Dataset.valid_times

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.