本文整理匯總了Python中numpy.core.numeric.complexfloating方法的典型用法代碼示例。如果您正苦於以下問題：Python numeric.complexfloating方法的具體用法？Python numeric.complexfloating怎麽用？Python numeric.complexfloating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.complexfloating方法的12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: getH
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def getH(self):
"""
Returns the (complex) conjugate transpose of `self`.
Equivalent to ``np.transpose(self)`` if `self` is real-valued.
Parameters
----------
None
Returns
-------
ret : matrix object
complex conjugate transpose of `self`
Examples
--------
>>> x = np.matrix(np.arange(12).reshape((3,4)))
>>> z = x - 1j*x; z
matrix([[ 0. +0.j, 1. -1.j, 2. -2.j, 3. -3.j],
[ 4. -4.j, 5. -5.j, 6. -6.j, 7. -7.j],
[ 8. -8.j, 9. -9.j, 10.-10.j, 11.-11.j]])
>>> z.getH()
matrix([[ 0. +0.j, 4. +4.j, 8. +8.j],
[ 1. +1.j, 5. +5.j, 9. +9.j],
[ 2. +2.j, 6. +6.j, 10.+10.j],
[ 3. +3.j, 7. +7.j, 11.+11.j]])
"""
if issubclass(self.dtype.type, N.complexfloating):
return self.transpose().conjugate()
else:
return self.transpose() 示例2: iscomplex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [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3: iscomplexobj
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def iscomplexobj(x):
"""
Check for a complex type or an array of complex numbers.
The type of the input is checked, not the value. Even if the input
has an imaginary part equal to zero, `iscomplexobj` evaluates to True.
Parameters
----------
x : any
The input can be of any type and shape.
Returns
-------
iscomplexobj : bool
The return value, True if `x` is of a complex type or has at least
one complex element.
See Also
--------
isrealobj, iscomplex
Examples
--------
>>> np.iscomplexobj(1)
False
>>> np.iscomplexobj(1+0j)
True
>>> np.iscomplexobj([3, 1+0j, True])
True
"""
try:
dtype = x.dtype
type_ = dtype.type
except AttributeError:
type_ = asarray(x).dtype.type
return issubclass(type_, _nx.complexfloating) 示例4: iscomplex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [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5: iscomplex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [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], dtype=bool)
"""
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 示例6: iscomplexobj
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def iscomplexobj(x):
"""
Check for a complex type or an array of complex numbers.
The type of the input is checked, not the value. Even if the input
has an imaginary part equal to zero, `iscomplexobj` evaluates to True.
Parameters
----------
x : any
The input can be of any type and shape.
Returns
-------
iscomplexobj : bool
The return value, True if `x` is of a complex type or has at least
one complex element.
See Also
--------
isrealobj, iscomplex
Examples
--------
>>> np.iscomplexobj(1)
False
>>> np.iscomplexobj(1+0j)
True
>>> np.iscomplexobj([3, 1+0j, True])
True
"""
try:
dtype = x.dtype
except AttributeError:
dtype = asarray(x).dtype
try:
return issubclass(dtype.type, _nx.complexfloating)
except AttributeError:
return False 示例7: iscomplexobj
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def iscomplexobj(x):
"""
Check for a complex type or an array of complex numbers.
The type of the input is checked, not the value. Even if the input
has an imaginary part equal to zero, `iscomplexobj` evaluates to True.
Parameters
----------
x : any
The input can be of any type and shape.
Returns
-------
iscomplexobj : bool
The return value, True if `x` is of a complex type or has at least
one complex element.
See Also
--------
isrealobj, iscomplex
Examples
--------
>>> np.iscomplexobj(1)
False
>>> np.iscomplexobj(1+0j)
True
>>> np.iscomplexobj([3, 1+0j, True])
True
"""
return issubclass(asarray(x).dtype.type, _nx.complexfloating) 示例8: isrealobj
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def isrealobj(x):
"""
Return True if x is a not complex type or an array of complex numbers.
The type of the input is checked, not the value. So even if the input
has an imaginary part equal to zero, `isrealobj` evaluates to False
if the data type is complex.
Parameters
----------
x : any
The input can be of any type and shape.
Returns
-------
y : bool
The return value, False if `x` is of a complex type.
See Also
--------
iscomplexobj, isreal
Examples
--------
>>> np.isrealobj(1)
True
>>> np.isrealobj(1+0j)
False
>>> np.isrealobj([3, 1+0j, True])
False
"""
return not issubclass(asarray(x).dtype.type, _nx.complexfloating)
#----------------------------------------------------------------------------- 示例9: sort_complex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def sort_complex(a):
"""
Sort a complex array using the real part first, then the imaginary part.
Parameters
----------
a : array_like
Input array
Returns
-------
out : complex ndarray
Always returns a sorted complex array.
Examples
--------
>>> np.sort_complex([5, 3, 6, 2, 1])
array([ 1.+0.j, 2.+0.j, 3.+0.j, 5.+0.j, 6.+0.j])
>>> np.sort_complex([1 + 2j, 2 - 1j, 3 - 2j, 3 - 3j, 3 + 5j])
array([ 1.+2.j, 2.-1.j, 3.-3.j, 3.-2.j, 3.+5.j])
"""
b = array(a, copy=True)
b.sort()
if not issubclass(b.dtype.type, _nx.complexfloating):
if b.dtype.char in 'bhBH':
return b.astype('F')
elif b.dtype.char == 'g':
return b.astype('G')
else:
return b.astype('D')
else:
return b 示例10: iscomplex
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [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 示例11: iscomplexobj
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def iscomplexobj(x):
"""
Check for a complex type or an array of complex numbers.
The type of the input is checked, not the value. Even if the input
has an imaginary part equal to zero, `iscomplexobj` evaluates to True.
Parameters
----------
x : any
The input can be of any type and shape.
Returns
-------
iscomplexobj : bool
The return value, True if `x` is of a complex type or has at least
one complex element.
See Also
--------
isrealobj, iscomplex
Examples
--------
>>> np.iscomplexobj(1)
False
>>> np.iscomplexobj(1+0j)
True
>>> np.iscomplexobj([3, 1+0j, True])
True
"""
return issubclass( asarray(x).dtype.type, _nx.complexfloating) 示例12: isrealobj
# 需要導入模塊: from numpy.core import numeric [as 別名]
# 或者: from numpy.core.numeric import complexfloating [as 別名]
def isrealobj(x):
"""
Return True if x is a not complex type or an array of complex numbers.
The type of the input is checked, not the value. So even if the input
has an imaginary part equal to zero, `isrealobj` evaluates to False
if the data type is complex.
Parameters
----------
x : any
The input can be of any type and shape.
Returns
-------
y : bool
The return value, False if `x` is of a complex type.
See Also
--------
iscomplexobj, isreal
Examples
--------
>>> np.isrealobj(1)
True
>>> np.isrealobj(1+0j)
False
>>> np.isrealobj([3, 1+0j, True])
False
"""
return not issubclass( asarray(x).dtype.type, _nx.complexfloating)
#-----------------------------------------------------------------------------