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CHANGELOG.md

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4.4.4

  • Add jamie corr method warning

4.4.3

  • Add GPU implementation warning

4.4.2

  • Complete reruns of all results (NOTE: Results likely differ when running with and without pre-trained models)
  • Correct unintuitive sequential evaluation behavior in evaluate_impact which caused erroneous chromatin region classification and negatively affected gene prioritization results
  • np.int deprecation update for MMD-MA.ipynb
  • Fix sklearn issue with np.matrix in scGLUE notebook
  • run.sh revised for more complex development solutions
  • SHAP version updated to fix deprecated np.bool reference
  • Small notebook revisions, as well as changes from package updates

4.4.1

  • Actually upgrade torch and torchvision
  • Adjust README.md
  • Fix pip-tools generation of requirements*.txt files

4.4.0

  • Fix certain compatibility issues, specifically for requirements.dev
  • Fix sklearn dependency
  • GPU compatibility
  • np.int deprecation updates
  • README.md no clone install support
  • Slightly changed edModelVar.impute behavior to expect preprocessed input
  • Suppress many unimpactful warnings
  • Upgrade PyTorch version

4.3.3

  • Small sequential argument fix
  • SVG visualizations

4.3.2

  • Added return_statistic to plot_auroc... function family
  • Additional statistic reporting surrounding dropout
  • Revised visualizations for loss clarity

4.3.1

  • Additional runs for imputation
  • Clarifications
  • More options
  • Small terminology fixes

4.3.0

  • Add memory logging
  • Added hybrid method to plot_integrated
  • Added plot_sample for showing individual cell correlations
  • Added sort_type option to sort_by_interest utility function
  • Fixed ordering for plot_distribution_alone
  • More runs, more data
  • New visualization for ATAC -> RNA imputation gene importance
  • Visualization fixes

4.2.3

  • Figure changes
  • Simulation data update

4.2.2

  • Added loss logging
  • Additional runs
  • Alternative phenotypes
  • Tuning
  • Bugfixes
  • More runs with partial correspondence
  • Reorganization of notebooks
  • Reruns
  • Revised hashing function

4.2.1

  • Reproducibility for UMAP

4.2.0

  • Added GNU GPL V3.0 License
  • Better sampling during training
  • Delete generate_plot class
  • File structure revisions
  • Raw ephys testing
  • README updates
  • Reproducibility for SHAP

4.1.8

  • Import hierarchy fix
  • umap-learn import fix
  • WR2MD import versioning

4.1.7

  • README.md updates
  • Reruns

4.1.6

  • Reruns
  • Small README.md changes

4.1.5

  • Change name from ComManDo to JAMIE
  • Include data in repo
  • README.md update

4.1.4

  • Reruns
  • Run leave-one-out on COLO320DM
  • Visualization changes and reporting

4.1.3

  • Reruns
  • Small change to evaluate_impact background preview

4.1.2

  • Reruns
  • Visualization updates
  • Weight standardization updates to reduce dimension dependence

4.1.1

  • Added feature_dict argument to plot_distribution_alone for custom xticks
  • Additional outlier protection for plot_distribution_alone visualizations
  • Small fix with label formatting

4.1.0

  • Add gradient clipping
  • Added plot_impact to evaluation module
  • Change early stop behavior and add min_epochs, mainly for KL annealing
  • Fix scaling on F and P subsets during training
  • Increase model robustness
  • Lots of small fixes, errors mainly appeared with large datasets
  • Model saving for all algorithms and outputs
  • Reruns
  • Visualization additions and changes

4.0.0

  • Add adjustText for cleaner text notations
  • Add batch_step option for typical AE iteration
  • Add more SHAP visualizations
  • Add outlier detection utility
  • Add scDART
  • Added auto-amending kwarg pca_dim
  • Added BABEL datasets
  • Adjusted evaluation figure text size
  • Applied outlier detection to plot_integrated
  • Change visualizations, especially for distributions
  • Changed losses to VAE by default, cosine, F
  • Changed sampling logic on distribution similarity calculation
  • Fix bug for non-aligned datasets in commando module
  • Fix SVD solver option in automated PCA
  • Implement full VAE
  • Implemented saving and loading models
  • New interesting feature finding algorithm
  • Stylistic changes in evaluation
  • Various visualizations in evaluation module

3.8.2

  • Fixed a bug concerning min-max normalization in the compute_distances function
  • Implement SHAP and add visualizations
  • Reruns

3.8.1

  • Distribution similarity measure
  • Evaluation style changes
  • Reruns

3.8.0

  • Add MMD-MA
  • Add VAE functionality
  • Add feature distribution previews
  • Add inversion to model preprocessing
  • Add trainable weighting to model aggregation function
  • Additional error handling
  • Additional visualization clarity
  • Include BrainChromatin dataset
  • Reruns
  • Separate plots from generate_figure module
  • Update evaluation module with imputed AUROC distribution
  • Visualization reformatting

3.7.7

  • Add configurable legend to generate_figure
  • Added correlation and p-value to calibration plots
  • Added feature_names argument to generate_figure
  • Many Formatting changes for generate_figure
  • Rename and format calibration plot
  • Reruns

3.7.6

  • Bugfix with None pca argument
  • Reruns, small notebook formatting changes

3.7.5

  • Added changeable k for test_LabelTA and integrated into generate_figure
  • Automatically chooses appropriate k
  • Added optional integrated_alg_shortnames to generate_figure
  • Fixed a bug where PCA was used on singular None modalities
  • Fixed (subverted) a python bug which culls vars exclusively in lambda functions
  • Previously prevented proper usage of multiple pca_dim
  • generate_figure formatting changes
  • Reruns, including PCA fix for scMNC-Visual

3.7.4

  • generate_figure add multi-column colors
  • generate_figure formatting, title, layout changes
  • Reruns
  • Small code formatting change

3.7.3

  • Add more comparison methods to notebooks
  • Change generate_figure default layout
  • Change optimizer for main JAMIE model
  • Change plotting style for generate_figure stats
  • Reruns

3.7.2

  • Add custom colors to generate_figure
  • Add metric heatmap to generate_figure
  • Fixes to dimensions and generalization in generate_figure
  • Formatting changes to default generate_figure
  • Reruns on all general_analysis notebooks

3.7.1

  • Rerun scGEM data

3.7.0

  • Add experimental corr_method
  • Added dist_method choice for sim_dist_func which takes cosine, euclidean
  • Generalize F representation to allow for negatives
  • Fixes problem with negative sim, diff, F, or P
  • Reruns
  • Use euclidean distance for sim_dist_func

3.6.1

  • Added plug-in pre-calculated F matrix through match_result
  • Allow for per-dataset pca_dim
  • Fixed preprocessing variable default in model
  • Test patch-seq dataset

3.6.0

  • Add pca before use on full model
  • Run on MMD-MA simulation data

3.5.4

  • Add Davies-Bouldin Index
  • Experimental losses
  • Run on motor data
  • Use PF_Ratio in runs

3.5.3

  • Fix scMNC data loading
  • generate_figure
    • Add _get_..._shape() functions
    • Add _group_plot() function for automated group partitioning
    • Add auto-selection of latent features for reconstruction visualization
    • Extend shape implementation
    • General reorganization
    • Streamlined main function
    • height_ratio fixes
  • Remove mapping timer printing

3.5.2

  • Added group partitioning functionality to generate_figure
  • Refactored generate_figure to a class object

3.5.1

  • Added custom model functionality with model_class argument
  • Added simple model weight visualization to generate_figure
  • Reruns on various levels of alignment
  • Revised generate_figure formatting and standardized module format

3.5.0

  • Added integrated_use_pca option for generate_figure
  • Experimented with new losses
  • New scaling on each loss variable
  • Notebook preprocessing changes
  • Reran notebooks
  • Revised sim-dist measure to only include positives
  • Revised model structure
  • Stepping with epochs now rather than batches

3.4.0.0

  • Mute output on various functions
  • Add tuning function utilities.tune_cm()
  • Add early stopping
  • Add experimental loss parameters
  • Add alternative similarity measures
  • Add correlation visualization in generate_figure
  • Revise loss_weights parameter
  • Revise loss bookkeeping
  • Fix F normalization
  • Fix model normalization issue
  • Remove KNN usage in main model
  • Reruns with higher construction losses

3.4.0

  • generate_figure
  • Added 3D plotting capability
  • Various formatting changes and style options
  • Silhouette coefficient visualizations
  • More modality prediction comparisons
  • Add MMD-MA comparison
  • Add scMNC data
  • Reruns

3.3.0

  • Added generate_figure to more concisely show results
  • Small changes in several algorithms to mute output
  • Renamed joint_embedding folder to general_analysis
  • Re-ran notebooks

3.2.0

  • Added test_label_dist to show inter-cell distance
  • Re-run and revise notebooks, especially for modality prediction

3.1.0

  • aligned_idx is now P, a matrix filled with priors
  • Combined P and F matrices into aggregate corr
  • Changes improved unaligned performance significantly
  • Slightly reduced aligned performance
  • Re-ran joint embedding notebooks
  • Fixed bug in knn calculation
  • Added perfect_alignment toggle for separate knn graph calculation method
  • Cleaned up no-longer-used files

3.0.0

  • Add evaluation graph for alignment assumptions
  • Merge notebooks
  • Example directory reorganization
  • Removed certain errant checks
  • Add modality prediction samples

2.1.0.9

  • Added compatibility for partially aligned datasets using overlapping average vectors
  • Added compatibility for differently-sized datasets
  • Added "mix-in" metrics to control how much training is done on aligned sets
  • Added more visualization for differently aligned datasets

2.1.0.8

  • Make loss function more modular
    • Add switchable distance function (Euclidean, Manhattan, Cosine, etc.)
  • Simplify loss function
  • Fix similarity function
  • Re-add connected KNN to F
  • Notebook reruns

2.1.0.7

  • Added inverse cross loss
  • Notebook reruns

2.1.0.6 (3.0.0.0)

  • Implement encoder-decoder model
  • Add custom model module
  • Re-run notebooks (doing well!)

2.1.0.5

  • Removed temporary neighborhood module
  • Added neighbor graph utility knn to nn_funcs module
  • Added guaranteed connectivity to knn
  • Tuning and reruns on all notebooks

2.1.0.4

  • Modified visualize UnionCom function
  • Cleaned loss handling in project_nlma
  • More robust loss output
  • Notebook rerun

2.1.0.3

  • Implemented test_closer, measuring fraction of samples closer to true match
  • Moved auxiliary loss calculations to new nn_funcs module
  • Revised loss function
  • Refactored code
  • Added matrix versions of UC term and NLMA
  • Added naïve implementation of Gromov-Wasserstein distance
  • Renamed and added notebooks scGEM and MMD-MA
  • Removed comparison.ipynb and added comparisons in each notebook
  • Reran notebooks

2.1.0.2

  • Added ALL FIRST and BATCH FIRST calculation modes to hybrid project_nlma
  • Renamed default NN step timing to BATCH FIRST
  • Finished vanilla loss run with improved label transfer accuracy (comparison_no-hybrid.ipynb)
  • Renamed and reran unfinished hybrid loss run (sample.ipynb)

2.1.0.1

  • Deprecated existing project_nlma
  • New project_nlma on tsne backend
  • Hybrid loss function
  • Unfinished test runs
  • Temporarily added partial neighborhood module from ManiNetCluster

2.1.0.0

  • Remove two-step, gradient optimizations temporarily
  • Comparison notebook
  • Fix NLMA scaling (coefficient fixes)
  • Re-added tsne projection method

2.0.5

  • Small construct_sparse fix

2.0.4

  • Cleanup, notes, file removal

2.0.3

  • CPU fixes
  • Large matrix exclusion fixes
  • Expand/shrink matrix normalization
  • Reruns
  • Notes on coefficient/F-combination difficulties

2.0.2

  • Small fixes
  • Reruns

2.0.1

  • AnnData input support
  • Cell cycle partitioning support
  • Notebook reruns

2.0.0

  • Two-step optimization
  • two_step_include_large
  • Redundant calculation
  • NLMA projection fixes
  • GPU compatibility
  • Sparse compatibility
  • Utility functions

1.0.0

  • Initial release