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.bumpversion.cfg

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[bumpversion]
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current_version = 0.1.2
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current_version = 0.1.6
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commit = True
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tag = True
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.coveragerc

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[run]
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omit = qolmat/_version.py

.flake8

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[flake8]
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exclude = .git,__pycache__,.vscode,tests
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exclude = .git,__pycache__,.vscode
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max-line-length=99
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ignore=E302,E305,W503,E203,E731,E402,E266,E712,F401,F821
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indent-size = 4

.github/workflows/publish.yml

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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v3
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uses: actions/setup-python@v4
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with:
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python-version: '3.10'
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- name: Install dependencies

.gitignore

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examples/figures/*
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examples/data/*
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examples/local
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data/data_local/*
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# VSCode
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.vscode

AUTHORS.rst

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Development Team
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----------------
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* Julien Roussel <jroussel@quantmetry.com>
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* Anh Khoa Ngo Ho <angoho@quantmetry.com>
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* Charles-Henri Prat <chprat@quantmetry.com>
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* Guillaume Saës <gsaes@quantmetry.com>
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* Julien Roussel <julien.a.roussel@capgemini.com>
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* Anh Khoa Ngo Ho <anh-khoa.ngo-ho@capgemini.com>
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* Guillaume Saës <guillaume.saes@capgemini.com>
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* Yasser Zidani <yasser.zidani@capgemini.com>
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Past Contributors
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-----------------
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* Mikaïl Duran
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* Rima Hajou
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* Thomas Morzadec
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* Charles-Henri Prat

HISTORY.rst

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History
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=======
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??
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0.1.7 (2024-06-13)
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------------------
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* Little's test implemented in a new hole_characterization module
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* Documentation now includes an analysis section with a tutorial
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* Hole generators now provide reproducible outputs
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0.1.5 (2024-04-17)
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------------------
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* CICD now relies on Node.js 20
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* New tests for comparator.py and data.py
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0.1.4 (2024-04-15)
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------------------
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* ImputerMean, ImputerMedian and ImputerMode have been merged into ImputerSimple
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* File preprocessing.py added with classes new MixteHGBM, BinTransformer, OneHotEncoderProjector and WrapperTransformer providing tools to manage mixed types data
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* Tutorial plot_tuto_categorical showcasing mixed type imputation
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* Titanic dataset added
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* accuracy metric implemented
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* metrics.py rationalized, and split with algebra.py
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0.1.3 (2024-03-07)
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------------------
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README.rst

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[6] García, S., Luengo, J., & Herrera, F. "Data preprocessing in data mining". 2015.
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(`pdf <https://www.academia.edu/download/60477900/Garcia__Luengo__Herrera-Data_Preprocessing_in_Data_Mining_-_Springer_International_Publishing_201520190903-77973-th1o73.pdf>`__)
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[7] Botterman, HL., Roussel, J., Morzadec, T., Jabbari, A., Brunel, N. "Robust PCA for Anomaly Detection and Data Imputation in Seasonal Time Series" (2022) in International Conference on Machine Learning, Optimization, and Data Science. Cham: Springer Nature Switzerland, (`pdf <https://link.springer.com/chapter/10.1007/978-3-031-25891-6_21>`__)
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📝 License
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==========
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docs/api.rst

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.. currentmodule:: qolmat
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Imputers
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=========
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Imputers API
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============
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.. autosummary::
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:toctree: generated/
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imputations.imputers.ImputerKNN
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imputations.imputers.ImputerInterpolation
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imputations.imputers.ImputerLOCF
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imputations.imputers.ImputerMedian
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imputations.imputers.ImputerMean
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imputations.imputers.ImputerSimple
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imputations.imputers.ImputerMICE
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imputations.imputers.ImputerMode
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imputations.imputers.ImputerNOCB
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imputations.imputers.ImputerOracle
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imputations.imputers.ImputerRegressor
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imputations.imputers.ImputerSoftImpute
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imputations.imputers.ImputerShuffle
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Comparator
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===========
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Comparator API
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==============
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:toctree: generated/
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:template: class.rst
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benchmark.comparator.Comparator
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Missing Patterns
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================
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Missing Patterns API
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====================
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benchmark.missing_patterns.GroupedHoleGenerator
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Metrics
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=======
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Metrics API
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===========
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.. autosummary::
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benchmark.metrics.mean_absolute_error
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benchmark.metrics.mean_absolute_percentage_error
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benchmark.metrics.weighted_mean_absolute_percentage_error
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benchmark.metrics.accuracy
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benchmark.metrics.dist_wasserstein
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benchmark.metrics.kl_divergence
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benchmark.metrics.kolmogorov_smirnov_test
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benchmark.metrics.pattern_based_weighted_mean_metric
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RPCA engine
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RPCA engine API
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===============
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imputations.rpca.rpca_pcp.RPCAPCP
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imputations.rpca.rpca_pcp.RpcaPcp
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imputations.rpca.rpca_noisy.RpcaNoisy
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EM engine
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Expectation-Maximization engine API
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imputations.em_sampler.MultiNormalEM
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imputations.em_sampler.VARpEM
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Diffusion engine
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Diffusion Model engine API
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==========================
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imputations.diffusions.ddpms.TabDDPM
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imputations.diffusions.ddpms.TsDDPM
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Preprocessing API
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=================
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.. autosummary::
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:toctree: generated/
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:template: class.rst
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imputations.preprocessing.MixteHGBM
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imputations.preprocessing.BinTransformer
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imputations.preprocessing.OneHotEncoderProjector
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imputations.preprocessing.WrapperTransformer
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.. autosummary::
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:toctree: generated/
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:template: function.rst
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imputations.preprocessing.make_pipeline_mixte_preprocessing
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imputations.preprocessing.make_robust_MixteHGB
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Utils
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Utils API
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:toctree: generated/

docs/conf.py

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author = "Quantmetry"
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# The full version, including alpha/beta/rc tags
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version = "0.1.2"
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version = "0.1.6"
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release = version
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# -- General configuration ---------------------------------------------------

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