Can i set float128 as the standard float-array in numpy

Question

So I have a problem with my numerical program, and I'm curious about whether it is a precision problem (i.e. round-off error). Is there a quick way to change all the float arrays in my program into float128 arrays, without going through my code and typing dtype='float128' all over the place. My arrays are all float64, but i never explicitly wrote dtype='float64', so i was hoping there was a way to change this default behavior.

Answer 1

I don't think there is a central "configuration" you could change to achieve this. Some options what you could do:

1. If you are creating arrays only by very few of NumPy's factory functions, substitute these functions by your own versions. If you import these functions like

   from numpy import empty
   

   you can just do

   from numpy import float128, empty as _empty
   def empty(*args, **kwargs):
       kwargs.update(dtype=float128)
       _empty(*args, **kwargs)
   

   If you are doing

   import numpy
   

   you can write a module mynumpy.py

   from numpy import *
   _empty = empty
   def empty(*args, **kwargs):
       kwargs.update(dtype=float128)
       _empty(*args, **kwargs)
   

   and import it like

   import mynumpy as numpy
   

2. Refactor your code to always use dtype=myfloat. This will make such changes easy in the future. You can combine this approach with the use of numpy.empty_like(), numpy.zeros_like() and numpy.ones_like() wherever appropriate to have the actual data type hardcoded in as few places as possible.

3. Sub-class numpy.ndarray and only use your custom constructors to create new arrays.