Add support for writing nested dictionaries to HDF5

[drewoldag]

Initial attempt to add support for nested dictionaries with numpy array values.

Problem & Solution Description (including issue #)

The goal is to be able to write out to an hdf5 file a structure that mirrors a nested dictionary where the leaf values are all numpy arrays. The current approach introduces a bit of recursion into the writeDictToHdf5 file. Still need to write a good handful of tests.

The specific use case here should support the following:

def write_dict(filename, ensemble_dict, **kwargs):
        # ensemble_dict has the form { <str> : <qp.Ensemble> }
        # output_tables has the form { <str> : <tabularized qp.Ensemble> }
        # where a tabularized qp.Ensemble is a dictionary of dicts with leaf values that are numpy arrays.

        output_tables = {}
        for key, val in ensemble_dict.items():
            # check that val is a qp.Ensemble
            if not isinstance(val, Ensemble):
                raise ValueError("All values in ensemble_dict must be qp.Ensemble")

            output_tables[key] = val.build_tables()
        io.writeDictsToHdf5(output_tables, filename, **kwargs)

Code Quality

• My code follows the code style of this project
• I have written unit tests or justified all instances of #pragma: no cover; in the case of a bugfix, a new test that breaks as a result of the bug has been added
• My code contains relevant comments and necessary documentation for future maintainers; the change is reflected in applicable demos/tutorials (with output cleared!) and added/updated docstrings use the NumPy docstring format
• Any breaking changes, described above, are accompanied by backwards compatibility and deprecation warnings

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 100.00%. Comparing base (4dadddb) to head (8475829).

Additional details and impacted files

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  Files            8         8           
  Lines          674       683    +9     
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+ Hits           674       683    +9     

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[eacharles]

Looks good, thanks