Numpy之文件存取的示例代码

import numpy as np
import os

os.chdir("d:\\")
a = np.arange(0,12)
a.reshape(3,4)
array([[ 0, 1, 2, 3],
    [ 4, 5, 6, 7],
    [ 8, 9, 10, 11]])

a.tofile("a.bin")                  #保存至a.bin

b = np.fromfile("a.bin", dtype=np.int32) #从文件中加载数组，错误的dtype会导致错误的结果
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])

b.reshape(3,4)
array([[ 0, 1, 2, 3],
    [ 4, 5, 6, 7],
    [ 8, 9, 10, 11]])
#读取的数据将为一维数组，需要使用reshape改变其数组结构

np.save("a.npy", a.reshape(3,4))
c = np.load("a.npy")
c
array([[ 0, 1, 2, 3],
    [ 4, 5, 6, 7],
    [ 8, 9, 10, 11]])

a = np.array([[1,2,3],[4,5,6]])
b = np.arange(0,1.0,0.1)
c = np.sin(b)
np.savez("result.npz", a, b, sin_arr=c) #使用sin_arr命名数组c
r = np.load("result.npz") #加载一次即可
r["arr_0"]
array([[1, 2, 3],
    [4, 5, 6]])
r["arr_1"]
array([ 0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
r["sin_arr"]
array([ 0.    , 0.09983342, 0.19866933, 0.29552021, 0.38941834,
    0.47942554, 0.56464247, 0.64421769, 0.71735609, 0.78332691])

a = np.arange(0,12,0.5).reshape(4,-1)
a
array([[ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5],
    [ 3. ,  3.5,  4. ,  4.5,  5. ,  5.5],
    [ 6. ,  6.5,  7. ,  7.5,  8. ,  8.5],
    [ 9. ,  9.5, 10. , 10.5, 11. , 11.5]])
np.savetxt("a.txt", a)
np.loadtxt("a.txt")
array([[ 0. ,  0.5,  1. ,  1.5,  2. ,  2.5],
    [ 3. ,  3.5,  4. ,  4.5,  5. ,  5.5],
    [ 6. ,  6.5,  7. ,  7.5,  8. ,  8.5],
    [ 9. ,  9.5, 10. , 10.5, 11. , 11.5]])
np.savetxt("a.txt", a, fmt="%d", delimiter=",") #指定存储数据类型为整型，分隔符为,
np.loadtxt("a.txt", delimiter=',') #以，分隔符读取
array([[ 0.,  0.,  1.,  1.,  2.,  2.],
    [ 3.,  3.,  4.,  4.,  5.,  5.],
    [ 6.,  6.,  7.,  7.,  8.,  8.],
    [ 9.,  9., 10., 10., 11., 11.]])