本文整理汇总了Python中numpy.lib.function_base._ureduce方法的典型用法代码示例。如果您正苦于以下问题：Python function_base._ureduce方法的具体用法？Python function_base._ureduce怎么用？Python function_base._ureduce使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类numpy.lib.function_base的用法示例。
在下文中一共展示了function_base._ureduce方法的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _nanmedian
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
def _nanmedian(a, axis=None, out=None, overwrite_input=False):
"""
Private function that doesn't support extended axis or keepdims.
These methods are extended to this function using _ureduce
See nanmedian for parameter usage
"""
if axis is None or a.ndim == 1:
part = a.ravel()
if out is None:
return _nanmedian1d(part, overwrite_input)
else:
out[...] = _nanmedian1d(part, overwrite_input)
return out
else:
# for small medians use sort + indexing which is still faster than
# apply_along_axis
# benchmarked with shuffled (50, 50, x) containing a few NaN
if a.shape[axis] < 600:
return _nanmedian_small(a, axis, out, overwrite_input)
result = np.apply_along_axis(_nanmedian1d, axis, a, overwrite_input)
if out is not None:
out[...] = result
return result 示例2: _nanquantile_unchecked
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
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 示例3: _nanquantile_ureduce_func
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
def _nanquantile_ureduce_func(a, q, axis=None, out=None, overwrite_input=False,
interpolation='linear'):
"""
Private function that doesn't support extended axis or keepdims.
These methods are extended to this function using _ureduce
See nanpercentile for parameter usage
"""
if axis is None or a.ndim == 1:
part = a.ravel()
result = _nanquantile_1d(part, q, overwrite_input, interpolation)
else:
result = np.apply_along_axis(_nanquantile_1d, axis, a, q,
overwrite_input, interpolation)
# apply_along_axis fills in collapsed axis with results.
# Move that axis to the beginning to match percentile's
# convention.
if q.ndim != 0:
result = np.moveaxis(result, axis, 0)
if out is not None:
out[...] = result
return result 示例4: _nanpercentile
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
def _nanpercentile(a, q, axis=None, out=None, overwrite_input=False,
interpolation='linear'):
"""
Private function that doesn't support extended axis or keepdims.
These methods are extended to this function using _ureduce
See nanpercentile for parameter usage
"""
if axis is None or a.ndim == 1:
part = a.ravel()
result = _nanpercentile1d(part, q, overwrite_input, interpolation)
else:
result = np.apply_along_axis(_nanpercentile1d, axis, a, q,
overwrite_input, interpolation)
# apply_along_axis fills in collapsed axis with results.
# Move that axis to the beginning to match percentile's
# convention.
if q.ndim != 0:
result = np.rollaxis(result, axis)
if out is not None:
out[...] = result
return result 示例5: _nanmedian
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
def _nanmedian(a, axis=None, out=None, overwrite_input=False):
"""
Private function that doesn't support extended axis or keepdims.
These methods are extended to this function using _ureduce
See nanmedian for parameter usage
"""
if axis is None or a.ndim == 1:
part = a.ravel()
if out is None:
return _nanmedian1d(part, overwrite_input)
else:
out[...] = _nanmedian1d(part, overwrite_input)
return out
else:
# for small medians use sort + indexing which is still faster than
# apply_along_axis
if a.shape[axis] < 400:
return _nanmedian_small(a, axis, out, overwrite_input)
result = np.apply_along_axis(_nanmedian1d, axis, a, overwrite_input)
if out is not None:
out[...] = result
return result 示例6: _nanpercentile
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
def _nanpercentile(a, q, axis=None, out=None, overwrite_input=False,
interpolation='linear'):
"""
Private function that doesn't support extended axis or keepdims.
These methods are extended to this function using _ureduce
See nanpercentile for parameter usage
"""
if axis is None:
part = a.ravel()
result = _nanpercentile1d(part, q, overwrite_input, interpolation)
else:
result = np.apply_along_axis(_nanpercentile1d, axis, a, q,
overwrite_input, interpolation)
# apply_along_axis fills in collapsed axis with results.
# Move that axis to the beginning to match percentile's
# convention.
if q.ndim != 0:
result = np.rollaxis(result, axis)
if out is not None:
out[...] = result
return result 示例7: _nanpercentile
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
def _nanpercentile(a, q, axis=None, out=None, overwrite_input=False,
interpolation='linear'):
"""
Private function that doesn't support extended axis or keepdims.
These methods are extended to this function using _ureduce
See nanpercentile for parameter usage
"""
if axis is None or a.ndim == 1:
part = a.ravel()
result = _nanpercentile1d(part, q, overwrite_input, interpolation)
else:
result = np.apply_along_axis(_nanpercentile1d, axis, a, q,
overwrite_input, interpolation)
# apply_along_axis fills in collapsed axis with results.
# Move that axis to the beginning to match percentile's
# convention.
if q.ndim != 0:
result = np.moveaxis(result, axis, 0)
if out is not None:
out[...] = result
return result 示例8: _nanpercentile
# 需要导入模块: from numpy.lib import function_base [as 别名]
# 或者: from numpy.lib.function_base import _ureduce [as 别名]
def _nanpercentile(a, q, axis=None, out=None, overwrite_input=False,
interpolation='linear', keepdims=False):
"""
Private function that doesn't support extended axis or keepdims.
These methods are extended to this function using _ureduce
See nanpercentile for parameter usage
"""
if axis is None:
part = a.ravel()
result = _nanpercentile1d(part, q, overwrite_input, interpolation)
else:
result = np.apply_along_axis(_nanpercentile1d, axis, a, q,
overwrite_input, interpolation)
if out is not None:
out[...] = result
return result