def _tensor_to_df(tens, measures): times = dt_helper.make_grid(batch_info['start_times'], tens.shape[1]) return TimeSeriesDataset.tensor_to_dataframe( tensor=tens, times=times, group_names=batch_info['group_names'], group_colname=group_colname, time_colname=time_colname, measures=measures)
def _tensor_to_df(tens, measures): times = batch_info.get('times', batch_info['start_times'][:, None] + np.arange(0, tens.shape[1])) return TimeSeriesDataset.tensor_to_dataframe( tensor=tens, times=times, group_names=batch_info['group_names'], group_colname=group_colname, time_colname=time_colname, measures=measures )
def _tensor_to_df(tens, measures): offsets = np.arange(0, tens.shape[1]) * ( batch_info['dt_unit'] if batch_info['dt_unit'] else 1) times = batch_info['start_times'][:, None] + offsets return TimeSeriesDataset.tensor_to_dataframe( tensor=tens, times=times, group_names=batch_info['group_names'], group_colname=group_colname, time_colname=time_colname, measures=measures)