Modularize bmb.plots sub-package
#674
Closed
Conversation
This file contains 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
deleted docs/notebooks/plot_cap.ipynb#
|
Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
|
This already looks quite impressive. Let me know if you want me to help with anything. |
|
Closing this draft PR since #684 refactored the |
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Outdated suggestions cannot be applied.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.
This PR modularizes the
bmb.plotssub-package into four modules. The idea is to encapsulate the functions and creation / change of data into a single module based on that modules objective.create_data.py: creates either adjusted predictions or comparisons dataplot_types.py: containsplot_numericalandplot_categoricalto perform plotting based on the data type of the main covariateplotting.py: contains functions to plot either adjusted predictions or comparisonsutils.py: contains commonly used functions for computing adjusted predictions or comparisons data.create_data.pyuses a lot of functions from this module.To Do:
plot_comparisonsis readyplot_capdefault args. not working for categorical regression #673def comparisons()accessible to the user?def predictions()function and make it accessible to user?black.pylint.