├── AVLearner.py ├── README.md ├── baseline.py ├── data └── README.md ├── data_prep ├── IEMOCAP_preprocess.py └── datagen.py ├── module ├── .DS_Store └── umap │ ├── .gitattributes │ ├── .gitignore │ ├── .idea │ ├── .gitignore │ ├── inspectionProfiles │ │ └── profiles_settings.xml │ └── umap-nan.iml │ ├── .pep8speaks.yml │ ├── .travis.yml │ ├── CODE_OF_CONDUCT.md │ ├── CONTRIBUTING.md │ ├── LICENSE.txt │ ├── Makefile │ ├── README.rst │ ├── appveyor.yml │ ├── azure-pipelines.yml │ ├── build │ └── lib │ │ └── umap │ │ ├── __init__.py │ │ ├── aligned_umap.py │ │ ├── distances.py │ │ ├── layouts.py │ │ ├── parametric_umap.py │ │ ├── plot.py │ │ ├── sparse.py │ │ ├── spectral.py │ │ ├── umap_.py │ │ ├── utils.py │ │ └── validation.py │ ├── ci_scripts │ ├── install.sh │ ├── success.sh │ └── test.sh │ ├── doc │ ├── .gitignore │ ├── Makefile │ ├── _static │ │ └── .gitkeep │ ├── aligned_umap_basic_usage.rst │ ├── aligned_umap_plotly_plot.html │ ├── aligned_umap_politics_demo.rst │ ├── api.rst │ ├── basic_usage.rst │ ├── basic_usage_bokeh_example.html │ ├── benchmarking.rst │ ├── bokeh_digits_plot.py │ ├── clustering.rst │ ├── composing_models.rst │ ├── conf.py │ ├── densmap_demo.rst │ ├── doc_requirements.txt │ ├── document_embedding.rst │ ├── embedding_space.rst │ ├── exploratory_analysis.rst │ ├── faq.rst │ ├── how_umap_works.rst │ ├── images │ │ ├── aligned_umap_pendigits_anim.gif │ │ ├── c_elegans_3d.jpg │ │ ├── galaxy10_2D_densmap.svg │ │ ├── galaxy10_2D_densmap_supervised.svg │ │ ├── galaxy10_2D_densmap_supervised_prediction.svg │ │ ├── galaxy10_2D_umap.svg │ │ ├── galaxy10_2D_umap_supervised.svg │ │ ├── galaxy10_2D_umap_supervised_prediction.svg │ │ ├── galaxy10_subset.svg │ │ ├── population_umap.jpg │ │ └── single_cell_umap.jpg │ ├── index.rst │ ├── interactive_viz.rst │ ├── inverse_transform.rst │ ├── make.bat │ ├── mutual_nn_umap.rst │ ├── outliers.rst │ ├── parameters.rst │ ├── parametric_umap.rst │ ├── performance.rst │ ├── plotting.rst │ ├── plotting_example_interactive.py │ ├── plotting_interactive_example.html │ ├── precomputed_k-nn.rst │ ├── release_notes.rst │ ├── reproducibility.rst │ ├── scientific_papers.rst │ ├── sparse.rst │ ├── supervised.rst │ └── transform.rst │ ├── docs_requirements.txt │ ├── examples │ ├── README.txt │ ├── digits │ │ ├── digits.html │ │ └── digits.py │ ├── galaxy10sdss.py │ ├── inverse_transform_example.py │ ├── iris │ │ ├── iris.html │ │ └── iris.py │ ├── mnist_torus_sphere_example.py │ ├── mnist_transform_new_data.py │ ├── plot_algorithm_comparison.py │ ├── plot_fashion-mnist_example.py │ ├── plot_feature_extraction_classification.py │ └── plot_mnist_example.py │ ├── notebooks │ ├── AnimatingUMAP.ipynb │ ├── Document embedding using UMAP.ipynb │ ├── Parametric_UMAP │ │ ├── 01.0-parametric-umap-mnist-embedding-basic.ipynb │ │ ├── 02.0-parametric-umap-mnist-embedding-convnet.ipynb │ │ ├── 03.0-parametric-umap-mnist-embedding-convnet-with-reconstruction.ipynb │ │ ├── 04.0-parametric-umap-mnist-embedding-convnet-with-autoencoder-loss.ipynb │ │ ├── 05.0-parametric-umap-with-callback.ipynb │ │ ├── 06.0-nonparametric-umap.ipynb │ │ └── 07.0-parametric-umap-global-loss.ipynb │ └── UMAP usage and parameters.ipynb │ ├── paper.bib │ ├── paper.md │ ├── requirements.txt │ ├── setup.py │ └── umap │ ├── __init__.py │ ├── aligned_umap.py │ ├── distances.py │ ├── layouts.py │ ├── parametric_umap.py │ ├── plot.py │ ├── sparse.py │ ├── spectral.py │ ├── tests │ ├── __init__.py │ ├── conftest.py │ ├── digits_embedding_42.npy │ ├── test_aligned_umap.py │ ├── test_chunked_parallel_spatial_metric.py │ ├── test_composite_models.py │ ├── test_data_input.py │ ├── test_densmap.py │ ├── test_parametric_umap.py │ ├── test_plot.py │ ├── test_spectral.py │ ├── test_umap.py │ ├── test_umap_get_feature_names_out.py │ ├── test_umap_metrics.py │ ├── test_umap_nn.py │ ├── test_umap_on_iris.py │ ├── test_umap_ops.py │ ├── test_umap_repeated_data.py │ ├── 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