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Add scipy (and maybe h5py) to requirements #140
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Hmm, I think the first three hdf5 and scipy, being binary libraries, can be quite difficult to install on some legacy systems. Some users may be happy with non-storage functionality. |
By the way, the conda package does have scipy as a run requirement, since conda can ensure a scipy install (pip not necessarily). https://github.com/conda-forge/ultranest-feedstock/blob/main/recipe/meta.yaml |
Fair enough, I understand not wanting scipy and hdf5 as default requirements for those reasons. |
The default is to not store, you have to opt in to storing by setting log_dir. |
Yes, my point was just that once you do switch on logging by setting that option, a "standard" user will likely immediately get an error, since the code uses HDF5 by default but this is not installed with ultranest. |
Without scipy installed, if you
pip install ultranest
and then try and import it, it fails sinceultranest/hotstart.py
is imported (via the__init__.py
and thenultranest/integrator.py
) and thehotstart.py
file tries to import scipy:UltraNest/ultranest/hotstart.py
Line 14 in bceff1a
So scipy should be added to
setup.py
as a requirement.In addition, if you enable logging via the
log_dir
argument, the default is to use HDF5 as the output formatUltraNest/ultranest/integrator.py
Line 1045 in bceff1a
so you can quickly get another failure if you don't have h5py installed.
I would say it therefore makes sense to either also add
h5py
as a requirement, or switch the default to csv/tsv.Happy to make a PR if you agree
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