I want to use numpy.savetxt()
to save an array of complex numbers to a text file. Problems:
fmt='%s'
, then numpy.loadtxt()
can't load it unless you specify dtype=complex, converters={0: lambda s: complex(s)}
. Even then, if there are NaN's in the array, loading still fails.It looks like someone has inquired about this multiple times on the Numpy mailing list and even filed a bug, but has not gotten a response. Before I put something together myself, is there a canonical way to do this?
It's easier and saves a few temporary arrays to just reinterpret the array as a real array.
Saving:
numpy.savetxt('outfile.txt', array.view(float))
Loading:
array = numpy.loadtxt('outfile.txt').view(complex)
If you prefer to have real and imaginary part on the same line in the file, you can use
numpy.savetxt('outfile.txt', array.view(float).reshape(-1, 2))
or
array = numpy.loadtxt('outfile.txt').view(complex).reshape(-1)
respectively.
(Note that neither view()
nor reshape()
copies the array -- it will just reinterpret the same data in a different way.)
Addendum from the question asker:
If you want to save more than one complex array in the same file, you can do it like so:
numpy.savetxt('outfile.txt', numpy.column_stack([
array1.view(float).reshape(-1, 2),
array2.view(float).reshape(-1, 2),
]))
array1, array2 = numpy.loadtxt('outfile.txt', unpack=True).view(complex)
The reshaping is necessary because numpy.view()
doesn't operate on strided arrays.