UMAP line plot to assess temporal smoothness in features space #176
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@ziw-liu , I was able to use the scripts to generate the figures. I just needed to pip install 'cmap' into my environment. |
It's part of the |
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Thanks @ziw-liu ! |
ziw-liu
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Oct 17, 2024
* Merging code related to figures (#146) * notes on standard report * Add code for generating figures --------- Co-authored-by: Alishba Imran <[email protected]> * produce a report of useful visualizations to assess the dimensionality and features learned by embeddings (#140) * notes on standard report * add lib of computed features * correlates PCA with computed features * compute for all timepoints * compute correlation * remove cv library usage * remove edge detection * convert to dataframe * for entire well * add std_dev feature * fix patch size --------- Co-authored-by: Soorya Pradeep <[email protected]> * Remove obsolete scripts for contrastive phenotyping (#150) * remove obsolete training and prediction scripts * lint contrastive scripts * SSL: fix MLP head and remove L2 normalization (#145) * draft projection head per Update the projection head (normalization and size). #139 * reorganize comments in example fit config * configurable stem stride and projection dimensions * update type hint and docstring for ContrastiveEncoder * clarify embedding_dim * use the forward method directly for projected * normalize projections only when fitting the projected features saved during prediction is now *not* normalized * remove unused logger * refactor training code into translation and representation modules * extract image logging functions * use AdamW instead of Adam for contrastive learning * inline single-use argument * fix normalization * fix MLP layer order * fix output dimensions * remove L2 normalization before computing loss * compute rank of features and projections * documentation --------- Co-authored-by: Shalin Mehta <[email protected]> * created and updated classify_feb_embeddings.py * Module and scripts for evaluating representations (#156) * docstring * move scripts from contrastive_scripts to viscy/scripts * organize files in applications/contrastive_phenotyping * delete unused evaluation code * more cleanup * refactor evaluation metrics for translation task * refactor viscy.evaluation -> viscy.translation.evaluation_metrics and viscy.representation.evaluation * WIP: representation evaluation module * WIP: representation eval - docstrings in numpy format * WIP: more documentation * refactor: feature_extractor moved to viscy.representation.evaluation * lint * bug fix * refactored common computations and dataset * add imbalance-learn dependecy to metrics * refactor classification of embeddings * organize viscy.representation.evaluation * ruff * Soorya's plotting script * WIP: combine two versions of plot_embeddings.py * simplify representation.viscy.evaluation - move LCA to its own module * refactor of viscy.representation.evaluation * refactored and tested PCA and UMAP plots --------- Co-authored-by: Soorya Pradeep <[email protected]> * delete duplicate file * lint * fix import paths * rename translation tests * rename translation metrics * Sample positive and negative samples with a time offset for the triplet contrastive task (#154) * wip: sample positive and negative samples from another time point * configure time interval in triplet data module * vectorized anchor filtering * conditional augmentation for anchor anchor is augmented if the positive is another time point * example training script for the CTC dataset this is optimized to run on MPS * add example CTC prediction config for MPS * add fig for mitosis * add script to save image patches * add save patches as npy * save figure at 300dpi * Linear probing (#160) * refactor linear probing with lightning * test convenience function * always convert to long before onehot * use onehot only during training * supply trainer through argument to avoid wrapping * only log per epoch * example script for linear probing * add comment about loss curve * fix sample filtering order for select tracks * add script to visualize integrated gradients * plot integrated gradients over time * Use sklearn's logistic regression for linear probing (#169) * use binary logistic regression to initialize the linear layer * plot integrated gradients from a binary classifier * add cmap to 'visual' requirements * move model assembling to lca * rename init argument * disable feature scaling * update test and evaluation scripts to use new API * add docstrings to LCA * Tweak attribution visualization (#170) * add maplotlib style sheet for figure making * add cell division attribution * add matplotlib style sheet * move attribution computation to lca * tweak contrast limits and text * add captum to optional dependencies * move attribution function to a method of the classifier * add script to show organelle dynamics * add occlusion attribution * more generic save path * add uninfected cell * tweak subplot spacing * UMAP line plot to assess temporal smoothness in features space (#176) * add maplotlib style sheet for figure making * add cell division attribution * add matplotlib style sheet * move attribution computation to lca * tweak contrast limits and text * add captum to optional dependencies * move attribution function to a method of the classifier * add script to show organelle dynamics * add occlusion attribution * more generic save path * add uninfected cell * tweak subplot spacing * lower case titles * reduce UMAP components to 2 and add indices * add script to make the bridge gaps figure * fixed import error * formatted with black * reduce to single arrow on plot * remove reduntant script * Fixes on correlation of PCA and UMAP components to computed_feature script (#159) * reduce initial patch size * add radial profiling * add function descriptions * add umap correlation * add def comments * change umap for all data * add script for 1 chan * add p-value analysis * add PCA analysis * remove duplicate script * Refactor and format code * Format code * Removed umap correlation * note for future refactor --------- Co-authored-by: Ziwen Liu <[email protected]> * updated eval module & cosine sim figures (#168) * updated files * format fixed for tests * updated scripts * umap dist code * bug fixes and linting * logistic regression script * add infection figure script * Add script for generating infection figure and perform prediction on the June dataset * Format code * Black format evaluation module and fix import in figure_cell_infection script * Refactor scatterplot colors and markers * Calculate model accuracy * Add script for appendix video * formatted code * updated displacement funcs for full embeddings * script for displacement computation * fix style * fix docstring format --------- Co-authored-by: Shalin Mehta <[email protected]> Co-authored-by: Soorya Pradeep <[email protected]> Co-authored-by: Ziwen Liu <[email protected]> * Fixup representation (#180) * fix docstrings and type hint for the ContrastiveEncoder * refactor the representation evaluation module into submodules * move shared image logging into utils * fix line end * fix import paths in example notebooks * Unified CLI entry point (#182) * remove obsolete metrics script for translation * move cellpose annotation script * consolidate CLI documentation * remove old CLI help * move translation CLI to its own module * move contrastive CLI to its own module * remove old CLI module * remove global entry script * share trainer class between tasks * move cli from init to main * inherit base CLI class for tasks * improve type hint and docstring * restore global CLI entry point * special case subclass mode for preprocessing * remove separate entry points * add CLI description message * make the setup function private * fix subclass mode detection * remove unused arguments from custom subcommands * use generic path in example * fix docstring style * update virtual staining example configs * update CTC SSL example configs * update infection SSL example configs * Remove outdated comment * updating the dlmbl notebooks * updating dependendencies to allow viscy>0.2 in examples * updating phase contrast demo notebook. * updating references to main * Store UMAP embeddings in SSL predictions (#184) * extract function for computing umap * specific return type for predict step * write umap in prediction * raise log level for umap computation * fix key conversion * Add representation section to readme (#186) * draft readme * direct link dynaCLR schematic * add DynaCLR schemetic figure * add static schematic and link to video --------- Co-authored-by: Ziwen Liu <[email protected]> Co-authored-by: Ziwen Liu <[email protected]> * fix link syntax in readme --------- Co-authored-by: Shalin Mehta <[email protected]> Co-authored-by: Alishba Imran <[email protected]> Co-authored-by: Soorya Pradeep <[email protected]> Co-authored-by: Alishba Imran <[email protected]> Co-authored-by: Soorya19Pradeep <[email protected]> Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
ziw-liu
added a commit
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Oct 21, 2024
* Merging code related to figures (#146) * notes on standard report * Add code for generating figures --------- Co-authored-by: Alishba Imran <[email protected]> * produce a report of useful visualizations to assess the dimensionality and features learned by embeddings (#140) * notes on standard report * add lib of computed features * correlates PCA with computed features * compute for all timepoints * compute correlation * remove cv library usage * remove edge detection * convert to dataframe * for entire well * add std_dev feature * fix patch size --------- Co-authored-by: Soorya Pradeep <[email protected]> * Remove obsolete scripts for contrastive phenotyping (#150) * remove obsolete training and prediction scripts * lint contrastive scripts * SSL: fix MLP head and remove L2 normalization (#145) * draft projection head per Update the projection head (normalization and size). #139 * reorganize comments in example fit config * configurable stem stride and projection dimensions * update type hint and docstring for ContrastiveEncoder * clarify embedding_dim * use the forward method directly for projected * normalize projections only when fitting the projected features saved during prediction is now *not* normalized * remove unused logger * refactor training code into translation and representation modules * extract image logging functions * use AdamW instead of Adam for contrastive learning * inline single-use argument * fix normalization * fix MLP layer order * fix output dimensions * remove L2 normalization before computing loss * compute rank of features and projections * documentation --------- Co-authored-by: Shalin Mehta <[email protected]> * created and updated classify_feb_embeddings.py * Module and scripts for evaluating representations (#156) * docstring * move scripts from contrastive_scripts to viscy/scripts * organize files in applications/contrastive_phenotyping * delete unused evaluation code * more cleanup * refactor evaluation metrics for translation task * refactor viscy.evaluation -> viscy.translation.evaluation_metrics and viscy.representation.evaluation * WIP: representation evaluation module * WIP: representation eval - docstrings in numpy format * WIP: more documentation * refactor: feature_extractor moved to viscy.representation.evaluation * lint * bug fix * refactored common computations and dataset * add imbalance-learn dependecy to metrics * refactor classification of embeddings * organize viscy.representation.evaluation * ruff * Soorya's plotting script * WIP: combine two versions of plot_embeddings.py * simplify representation.viscy.evaluation - move LCA to its own module * refactor of viscy.representation.evaluation * refactored and tested PCA and UMAP plots --------- Co-authored-by: Soorya Pradeep <[email protected]> * delete duplicate file * lint * fix import paths * rename translation tests * rename translation metrics * Sample positive and negative samples with a time offset for the triplet contrastive task (#154) * wip: sample positive and negative samples from another time point * configure time interval in triplet data module * vectorized anchor filtering * conditional augmentation for anchor anchor is augmented if the positive is another time point * example training script for the CTC dataset this is optimized to run on MPS * add example CTC prediction config for MPS * add fig for mitosis * add script to save image patches * add save patches as npy * save figure at 300dpi * Linear probing (#160) * refactor linear probing with lightning * test convenience function * always convert to long before onehot * use onehot only during training * supply trainer through argument to avoid wrapping * only log per epoch * example script for linear probing * add comment about loss curve * fix sample filtering order for select tracks * add script to visualize integrated gradients * plot integrated gradients over time * Use sklearn's logistic regression for linear probing (#169) * use binary logistic regression to initialize the linear layer * plot integrated gradients from a binary classifier * add cmap to 'visual' requirements * move model assembling to lca * rename init argument * disable feature scaling * update test and evaluation scripts to use new API * add docstrings to LCA * Tweak attribution visualization (#170) * add maplotlib style sheet for figure making * add cell division attribution * add matplotlib style sheet * move attribution computation to lca * tweak contrast limits and text * add captum to optional dependencies * move attribution function to a method of the classifier * add script to show organelle dynamics * add occlusion attribution * more generic save path * add uninfected cell * tweak subplot spacing * UMAP line plot to assess temporal smoothness in features space (#176) * add maplotlib style sheet for figure making * add cell division attribution * add matplotlib style sheet * move attribution computation to lca * tweak contrast limits and text * add captum to optional dependencies * move attribution function to a method of the classifier * add script to show organelle dynamics * add occlusion attribution * more generic save path * add uninfected cell * tweak subplot spacing * lower case titles * reduce UMAP components to 2 and add indices * add script to make the bridge gaps figure * fixed import error * formatted with black * reduce to single arrow on plot * remove reduntant script * Fixes on correlation of PCA and UMAP components to computed_feature script (#159) * reduce initial patch size * add radial profiling * add function descriptions * add umap correlation * add def comments * change umap for all data * add script for 1 chan * add p-value analysis * add PCA analysis * remove duplicate script * Refactor and format code * Format code * Removed umap correlation * note for future refactor --------- Co-authored-by: Ziwen Liu <[email protected]> * updated eval module & cosine sim figures (#168) * updated files * format fixed for tests * updated scripts * umap dist code * bug fixes and linting * logistic regression script * add infection figure script * Add script for generating infection figure and perform prediction on the June dataset * Format code * Black format evaluation module and fix import in figure_cell_infection script * Refactor scatterplot colors and markers * Calculate model accuracy * Add script for appendix video * formatted code * updated displacement funcs for full embeddings * script for displacement computation * fix style * fix docstring format --------- Co-authored-by: Shalin Mehta <[email protected]> Co-authored-by: Soorya Pradeep <[email protected]> Co-authored-by: Ziwen Liu <[email protected]> * Fixup representation (#180) * fix docstrings and type hint for the ContrastiveEncoder * refactor the representation evaluation module into submodules * move shared image logging into utils * fix line end * fix import paths in example notebooks * Unified CLI entry point (#182) * remove obsolete metrics script for translation * move cellpose annotation script * consolidate CLI documentation * remove old CLI help * move translation CLI to its own module * move contrastive CLI to its own module * remove old CLI module * remove global entry script * share trainer class between tasks * move cli from init to main * inherit base CLI class for tasks * improve type hint and docstring * restore global CLI entry point * special case subclass mode for preprocessing * remove separate entry points * add CLI description message * make the setup function private * fix subclass mode detection * remove unused arguments from custom subcommands * use generic path in example * fix docstring style * update virtual staining example configs * update CTC SSL example configs * update infection SSL example configs * Remove outdated comment * updating the dlmbl notebooks * updating dependendencies to allow viscy>0.2 in examples * updating phase contrast demo notebook. * updating references to main * Store UMAP embeddings in SSL predictions (#184) * extract function for computing umap * specific return type for predict step * write umap in prediction * raise log level for umap computation * fix key conversion * Add representation section to readme (#186) * draft readme * direct link dynaCLR schematic * add DynaCLR schemetic figure * add static schematic and link to video --------- Co-authored-by: Ziwen Liu <[email protected]> Co-authored-by: Ziwen Liu <[email protected]> * fix link syntax in readme --------- Co-authored-by: Shalin Mehta <[email protected]> Co-authored-by: Alishba Imran <[email protected]> Co-authored-by: Soorya Pradeep <[email protected]> Co-authored-by: Alishba Imran <[email protected]> Co-authored-by: Soorya19Pradeep <[email protected]> Co-authored-by: Eduardo Hirata-Miyasaki <[email protected]>
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Also reduce the UMAP components in
viscy.representation.evaluation.compute_umap()to 2.