Issue
If you try to make an array with large number of dimensions in numpy, it throws an exception:
In [1]: import numpy as np
In [2]: a = np.zeros((1,) * 33)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-2-32dc30f6e439> in <module>()
----> 1 a = np.zeros((1,) * 33)
ValueError: sequence too large; must be smaller than 32
Are there any simple workarounds to this?
What are the reasons why numpy doesn't allow creating such arrays?
Solution
From the NumPy source code:
/*
* There are several places in the code where an array of dimensions
* is allocated statically. This is the size of that static
* allocation.
*
* The array creation itself could have arbitrary dimensions but all
* the places where static allocation is used would need to be changed
* to dynamic (including inside of several structures)
*/
#define NPY_MAXDIMS 32
#define NPY_MAXARGS 32
You could change those defines and build from source a non-compatible version that fits your needs.
Answered By - Jaime
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