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小编给大家分享一下Python中numpy.load()的使用方法,希望大家阅读完这篇文章后大所收获,下面让我们一起去探讨吧!
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用法:
numpy.load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding=’ASCII’)
参数:
file :file-like对象,字符串或pathlib.Path。要读取的文件。 File-like对象必须支持seek()和read()方法。
mmap_mode :如果不为None,则使用给定模式memory-map文件(有关详细信息,请参见numpy.memmap
模式说明)。
allow_pickle :允许加载存储在npy文件中的腌制对象数组。
fix_imports :仅在在Python 3上加载Python 2生成的腌制文件时有用,该文件包括包含对象数组的npy /npz文件。
encoding :仅当在Python 3中加载Python 2生成的腌制文件时有用,该文件包含包含对象数组的npy /npz文件。
Returns :数据存储在文件中。对于.npz文件,必须关闭NpzFile类的返回实例,以避免泄漏文件描述符。
代码1:
# Python program explaining # load() function import numpy as geek a = geek.array(([i + j for i in range(3) for j in range(3)])) # a is printed. print("a is:") print(a) geek.save('geekfile', a) print("the array is saved in the file geekfile.npy") # the array is saved in the file geekfile.npy b = geek.load('geekfile.npy') # the array is loaded into b print("b is:") print(b) # b is printed from geekfile.npy print("b is printed from geekfile.npy")
输出:
a is: [0, 1, 2, 1, 2, 3, 2, 3, 4] the array is saved in the file geekfile.npy b is: [0, 1, 2, 1, 2, 3, 2, 3, 4] b is printed from geekfile.npy
代码2:
# Python program explaining # load() function import numpy as geek # a and b are numpy arrays. a = geek.array(([i + j for i in range(3) for j in range(3)])) b = geek.array([i + 1 for i in range(3)]) # a and b are printed. print("a is:") print(a) print("b is:") print(b) # a and b are stored in geekfile.npz geek.savez('geekfile.npz', a = a, b = b) print("a and b are stored in geekfile.npz") # compressed file is loaded c = geek.load('geekfile.npz') print("after loading...") print("a is:", c['a']) print("b is:", c['b'])
输出:
a is: [0 1 2 1 2 3 2 3 4] b is: [1 2 3] a and b are stored in geekfile.npz after loading... a is:[0 1 2 1 2 3 2 3 4] b is:[1 2 3]
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