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Refactor Split Data Module #19

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roshankern
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This PR is ready for review!

In this PR, the split data module is changed to load in labeled_data instead of training_data for clarity. See #18 for more information.

The index of labeled data is also changed from index to labeled_data_index to clarify what the index is for.

@roshankern roshankern requested a review from gwaybio March 9, 2023 23:45
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LGTM! a couple comments that you probably want to address prior to merging

@roshankern roshankern merged commit d6bb437 into WayScience:cp-feature-refactor Mar 10, 2023
@roshankern roshankern deleted the refactor-split-module branch March 10, 2023 02:23
roshankern added a commit that referenced this pull request Jul 6, 2023
* Refactor Download Module (#18)

* refactor module

* remove training data file

* Update 0.download_data/scripts/nbconverted/download_data.py

Co-authored-by: Erik Serrano <[email protected]>

* eric suggestions

---------

Co-authored-by: Erik Serrano <[email protected]>

* Refactor Split Data Module (#19)

* refactor module

* greg suggestions

* Train module refactor (#20)

* refactor format module

* use straify function

* rerun train module

* black formatting

* docs, nbconvert

* nbconvert

* rerun pipeline, rename model

* fix typo

* Update 2.train_model/README.md

Co-authored-by: Gregory Way <[email protected]>

* Update 2.train_model/README.md

Co-authored-by: Gregory Way <[email protected]>

* Update 2.train_model/README.md

Co-authored-by: Gregory Way <[email protected]>

* notebook run

---------

Co-authored-by: Gregory Way <[email protected]>

* Refactor evaluate module (#21)

* refactor clas pr curves

* refactor confusion matrix

* refactor F1 scores

* refactor model predictions

* documentation

* dave suggestions

* erik suggestions, reconvert

* Refactor interpret module (#22)

* refactor interpret notebook

* docs, reconvert script

* greg suggestions

* Get Leave One Image Out Probabilities (#23)

* add LOIO notebook

* LOIO notebook

* update notebook

* download and split data with cell UUIDs

* move LOIO

* finish LOIO

* black formatting

* rerun notebook

* rerun notebook, dave suggestions

* greg comment

* Train single class models (#25)

* move multiclass models

* rename files, fix sh

* single class models notebook

* run notebook

* binarize labels

* train single class models

* reconvert notebooks

* update readme

* rename sh file

* remove models

* eric readme suggestions

* rerun notebook, eric suggestions

* Add Single Class Model PR Curves (#26)

* get SCM PR curves

* shuffled baseline

* retrain single class models with correct kernel

* rerun pr curves notebook

* remove nones

* rerun multiclass model

* rerun notebook

* move file

* docs, black formatting

* format notebook

* Update 3.evaluate_model/README.md

Co-authored-by: Dave Bunten <[email protected]>

* dave suggestions

* reconvert notebook

---------

Co-authored-by: Dave Bunten <[email protected]>

* Add SCM confusion matrices and F1 scores (#27)

* get SCM PR curves

* shuffled baseline

* retrain single class models with correct kernel

* rerun pr curves notebook

* remove nones

* rerun multiclass model

* rerun notebook

* move file

* create SCM confusion matrix

* rerun notebook

* add changes from last PR

* rerun notebook

* add SCM F1, update SCM confusion matrices

* documentation

* rerun notebook

* Update utils/evaluate_utils.py

Co-authored-by: Dave Bunten <[email protected]>

* Update utils/evaluate_utils.py

Co-authored-by: Dave Bunten <[email protected]>

* Update 3.evaluate_model/scripts/nbconverted/F1_scores.py

Co-authored-by: Dave Bunten <[email protected]>

* dave suggestions

---------

Co-authored-by: Dave Bunten <[email protected]>

* Get SCM Predictions and LOIO Probabilities (#29)

* get SCM LOIO probas

* reconvert notebook

* get model predictions

* rerun LOIO

* reconvert notebook

* save and reconvert notebook

* eric suggestions

* Add SCM Interpretations (#30)

* add scm coefficients

* rerun interpret multi-class model

* compare model coefficients

* nbconvert

* readme

* make all correlations negative

* rerun training

* rerun evaluate

* rerun interpret

* docs

* newline

* rerun LOIO

* Remove unused cp features (#31)

* rerun download/split modules

* rerun multicalss models

* rerun single class model

* rerun evaluate module

* get LOIO probas

* rerun interpret module

* rerun download data

* Adding CP features to ggplot visualization (#24)

* set colors for model types

* visualize precision recall with CP and DP+CP

* add F1 score barchart visualization

* minor tweak of f1 score print

* ignore mac files

* merge main and rerun viz

* change color scheme for increased contrast

* add f1 score of the top model, and rerun with updated colors

* nrow = 3 in facet

* change name of weighted f1 score

* update single cell images module (#32)

* Refactor validate module (#33)

* update validate module

* refactor validation

* get correlations

* convert notebook

* update readme

* formatting, documentation

* reset index

* vadd view notebook

* docs, black formatting

* ccc credit

* show all correlations

* add notebook

* remove preview notebook

* convert notebook

* add differences heatmaps

* preview correlation differences

* add docs

* black formatting

---------

Co-authored-by: Erik Serrano <[email protected]>
Co-authored-by: Gregory Way <[email protected]>
Co-authored-by: Dave Bunten <[email protected]>
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2 participants