Python 如何正确保存和加载 numpy.array() 数据？
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How to save and load numpy.array() data properly?
提问by bluevoxel
I wonder, how to save and load numpy.arraydata properly. Currently I'm using the numpy.savetxt()method. For example, if I got an array markers, which looks like this:
我想知道，如何numpy.array正确保存和加载数据。目前我正在使用该numpy.savetxt()方法。例如，如果我有一个数组markers，它看起来像这样：
I try to save it by the use of:
我尝试使用以下方法保存它：
numpy.savetxt('markers.txt', markers)
In other script I try to open previously saved file:
在其他脚本中，我尝试打开以前保存的文件：
markers = np.fromfile("markers.txt")
And that's what I get...
这就是我得到的......
Saved data first looks like this:
保存的数据首先看起来像这样：
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
0.000000000000000000e+00
But when I save just loaded data by the use of the same method, ie. numpy.savetxt()it looks like this:
但是当我使用相同的方法保存刚刚加载的数据时，即。numpy.savetxt()它看起来像这样：
1.398043286095131769e-76
1.398043286095288860e-76
1.396426376485745879e-76
1.398043286055061908e-76
1.398043286095288860e-76
1.182950697433698368e-76
1.398043275797188953e-76
1.398043286095288860e-76
1.210894289234927752e-99
1.398040649781712473e-76
What am I doing wrong? PS there are no other "backstage" operation which I perform. Just saving and loading, and that's what I get. Thank you in advance.
我究竟做错了什么？PS我没有执行其他“后台”操作。只是保存和加载，这就是我得到的。先感谢您。
采纳答案by xnx
The most reliable way I have found to do this is to use np.savetxtwith np.loadtxtand not np.fromfilewhich is better suited to binary files written with tofile. The np.fromfileand np.tofilemethods write and read binary files whereas np.savetxtwrites a text file.
So, for example:
我发现最可靠的方法是使用np.savetxtwithnp.loadtxt而 notnp.fromfile哪个更适合用tofile. 该np.fromfile和np.tofile方法写入和读取二进制文件，而np.savetxt写入一个文本文件。因此，例如：
In [1]: a = np.array([1, 2, 3, 4])
In [2]: np.savetxt('test1.txt', a, fmt='%d')
In [3]: b = np.loadtxt('test1.txt', dtype=int)
In [4]: a == b
Out[4]: array([ True, True, True, True], dtype=bool)
Or:
或者：
In [5]: a.tofile('test2.dat')
In [6]: c = np.fromfile('test2.dat', dtype=int)
In [7]: c == a
Out[7]: array([ True, True, True, True], dtype=bool)
I use the former method even if it is slower and creates bigger files (sometimes): the binary format can be platform dependent (for example, the file format depends on the endianness of your system).
我使用前一种方法，即使它速度较慢并创建更大的文件（有时）：二进制格式可能依赖于平台（例如，文件格式取决于系统的字节序）。
There is a platform independentformat for NumPy arrays, which can be saved and read with np.saveand np.load:
NumPy 数组有一种与平台无关的格式，可以使用np.save和保存和读取np.load：
In [8]: np.save('test3.npy', a) # .npy extension is added if not given
In [9]: d = np.load('test3.npy')
In [10]: a == d
Out[10]: array([ True, True, True, True], dtype=bool)
回答by ali_m
np.fromfile()has a sep=keyword argument:
np.fromfile()有一个sep=关键字参数：
Separator between items if file is a text file. Empty (“”) separator means the file should be treated as binary. Spaces (” ”) in the separator match zero or more whitespace characters. A separator consisting only of spaces must match at least one whitespace.
如果文件是文本文件，则项目之间的分隔符。空（“”）分隔符表示文件应被视为二进制文件。分隔符中的空格（“”）匹配零个或多个空白字符。仅由空格组成的分隔符必须至少匹配一个空格。
The default value of sep=""means that np.fromfile()tries to read it as a binary file rather than a space-separated text file, so you get nonsense values back. If you use np.fromfile('markers.txt', sep=" ")you will get the result you are looking for.
的默认值sep=""意味着np.fromfile()尝试将其作为二进制文件而不是空格分隔的文本文件读取，因此您会得到无意义的值。如果您使用，np.fromfile('markers.txt', sep=" ")您将获得您正在寻找的结果。
However, as others have pointed out, np.loadtxt()is the preferred way to convert text files to numpy arrays, and unless the file needs to be human-readable it is usually better to use binary formats instead (e.g. np.load()/np.save()).
然而，正如其他人指出的那样，np.loadtxt()是将文本文件转换为 numpy 数组的首选方法，除非文件需要人类可读，否则通常最好使用二进制格式（例如np.load()/ np.save()）。
回答by Sherzod
np.save('data.npy', num_arr) # save
new_num_arr = np.load('data.npy') # load
