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openide/python/helpers/python-skeletons/numpy/core/multiarray.py
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Python

class ndarray(object):
"""
ndarray(shape, dtype=float, buffer=None, offset=0,
strides=None, order=None)
An array object represents a multidimensional, homogeneous array
of fixed-size items. An associated data-type object describes the
format of each element in the array (its byte-order, how many bytes it
occupies in memory, whether it is an integer, a floating point number,
or something else, etc.)
Arrays should be constructed using `array`, `zeros` or `empty` (refer
to the See Also section below). The parameters given here refer to
a low-level method (`ndarray(...)`) for instantiating an array.
For more information, refer to the `numpy` module and examine the
the methods and attributes of an array.
Parameters
----------
(for the __new__ method; see Notes below)
shape : tuple of ints
Shape of created array.
dtype : data-type, optional
Any object that can be interpreted as a numpy data type.
buffer : object exposing buffer interface, optional
Used to fill the array with data.
offset : int, optional
Offset of array data in buffer.
strides : tuple of ints, optional
Strides of data in memory.
order : {'C', 'F'}, optional
Row-major or column-major order.
Attributes
----------
T : ndarray
Transpose of the array.
data : buffer
The array's elements, in memory.
dtype : dtype object
Describes the format of the elements in the array.
flags : dict
Dictionary containing information related to memory use, e.g.,
'C_CONTIGUOUS', 'OWNDATA', 'WRITEABLE', etc.
flat : numpy.flatiter object
Flattened version of the array as an iterator. The iterator
allows assignments, e.g., ``x.flat = 3`` (See `ndarray.flat` for
assignment examples; TODO).
imag : ndarray
Imaginary part of the array.
real : ndarray
Real part of the array.
size : int
Number of elements in the array.
itemsize : int
The memory use of each array element in bytes.
nbytes : int
The total number of bytes required to store the array data,
i.e., ``itemsize * size``.
ndim : int
The array's number of dimensions.
shape : tuple of ints
Shape of the array.
strides : tuple of ints
The step-size required to move from one element to the next in
memory. For example, a contiguous ``(3, 4)`` array of type
``int16`` in C-order has strides ``(8, 2)``. This implies that
to move from element to element in memory requires jumps of 2 bytes.
To move from row-to-row, one needs to jump 8 bytes at a time
(``2 * 4``).
ctypes : ctypes object
Class containing properties of the array needed for interaction
with ctypes.
base : ndarray
If the array is a view into another array, that array is its `base`
(unless that array is also a view). The `base` array is where the
array data is actually stored.
See Also
--------
array : Construct an array.
zeros : Create an array, each element of which is zero.
empty : Create an array, but leave its allocated memory unchanged (i.e.,
it contains "garbage").
dtype : Create a data-type.
Notes
-----
There are two modes of creating an array using ``__new__``:
1. If `buffer` is None, then only `shape`, `dtype`, and `order`
are used.
2. If `buffer` is an object exposing the buffer interface, then
all keywords are interpreted.
No ``__init__`` method is needed because the array is fully initialized
after the ``__new__`` method.
Examples
--------
These examples illustrate the low-level `ndarray` constructor. Refer
to the `See Also` section above for easier ways of constructing an
ndarray.
First mode, `buffer` is None:
>>> np.ndarray(shape=(2,2), dtype=float, order='F')
array([[ -1.13698227e+002, 4.25087011e-303],
[ 2.88528414e-306, 3.27025015e-309]]) #random
Second mode:
>>> np.ndarray((2,), buffer=np.array([1,2,3]),
... offset=np.int_().itemsize,
... dtype=int) # offset = 1*itemsize, i.e. skip first element
array([2, 3])
"""
pass
def __mul__(self, y): # real signature unknown; restored from __doc__
"""
x.__mul__(y) <==> x*y
Returns
-------
out : ndarray
"""
pass
def __neg__(self, *args, **kwargs): # real signature unknown
"""
x.__neg__() <==> -x
Returns
-------
out : ndarray
"""
pass
def __rmul__(self, y): # real signature unknown; restored from __doc__
"""
x.__rmul__(y) <==> y*x
Returns
-------
out : ndarray
"""
pass
def __abs__(self): # real signature unknown; restored from __doc__
"""
x.__abs__() <==> abs(x)
Returns
-------
out : ndarray
"""
pass
def __add__(self, y): # real signature unknown; restored from __doc__
"""
x.__add__(y) <==> x+y
Returns
-------
out : ndarray
"""
pass
def __radd__(self, y): # real signature unknown; restored from __doc__
"""
x.__radd__(y) <==> y+x
Returns
-------
out : ndarray
"""
pass
def __copy__(self, order=None): # real signature unknown; restored from __doc__
"""
a.__copy__([order])
Return a copy of the array.
Parameters
----------
order : {'C', 'F', 'A'}, optional
If order is 'C' (False) then the result is contiguous (default).
If order is 'Fortran' (True) then the result has fortran order.
If order is 'Any' (None) then the result has fortran order
only if the array already is in fortran order.
Returns
-------
out : ndarray
"""
pass
def __div__(self, y): # real signature unknown; restored from __doc__
"""
x.__div__(y) <==> x/y
Returns
-------
out : ndarray
"""
pass
def __rdiv__(self, y): # real signature unknown; restored from __doc__
"""
x.__rdiv__(y) <==> y/x
Returns
-------
out : ndarray
"""
pass
def __truediv__(self, y): # real signature unknown; restored from __doc__
"""
x.__truediv__(y) <==> x/y
Returns
-------
out : ndarray
"""
pass
def __rtruediv__(self, y): # real signature unknown; restored from __doc__
"""
x.__rtruediv__(y) <==> y/x
Returns
-------
out : ndarray
"""
pass
def __floordiv__(self, y): # real signature unknown; restored from __doc__
"""
x.__floordiv__(y) <==> x//y
Returns
-------
out : ndarray
"""
pass
def __rfloordiv__(self, y): # real signature unknown; restored from __doc__
"""
x.__rfloordiv__(y) <==> y//x
Returns
-------
out : ndarray
"""
pass
def __mod__(self, y): # real signature unknown; restored from __doc__
"""
x.__mod__(y) <==> x%y
Returns
-------
out : ndarray
"""
pass
def __rmod__(self, y): # real signature unknown; restored from __doc__
"""
x.__rmod__(y) <==> y%x
Returns
-------
out : ndarray
"""
pass
def __lshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__lshift__(y) <==> x<<y
Returns
-------
out : ndarray
"""
pass
def __rlshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__rlshift__(y) <==> y<<x
Returns
-------
out : ndarray
"""
pass
def __rshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__rshift__(y) <==> x>>y
Returns
-------
out : ndarray
"""
pass
def __rrshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__rrshift__(y) <==> y>>x
Returns
-------
out : ndarray
"""
pass
def __and__(self, y): # real signature unknown; restored from __doc__
"""
x.__and__(y) <==> x&y
Returns
-------
out : ndarray
"""
pass
def __rand__(self, y): # real signature unknown; restored from __doc__
"""
x.__rand__(y) <==> y&x
Returns
-------
out : ndarray
"""
pass
def __or__(self, y): # real signature unknown; restored from __doc__
"""
x.__or__(y) <==> x|y
Returns
-------
out : ndarray
"""
pass
def __pos__(self, *args, **kwargs): # real signature unknown
"""
x.__pos__() <==> +x
Returns
-------
out : ndarray
"""
pass
def __ror__(self, y): # real signature unknown; restored from __doc__
"""
x.__ror__(y) <==> y|x
Returns
-------
out : ndarray
"""
pass
def __xor__(self, y): # real signature unknown; restored from __doc__
"""
x.__xor__(y) <==> x^y
Returns
-------
out : ndarray
"""
pass
def __rxor__(self, y): # real signature unknown; restored from __doc__
"""
x.__rxor__(y) <==> y^x
Returns
-------
out : ndarray
"""
pass
def __ge__(self, y): # real signature unknown; restored from __doc__
"""
x.__ge__(y) <==> x>=y
Returns
-------
out : ndarray
"""
pass
def __rge__(self, y): # real signature unknown; restored from __doc__
"""
x.__rge__(y) <==> y>=x
Returns
-------
out : ndarray
"""
pass
def __eq__(self, y): # real signature unknown; restored from __doc__
"""
x.__eq__(y) <==> x==y
Returns
-------
out : ndarray
"""
pass
def __req__(self, y): # real signature unknown; restored from __doc__
"""
x.__req__(y) <==> y==x
Returns
-------
out : ndarray
"""
pass
def __sub__(self, y): # real signature unknown; restored from __doc__
"""
x.__sub__(y) <==> x-y
Returns
-------
out : ndarray
"""
pass
def __rsub__(self, y): # real signature unknown; restored from __doc__
"""
x.__rsub__(y) <==> y-x
Returns
-------
out : ndarray
"""
pass
def __lt__(self, y): # real signature unknown; restored from __doc__
"""
x.__lt__(y) <==> x<y
Returns
-------
out : ndarray
"""
pass
def __rlt__(self, y): # real signature unknown; restored from __doc__
"""
x.__rlt__(y) <==> y<x
Returns
-------
out : ndarray
"""
pass
def __le__(self, y): # real signature unknown; restored from __doc__
"""
x.__le__(y) <==> x<=y
Returns
-------
out : ndarray
"""
pass
def __rle__(self, y): # real signature unknown; restored from __doc__
"""
x.__rle__(y) <==> y<=x
Returns
-------
out : ndarray
"""
pass
def __gt__(self, y): # real signature unknown; restored from __doc__
"""
x.__gt__(y) <==> x>y
Returns
-------
out : ndarray
"""
pass
def __rgt__(self, y): # real signature unknown; restored from __doc__
"""
x.__rgt__(y) <==> y>x
Returns
-------
out : ndarray
"""
pass
def __ne__(self, y): # real signature unknown; restored from __doc__
"""
x.__ne__(y) <==> x!=y
Returns
-------
out : ndarray
"""
pass
def __rne__(self, y): # real signature unknown; restored from __doc__
"""
x.__rne__(y) <==> y!=x
Returns
-------
out : ndarray
"""
pass
def __iadd__(self, y): # real signature unknown; restored from __doc__
"""
x.__iadd__(y) <==> x+=y
Returns
-------
out : ndarray
"""
pass
def __riadd__(self, y): # real signature unknown; restored from __doc__
"""
x.__riadd__(y) <==> y+=x
Returns
-------
out : ndarray
"""
pass
def __isub__(self, y): # real signature unknown; restored from __doc__
"""
x.__isub__(y) <==> x-=y
Returns
-------
out : ndarray
"""
pass
def __risub__(self, y): # real signature unknown; restored from __doc__
"""
x.__risub__(y) <==> y-=x
Returns
-------
out : ndarray
"""
pass
def __imul__(self, y): # real signature unknown; restored from __doc__
"""
x.__imul__(y) <==> x*=y
Returns
-------
out : ndarray
"""
pass
def __rimul__(self, y): # real signature unknown; restored from __doc__
"""
x.__rimul__(y) <==> y*=x
Returns
-------
out : ndarray
"""
pass
def __idiv__(self, y): # real signature unknown; restored from __doc__
"""
x.__idiv__(y) <==> x/=y
Returns
-------
out : ndarray
"""
pass
def __ridiv__(self, y): # real signature unknown; restored from __doc__
"""
x.__ridiv__(y) <==> y/=x
Returns
-------
out : ndarray
"""
pass
def __itruediv__(self, y): # real signature unknown; restored from __doc__
"""
x.__itruediv__(y) <==> x/y
Returns
-------
out : ndarray
"""
pass
def __ritruediv__(self, y): # real signature unknown; restored from __doc__
"""
x.__ritruediv__(y) <==> y/x
Returns
-------
out : ndarray
"""
pass
def __ifloordiv__(self, y): # real signature unknown; restored from __doc__
"""
x.__ifloordiv__(y) <==> x//y
Returns
-------
out : ndarray
"""
pass
def __rifloordiv__(self, y): # real signature unknown; restored from __doc__
"""
x.__rifloordiv__(y) <==> y//x
Returns
-------
out : ndarray
"""
pass
def __imod__(self, y): # real signature unknown; restored from __doc__
"""
x.__imod__(y) <==> x%=y
Returns
-------
out : ndarray
"""
pass
def __rimod__(self, y): # real signature unknown; restored from __doc__
"""
x.__rimod__(y) <==> y%=x
Returns
-------
out : ndarray
"""
pass
def __ipow__(self, y): # real signature unknown; restored from __doc__
"""
x.__ipow__(y) <==> x**=y
Returns
-------
out : ndarray
"""
pass
def __ripow__(self, y): # real signature unknown; restored from __doc__
"""
x.__ripow__(y) <==> y**=x
Returns
-------
out : ndarray
"""
pass
def __ilshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__ilshift__(y) <==> x<<=y
Returns
-------
out : ndarray
"""
pass
def __rilshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__rilshift__(y) <==> y<<=x
Returns
-------
out : ndarray
"""
pass
def __irshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__irshift__(y) <==> x>>=y
Returns
-------
out : ndarray
"""
pass
def __rirshift__(self, y): # real signature unknown; restored from __doc__
"""
x.__rirshift__(y) <==> y>>=x
Returns
-------
out : ndarray
"""
pass
def __iand__(self, y): # real signature unknown; restored from __doc__
"""
x.__iand__(y) <==> x&=y
Returns
-------
out : ndarray
"""
pass
def __riand__(self, y): # real signature unknown; restored from __doc__
"""
x.__riand__(y) <==> y&=x
Returns
-------
out : ndarray
"""
pass
def __invert__(self, *args, **kwargs): # real signature unknown
"""
x.__invert__() <==> ~x
Returns
-------
out : ndarray
"""
pass
def __ior__(self, y): # real signature unknown; restored from __doc__
"""
x.__ior__(y) <==> x|=y
Returns
-------
out : ndarray
"""
pass
def __rior__(self, y): # real signature unknown; restored from __doc__
"""
x.__rior__(y) <==> y|=x
Returns
-------
out : ndarray
"""
pass
def __ixor__(self, y): # real signature unknown; restored from __doc__
"""
x.__ixor__(y) <==> x^=y
Returns
-------
out : ndarray
"""
pass
def __rixor__(self, y): # real signature unknown; restored from __doc__
"""
x.__rixor__(y) <==> y^=x
Returns
-------
out : ndarray
"""
pass
def __pow__(self, y): # real signature unknown; restored from __doc__
"""
x.__pow__(y) <==> x**y
Returns
-------
out : ndarray
"""
pass
def __divmod__(self, y): # real signature unknown; restored from __doc__
"""
x.__divmod__(y) <==> x%y
Returns
-------
out : ndarray
"""
pass