def setdiff(eq1, eq2):
eq1, eq2 = eqsize(eq1, eq2)
c1 = [None] * eq1.shape
c2 = [None] * eq2.shape
for i in range(0, eq1.size):
c1.append[i] = hash(eq2[i])
for i in range(0, eq2.size):
c2[i] = hash(eq2[i])
ia = np.delete(np.arange(np.alen(c1)), np.searchsorted(c1, c2))
ia = (ia[:]).conj().T
p = eq1[ia]
return p, ia
python类alen()的实例源码
def _validate_dataset(ds):
if not type(ds.data) is np.ndarray:
return ['Dataset.data must be a numpy.ndarray']
elif np.alen(ds.data) < 1:
return ['Dataset.data must not be empty']
elif not np.issubdtype(ds.data.dtype, np.float64):
return ['Dataset.data.dtype must be numpy.float64']
if ds.is_scale:
if len(ds.data.shape) != 1:
return ['Scales must be one-dimensional']
if np.any(np.diff(ds.data) <= 0):
return ['Scales must be strictly monotonic increasing']
else:
if (len(ds.data.shape) >= 1) and (ds.data.shape[0] > 0) and not (len(ds.data.shape) == len(ds.scales)):
return ['The number of scales does not match the number of dimensions']
return []
def test_basic(self):
m = np.array([1, 2, 3])
self.assertEqual(np.alen(m), 3)
m = np.array([[1, 2, 3], [4, 5, 7]])
self.assertEqual(np.alen(m), 2)
m = [1, 2, 3]
self.assertEqual(np.alen(m), 3)
m = [[1, 2, 3], [4, 5, 7]]
self.assertEqual(np.alen(m), 2)
def test_singleton(self):
self.assertEqual(np.alen(5), 1)
def alen(a):
"""
Return the length of the first dimension of the input array.
Parameters
----------
a : array_like
Input array.
Returns
-------
alen : int
Length of the first dimension of `a`.
See Also
--------
shape, size
Examples
--------
>>> a = np.zeros((7,4,5))
>>> a.shape[0]
7
>>> np.alen(a)
7
"""
try:
return len(a)
except TypeError:
return len(array(a, ndmin=1))
def test_basic(self):
m = np.array([1, 2, 3])
self.assertEqual(np.alen(m), 3)
m = np.array([[1, 2, 3], [4, 5, 7]])
self.assertEqual(np.alen(m), 2)
m = [1, 2, 3]
self.assertEqual(np.alen(m), 3)
m = [[1, 2, 3], [4, 5, 7]]
self.assertEqual(np.alen(m), 2)
def test_singleton(self):
self.assertEqual(np.alen(5), 1)
def alen(a):
"""
Return the length of the first dimension of the input array.
Parameters
----------
a : array_like
Input array.
Returns
-------
alen : int
Length of the first dimension of `a`.
See Also
--------
shape, size
Examples
--------
>>> a = np.zeros((7,4,5))
>>> a.shape[0]
7
>>> np.alen(a)
7
"""
try:
return len(a)
except TypeError:
return len(array(a, ndmin=1))
fromnumeric.py 文件源码
项目：PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
项目源码
文件源码
阅读 29
收藏 0
点赞 0
评论 0
def alen(a):
"""
Return the length of the first dimension of the input array.
Parameters
----------
a : array_like
Input array.
Returns
-------
alen : int
Length of the first dimension of `a`.
See Also
--------
shape, size
Examples
--------
>>> a = np.zeros((7,4,5))
>>> a.shape[0]
7
>>> np.alen(a)
7
"""
try:
return len(a)
except TypeError:
return len(array(a, ndmin=1))
def alen(a):
"""
Return the length of the first dimension of the input array.
Parameters
----------
a : array_like
Input array.
Returns
-------
alen : int
Length of the first dimension of `a`.
See Also
--------
shape, size
Examples
--------
>>> a = np.zeros((7,4,5))
>>> a.shape[0]
7
>>> np.alen(a)
7
"""
try:
return len(a)
except TypeError:
return len(array(a, ndmin=1))
def test_basic(self):
m = np.array([1, 2, 3])
self.assertEqual(np.alen(m), 3)
m = np.array([[1, 2, 3], [4, 5, 7]])
self.assertEqual(np.alen(m), 2)
m = [1, 2, 3]
self.assertEqual(np.alen(m), 3)
m = [[1, 2, 3], [4, 5, 7]]
self.assertEqual(np.alen(m), 2)
def test_singleton(self):
self.assertEqual(np.alen(5), 1)
def alen(a):
"""
Return the length of the first dimension of the input array.
Parameters
----------
a : array_like
Input array.
Returns
-------
alen : int
Length of the first dimension of `a`.
See Also
--------
shape, size
Examples
--------
>>> a = np.zeros((7,4,5))
>>> a.shape[0]
7
>>> np.alen(a)
7
"""
try:
return len(a)
except TypeError:
return len(array(a, ndmin=1))
def test_basic(self):
m = np.array([1, 2, 3])
self.assertEqual(np.alen(m), 3)
m = np.array([[1, 2, 3], [4, 5, 7]])
self.assertEqual(np.alen(m), 2)
m = [1, 2, 3]
self.assertEqual(np.alen(m), 3)
m = [[1, 2, 3], [4, 5, 7]]
self.assertEqual(np.alen(m), 2)
def test_singleton(self):
self.assertEqual(np.alen(5), 1)
def alen(a):
"""
Return the length of the first dimension of the input array.
Parameters
----------
a : array_like
Input array.
Returns
-------
alen : int
Length of the first dimension of `a`.
See Also
--------
shape, size
Examples
--------
>>> a = np.zeros((7,4,5))
>>> a.shape[0]
7
>>> np.alen(a)
7
"""
try:
return len(a)
except TypeError:
return len(array(a, ndmin=1))
def test_basic(self):
m = np.array([1, 2, 3])
self.assertEqual(np.alen(m), 3)
m = np.array([[1, 2, 3], [4, 5, 7]])
self.assertEqual(np.alen(m), 2)
m = [1, 2, 3]
self.assertEqual(np.alen(m), 3)
m = [[1, 2, 3], [4, 5, 7]]
self.assertEqual(np.alen(m), 2)
def test_singleton(self):
self.assertEqual(np.alen(5), 1)
def alen(a):
"""
Return the length of the first dimension of the input array.
Parameters
----------
a : array_like
Input array.
Returns
-------
alen : int
Length of the first dimension of `a`.
See Also
--------
shape, size
Examples
--------
>>> a = np.zeros((7,4,5))
>>> a.shape[0]
7
>>> np.alen(a)
7
"""
try:
return len(a)
except TypeError:
return len(array(a, ndmin=1))
def shape(a):
"""
Return the shape of an array.
Parameters
----------
a : array_like
Input array.
Returns
-------
shape : tuple of ints
The elements of the shape tuple give the lengths of the
corresponding array dimensions.
See Also
--------
alen
ndarray.shape : Equivalent array method.
Examples
--------
>>> np.shape(np.eye(3))
(3, 3)
>>> np.shape([[1, 2]])
(1, 2)
>>> np.shape([0])
(1,)
>>> np.shape(0)
()
>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
>>> np.shape(a)
(2,)
>>> a.shape
(2,)
"""
try:
result = a.shape
except AttributeError:
result = asarray(a).shape
return result
def shape(a):
"""
Return the shape of an array.
Parameters
----------
a : array_like
Input array.
Returns
-------
shape : tuple of ints
The elements of the shape tuple give the lengths of the
corresponding array dimensions.
See Also
--------
alen
ndarray.shape : Equivalent array method.
Examples
--------
>>> np.shape(np.eye(3))
(3, 3)
>>> np.shape([[1, 2]])
(1, 2)
>>> np.shape([0])
(1,)
>>> np.shape(0)
()
>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
>>> np.shape(a)
(2,)
>>> a.shape
(2,)
"""
try:
result = a.shape
except AttributeError:
result = asarray(a).shape
return result
fromnumeric.py 文件源码
项目：PyDataLondon29-EmbarrassinglyParallelDAWithAWSLambda
作者: SignalMedia
项目源码
文件源码
阅读 28
收藏 0
点赞 0
评论 0
def shape(a):
"""
Return the shape of an array.
Parameters
----------
a : array_like
Input array.
Returns
-------
shape : tuple of ints
The elements of the shape tuple give the lengths of the
corresponding array dimensions.
See Also
--------
alen
ndarray.shape : Equivalent array method.
Examples
--------
>>> np.shape(np.eye(3))
(3, 3)
>>> np.shape([[1, 2]])
(1, 2)
>>> np.shape([0])
(1,)
>>> np.shape(0)
()
>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
>>> np.shape(a)
(2,)
>>> a.shape
(2,)
"""
try:
result = a.shape
except AttributeError:
result = asarray(a).shape
return result
def shape(a):
"""
Return the shape of an array.
Parameters
----------
a : array_like
Input array.
Returns
-------
shape : tuple of ints
The elements of the shape tuple give the lengths of the
corresponding array dimensions.
See Also
--------
alen
ndarray.shape : Equivalent array method.
Examples
--------
>>> np.shape(np.eye(3))
(3, 3)
>>> np.shape([[1, 2]])
(1, 2)
>>> np.shape([0])
(1,)
>>> np.shape(0)
()
>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
>>> np.shape(a)
(2,)
>>> a.shape
(2,)
"""
try:
result = a.shape
except AttributeError:
result = asarray(a).shape
return result
def shape(a):
"""
Return the shape of an array.
Parameters
----------
a : array_like
Input array.
Returns
-------
shape : tuple of ints
The elements of the shape tuple give the lengths of the
corresponding array dimensions.
See Also
--------
alen
ndarray.shape : Equivalent array method.
Examples
--------
>>> np.shape(np.eye(3))
(3, 3)
>>> np.shape([[1, 2]])
(1, 2)
>>> np.shape([0])
(1,)
>>> np.shape(0)
()
>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
>>> np.shape(a)
(2,)
>>> a.shape
(2,)
"""
try:
result = a.shape
except AttributeError:
result = asarray(a).shape
return result
def shape(a):
"""
Return the shape of an array.
Parameters
----------
a : array_like
Input array.
Returns
-------
shape : tuple of ints
The elements of the shape tuple give the lengths of the
corresponding array dimensions.
See Also
--------
alen
ndarray.shape : Equivalent array method.
Examples
--------
>>> np.shape(np.eye(3))
(3, 3)
>>> np.shape([[1, 2]])
(1, 2)
>>> np.shape([0])
(1,)
>>> np.shape(0)
()
>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
>>> np.shape(a)
(2,)
>>> a.shape
(2,)
"""
try:
result = a.shape
except AttributeError:
result = asarray(a).shape
return result
def shape(a):
"""
Return the shape of an array.
Parameters
----------
a : array_like
Input array.
Returns
-------
shape : tuple of ints
The elements of the shape tuple give the lengths of the
corresponding array dimensions.
See Also
--------
alen
ndarray.shape : Equivalent array method.
Examples
--------
>>> np.shape(np.eye(3))
(3, 3)
>>> np.shape([[1, 2]])
(1, 2)
>>> np.shape([0])
(1,)
>>> np.shape(0)
()
>>> a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
>>> np.shape(a)
(2,)
>>> a.shape
(2,)
"""
try:
result = a.shape
except AttributeError:
result = asarray(a).shape
return result
