_writers[2].writerow(
            [some_frame_key, some_frame_timecode.get_timecode(), some_metric_value])

        # File 3: Wrong Header Names [StatsFileCorrupt]
        stats_writers[3].writerow([COLUMN_NAME_FPS, '%.10f' % base_timecode.get_framerate()])
        stats_writers[3].writerow(
            [COLUMN_NAME_TIMECODE, COLUMN_NAME_FRAME_NUMBER, some_metric_key])
        stats_writers[3].writerow(
            [some_frame_key, some_frame_timecode.get_timecode(), some_metric_value])

        for stats_file in stats_files: stats_file.close()

        stats_files = [open(stats_file, 'rt') for stats_file in TEST_STATS_FILES]

        with pytest.raises(StatsFileCorrupt):
            stats_manager.load_from_csv(stats_files[0], base_timecode)
        with pytest.raises(StatsFileCorrupt):
            stats_manager.load_from_csv(stats_files[1], base_timecode)
        with pytest.raises(StatsFileFramerateMismatch):
            stats_manager.load_from_csv(stats_files[2], base_timecode)
        with pytest.raises(StatsFileCorrupt):
            stats_manager.load_from_csv(stats_files[3], base_timecode)

    finally:
        for stats_file in stats_files: stats_file.close()
        for stats_file in TEST_STATS_FILES: os.remove(stats_file)

# If the file is blank or we couldn't decode anything, assume the file was empty.
            return num_frames
        # First Row (FPS = [...]) and ensure framerate equals base_timecode if set.
        if not len(row) == 2 or not row[0] == COLUMN_NAME_FPS:
            raise StatsFileCorrupt()
        stats_file_framerate = float(row[1])
        if stats_file_framerate < MINIMUM_FRAMES_PER_SECOND_FLOAT:
            raise StatsFileCorrupt("Invalid framerate detected in CSV stats file "
                                   "(decoded FPS: %f)." % stats_file_framerate)
        if base_timecode is not None and not base_timecode.equal_framerate(stats_file_framerate):
            raise StatsFileFramerateMismatch(base_timecode.get_framerate(), stats_file_framerate)
        # Second Row: Frame Num, Timecode, [metrics...]
        try:
            row = next(csv_reader)
        except StopIteration:
            raise StatsFileCorrupt("Header row(s) missing.")
        if not row or not len(row) >= 2:
            raise StatsFileCorrupt()
        if row[0] != COLUMN_NAME_FRAME_NUMBER or row[1] != COLUMN_NAME_TIMECODE:
            raise StatsFileCorrupt()
        num_cols = len(row)
        num_metrics = num_cols - 2
        if not num_metrics > 0:
            raise StatsFileCorrupt('No metrics defined in CSV file.')
        metric_keys = row[2:]
        num_frames = 0
        for row in csv_reader:
            metric_dict = {}
            if not len(row) == num_cols:
                raise StatsFileCorrupt('Wrong number of columns detected in stats file row.')
            for i, metric_str in enumerate(row[2:]):
                if metric_str and metric_str != 'None':

def _open_stats_file(self):

        if self.stats_manager is None:
            self.stats_manager = StatsManager()

        if self.stats_file_path is not None:
            if os.path.exists(self.stats_file_path):
                logging.info('Loading frame metrics from stats file: %s',
                             os.path.basename(self.stats_file_path))
                try:
                    with open(self.stats_file_path, 'rt') as stats_file:
                        self.stats_manager.load_from_csv(stats_file, self.base_timecode)
                except StatsFileCorrupt:
                    error_strs = [
                        'Could not load stats file.', 'Failed to parse stats file:',
                        'Could not load frame metrics from stats file - file is corrupt or not a'
                        ' valid PySceneDetect stats file. If the file exists, ensure that it is'
                        ' a valid stats file CSV, otherwise delete it and run PySceneDetect again'
                        ' to re-generate the stats file.']
                    logging.error('\n'.join(error_strs))
                    raise click.BadParameter(
                        '\n  Could not load given stats file, see above output for details.',
                        param_hint='input stats file')
                except StatsFileFramerateMismatch as ex:
                    error_strs = [
                        'could not load stats file.', 'Failed to parse stats file:',
                        'Framerate differs between stats file (%.2f FPS) and input'
                        ' video%s (%.2f FPS)' % (
                            ex.stats_file_fps,

except StopIteration:
            raise StatsFileCorrupt("Header row(s) missing.")
        if not row or not len(row) >= 2:
            raise StatsFileCorrupt()
        if row[0] != COLUMN_NAME_FRAME_NUMBER or row[1] != COLUMN_NAME_TIMECODE:
            raise StatsFileCorrupt()
        num_cols = len(row)
        num_metrics = num_cols - 2
        if not num_metrics > 0:
            raise StatsFileCorrupt('No metrics defined in CSV file.')
        metric_keys = row[2:]
        num_frames = 0
        for row in csv_reader:
            metric_dict = {}
            if not len(row) == num_cols:
                raise StatsFileCorrupt('Wrong number of columns detected in stats file row.')
            for i, metric_str in enumerate(row[2:]):
                if metric_str and metric_str != 'None':
                    try:
                        metric_dict[metric_keys[i]] = float(metric_str)
                    except ValueError:
                        raise StatsFileCorrupt('Corrupted value in stats file: %s' % metric_str)
            self.set_metrics(int(row[0]), metric_dict)
            num_frames += 1
        logging.info('Loaded %d metrics for %d frames.', num_metrics, num_frames)
        if reset_save_required:
            self._metrics_updated = False
        return num_frames

def _open_stats_file(self):

        if self.stats_manager is None:
            self.stats_manager = StatsManager()

        if self.stats_file_path is not None:
            if os.path.exists(self.stats_file_path):
                logging.info('Loading frame metrics from stats file: %s',
                             os.path.basename(self.stats_file_path))
                try:
                    with open(self.stats_file_path, 'rt') as stats_file:
                        self.stats_manager.load_from_csv(stats_file, self.base_timecode)
                except StatsFileCorrupt:
                    error_strs = [
                        'Could not load stats file.', 'Failed to parse stats file:',
                        'Could not load frame metrics from stats file - file is corrupt or not a'
                        ' valid PySceneDetect stats file. If the file exists, ensure that it is'
                        ' a valid stats file CSV, otherwise delete it and run PySceneDetect again'
                        ' to re-generate the stats file.']
                    logging.error('\n'.join(error_strs))
                    raise click.BadParameter(
                        '\n  Could not load given stats file, see above output for details.',
                        param_hint='input stats file')
                except StatsFileFramerateMismatch as ex:
                    error_strs = [
                        'could not load stats file.', 'Failed to parse stats file:',
                        'Framerate differs between stats file (%.2f FPS) and input'
                        ' video%s (%.2f FPS)' % (
                            ex.stats_file_fps,

"(decoded FPS: %f)." % stats_file_framerate)
        if base_timecode is not None and not base_timecode.equal_framerate(stats_file_framerate):
            raise StatsFileFramerateMismatch(base_timecode.get_framerate(), stats_file_framerate)
        # Second Row: Frame Num, Timecode, [metrics...]
        try:
            row = next(csv_reader)
        except StopIteration:
            raise StatsFileCorrupt("Header row(s) missing.")
        if not row or not len(row) >= 2:
            raise StatsFileCorrupt()
        if row[0] != COLUMN_NAME_FRAME_NUMBER or row[1] != COLUMN_NAME_TIMECODE:
            raise StatsFileCorrupt()
        num_cols = len(row)
        num_metrics = num_cols - 2
        if not num_metrics > 0:
            raise StatsFileCorrupt('No metrics defined in CSV file.')
        metric_keys = row[2:]
        num_frames = 0
        for row in csv_reader:
            metric_dict = {}
            if not len(row) == num_cols:
                raise StatsFileCorrupt('Wrong number of columns detected in stats file row.')
            for i, metric_str in enumerate(row[2:]):
                if metric_str and metric_str != 'None':
                    try:
                        metric_dict[metric_keys[i]] = float(metric_str)
                    except ValueError:
                        raise StatsFileCorrupt('Corrupted value in stats file: %s' % metric_str)
            self.set_metrics(int(row[0]), metric_dict)
            num_frames += 1
        logging.info('Loaded %d metrics for %d frames.', num_metrics, num_frames)
        if reset_save_required:

def __init__(self, message=
                 "Could not load frame metric data data from passed CSV file."):
        # type: (str, str)
        # Pass message string to base Exception class.
        super(StatsFileCorrupt, self).__init__(message)

num_cols = len(row)
        num_metrics = num_cols - 2
        if not num_metrics > 0:
            raise StatsFileCorrupt('No metrics defined in CSV file.')
        metric_keys = row[2:]
        num_frames = 0
        for row in csv_reader:
            metric_dict = {}
            if not len(row) == num_cols:
                raise StatsFileCorrupt('Wrong number of columns detected in stats file row.')
            for i, metric_str in enumerate(row[2:]):
                if metric_str and metric_str != 'None':
                    try:
                        metric_dict[metric_keys[i]] = float(metric_str)
                    except ValueError:
                        raise StatsFileCorrupt('Corrupted value in stats file: %s' % metric_str)
            self.set_metrics(int(row[0]), metric_dict)
            num_frames += 1
        logging.info('Loaded %d metrics for %d frames.', num_metrics, num_frames)
        if reset_save_required:
            self._metrics_updated = False
        return num_frames