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Python docker

Docker image builder for Quantitative analysis (QA)
Embedding most used python modules

Features

Compute

  • Pca
  • Lda
  • Covariance
  • Correlation
  • ...

Render

  • Scatter
  • Heatmap
  • Score plot
  • Correlation circle
  • ...

Modules

Feel free to add your owns in requirements.txt.
If changes => build.

Npm packages

Some python modules required node libs to save figures, see package.jon.
If changes => build.

Sizes

  • Python modules (460Mo)
  • Node modules (250Mo)
  • python:3.9-slim-bullseye image (250Mo)
  • Debian extra packages (20Mo)

Requirements

  • Docker

Build

Simply

./build.sh

Clean exited containers

./clean.sh

Run

Default user is pca change -u option to use root.

  • Interractive
./runit.sh
  • One shot
./run.sh

Volumes

  • Workspace is mounted on $HOME/pca

Samples graphics

Eigens visualisation

ℹ️ Understanding eigen vectors visualisation

  • Initial rectangle dashed.
  • Projected rectangle filled.

Determining new plan axis with lines(e1,e2) from points (p1,Tp1) and (p2,Tp2).

eigensviz

Correlation circle

ℹ️ variable factor map
AKA variable factor map.
Generated by mlxtend modules on iris dataset.

vfmap

Heatmap

ℹ️ Heatmap
Generated by mlxtend modules on external housing dataset.

Heatmap

Pca scatter

ℹ️ Scatter
Generated by altair/altair_saver modules on iris dataset.

scatter