Draft
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Currently the
get_array_binary_maskandcombine_sensor_dataof the kWaveArray are pretty slow for a large number of array elements.They would benefit from
This (draft) PR implements a few ideas for the refactoring part.
get_array_binary_mask:
off_grid_pointsall at once, which saves many calls tooff_grid_pointsand avoids or'ing the final maskcombine_sensor_data
added options to input the sensor_mask, so it doesn't have to be calculated a second time
added an option to return the grid_weights sparsely. Currently the weights are collected in an array, then
matlab_findis used to find the non-zero voxels. Insteadoff_grid_pointscan compute the grid_weights in a collections.Counter, so that we don't have to additionally find them in a large array.additional idea: make
off_grid_pointsreturn a function that can quickly return the weights of an element without all the other stuff that happens inoff_grid_points. This could be useful in the element loop ofcombine_sensor_data, where we have to compute the weights of each element individually.Regarding parallelization: I think joblib would probably be a good choice, but I don't have a lot of experience with that.