Python中的numpy函数的使用ones，zeros，eye

在看别人写的代码时，看到的不知道的函数，就在这里记下来。

原文是这样用的：

 1 weights = ones((numfeatures,1)) 

 在python中help（）：

import numpy as np 
help(np.ones)

 1 Help on function ones in module numpy.core.numeric:
 2 
 3 ones(shape, dtype=None, order='C')
 4     Return a new array of given shape and type, filled with ones.
 5     
 6     Parameters
 7     ----------
 8     shape : int or sequence of ints
 9         Shape of the new array, e.g., ``(2, 3)`` or ``2``.
10     dtype : data-type, optional
11         The desired data-type for the array, e.g., `numpy.int8`.  Default is
12         `numpy.float64`.
13     order : {'C', 'F'}, optional
14         Whether to store multidimensional data in C- or Fortran-contiguous
15         (row- or column-wise) order in memory.
16     
17     Returns
18     -------
19     out : ndarray
20         Array of ones with the given shape, dtype, and order.
21     
22     See Also
23     --------
24     zeros, ones_like
25     
26     Examples
27     --------
28     >>> np.ones(5)
29     array([ 1.,  1.,  1.,  1.,  1.])
30     
31     >>> np.ones((5,), dtype=np.int)
32     array([1, 1, 1, 1, 1])
33     
34     >>> np.ones((2, 1))
35     array([[ 1.],
36            [ 1.]])
37     
38     >>> s = (2,2)
39     >>> np.ones(s)
40     array([[ 1.,  1.],
41            [ 1.,  1.]])

 

zeros：

 1 Help on built-in function zeros in module numpy.core.multiarray:
 2 
 3 zeros(...)
 4     zeros(shape, dtype=float, order='C')
 5     
 6     Return a new array of given shape and type, filled with zeros.
 7     
 8     Parameters
 9     ----------
10     shape : int or sequence of ints
11         Shape of the new array, e.g., ``(2, 3)`` or ``2``.
12     dtype : data-type, optional
13         The desired data-type for the array, e.g., `numpy.int8`.  Default is
14         `numpy.float64`.
15     order : {'C', 'F'}, optional
16         Whether to store multidimensional data in C- or Fortran-contiguous
17         (row- or column-wise) order in memory.
18     
19     Returns
20     -------
21     out : ndarray
22         Array of zeros with the given shape, dtype, and order.
23     
24     See Also
25     --------
26     zeros_like : Return an array of zeros with shape and type of input.
27     ones_like : Return an array of ones with shape and type of input.
28     empty_like : Return an empty array with shape and type of input.
29     ones : Return a new array setting values to one.
30     empty : Return a new uninitialized array.
31     
32     Examples
33     --------
34     >>> np.zeros(5)
35     array([ 0.,  0.,  0.,  0.,  0.])
36     
37     >>> np.zeros((5,), dtype=np.int)
38     array([0, 0, 0, 0, 0])
39     
40     >>> np.zeros((2, 1))
41     array([[ 0.],
42            [ 0.]])
43     
44     >>> s = (2,2)
45     >>> np.zeros(s)
46     array([[ 0.,  0.],
47            [ 0.,  0.]])
48     
49     >>> np.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
50     array([(0, 0), (0, 0)],
51           dtype=[('x', ''), ('y', '')])

eye：

 1 Help on function eye in module numpy.lib.twodim_base:
 2 
 3 eye(N, M=None, k=0, dtype=<class 'float'>)
 4     Return a 2-D array with ones on the diagonal and zeros elsewhere.
 5     
 6     Parameters
 7     ----------
 8     N : int #行数
 9       Number of rows in the output. 
10     M : int, optional#列数
11       Number of columns in the output. If None, defaults to `N`.
12     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
13       Index of the diagonal: 0 (the default) refers to the main diagonal,
14       a positive value refers to an upper diagonal, and a negative value
15       to a lower diagonal.
16     dtype : data-type, optional
17       Data-type of the returned array.
18     
19     Returns
20     -------
21     I : ndarray of shape (N,M)
22       An array where all elements are equal to zero, except for the `k`-th
23       diagonal, whose values are equal to one.
24     
25     See Also
26     --------
27     identity : (almost) equivalent function
28     diag : diagonal 2-D array from a 1-D array specified by the user.
29     
30     Examples
31     --------
32     >>> np.eye(2, dtype=int)
33     array([[1, 0],
34            [0, 1]])
35     >>> np.eye(3, k=1)
36     array([[ 0.,  1.,  0.],
37            [ 0.,  0.,  1.],
38            [ 0.,  0.,  0.]])

 

转载于:https://www.cnblogs.com/qamra/p/8371344.html