Long doubles make histogram2d fail subtly, maybe add type check?

[matteobachetti]

I'm experimenting with various optimizations in the pulsar search code in HENDRICS (StingraySoftware/HENDRICS#65). One of my bottlenecks was a 2d histogram operation, and I gave a shot to yours. Tested with simulated data, everything worked and histogram2d was not a bottleneck anymore. Yay!
However...
When I used it on real data, Jupyter notebook was giving "dead kernel" messages with no information whatsoever. After spending one day banging my head, I tried to cast the longdouble arrays to double, and everything worked again.

It would help to add a type check, raising a ValueError or something similar if the number type is unsupported.

[astrofrog]

The code should normally cast to double automatically here:

https://github.com/astrofrog/fast-histogram/blob/master/fast_histogram/_histogram_core.c#L111

but it might be this doesn't work for long double somehow. If anyone wants to help investigate, please feel free to! (otherwise will try and look soon)

[tcassanelli]

has there been any update in this? I am trying with np.float128 and it returns this error:

    res = asanyarray(func1d(inarr_view[ind0], *args, **kwargs))
  File "/Users/tomascassanelli/anaconda3/lib/python3.8/site-packages/fast_histogram/histogram.py", line 58, in histogram1d
    return _histogram1d(x, nx, xmin, xmax)
RuntimeError: Couldn't set up iterator

[astrofrog]

I haven't had a chance to investigate