Python *.npy 中数据的存储方式是什么？
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What is the way data is stored in *.npy?
提问by illegal-immigrant
I'm saving NumPy arrays using numpy.save function. I want other developers to have capability to read data from those file using C language. So I need to know,how numpy organizes binary data in file.OK, it's obvious when I'm saving array of 'i4' but what about array of arrays that contains some structures?Can't find any info in documentation
我正在使用 numpy.save 函数保存 NumPy 数组。我希望其他开发人员能够使用 C 语言从这些文件中读取数据。所以我需要知道，numpy 如何组织文件中的二进制数据。好的，当我保存 'i4' 数组时很明显，但是包含一些结构的数组数组呢？在文档中找不到任何信息
UPD : lets say tha data is something like :
UPD：可以说数据是这样的：
dt = np.dtype([('outer','(3,)<i4'),('outer2',[('inner','(10,)<i4'),('inner2','f8')])])
UPD2 : What about saving "dynamic" data (dtype - object)
UPD2：如何保存“动态”数据（dtype - 对象）
import numpy as np
a = [0,0,0]
b = [0,0]
c = [a,b]
dtype = np.dtype([('Name', '|S2'), ('objValue', object)])
data = np.zeros(3, dtype)
data[0]['objValue'] = a
data[1]['objValue'] = b
data[2]['objValue'] = c
data[0]['Name'] = 'a'
data[1]['Name'] = 'b'
data[2]['Name'] = 'c'
np.save(r'D:\in.npy', data)
Is it real to read that thing from C?
从 C 中读到那个东西是真的吗？
采纳答案by kennytm
The npy file format is documented in numpy's NEP 1 — A Simple File Format for NumPy Arrays.
npy 文件格式记录在 numpy 的NEP 1 — NumPy 数组的简单文件格式中。
For instance, the code
例如，代码
>>> dt=numpy.dtype([('outer','(3,)<i4'),
... ('outer2',[('inner','(10,)<i4'),('inner2','f8')])])
>>> a=numpy.array([((1,2,3),((10,11,12,13,14,15,16,17,18,19),3.14)),
... ((4,5,6),((-1,-2,-3,-4,-5,-6,-7,-8,-9,-20),6.28))],dt)
>>> numpy.save('1.npy', a)
results in the file:
结果在文件中：
93 4E 55 4D 50 59 magic ("\x93NUMPY")
01 major version (1)
00 minor version (0)
96 00 HEADER_LEN (0x0096 = 150)
7B 27 64 65 73 63 72 27
3A 20 5B 28 27 6F 75 74
65 72 27 2C 20 27 3C 69
34 27 2C 20 28 33 2C 29
29 2C 20 28 27 6F 75 74
65 72 32 27 2C 20 5B 28
27 69 6E 6E 65 72 27 2C
20 27 3C 69 34 27 2C 20
28 31 30 2C 29 29 2C 20
28 27 69 6E 6E 65 72 32 Header, describing the data structure
27 2C 20 27 3C 66 38 27 "{'descr': [('outer', '<i4', (3,)),
29 5D 29 5D 2C 20 27 66 ('outer2', [
6F 72 74 72 61 6E 5F 6F ('inner', '<i4', (10,)),
72 64 65 72 27 3A 20 46 ('inner2', '<f8')]
61 6C 73 65 2C 20 27 73 )],
68 61 70 65 27 3A 20 28 'fortran_order': False,
32 2C 29 2C 20 7D 20 20 'shape': (2,), }"
20 20 20 20 20 20 20 20
20 20 20 20 20 0A
01 00 00 00 02 00 00 00 03 00 00 00 (1,2,3)
0A 00 00 00 0B 00 00 00 0C 00 00 00
0D 00 00 00 0E 00 00 00 0F 00 00 00
10 00 00 00 11 00 00 00 12 00 00 00
13 00 00 00 (10,11,12,13,14,15,16,17,18,19)
1F 85 EB 51 B8 1E 09 40 3.14
04 00 00 00 05 00 00 00 06 00 00 00 (4,5,6)
FF FF FF FF FE FF FF FF FD FF FF FF
FC FF FF FF FB FF FF FF FA FF FF FF
F9 FF FF FF F8 FF FF FF F7 FF FF FF
EC FF FF FF (-1,-2,-3,-4,-5,-6,-7,-8,-9,-20)
1F 85 EB 51 B8 1E 19 40 6.28
回答by unutbu
The format is described in numpy/lib/format.py, where you can also see the Python source code used to load npy files. np.loadis defined here.
格式在numpy/lib/format.py 中进行了描述，您还可以在其中查看用于加载 npy 文件的 Python 源代码。在这里np.load定义。
