numpy数组的类似Python列表的字符串表示形式

Question

Consider there is a few rather long numpy arrays:

importy numpy as np;
long_array1 = np.array([random.random() for i in range(10000)]);
long_array2 = np.array([random.random() for i in range(10000)]);
long_array3 = np.array([random.random() for i in range(10000)]);

I would like to save the arrays into the file file.dat , one row per numpy array. The text representation of an array should be in a python array-like format, ie in the case of following numpy array:

a = np.array([0.3213,0.145323,0.852,0.723,0.421452])

I want to save following line in the file.

[0.3213,0.145323,0.852,0.723,0.421452]

There is what I do:

array1_str = ",".join([str(item) for item in long_array1]);
array2_str = ",".join([str(item) for item in long_array2]);
array3_str = ",".join([str(item) for item in long_array3]);

with open("file.dat","w") as file_arrays:
    file_arrays.write("[" + array1_str + "]\n");
    file_arrays.write("[" + array2_str + "]\n");
    file_arrays.write("[" + array3_str + "]\n");

Everything works fine actually. I am just doubtful about the efficiency of my code. I am almost sure there has to be another (better and more efficient) way how to do this. I welcome comments to the random list generation as well.

Answer 1

This is the fastest way:

','.join(map(str, long_array1.tolist()))

If you want to keep the text more compact, this is fast too:

','.join(map(lambda x: '%.7g' % x, long_array1.tolist()))

Source: I benchmarked every possible method for this as the maintainer of the pycollada library.

Answer 2

Since you want a Python-list-like format, how about actually using the Python list format?

array1_str = repr(list(long_array1))

That's going to stay mostly in C-land and performance should be much better.

If you don't want the spaces, take 'em out after:

array1_str = repr(list(long_array1)).translate(None, " ")

Memory usage may be an issue, however.

Answer 3

sounds like you might be able to use the numpy.savetxt() for this;

something like:

def dump_array(outfile, arraylike):
    outfile.write('[')
    numpy.savetxt(outfile, arraylike, newline=',', fmt="%s")
    outfile.write(']\n')

although i don't think the corresponding numpy.loadtxt() will be able to read in this format.