Numpy

一. Numpy 常用操作

a. xxxx

import numpy as np

print(np.arange(1,11))
    #[ 1  2  3  4  5  6  7  8  9 10]

print(np.arange(1,11).reshape([2,5]))
    #  [
    #    [ 1  2  3  4  5]
    #    [ 6  7  8  9 10]
    #  ]


li = np.arange(1,11).reshape([2,5])

print(li)
    # [
    #    [ 1  2  3  4  5]
    #    [ 6  7  8  9 10]
    # ]
print(np.exp(li))   #自然指数
    # [
    #    [  2.71828183e+00   7.38905610e+00   2.00855369e+01   5.45981500e+01  1.48413159e+02]
    #    [  4.03428793e+02   1.09663316e+03   2.98095799e+03   8.10308393e+03  2.20264658e+04]
    # ]
print(np.exp2(li))  #自然指数的平方
    # [
    #    [    2.     4.     8.    16.    32.]
    #    [   64.   128.   256.   512.  1024.]
    # ]
print(np.sqrt(li))  #开方
    # [
    #   [ 1.          1.41421356  1.73205081  2.          2.23606798]
    #   [ 2.44948974  2.64575131  2.82842712  3.          3.16227766]
    # ]

b. 单个数组操作

li = np.array([
    [[1,2,3,4],[4,5,6,7]],
    [[7,8,9,10],[10,11,12,13]],
    [[14,15,16,17],[18,19,20,21]]
])
print(li.sum())     #求和
    #252
print(li.sum(axis=0))   #最外层
    # [
    #    [22 25 28 31]
    #    [32 35 38 41]
    # ]
print(li.sum(axis=1))   #第一层
    # [
    #   [ 5  7  9 11]
    #   [17 19 21 23]
    #   [32 34 36 38]
    # ]
print(li.sum(axis=2))
    # [
    #   [10 22]
    #   [34 46]
    #   [62 78]
    # ]

c. 多个数组操作

#多个数组操作

li1 = np.array([10,20,30,40])
li2 = np.array([4,3,2,1])

print(li1.reshape([2,2]),li2.reshape([2,2]))
    # [ [10 20][30 40] ]
    # [ [4 3][2 1]   ]

print(np.dot(li1.reshape([2,2]),li2.reshape([2,2])))
    # [ [ 80  50][200 130] ]


print(np.concatenate((li1,li2)))       #追加
    # [10 20 30 40  4  3  2  1]
print(np.vstack((li1,li2)))
    # [[10 20 30 40] [ 4  3  2  1]]
print(np.hstack((li1,li2)))
    # [10 20 30 40  4  3  2  1]


print(np.split(li1,2))                 #分开
    #[array([10, 20]), array([30, 40])]

二.  线性方程组 矩阵

import numpy as np
from numpy.linalg import *

#numpy 线性方程组 和矩阵

#print(np.eye(3))        #矩阵
    #[[ 1.  0.  0.]
    # [ 0.  1.  0.]
    # [ 0.  0.  1.]]

li = np.array([         #自定义矩阵
    [1.,2.],[3.,4.]
])
#print(li)
    # [[ 1.  2.][ 3.  4.]]

print(inv(li))
    # [[-2.   1. ][ 1.5 -0.5]]

print(li.transpose())
    # [[ 1.  3.][ 2.  4.]]

print(det(li))
    # -2.0

print(eig(li))
    #(array([-0.37228132,  5.37228132]), array([[-0.82456484, -0.41597356],[ 0.56576746, -0.90937671]]))