python - Using numpy.array with large number of dimensions

Question

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?

Answer 1

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.