格式化NumPy数组 [英] Formatting a NumPy array

问题描述

我想要这个:

        SP,1,2,3
        1,1.000000e+00,2.000000e+00,3.000000e+00
        2,1.630000e+01,1.990000e+01,1.840000e+01
        3,1.630000e+01,1.990000e+01,1.840000e+01
        4,1.630000e+01,1.990000e+01,1.840000e+01

我有以下代码:

np.savetxt("Final Array.csv", my_array, fmt="%10.6e", delimiter=',')

它产生:

    1.000000e+00,2.000000e+00,3.000000e+00
    1.630000e+01,1.990000e+01,1.840000e+01
    1.630000e+01,1.990000e+01,1.840000e+01
    1.630000e+01,1.990000e+01,1.840000e+01

我已经为最上面的行和最左边的列创建了数组.

I already have the arrays created for the top row and the left column.

如何设置格式，以便在保持数字格式正确的同时仍保留最左边的列，而最上面的行则保持原样?

How do I format this so that I can keep the numbers formatted correctly while still having the left most column, and the top row stay formatted as they are?

我正在使用vstack和hstack将它们组合在一起，但是"SP"也引起了问题，因为它不是浮点数.

I am using vstack and hstack to combine these, but the "SP" is also causing problems because it isn't a float.

我可以格式化它们，将其全部转换为字符串，合并然后保存txt吗?

Could I maybe format them, convert it all to a string, combine and then savetxt?

推荐答案

一个简单的解决方案需要创建一个与my_array长度相同的临时数组和一个额外的列.

A simple solution requires to create a temporary array with the same length as my_array and an extra column.

temp = np.empty((my_array.shape[0], my_array.shape[1]+1))

然后，在第一列中填充所需的索引，在最后一列中填充初始数组:

Then, fill the first column with the indices you want, and the last columns with your initial array:

temp[:,1:] = my_array
temp[:,0] = np.arange(1, len(my_array)+1)

要写入标题，必须首先以书面形式打开文件.您仍然可以将文件对象传递给np.savetxt，只需修改格式字符串，以使第一列写为int，其他列写为"%10.6e":

In order to write the header, you have to open the file in writing first. You can still pass the file object to np.savetxt, you just have to modify the format string so that your first column is written as int, the others as "%10.6e":

with open('final.csv', 'w') as f:
    f.write("SP,1,2,3\n")
    np.savetxt(f, temp, fmt="%i,%10.6e,%10.6e,%10.6e",delimiter=",")

一种更具交互性的方式来定义格式字符串，具体取决于my_array的列数

A more interactive way to define your format string, depending on the number of columns of my_array is

fmt = ",".join(["%i"] + ["%10.6e"] * my_array.shape[1])
np.savetxt(f, temp, fmt=fmt, delimiter=",")

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