Reputation: 3575
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.
Upvotes: 21
Views: 18853
Reputation: 601421
I don't think there is a central "configuration" you could change to achieve this. Some options what you could do:
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
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.
Sub-class numpy.ndarray
and only use your custom constructors to create new arrays.
Upvotes: 21