Python中的numpy函数的使用ones，zeros，eye

import numpy as np
help(np.ones)

Help on function ones in module numpy.core.numeric: ones(shape, dtype=None, order='C')
Return a new array of given shape and type, filled with ones. Parameters
----------
shape : int or sequence of ints
Shape of the new array, e.g., ``(2, 3)`` or ``2``.
dtype : data-type, optional
The desired data-type for the array, e.g., `numpy.int8`. Default is
`numpy.float64`.
order : {'C', 'F'}, optional
Whether to store multidimensional data in C- or Fortran-contiguous
(row- or column-wise) order in memory. Returns
-------
out : ndarray
Array of ones with the given shape, dtype, and order. See Also
--------
zeros, ones_like Examples
--------
>>> np.ones(5)
array([ 1., 1., 1., 1., 1.]) >>> np.ones((5,), dtype=np.int)
array([1, 1, 1, 1, 1]) >>> np.ones((2, 1))
array([[ 1.],
[ 1.]]) >>> s = (2,2)
>>> np.ones(s)
array([[ 1., 1.],
[ 1., 1.]])

Help on built-in function zeros in module numpy.core.multiarray: zeros(...)
zeros(shape, dtype=float, order='C') Return a new array of given shape and type, filled with zeros. Parameters
----------
shape : int or sequence of ints
Shape of the new array, e.g., ``(2, 3)`` or ``2``.
dtype : data-type, optional
The desired data-type for the array, e.g., `numpy.int8`. Default is
`numpy.float64`.
order : {'C', 'F'}, optional
Whether to store multidimensional data in C- or Fortran-contiguous
(row- or column-wise) order in memory. Returns
-------
out : ndarray
Array of zeros with the given shape, dtype, and order. See Also
--------
zeros_like : Return an array of zeros with shape and type of input.
ones_like : Return an array of ones with shape and type of input.
empty_like : Return an empty array with shape and type of input.
ones : Return a new array setting values to one.
empty : Return a new uninitialized array. Examples
--------
>>> np.zeros(5)
array([ 0., 0., 0., 0., 0.]) >>> np.zeros((5,), dtype=np.int)
array([0, 0, 0, 0, 0]) >>> np.zeros((2, 1))
array([[ 0.],
[ 0.]]) >>> s = (2,2)
>>> np.zeros(s)
array([[ 0., 0.],
[ 0., 0.]]) >>> np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
array([(0, 0), (0, 0)],
dtype=[('x', '<i4'), ('y', '<i4')])

Help on function eye in module numpy.lib.twodim_base: eye(N, M=None, k=0, dtype=<class 'float'>)
Return a 2-D array with ones on the diagonal and zeros elsewhere. Parameters
----------
N : int #行数
Number of rows in the output.
M : int, optional#列数
Number of columns in the output. If None, defaults to `N`.
k : int, optional#对角线的位置，0的时候是正对角线，+1就是对角线向上移，-1就是对角线向下移
Index of the diagonal: 0 (the default) refers to the main diagonal,
a positive value refers to an upper diagonal, and a negative value
to a lower diagonal.
dtype : data-type, optional
Data-type of the returned array. Returns
-------
I : ndarray of shape (N,M)
An array where all elements are equal to zero, except for the `k`-th
diagonal, whose values are equal to one. See Also
--------
identity : (almost) equivalent function
diag : diagonal 2-D array from a 1-D array specified by the user. Examples
--------
>>> np.eye(2, dtype=int)
array([[1, 0],
[0, 1]])
>>> np.eye(3, k=1)
array([[ 0., 1., 0.],
[ 0., 0., 1.],
[ 0., 0., 0.]])