Python numpy.datetime_data() Examples

The following are 26 code examples of numpy.datetime_data(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module numpy , or try the search function

Example #1

Source File: common.py From recruit with Apache License 2.0

6 votes

def _validate_date_like_dtype(dtype):
    """
    Check whether the dtype is a date-like dtype. Raises an error if invalid.

    Parameters
    ----------
    dtype : dtype, type
        The dtype to check.

    Raises
    ------
    TypeError : The dtype could not be casted to a date-like dtype.
    ValueError : The dtype is an illegal date-like dtype (e.g. the
                 the frequency provided is too specific)
    """

    try:
        typ = np.datetime_data(dtype)[0]
    except ValueError as e:
        raise TypeError('{error}'.format(error=e))
    if typ != 'generic' and typ != 'ns':
        msg = '{name!r} is too specific of a frequency, try passing {type!r}'
        raise ValueError(msg.format(name=dtype.name, type=dtype.type.__name__))

Example #2

Source File: common.py From vnpy_crypto with MIT License

6 votes

def _validate_date_like_dtype(dtype):
    """
    Check whether the dtype is a date-like dtype. Raises an error if invalid.

    Parameters
    ----------
    dtype : dtype, type
        The dtype to check.

    Raises
    ------
    TypeError : The dtype could not be casted to a date-like dtype.
    ValueError : The dtype is an illegal date-like dtype (e.g. the
                 the frequency provided is too specific)
    """

    try:
        typ = np.datetime_data(dtype)[0]
    except ValueError as e:
        raise TypeError('{error}'.format(error=e))
    if typ != 'generic' and typ != 'ns':
        msg = '{name!r} is too specific of a frequency, try passing {type!r}'
        raise ValueError(msg.format(name=dtype.name, type=dtype.type.__name__))

Example #3

Source File: common.py From elasticintel with GNU General Public License v3.0

6 votes

def _validate_date_like_dtype(dtype):
    """
    Check whether the dtype is a date-like dtype. Raises an error if invalid.

    Parameters
    ----------
    dtype : dtype, type
        The dtype to check.

    Raises
    ------
    TypeError : The dtype could not be casted to a date-like dtype.
    ValueError : The dtype is an illegal date-like dtype (e.g. the
                 the frequency provided is too specific)
    """

    try:
        typ = np.datetime_data(dtype)[0]
    except ValueError as e:
        raise TypeError('{error}'.format(error=e))
    if typ != 'generic' and typ != 'ns':
        msg = '{name!r} is too specific of a frequency, try passing {type!r}'
        raise ValueError(msg.format(name=dtype.name, type=dtype.type.__name__))

Example #4

Source File: common.py From Splunking-Crime with GNU Affero General Public License v3.0

6 votes

def _validate_date_like_dtype(dtype):
    """
    Check whether the dtype is a date-like dtype. Raises an error if invalid.

    Parameters
    ----------
    dtype : dtype, type
        The dtype to check.

    Raises
    ------
    TypeError : The dtype could not be casted to a date-like dtype.
    ValueError : The dtype is an illegal date-like dtype (e.g. the
                 the frequency provided is too specific)
    """

    try:
        typ = np.datetime_data(dtype)[0]
    except ValueError as e:
        raise TypeError('{error}'.format(error=e))
    if typ != 'generic' and typ != 'ns':
        msg = '{name!r} is too specific of a frequency, try passing {type!r}'
        raise ValueError(msg.format(name=dtype.name, type=dtype.type.__name__))

Example #5

Source File: common.py From predictive-maintenance-using-machine-learning with Apache License 2.0

6 votes

def _validate_date_like_dtype(dtype):
    """
    Check whether the dtype is a date-like dtype. Raises an error if invalid.

    Parameters
    ----------
    dtype : dtype, type
        The dtype to check.

    Raises
    ------
    TypeError : The dtype could not be casted to a date-like dtype.
    ValueError : The dtype is an illegal date-like dtype (e.g. the
                 the frequency provided is too specific)
    """

    try:
        typ = np.datetime_data(dtype)[0]
    except ValueError as e:
        raise TypeError('{error}'.format(error=e))
    if typ != 'generic' and typ != 'ns':
        msg = '{name!r} is too specific of a frequency, try passing {type!r}'
        raise ValueError(msg.format(name=dtype.name, type=dtype.type.__name__))

Example #6

Source File: test_datetime.py From keras-lambda with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #7

Source File: _dtype.py From recruit with Apache License 2.0

5 votes

def _datetime_metadata_str(dtype):
    # TODO: this duplicates the C append_metastr_to_string
    unit, count = np.datetime_data(dtype)
    if unit == 'generic':
        return ''
    elif count == 1:
        return '[{}]'.format(unit)
    else:
        return '[{}{}]'.format(count, unit)

Example #8

Source File: test_datetime.py From twitter-stock-recommendation with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #9

Source File: test_datetime.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #10

Source File: _dtype.py From Carnets with BSD 3-Clause "New" or "Revised" License

5 votes

def _datetime_metadata_str(dtype):
    # TODO: this duplicates the C append_metastr_to_string
    unit, count = np.datetime_data(dtype)
    if unit == 'generic':
        return ''
    elif count == 1:
        return '[{}]'.format(unit)
    else:
        return '[{}{}]'.format(count, unit)

Example #11

Source File: test_datetime.py From coffeegrindsize with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #12

Source File: _dtype.py From coffeegrindsize with MIT License

5 votes

def _datetime_metadata_str(dtype):
    # TODO: this duplicates the C append_metastr_to_string
    unit, count = np.datetime_data(dtype)
    if unit == 'generic':
        return ''
    elif count == 1:
        return '[{}]'.format(unit)
    else:
        return '[{}{}]'.format(count, unit)

Example #13

Source File: test_datetime.py From elasticintel with GNU General Public License v3.0

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #14

Source File: test_datetime.py From ImageFusion with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #15

Source File: test_datetime.py From mxnet-lambda with Apache License 2.0

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #16

Source File: test_datetime.py From pySINDy with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #17

Source File: test_datetime.py From predictive-maintenance-using-machine-learning with Apache License 2.0

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #18

Source File: _dtype.py From predictive-maintenance-using-machine-learning with Apache License 2.0

5 votes

def _datetime_metadata_str(dtype):
    # TODO: this duplicates the C append_metastr_to_string
    unit, count = np.datetime_data(dtype)
    if unit == 'generic':
        return ''
    elif count == 1:
        return '[{}]'.format(unit)
    else:
        return '[{}{}]'.format(count, unit)

Example #19

Source File: test_datetime.py From GraphicDesignPatternByPython with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #20

Source File: test_datetime.py From Mastering-Elasticsearch-7.0 with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #21

Source File: _dtype.py From Mastering-Elasticsearch-7.0 with MIT License

5 votes

def _datetime_metadata_str(dtype):
    # TODO: this duplicates the C append_metastr_to_string
    unit, count = np.datetime_data(dtype)
    if unit == 'generic':
        return ''
    elif count == 1:
        return '[{}]'.format(unit)
    else:
        return '[{}{}]'.format(count, unit)

Example #22

Source File: test_datetime.py From Computable with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #23

Source File: test_datetime.py From vnpy_crypto with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #24

Source File: test_datetime.py From auto-alt-text-lambda-api with MIT License

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #25

Source File: test_datetime.py From recruit with Apache License 2.0

5 votes

def test_basic(self):
        a = np.array(['1980-03-23'], dtype=np.datetime64)
        assert_equal(np.datetime_data(a.dtype), ('D', 1))

Example #26

Source File: features.py From torch-kalman with MIT License

4 votes

def fourier_model_mat(datetimes: np.ndarray,
                      K: int,
                      period: Union[np.timedelta64, str],
                      output_fmt: str = 'float64') -> np.ndarray:
    """
    :param datetimes: An array of datetimes.
    :param K: The expansion integer.
    :param period: Either a np.timedelta64, or one of {'weekly','yearly','daily'}
    :param start_datetime: A np.datetime64 on which to consider the season-start; useful for aligning (e.g) weekly
    seasons to start on Monday, or daily seasons to start on a particular hour. Default is first monday after epoch.
    :param output_fmt: A numpy dtype, or 'dataframe' to output a dataframe.
    :return: A numpy array (or dataframe) with the expanded fourier series.
    """
    # parse period:
    name = 'fourier'
    if isinstance(period, str):
        name = period
        if period == 'weekly':
            period = np.timedelta64(7, 'D')
        elif period == 'yearly':
            period = np.timedelta64(int(365.25 * 24), 'h')
        elif period == 'daily':
            period = np.timedelta64(24, 'h')
        else:
            raise ValueError("Unrecognized `period`.")

    period_int = period.view('int64')
    dt_helper = DateTimeHelper(dt_unit=np.datetime_data(period)[0])
    time = dt_helper.validate_datetimes(datetimes).view('int64')

    output_dataframe = (output_fmt.lower() == 'dataframe')
    if output_dataframe:
        output_fmt = 'float64'

    # fourier matrix:
    out_shape = tuple(datetimes.shape) + (K * 2,)
    out = np.empty(out_shape, dtype=output_fmt)
    columns = []
    for idx in range(K):
        k = idx + 1
        for is_cos in range(2):
            val = 2. * np.pi * k * time / period_int
            out[..., idx * 2 + is_cos] = np.sin(val) if is_cos == 0 else np.cos(val)
            columns.append(f"{name}_K{k}_{'cos' if is_cos else 'sin'}")

    if output_dataframe:
        if len(out_shape) > 2:
            raise ValueError("Cannot output dataframe when input is 2+D array.")
        from pandas import DataFrame
        out = DataFrame(out, columns=columns)

    return out