Python numpy.core() Examples

The following are 24 code examples of numpy.core(). 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: function_helpers.py    From Carnets with BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up
def block(arrays):
    # We need to override block since the numpy implementation can take two
    # different paths, one for concatenation, one for creating a large empty
    # result array in which parts are set.  Each assumes array input and
    # cannot be used directly.  Since it would be very costly to inspect all
    # arrays and then turn them back into a nested list, we just copy here the
    # second implementation, np.core.shape_base._block_slicing, since it is
    # shortest and easiest.
    (arrays, list_ndim, result_ndim,
     final_size) = np.core.shape_base._block_setup(arrays)
    shape, slices, arrays = np.core.shape_base._block_info_recursion(
        arrays, list_ndim, result_ndim)
    # Here, one line of difference!
    arrays, unit = _quantities2arrays(*arrays)
    # Back to _block_slicing
    dtype = np.result_type(*[arr.dtype for arr in arrays])
    F_order = all(arr.flags['F_CONTIGUOUS'] for arr in arrays)
    C_order = all(arr.flags['C_CONTIGUOUS'] for arr in arrays)
    order = 'F' if F_order and not C_order else 'C'
    result = np.empty(shape=shape, dtype=dtype, order=order)
    for the_slice, arr in zip(slices, arrays):
        result[(Ellipsis,) + the_slice] = arr
    return result, unit, None 
Example #2
Source File: utils.py    From ImageFusion with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #3
Source File: utils.py    From keras-lambda with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #4
Source File: utils.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #5
Source File: utils.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #6
Source File: utils.py    From Carnets with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #7
Source File: function_helpers.py    From Carnets with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def array2string(a, *args, **kwargs):
    # array2string breaks on quantities as it tries to turn individual
    # items into float, which works only for dimensionless.  Since the
    # defaults would not keep any unit anyway, this is rather pointless -
    # we're better off just passing on the array view.  However, one can
    # also work around this by passing on a formatter (as is done in Angle).
    # So, we do nothing if the formatter argument is present and has the
    # relevant formatter for our dtype.
    formatter = args[6] if len(args) >= 7 else kwargs.get('formatter', None)

    if formatter is None:
        a = a.value
    else:
        # See whether it covers our dtype.
        from numpy.core.arrayprint import _get_format_function

        with np.printoptions(formatter=formatter) as options:
            try:
                ff = _get_format_function(a.value, **options)
            except Exception:
                # Shouldn't happen, but possibly we're just not being smart
                # enough, so let's pass things on as is.
                pass
            else:
                # If the selected format function is that of numpy, we know
                # things will fail
                if 'numpy' in ff.__module__:
                    a = a.value

    return (a,) + args, kwargs, None, None 
Example #8
Source File: function_helpers.py    From Carnets with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def array_str(arr, *args, **kwargs):
    # TODO: The addition of the unit doesn't worry about line length.
    # Could copy & adapt _array_repr_implementation from
    # numpy.core.arrayprint.py
    no_unit = np.array_str(arr.value, *args, **kwargs)
    return no_unit + arr._unitstr, None, None 
Example #9
Source File: function_helpers.py    From Carnets with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def array_repr(arr, *args, **kwargs):
    # TODO: The addition of "unit='...'" doesn't worry about line
    # length.  Could copy & adapt _array_repr_implementation from
    # numpy.core.arrayprint.py
    cls_name = arr.__class__.__name__
    fake_name = '_' * len(cls_name)
    fake_cls = type(fake_name, (np.ndarray,), {})
    no_unit = np.array_repr(arr.view(fake_cls),
                            *args, **kwargs).replace(fake_name, cls_name)
    unit_part = f"unit='{arr.unit}'"
    pre, dtype, post = no_unit.rpartition('dtype')
    if dtype:
        return f"{pre}{unit_part}, {dtype}{post}", None, None
    else:
        return f"{no_unit[:-1]}, {unit_part})", None, None 
Example #10
Source File: utils.py    From coffeegrindsize with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #11
Source File: utils.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #12
Source File: utils.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #13
Source File: utils.py    From recruit with Apache License 2.0 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #14
Source File: utils.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #15
Source File: utils.py    From pySINDy with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #16
Source File: utils.py    From Fluid-Designer with GNU General Public License v3.0 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #17
Source File: utils.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #18
Source File: utils.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #19
Source File: utils.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #20
Source File: utils.py    From Computable with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #21
Source File: utils.py    From vnpy_crypto with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #22
Source File: utils.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #23
Source File: utils.py    From lambda-packs with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d 
Example #24
Source File: utils.py    From lambda-packs with MIT License 5 votes vote down vote up
def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d