Python numpy._NoValue() Examples

The following are 30 code examples of numpy._NoValue(). 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: utils.py    From tangent with Apache License 2.0 7 votes vote down vote up 
def unreduce_array(array, shape, axis, keepdims):
  """Reverse summing over a dimension, NumPy implementation.

  Args:
    array: The array that was reduced.
    shape: The original shape of the array before reduction.
    axis: The axis or axes that were summed.
    keepdims: Whether these axes were kept as singleton axes.

  Returns:
    An array with axes broadcast to match the shape of the original array.
  """
  # NumPy uses a special default value for keepdims, which is equivalent to
  # False.
  if axis is not None and (not keepdims or keepdims is numpy._NoValue):  # pylint: disable=protected-access
    if isinstance(axis, int):
      axis = axis,
    for ax in sorted(axis):
      array = numpy.expand_dims(array, ax)
  return numpy.broadcast_to(array, shape)


# The values are unary functions.
Example #2
Source File: test_reloading.py    From coffeegrindsize with MIT License 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #3
Source File: nanfunctions.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #4
Source File: test_reloading.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #5
Source File: nanfunctions.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #6
Source File: fromnumeric.py    From Carnets with BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up 
def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs):
    passkwargs = {k: v for k, v in kwargs.items()
                  if v is not np._NoValue}

    if type(obj) is not mu.ndarray:
        try:
            reduction = getattr(obj, method)
        except AttributeError:
            pass
        else:
            # This branch is needed for reductions like any which don't
            # support a dtype.
            if dtype is not None:
                return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
            else:
                return reduction(axis=axis, out=out, **passkwargs)

    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
Example #7
Source File: nanfunctions.py    From recruit with Apache License 2.0 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #8
Source File: test_reloading.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #9
Source File: test_reloading.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #10
Source File: fromnumeric.py    From vnpy_crypto with MIT License 6 votes vote down vote up 
def sometrue(a, axis=None, out=None, keepdims=np._NoValue):
    """
    Check whether some values are true.

    Refer to `any` for full documentation.

    See Also
    --------
    any : equivalent function

    """
    arr = asanyarray(a)
    kwargs = {}
    if keepdims is not np._NoValue:
        kwargs['keepdims'] = keepdims
    return arr.any(axis=axis, out=out, **kwargs)
Example #11
Source File: fromnumeric.py    From coffeegrindsize with MIT License 6 votes vote down vote up 
def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs):
    passkwargs = {k: v for k, v in kwargs.items()
                  if v is not np._NoValue}

    if type(obj) is not mu.ndarray:
        try:
            reduction = getattr(obj, method)
        except AttributeError:
            pass
        else:
            # This branch is needed for reductions like any which don't
            # support a dtype.
            if dtype is not None:
                return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
            else:
                return reduction(axis=axis, out=out, **passkwargs)

    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
Example #12
Source File: test_reloading.py    From Mastering-Elasticsearch-7.0 with MIT License 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #13
Source File: nanfunctions.py    From coffeegrindsize with MIT License 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #14
Source File: nanfunctions.py    From Mastering-Elasticsearch-7.0 with MIT License 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #15
Source File: fromnumeric.py    From Mastering-Elasticsearch-7.0 with MIT License 6 votes vote down vote up 
def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs):
    passkwargs = {k: v for k, v in kwargs.items()
                  if v is not np._NoValue}

    if type(obj) is not mu.ndarray:
        try:
            reduction = getattr(obj, method)
        except AttributeError:
            pass
        else:
            # This branch is needed for reductions like any which don't
            # support a dtype.
            if dtype is not None:
                return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
            else:
                return reduction(axis=axis, out=out, **passkwargs)

    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
Example #16
Source File: test_reloading.py    From GraphicDesignPatternByPython with MIT License 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #17
Source File: fromnumeric.py    From twitter-stock-recommendation with MIT License 6 votes vote down vote up 
def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs):
    passkwargs = {}
    for k, v in kwargs.items():
        if v is not np._NoValue:
            passkwargs[k] = v

    if type(obj) is not mu.ndarray:
        try:
            reduction = getattr(obj, method)
        except AttributeError:
            pass
        else:
            # This branch is needed for reductions like any which don't
            # support a dtype.
            if dtype is not None:
                return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
            else:
                return reduction(axis=axis, out=out, **passkwargs)

    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
Example #18
Source File: nanfunctions.py    From GraphicDesignPatternByPython with MIT License 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #19
Source File: fromnumeric.py    From GraphicDesignPatternByPython with MIT License 6 votes vote down vote up 
def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs):
    passkwargs = {}
    for k, v in kwargs.items():
        if v is not np._NoValue:
            passkwargs[k] = v

    if type(obj) is not mu.ndarray:
        try:
            reduction = getattr(obj, method)
        except AttributeError:
            pass
        else:
            # This branch is needed for reductions like any which don't
            # support a dtype.
            if dtype is not None:
                return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
            else:
                return reduction(axis=axis, out=out, **passkwargs)

    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
Example #20
Source File: test_reloading.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #21
Source File: fromnumeric.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def sometrue(a, axis=None, out=None, keepdims=np._NoValue):
    """
    Check whether some values are true.

    Refer to `any` for full documentation.

    See Also
    --------
    any : equivalent function

    """
    arr = asanyarray(a)
    kwargs = {}
    if keepdims is not np._NoValue:
        kwargs['keepdims'] = keepdims
    return arr.any(axis=axis, out=out, **kwargs)
Example #22
Source File: nanfunctions.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #23
Source File: fromnumeric.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 6 votes vote down vote up 
def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs):
    passkwargs = {k: v for k, v in kwargs.items()
                  if v is not np._NoValue}

    if type(obj) is not mu.ndarray:
        try:
            reduction = getattr(obj, method)
        except AttributeError:
            pass
        else:
            # This branch is needed for reductions like any which don't
            # support a dtype.
            if dtype is not None:
                return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
            else:
                return reduction(axis=axis, out=out, **passkwargs)

    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
Example #24
Source File: test_reloading.py    From pySINDy with MIT License 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #25
Source File: test_reloading.py    From elasticintel with GNU General Public License v3.0 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #26
Source File: nanfunctions.py    From pySINDy with MIT License 6 votes vote down vote up 
def _nanquantile_unchecked(a, q, axis=None, out=None, overwrite_input=False,
                           interpolation='linear', keepdims=np._NoValue):
    """Assumes that q is in [0, 1], and is an ndarray"""
    # apply_along_axis in _nanpercentile doesn't handle empty arrays well,
    # so deal them upfront
    if a.size == 0:
        return np.nanmean(a, axis, out=out, keepdims=keepdims)

    r, k = function_base._ureduce(
        a, func=_nanquantile_ureduce_func, q=q, axis=axis, out=out,
        overwrite_input=overwrite_input, interpolation=interpolation
    )
    if keepdims and keepdims is not np._NoValue:
        return r.reshape(q.shape + k)
    else:
        return r
Example #27
Source File: fromnumeric.py    From pySINDy with MIT License 6 votes vote down vote up 
def _wrapreduction(obj, ufunc, method, axis, dtype, out, **kwargs):
    passkwargs = {}
    for k, v in kwargs.items():
        if v is not np._NoValue:
            passkwargs[k] = v

    if type(obj) is not mu.ndarray:
        try:
            reduction = getattr(obj, method)
        except AttributeError:
            pass
        else:
            # This branch is needed for reductions like any which don't
            # support a dtype.
            if dtype is not None:
                return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
            else:
                return reduction(axis=axis, out=out, **passkwargs)

    return ufunc.reduce(obj, axis, dtype, out, **passkwargs)
Example #28
Source File: test_reloading.py    From mxnet-lambda with Apache License 2.0 6 votes vote down vote up 
def test_numpy_reloading():
    # gh-7844. Also check that relevant globals retain their identity.
    import numpy as np
    import numpy._globals

    _NoValue = np._NoValue
    VisibleDeprecationWarning = np.VisibleDeprecationWarning
    ModuleDeprecationWarning = np.ModuleDeprecationWarning

    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)

    assert_raises(RuntimeError, reload, numpy._globals)
    reload(np)
    assert_(_NoValue is np._NoValue)
    assert_(ModuleDeprecationWarning is np.ModuleDeprecationWarning)
    assert_(VisibleDeprecationWarning is np.VisibleDeprecationWarning)
Example #29
Source File: fromnumeric.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def sometrue(a, axis=None, out=None, keepdims=np._NoValue):
    """
    Check whether some values are true.

    Refer to `any` for full documentation.

    See Also
    --------
    any : equivalent function

    """
    arr = asanyarray(a)
    kwargs = {}
    if keepdims is not np._NoValue:
        kwargs['keepdims'] = keepdims
    return arr.any(axis=axis, out=out, **kwargs)
Example #30
Source File: fromnumeric.py    From mxnet-lambda with Apache License 2.0 6 votes vote down vote up 
def sometrue(a, axis=None, out=None, keepdims=np._NoValue):
    """
    Check whether some values are true.

    Refer to `any` for full documentation.

    See Also
    --------
    any : equivalent function

    """
    arr = asanyarray(a)
    kwargs = {}
    if keepdims is not np._NoValue:
        kwargs['keepdims'] = keepdims
    return arr.any(axis=axis, out=out, **kwargs)