numpy 简单用法

numpy.array 参数类型要一样，而list参数可以不同
import numpy
vector=numpy.array([5,6,7,8,9])
matrix=numpy.array([[1,2,3],[2,3,4],[4,5,6]])
print(vector)
print(matrix)
print(vector.shape)
print(matrix.shape)
vector.dtype

>>>
[5 6 7 8 9]
[[1 2 3]
 [2 3 4]
 [4 5 6]]
(5,)
(3, 3)
dtype('int32')

matrix=numpy.array([[1,2,3],[2,3,4],[4,5,6]])
vector=numpy.array([5,6,7,8,9])
print(vector[1:4])
print(matrix[:,:2])
vector==7
matrix==3

>>>
[6 7 8]
[[1 2]
 [2 3]
 [4 5]]
Out[20]:
array([[False, False,  True],
       [False,  True, False],
       [False, False, False]], dtype=bool)

vector=numpy.array([5,6,7,8,9])
equal_seven=(vector==7)
print(vector[equal_seven])

>>>
[7]

vector=numpy.array([5,6,7,8,9])
equal_seven_and_eight=(vector==7)&(vector==8)
print(equal_seven_and_eight)
equal_seven_or_eight=(vector==7)|(vector==8)
print(equal_seven_or_eight)

>>>
[False False False False False]
[False False  True  True False]

vector=numpy.array([5,6,7,8,9])
print(vector.dtype)
vectors=vector.astype(float)
print(vectors.dtype)
print(vectors)

>>>
int32
float64
[ 5.  6.  7.  8.  9.]

vector=numpy.array([5,6,7,8,9])
print(vector.min())#求最小值

>>>
5


matrix=numpy.array([[1,2,3],[2,3,4],[4,5,6]])
print(matrix.sum(axis=0))#按列求和
print(matrix.sum(axis=1))#按行求和

>>>
[ 7 10 13]
[ 6  9 15]

import numpy as np
print(np.arange(15))#生成数列
a=np.arange(15).reshape(3,5)#将数列变成矩阵
print(a)

>>>
[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14]
[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]]

a.shape#行列数
>>>
(3, 5)

a.ndim #矩阵的维度 
>>>
2

a.dtype.name#类型
>>>
'int32'

a.size#总共元素的个数
>>>
15

np.zeros((3,4))#创建0矩阵，它默认float类型
>>>
array([[ 0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.],
       [ 0.,  0.,  0.,  0.]])

np.ones((2,3,4),dtype=np.int32)#2-矩阵个数，3-矩阵行数，4-矩阵列数，将类型转化为int型
>>>
array([[[1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1]],

       [[1, 1, 1, 1],
        [1, 1, 1, 1],
        [1, 1, 1, 1]]])

np.arange(10,30,5)#以10开始，0结束，步长为5生成向量
>>>
array([10, 15, 20, 25])

np.random.random((2,3))#-1到+1之间的数，组成2行3列矩阵
>>>
array([[ 0.34030141,  0.07582737,  0.09042225],
       [ 0.43623825,  0.28065344,  0.40964751]])

from numpy import pi#引入pi
np.linspace( 0, 2*pi, 100 )#在0到2*pi之间平均生成20个数
>>>
array([ 0.        ,  0.33069396,  0.66138793,  0.99208189,  1.32277585,
        1.65346982,  1.98416378,  2.31485774,  2.64555171,  2.97624567,
        3.30693964,  3.6376336 ,  3.96832756,  4.29902153,  4.62971549,
        4.96040945,  5.29110342,  5.62179738,  5.95249134,  6.28318531])
In [ ]:

​

a=np.array([10,11,12,13])
b=np.arange(4)
print(a)
print(b)
c=a-b
print(c)
c=c-1
print(c)
print(b**2)
print(a<3)

>>>
[10 11 12 13]
[0 1 2 3]
[10 10 10 10]
[9 9 9 9]
[0 1 4 9]
[False False False False]

A = np.array( [[1,1],
               [0,1]] )
B = np.array( [[2,0],
               [3,4]] )
print (A)
print ('-------')
print (B)
print ('-------')
print (A*B)#求内积
print ('-------')
print (A.dot(B))#矩阵a与矩阵b相乘方法1
print ('-------')
print (np.dot(A, B)) #矩阵a与矩阵b相乘方法2

>>>
[[1 1]
 [0 1]]
-------
[[2 0]
 [3 4]]
-------
[[2 0]
 [0 4]]
-------
[[5 4]
 [3 4]]
-------
[[5 4]
 [3 4]]

import numpy as np
B=np.arange(3)
print(B)
print(np.exp(B))#e的1次，e的2次，e的3次
print(np.sqrt(B))#0,1,2开根号

>>>
[0 1 2]
[ 1.          2.71828183  7.3890561 ]
[ 0.          1.          1.41421356]

a = np.floor(10*np.random.random((3,4)))#floor取整
print ('a',a)
print ('--------')
b=a.ravel()#将矩阵变成向量
print('b',b)
print ('--------')
c=b.reshape(6,2)#将向量变成矩阵
print('c',c)
print ('--------')
d=c.shape = (2, 6)
print ('d',d) 
print ('--------')
print (a.T)#a转置

>>>
a [[ 5.  2.  8.  7.]
 [ 0.  7.  9.  2.]
 [ 0.  8.  0.  0.]]
--------
b [ 5.  2.  8.  7.  0.  7.  9.  2.  0.  8.  0.  0.]
--------
c [[ 5.  2.]
 [ 8.  7.]
 [ 0.  7.]
 [ 9.  2.]
 [ 0.  8.]
 [ 0.  0.]]
--------
d (2, 6)
--------
[[ 5.  0.  0.]
 [ 2.  7.  8.]
 [ 8.  9.  0.]
 [ 7.  2.  0.]]

import numpy as np
a = np.floor(10*np.random.random((2,2)))
b = np.floor(10*np.random.random((2,2)))
print (a)
print ('---')
print (b)
print ('---')
print (np.vstack((a,b)))#将两个矩阵拼接
#np.hstack((a,b))

>>>
[[ 3.  7.]
 [ 2.  6.]]
---
[[ 9.  6.]
 [ 0.  7.]]
---
[[ 3.  7.]
 [ 2.  6.]
 [ 9.  6.]
 [ 0.  7.]]

import numpy as np
a = np.floor(10*np.random.random((2,2)))
b = np.floor(10*np.random.random((2,2)))
print (a)
print ('---')
print (b)
print ('---')
print (np.hstack((a,b)))#将两个矩阵按行拼接

>>>
[[ 4.  1.]
 [ 5.  3.]]
---
[[ 6.  3.]
 [ 4.  4.]]
---
[[ 4.  1.  6.  3.]
 [ 5.  3.  4.  4.]]
In [9]:

a = np.floor(10*np.random.random((2,12)))
print (a)
print ('---')
print (np.hsplit(a,3))#将矩阵a按行平均切成3份
print ('---')
print (np.hsplit(a,(3,4))) #将矩阵a按行，在3处切一次，在4处切一次
a = np.floor(10*np.random.random((12,2)))
print ('---')
print (a)
np.vsplit(a,3)#将矩阵a按列平均切成3份

>>>
[[ 9.  8.  3.  2.  5.  6.  4.  7.  2.  5.  6.  7.]
 [ 3.  8.  3.  5.  2.  6.  6.  0.  1.  8.  9.  1.]]
---
[array([[ 9.,  8.,  3.,  2.],
       [ 3.,  8.,  3.,  5.]]),
 array([[ 5.,  6.,  4.,  7.],
       [ 2.,  6.,  6.,  0.]]), 
array([[ 2.,  5.,  6.,  7.],
       [ 1.,  8.,  9.,  1.]])]
---
[array([[ 9.,  8.,  3.],
       [ 3.,  8.,  3.]]),
array([[ 2.],[ 5.]]), 
array([[ 5.,  6.,  4.,  7.,  2.,  5.,  6.,  7.],
       [ 2.,  6.,  6.,  0.,  1.,  8.,  9.,  1.]])]
---
[[ 4.  4.]
 [ 3.  5.]
 [ 9.  7.]
 [ 6.  0.]
 [ 5.  8.]
 [ 1.  4.]
 [ 1.  5.]
 [ 7.  1.]
 [ 2.  5.]
 [ 0.  4.]
 [ 1.  0.]
 [ 3.  1.]]
Out[3]:
[array([[ 4.,  4.],
        [ 3.,  5.],
        [ 9.,  7.],
        [ 6.,  0.]]), 
array([[ 5.,  8.],
        [ 1.,  4.],
        [ 1.,  5.],
        [ 7.,  1.]]),
 array([[ 2.,  5.],
        [ 0.,  4.],
        [ 1.,  0.],
        [ 3.,  1.]])]