写作和阅读使用numpy.savetxt和numpy.loadtxt复数 [英] Writing and reading complex numbers using numpy.savetxt and numpy.loadtxt

问题描述

我需要写入和读取复数。我想用 numpy.savetxt 和 numpy.loadtxt 这样做。自从我写了code是相当大的我创建了一个测试文件，试图读写复数。

I need to write and read complex numbers. I would like to use numpy.savetxt and numpy.loadtxt to do so. Since the code that I have written is rather big I created a test file to try to write and read complex numbers.

到目前为止，我已经能够使用 numpy.savetxt 编写复杂的数字。在code是以下内容：

So far I have been able to write complex numbers using numpy.savetxt. The code is the following:

import numpy

d1 = -0.240921619563 - 0.0303165074169j
d2 = -0.340921619563 - 0.0403165074169j
d3 = -0.440921619563 - 0.0503165074169j
d4 = -0.540921619563 - 0.0603165074169j

array = numpy.array([d1, d2, d3, d4])

save = open("test.dat", "w")
numpy.savetxt(save, array.reshape(1, array.shape[0]), newline = "\r\n", fmt = "%.10f")

save.close()

这给出了以下的输出：

 (-0.2409216196+-0.0303165074j)  (-0.3409216196+-0.0403165074j)  (-0.4409216196+-0.0503165074j)  (-0.5409216196+-0.0603165074j)

所有的，我现在希望能够做的是实际读取/加载数据。剧本我已经是：

All that I now want to be able to do is actually read/load the data. The script I have is:

import numpy

d = numpy.loadtxt("test.dat")

这件code是不够的，我目前无法加载数据。我的问题是类似这个。但是，通过手动替换 + - 以 A - 我仍然无法加载数据。我认为，解决的办法是为 numpy.loadtxt 的 DTYPE 选项。我一直没能虽然看着办吧。

This piece of code is not sufficient and I am currently unable to load the data. My problem is similar to this one. However, by manually replacing the +- by a - I am still unable to load the data. I think the solution lies in the dtype option for numpy.loadtxt. I have not been able to figure it out though.

您帮助是极大的AP preciated！

Your help is greatly appreciated!

推荐答案

感谢华伦Weckesser！你建议的链接对我帮助很大。我现在有两个工作的脚本：一个使用 numpy的从文件写入使用 numpy.savetxt 复数和一个用于读/加载复数。 loadtxt 。

Thanks Warren Weckesser! The link you suggested helped me a lot. I now have two working scripts: one for writing complex numbers using numpy.savetxt and one for reading/loading the complex numbers from the file using numpy.loadtxt.

对于未来的引用文件，其codeS列举如下。

For future references, the codes are listed below.

写作：

import numpy

d1 = -0.240921619563-0.0303165074169j
d2 = -0.340921619563-0.0403165074169j
d3 = -0.440921619563-0.0503165074169j
d4 = -0.540921619563-0.0603165074169j

array = numpy.array([d1, d2, d3, d4])

save = open("test.dat","w")
numpy.savetxt(save, array.reshape(1, array.shape[0]), newline = "\r\n", fmt = '%.4f%+.4fj '*4)

save.close()

读/载入：

import numpy

coeffs = numpy.loadtxt("test.dat", dtype = numpy.complex128)

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