Graphical tools

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** LibreOffice Draw (free and open-source)
** LibreOffice Draw (free and open-source)
** Through presentation software such as Powerpoint, Keynote, …
** Through presentation software such as Powerpoint, Keynote, …
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** Web-based options: Google draw (in Google disk), Draw.io, Figma, Lucid charts, …
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** Web-based options: Google draw (in Google disk), [https://www.drawio.com Draw.io], Figma, Lucid charts, …
* Raster Graphics Editors
* Raster Graphics Editors
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*** check the [https://github.com/matplotlib/cheatsheets cheat sheets]
*** check the [https://github.com/matplotlib/cheatsheets cheat sheets]
** Seaborn (statistical data visualization; uses Matplotlib internally. See for example this [https://elitedatascience.com/python-seaborn-tutorial tutorial])
** Seaborn (statistical data visualization; uses Matplotlib internally. See for example this [https://elitedatascience.com/python-seaborn-tutorial tutorial])
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** [https://github.com/juuf/IN5490/blob/main/IN5490.ipynb Jupyter Notebook] (former ROBIN PhD-student Julian)
* R
* R
** ggplot2 (with Rstudio)
** ggplot2 (with Rstudio)
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* Gnuplot
* Gnuplot
* Desmos.com (web based)
* Desmos.com (web based)
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* javaFX
 
* excel (UiO)
* excel (UiO)
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*** Matlab/Octave: https://github.com/matlab2tikz/matlab2tikz
*** Matlab/Octave: https://github.com/matlab2tikz/matlab2tikz
*** It is possible to either input the code directly through <code>\input{}</code> or to compile the figure first [https://blog.modelworks.ch/producing-stand-alone-figures-with-tikz-in-latex/ through] the ''standalone'' class
*** It is possible to either input the code directly through <code>\input{}</code> or to compile the figure first [https://blog.modelworks.ch/producing-stand-alone-figures-with-tikz-in-latex/ through] the ''standalone'' class
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* For example plots that show how to tweak plotting parameters, see [https://github.com/juuf/IN5490/blob/11cda138be6c31b64282356543254d20422aa7a9/IN5490.ipynb here]
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* To see how plotting parameters can be tuned given concrete examples, see [https://github.com/juuf/IN5490/blob/5a4a6bb0098402166ceb623bcfd5c3402c5b4f72/IN5490.ipynb here]. Based on an example data set, first distributional plots are shown. Then the default plotting parameters are tuned.

Current revision as of 13:14, 23 March 2024

Contents

Figures/Illustrations

  • Vector Graphics Editors
    • Inkscape (free and open-source)
    • Adobe Illustrator (for students only through UiO programkiosk)
    • Directly in LaTeX (PGF/TikZ: https://github.com/pgf-tikz/pgf; some examples)
    • LibreOffice Draw (free and open-source)
    • Through presentation software such as Powerpoint, Keynote, …
    • Web-based options: Google draw (in Google disk), Draw.io, Figma, Lucid charts, …
  • Raster Graphics Editors
    • Gimp (free and open-source)
    • Adobe Photoshop (for students only through UiO programkiosk)
    • Photopea (online editor)
  • 3D Computer Graphics Editors
    • Blender (free and open-source)
    • Autodesk Maya
    • see also here

Plotting Apps

  • Python
  • R
    • ggplot2 (with Rstudio)
  • Matlab (available at UiO)
  • Octave (free alternative to matlab)
  • Gnuplot
  • Desmos.com (web based)
  • excel (UiO)

Digitalize Figures

To qualitatively compare one's own data with other published data, it is sometimes needed to obtain the concrete data of the respective publication. In that case there are multiple ways to do that:

Tips on Exporting Figures

  • Before saving the graphics in the respective programs
  • Sometimes it is neccessary to use png format (e.g. in case of render graphics or plots with an essential transparency effect)
    • In that case, one should pick a proper resolution for the export file while accounting for its file size
    • Possible ways to compress the png file is to use for example pngquant, AdvanceCOMP or ImageMagick
  • Exporting to LaTeX
  • To see how plotting parameters can be tuned given concrete examples, see here. Based on an example data set, first distributional plots are shown. Then the default plotting parameters are tuned.
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