Numpy 2.0.0 doesn't allow out of range integers when casting to np.uint64

[ehiggins0]

As of June 16, numpy 2.0.0 was released with breaking changes regarding the handling of out of bounds values when casting. This breaks the below line since python's native hash function can output out of bound values:

xarray-spatial/xrspatial/gpu_rtx/mesh_utils.py

Line 7 in 555706c

datahash = np.uint64(hash(str(raster.data.get())))

2024-06-18T22:51:25.961Z	File "/usr/local/lib/python3.10/dist-packages/xrspatial/viewshed.py", line 1663, in viewshed
2024-06-18T22:51:25.961Z	return viewshed_gpu(raster, x, y, observer_elev, target_elev)
2024-06-18T22:51:25.961Z	File "/usr/local/lib/python3.10/dist-packages/xrspatial/gpu_rtx/viewshed.py", line 280, in viewshed_gpu
2024-06-18T22:51:25.961Z	scale = create_triangulation(raster, optix)
2024-06-18T22:51:25.961Z	File "/usr/local/lib/python3.10/dist-packages/xrspatial/gpu_rtx/mesh_utils.py", line 7, in create_triangulation
2024-06-18T22:51:25.961Z	datahash = np.uint64(hash(str(raster.data.get())))
2024-06-18T22:51:25.961Z	OverflowError: Python integer -2413162623232959393 out of bounds for uint64

The easy workaround for now is to pin the local numpy version to 1.26.4, but it might be a good idea to a) add this to readme/dependencies for now, and/or b) move to a better hash function that does not result in negative numbers.

[brendancol]

@ehiggins0 hey thanks so much for the info and we'll look to upgrade the datahash above