ParallelPlots

General

This Project is for the TU-Berlin Course "Julia Programming for Machine Learning"
Please make sure, that Julia 1.10 is used!

This Module will return you a nice Makie Plot you can use to display your Data with Parallel Coordinates

Getting Started

Install Dependencies & Use ParallelPlots

Script/REPL

Pkg> add https://github.com/moritz155/ParallelPlots

Notebook

using Pkg
Pkg.add(url="https://github.com/moritz155/ParallelPlots")
using ParallelPlots

Usage

Available Parameter

Parameter	Default	Example	Description
title::String	""	title="My Title"	The Title of The Figure,
colormap	:viridis	colormap=:thermal	The Colors of the Lines
color_feature	nothing	color_feature="weight"	The Color of the Lines will be based on the values of this selected feature. If nothing, the last feature will be used
feature_labels	nothing	feature_labels=["Weight","Age"]	Add your own Axis labels, just use the exact amount of labes as you have axis
feature_selection	nothing	feature_selection=["weight","age"]	Select, which features should be Displayed. If color_feature is not in this List, use the last one
curve	false	curve=true	Show the Lines Curved
show_color_legend	nothing	show_color_legend=true	Show the Color Legend. If parameter not set & color_feature not shown, it will be displayed automaticly
scale	nothing	scale=[log2, identity, log10]	Choose, how each Axis should be scaled. In the Example. The first Axis will be log2, the second linear and the third log10

Examples

julia> using ParallelPlots
julia> parallelplot(DataFrame(height=160:180,weight=60:80,age=20:40))

# If you want to set the size of the plot (default width:800, height:600)
julia> parallelplot( DataFrame(height=160:180,weight=60:80,age=20:40), figure = (resolution = (300, 300),) )

# You can update as well the Graph with Observables
julia> df_observable = Observable(DataFrame(height=160:180,weight=60:80,age=20:40))
julia> fig, ax, sc = parallelplot(df_observable)

# If you want to add a Title for the Figure, sure you can!
julia> parallelplot(DataFrame(height=160:180,weight=reverse(60:80),age=20:40),title="My Title")

# If you want to specify the axis labels, make sure to use the same number of labels as you have axis!
julia> parallelplot(DataFrame(height=160:180,weight=reverse(60:80),age=20:40), feature_labels=["Height","Weight","Age"])

# Adjust Color and and feature
parallelplot(df,
        # You choose which axis/feature should be in charge for the coloring
        color_feature="weight",
        # you can as well select, which Axis should be shown
        feature_selection=["height","age","income"],
        # and label them as you like
        feature_labels=["Height","Age","Income"],
        # you can change the ColorMap (https://docs.makie.org/dev/explanations/colors)
        colormap=:thermal,
        # ...and can choose to display the color legend.
        # If this Attribute is not set,
        # it will only show the ColorBar, when the color feature is not in the selected feature
        show_color_legend = true
    )

# Adjust the Axis scale
parallelplot(df,
        feature_selection=["height","age","income"],
        scale=[log2, identity, log10]
    )

Working on ParallelPlots / Cheatsheet

1. Using ParallelPlots

   • Moving to the project folder
   • julia --project
     • You will see julia>
   • To move to the pkg, type in ]

2. Running commands

   • Adding external Dependencies
     • (ParallelPlots) pkg>add 'DepName'
   • Run Tests to check if ParallelPlots is still working as intended
     • (ParallelPlots) pkg>test
   • Build
     • (ParallelPlots) pkg>build
   • Precompile
     • (ParallelPlots) pkg>precompile

Create Docs

• move to ./docs folder with command line
• run julia --project make.jl