int vs. np.int about xraylib HOT 6 CLOSED

I cannot seem to reproduce this (or maybe I am not understanding your issue 😄 ) on a RHEL6 Linux box running python 2.7.12 (Anaconda):

>>> import xraylib as xrl
>>> xrl.AtomicNumberToSymbol(26)
'Fe'
>>> import numpy as np
>>> a = np.array([26])
>>> xrl.AtomicNumberToSymbol(a[0])
'Fe'
>>> a = np.array([26], dtype=np.int)
>>> xrl.AtomicNumberToSymbol(a[0])
'Fe'

What versions of xraylib and python are you using, and on which platform are you running it?

from xraylib.

Hmm, what you're running does not work for me. I'm running Python 3.5.2 on a Ubuntu 16.04 LTS system, using xraylib from the conda repo (https://anaconda.org/tacaswell/xraylib). It works fine for:

import xraylib as xrl
xrl.AtomicNumberToSymbol(1)

'H'

However not for:

import xraylib as xrl
a = np.array([1])
xrl.AtomicNumberToSymbol(a)

File "<ipython-input-12-10c1439dda30>", line 1, in <module>
   xrl.AtomicNumberToSymbol(a)
TypeError: in method 'AtomicNumberToSymbol', argument 1 of type 'int'

For that I have to define it as:

import xraylib as xrl
a = np.asscalar(np.array([1]))
xrl.AtomicNumberToSymbol(a)

'H'

Could it be a python2 vs python3 thing? Posted it as an xraylib-issue since I thought it was due to some native-int definition, but it could be my system doing strange stuff...

from xraylib.

It's indeed a python3 feature which appears to be related to all integers being 64-bit in python3.

I am looking into it.

from xraylib.

Think I fixed it in #39. From what I understand numpy scalars were actually never supposed to work with the SWIG generated bindings according to the numpy docs.

My latest changes appears to work fine with both built-in Python types as well numpy scalars. Feel free to give it a try,

from xraylib.

Very nice! Thanks for the effort!

from xraylib.

You're welcome, thanks for reporting this issue

from xraylib.