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Data science toolkit (TK) from Quality-Safety research Institute (QSI).

Project description

qsi-tk

Data science toolkit (TK) from Quality-Safety research Institute (QSI)

Installation

pip install qsi-tk

Contents

This package is a master library containing various previous packages published by our team.

module sub-module description standalone pypi package publication
qsi.io File I/O, Dataset loading TODO qsi-tk open datasets with algorithms
qsi.io.aug Data augmentation, e.g., generative models TODO Data aug with deep generative models. e.g., " variational autoencoders, generative adversarial networks, autoregressive models, KDE, normalizing flow models, energy-based models, and score-based models. "
qsi.io.pre Data processing, e.g., channel alignment and 1D-laplacian kernel fs for e-nose data; x-binning, baseline removal for TOF MS. TODO
qsi.vis Plotting
qsi.cs compressed sensing cs1 Adaptive compressed sensing of Raman spectroscopic profiling data for discriminative tasks [J]. Talanta, 2020, doi: 10.1016/j.talanta.2019.120681
Task-adaptive eigenvector-based projection (EBP) transform for compressed sensing: A case study of spectroscopic profiling sensor [J]. Analytical Science Advances. Chemistry Europe, 2021, doi: 10.1002/ansa.202100018
Compressed Sensing library for spectroscopic profiling data [J]. Software Impacts, 2023, doi: 10.1016/j.simpa.2023.100492
qsi.fs
qsi.fs.nch_time_series_fs multi-channel enose data fs with 1d-laplacian conv kernel TODO
qsi.fs.glasso Structured-fs of Raman data with group lasso TODO
qsi.ks kernels ackl TODO
qsi.dr qsi.dr.metrics Dimensionality Reduction (DR) quality metrics pyDRMetrics, wDRMetrics pyDRMetrics - A Python toolkit for dimensionality reduction quality assessment, Heliyon, Volume 7, Issue 2, 2021, e06199, ISSN 2405-8440, doi: 10.1016/j.heliyon.2021.e06199.
qsi.dr.mf matrix-factorization based DR pyMFDR Matrix Factorization Based Dimensionality Reduction Algorithms - A Comparative Study on Spectroscopic Profiling Data [J], Analytical Chemistry, 2022. doi: 10.1021/acs.analchem.2c01922
qsi.cla qsi.cla.metrics classifiability analysis pyCLAMs, wCLAMs A unified classifiability analysis framework based on meta-learner and its application in spectroscopic profiling data [J]. Applied Intelligence, 2021, doi: 10.1007/s10489-021-02810-8
pyCLAMs: An integrated Python toolkit for classifiability analysis [J]. SoftwareX, 2022, doi: 10.1016/j.softx.2022.101007
qsi.cla.ensemble homo-stacking, hetero-stacking, FSSE pyNNRW Spectroscopic Profiling-based Geographic Herb Identification by Neural Network with Random Weights [J]. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2022, doi: 10.1016/j.saa.2022.121348
qsi.cla.kernel kernel-NNRW
qsi.cla.nnrw neural networks with random weights
qsi.pipeline General data analysis pipelines.
qsi.gui Web-based apps. e.g., `python -m qsi.gui.chaihu` will launch the app for bupleurum origin discrimination.

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