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I'm working in Python with NumPy arrays of complex numbers that extend well past the normal floating point limits of NumPy’s default Complex type (numbers greater than 10^500). I wanted to know if there was some way I could extend NumPy so that it will be able to handle complex numbers with this sort of magnitude. For example, is there a way to make a NumPy complex type that uses functionality from the Decimal module?

I know there are resources available such as mpmath that could probably do what I need. However, it is a requirement of my project that I use NumPy.

For anyone that's interested in why I need these enormous numbers, it's because I'm working on a numerical relativity simulation of the early universe.

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  • Did you try to create a numpy array of mpmath objects? Commented Feb 13, 2014 at 9:32
  • There's some info about user-defined data types in NumPy docs Commented Feb 13, 2014 at 9:33
  • I hadn't thought about making an array of mpmath objects, I'l give it a try. Also that user-defined types article looks promising. Thank you both, I'll get back to you with the results. Commented Feb 13, 2014 at 10:12

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Depending on your platform, you may have support for complex192 and/or complex256. These are generally not available on Intel platforms under Windows, but they are on some others—if your code is running on Solaris or on a supercomputer cluster, it may support one of these types. On Linux, you may even find them available or you could create your array using dtype=object and then use bigfloat or gmpy2.mpc.

  1. complex256 numbers up to 104932 + 104932j
  2. complex192 ditto, but with less precision
  3. I have even seen mention of NumPy and complex512...
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Hmmm, my work is currently being split across both a windows machine and a Linux box...either I'll have to make both machines Linux, or find another solution. Thank you though, it gives me a nice avenue of investigation to look into.

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