Dominik - 1 month ago 4x

Python Question

I need to sum up elements in a 1D

`numpy`

`data`

`labels`

`numba`

`int()`

`ret[int(find(labels, g))] += y`

`TypeError: unsupported array index type ?int64`

Is there a better workaround that explicit casting?

`import numpy as np`

from numba import jit

labels = np.array([45, 85, 99, 89, 45, 86, 348, 764])

n = int(1e3)

data = np.random.random(n)

groups = np.random.choice(a=labels, size=n, replace=True)

@jit(nopython=True)

def find(seq, value):

for ct, x in enumerate(seq):

if x == value:

return ct

@jit(nopython=True)

def subsumNumba(data, groups, labels):

ret = np.zeros(len(labels))

for y, g in zip(data, groups):

# not working without casting with int()

ret[int(find(labels, g))] += y

return ret

Answer

The problem is that `find`

can either return an `int`

or `None`

if it doesn't find anything, thus I think the `?int64`

error. To avoid casting, you need to provide an `int`

return value when `find`

exits without finding the desired value and then handle it in the caller.

Source (Stackoverflow)

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