Dataset.valid_times¶
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Dataset.
valid_times
¶ Indexes into the dataset by valid time.
Examples
>>> with bth5.open(temp_h5, '/', mode='w', value_dtype=np.int64) as ds: ... ds.write(np.datetime64("2018-06-21 12:26:47"), 2.0) ... ds.write(np.datetime64("2018-06-21 12:26:49"), 2.0) >>> with bth5.open(temp_h5, '/', mode='r', value_dtype=np.int64) as ds: ... ds.valid_times[:] ... ds.valid_times[np.datetime64("2018-06-21 12:26:47"):np.datetime64("2018-06-21 12:26:48")] ... ds.valid_times[np.datetime64("2018-06-21 12:26:48"):] ... ds.valid_times[:np.datetime64("2018-06-21 12:26:48")] ... ds.valid_times[np.datetime64("2018-06-21 12:26:49")] array([(0, '2018-06-21T12:26:47.000000', 2), (0, '2018-06-21T12:26:49.000000', 2)], dtype=[('transaction_id', '<u8'), ('valid_time', '<M8[us]'), ('value', '<i8')]) array([(0, '2018-06-21T12:26:47.000000', 2)], dtype=[('transaction_id', '<u8'), ('valid_time', '<M8[us]'), ('value', '<i8')]) array([(0, '2018-06-21T12:26:49.000000', 2)], dtype=[('transaction_id', '<u8'), ('valid_time', '<M8[us]'), ('value', '<i8')]) array([(0, '2018-06-21T12:26:47.000000', 2)], dtype=[('transaction_id', '<u8'), ('valid_time', '<M8[us]'), ('value', '<i8')]) (0, '2018-06-21T12:26:49.000000', 2) >>> with bth5.open(temp_h5, '/', mode='r', value_dtype=np.int64) as ds: ... ds.valid_times[np.datetime64("2018-06-21 12:26:48")] Traceback (most recent call last): ... ValueError: The specified date was not found in the dataset, use interpolate_value.