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Right now our tests for compute_MVBS are pretty messy and we can benefit from reworking this for robustness and readability.
A laundry list of the few things I noticed while working on #753 were:
operations in _construct_MVBS_toy_data and _construct_MVBS_test_data either are hard to decipher or seem can be simplified. It may be the best to rewrite these.
factor out common components between test_compute_MVBS_index_binning and test_compute_MVBS to reduce redundancy and avoid error
the above work with constructed data
test_preprocess_mvbs runs through the mechanism for real data, we should keep this but consider adding variations of the target echo_range and ping_time binning intervals
add test for Sv data with different length along the range_sample dimension for different channel
use np.equal instead of np.allclose when testing computed values
use pytest parameterization to reduce clutter and redundancy
separate out MVBS-related tests to a separate .py file
The text was updated successfully, but these errors were encountered:
Right now our tests for
compute_MVBS
are pretty messy and we can benefit from reworking this for robustness and readability.A laundry list of the few things I noticed while working on #753 were:
_construct_MVBS_toy_data
and_construct_MVBS_test_data
either are hard to decipher or seem can be simplified. It may be the best to rewrite these.test_compute_MVBS_index_binning
andtest_compute_MVBS
to reduce redundancy and avoid errortest_preprocess_mvbs
runs through the mechanism for real data, we should keep this but consider adding variations of the target echo_range and ping_time binning intervalsrange_sample
dimension for different channelnp.equal
instead ofnp.allclose
when testing computed valuespytest
parameterization to reduce clutter and redundancyThe text was updated successfully, but these errors were encountered: