Dataset.transaction_times¶
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Dataset.
transaction_times
¶ Index into the transaction index by transaction 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.transaction_times[:] array([('2019-09-19T10:32:00.210817', '2018-06-21T12:26:47.000000', '2018-06-21T12:26:49.000000', 0, 2)], dtype=[('transaction_time', '<M8[us]'), ('start_valid_time', '<M8[us]'), ('end_valid_time', '<M8[us]'), ('start_idx', '<u8'), ('end_idx', '<u8')])