本文整理匯總了Python中numpy.core.numeric.asanyarray方法的典型用法代碼示例。如果您正苦於以下問題：Python numeric.asanyarray方法的具體用法？Python numeric.asanyarray怎麽用？Python numeric.asanyarray使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類numpy.core.numeric的用法示例。
在下文中一共展示了numeric.asanyarray方法的9個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: _mean
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def _mean(a, axis=None, dtype=None, out=None, keepdims=False):
arr = asanyarray(a)
rcount = _count_reduce_items(arr, axis)
# Make this warning show up first
if rcount == 0:
warnings.warn("Mean of empty slice.", RuntimeWarning)
# Cast bool, unsigned int, and int to float64 by default
if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)):
dtype = mu.dtype('f8')
ret = umr_sum(arr, axis, dtype, out, keepdims)
if isinstance(ret, mu.ndarray):
ret = um.true_divide(
ret, rcount, out=ret, casting='unsafe', subok=False)
elif hasattr(ret, 'dtype'):
ret = ret.dtype.type(ret / rcount)
else:
ret = ret / rcount
return ret 示例2: _mean
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def _mean(a, axis=None, dtype=None, out=None, keepdims=False):
arr = asanyarray(a)
rcount = _count_reduce_items(arr, axis)
# Make this warning show up first
if rcount == 0:
warnings.warn("Mean of empty slice.", RuntimeWarning)
# Cast bool, unsigned int, and int to float64 by default
if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)):
dtype = mu.dtype('f8')
ret = um.add.reduce(arr, axis=axis, dtype=dtype, out=out, keepdims=keepdims)
if isinstance(ret, mu.ndarray):
ret = um.true_divide(
ret, rcount, out=ret, casting='unsafe', subok=False)
else:
ret = ret.dtype.type(ret / rcount)
return ret 示例3: _mean
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def _mean(a, axis=None, dtype=None, out=None, keepdims=False):
arr = asanyarray(a)
rcount = _count_reduce_items(arr, axis)
# Make this warning show up first
if rcount == 0:
warnings.warn("Mean of empty slice.", RuntimeWarning)
# Cast bool, unsigned int, and int to float64 by default
if dtype is None and issubclass(arr.dtype.type, (nt.integer, nt.bool_)):
dtype = mu.dtype('f8')
ret = umr_sum(arr, axis, dtype, out, keepdims)
if isinstance(ret, mu.ndarray):
ret = um.true_divide(
ret, rcount, out=ret, casting='unsafe', subok=False)
elif hasattr(ret, 'dtype'):
ret = ret.dtype.type(ret / rcount)
else:
ret = ret / rcount
return ret 示例4: real
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def real(val):
"""
Return the real part of the complex argument.
Parameters
----------
val : array_like
Input array.
Returns
-------
out : ndarray or scalar
The real component of the complex argument. If `val` is real, the type
of `val` is used for the output. If `val` has complex elements, the
returned type is float.
See Also
--------
real_if_close, imag, angle
Examples
--------
>>> a = np.array([1+2j, 3+4j, 5+6j])
>>> a.real
array([ 1., 3., 5.])
>>> a.real = 9
>>> a
array([ 9.+2.j, 9.+4.j, 9.+6.j])
>>> a.real = np.array([9, 8, 7])
>>> a
array([ 9.+2.j, 8.+4.j, 7.+6.j])
>>> np.real(1 + 1j)
1.0
"""
try:
return val.real
except AttributeError:
return asanyarray(val).real 示例5: imag
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def imag(val):
"""
Return the imaginary part of the complex argument.
Parameters
----------
val : array_like
Input array.
Returns
-------
out : ndarray or scalar
The imaginary component of the complex argument. If `val` is real,
the type of `val` is used for the output. If `val` has complex
elements, the returned type is float.
See Also
--------
real, angle, real_if_close
Examples
--------
>>> a = np.array([1+2j, 3+4j, 5+6j])
>>> a.imag
array([ 2., 4., 6.])
>>> a.imag = np.array([8, 10, 12])
>>> a
array([ 1. +8.j, 3.+10.j, 5.+12.j])
>>> np.imag(1 + 1j)
1.0
"""
try:
return val.imag
except AttributeError:
return asanyarray(val).imag 示例6: iscomplex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def iscomplex(x):
"""
Returns a bool array, where True if input element is complex.
What is tested is whether the input has a non-zero imaginary part, not if
the input type is complex.
Parameters
----------
x : array_like
Input array.
Returns
-------
out : ndarray of bools
Output array.
See Also
--------
isreal
iscomplexobj : Return True if x is a complex type or an array of complex
numbers.
Examples
--------
>>> np.iscomplex([1+1j, 1+0j, 4.5, 3, 2, 2j])
array([ True, False, False, False, False, True])
"""
ax = asanyarray(x)
if issubclass(ax.dtype.type, _nx.complexfloating):
return ax.imag != 0
res = zeros(ax.shape, bool)
return res[()] # convert to scalar if needed 示例7: iscomplex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def iscomplex(x):
"""
Returns a bool array, where True if input element is complex.
What is tested is whether the input has a non-zero imaginary part, not if
the input type is complex.
Parameters
----------
x : array_like
Input array.
Returns
-------
out : ndarray of bools
Output array.
See Also
--------
isreal
iscomplexobj : Return True if x is a complex type or an array of complex
numbers.
Examples
--------
>>> np.iscomplex([1+1j, 1+0j, 4.5, 3, 2, 2j])
array([ True, False, False, False, False, True])
"""
ax = asanyarray(x)
if issubclass(ax.dtype.type, _nx.complexfloating):
return ax.imag != 0
res = zeros(ax.shape, bool)
return +res # convert to array-scalar if needed 示例8: fix
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def fix(x, y=None):
"""
Round to nearest integer towards zero.
Round an array of floats element-wise to nearest integer towards zero.
The rounded values are returned as floats.
Parameters
----------
x : array_like
An array of floats to be rounded
y : ndarray, optional
Output array
Returns
-------
out : ndarray of floats
The array of rounded numbers
See Also
--------
trunc, floor, ceil
around : Round to given number of decimals
Examples
--------
>>> np.fix(3.14)
3.0
>>> np.fix(3)
3.0
>>> np.fix([2.1, 2.9, -2.1, -2.9])
array([ 2., 2., -2., -2.])
"""
x = nx.asanyarray(x)
y1 = nx.floor(x)
y2 = nx.ceil(x)
if y is None:
y = nx.asanyarray(y1)
y[...] = nx.where(x >= 0, y1, y2)
return y 示例9: iscomplex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import asanyarray [as 別名]
def iscomplex(x):
"""
Returns a bool array, where True if input element is complex.
What is tested is whether the input has a non-zero imaginary part, not if
the input type is complex.
Parameters
----------
x : array_like
Input array.
Returns
-------
out : ndarray of bools
Output array.
See Also
--------
isreal
iscomplexobj : Return True if x is a complex type or an array of complex
numbers.
Examples
--------
>>> np.iscomplex([1+1j, 1+0j, 4.5, 3, 2, 2j])
array([ True, False, False, False, False, True])
"""
ax = asanyarray(x)
if issubclass(ax.dtype.type, _nx.complexfloating):
return ax.imag != 0
res = zeros(ax.shape, bool)
return +res # convet to array-scalar if needed