Graphical tools

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=== Figures / Illustrations ===
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=== Videos ===
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* For sharing videos with the thesis: figshare
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* Adobe Illustrator - for students only in kiosk?
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=== Figures/Illustrations ===
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* Powerpoint
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* Vector Graphics Editors
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* Directly in Latex (Ti''k''Z/PGF: https://github.com/pgf-tikz/pgf)
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** Inkscape (free and open-source)
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* [http://www.uio.no/tjenester/it/maskin/programvare/programkiosk/ uio programkiosk]
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** Adobe Illustrator (for students only through [http://www.uio.no/tjenester/it/maskin/programvare/programkiosk/ UiO programkiosk])
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* Inkscape
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** Directly in LaTeX (PGF/Ti''k''Z: https://github.com/pgf-tikz/pgf; some [https://texample.net/tikz/examples/ examples])
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* Lucid charts
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** LibreOffice Draw (free and open-source)
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* Google draw, in Google disk
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** Through presentation software such as Powerpoint, Keynote, …
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* Photopea (online editor)
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** Web-based options: Google draw (in Google disk), [https://www.drawio.com Draw.io], Figma, Lucid charts, …
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* Figma?
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* Draw.io
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* Linux-program for grafer, finn ut navn
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=== Plotting, Graphs ===
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* Raster Graphics Editors
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** Gimp (free and open-source)
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** Adobe Photoshop (for students only through [http://www.uio.no/tjenester/it/maskin/programvare/programkiosk/ UiO programkiosk])
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** Photopea (online editor)
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*3D Computer Graphics Editors
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** Blender (free and open-source)
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** Autodesk Maya
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** see also [https://robin.wiki.ifi.uio.no/3D-software here]
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=== Plotting Apps ===
* Python
* Python
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** Matplotlib (see [https://github.com/jbmouret/matplotlib_for_papers Mouret's tutorial for publication quality plots ])
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** Matplotlib
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** Seaborn - easy to create good looking plots ([https://elitedatascience.com/python-seaborn-tutorial tutorial here])
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*** see [https://github.com/jbmouret/matplotlib_for_papers Mouret's tutorial] for publication quality plots
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** Export to Latex (Ti''k''Z/PGF; https://github.com/nschloe/tikzplotlib)
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*** check the [https://github.com/matplotlib/cheatsheets cheat sheets]
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* R - ggplot2 (with Rstudio)
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** Seaborn (statistical data visualization; uses Matplotlib internally. See for example this [https://elitedatascience.com/python-seaborn-tutorial tutorial])
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** Export to Latex (TikZ/PGF; https://github.com/daqana/tikzDevice)
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** [https://github.com/juuf/IN5490/blob/main/IN5490.ipynb Jupyter Notebook] (former ROBIN PhD-student Julian)
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* Gnuplot (free)
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* R
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* Desmos.com (web based)
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** ggplot2 (with Rstudio)
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* Matlab (available at uio)
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* Matlab (available at UiO)
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** Export to Latex (Ti''k''Z/PGF; https://github.com/matlab2tikz/matlab2tikz)
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* Octave (free alternative to matlab)
* Octave (free alternative to matlab)
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* javaFX
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* Gnuplot
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* excel (uio)
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* Desmos.com (web based)
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* excel (UiO)
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=== How to convert to latex format ===
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* recommended approach: save as pdf, use pdfcrop, includegraphics in latex
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** avoid bitmap graphics if possible and especially jpg!
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* epstopdf - usually installed with latex
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* pdfcrop - usually installed with latex
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=== Digitalize Figures ===
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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:
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* Python: https://github.com/dilawar/PlotDigitizer
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* Matlab: https://blogs.mathworks.com/steve/2013/12/31/automating-data-extraction-1/
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* External App: [https://automeris.io/WebPlotDigitizer/ WebPlotDigitizer]
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add more info here
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=== Tips on Exporting Figures  ===
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* Before saving the graphics in the respective programs
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** Avoid bitmap graphics if possible and especially jpg!
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** Preferably use vector graphics such as svg, pdf or eps (can be edited with vector graphics editors)
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** Check your colour maps! (see https://www.nature.com/articles/s41467-020-19160-7 or https://matplotlib.org/stable/tutorials/colors/colormaps.html)
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** Check font size, font type, line width, marker size, proportion, aspect ratio and resolution! Tuning those parameters makes a significant impact on how your figures are perceived!
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** Example plots with mostly default (left) and adapted (right) plotting parameters.
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** [[Fil:TestT .png|400px|middle]][[Fil:Test.png|250px|middle]]
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** Make sure that your figures are still readable when printing them in grayscale
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* Sometimes it is neccessary to use png format (e.g. in case of render graphics or plots with an essential transparency effect)
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** In that case, one should pick a proper resolution for the export file while accounting for its file size
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** Possible ways to compress the png file is to use for example [https://pngquant.org/ pngquant], [http://www.advancemame.it/comp-readme AdvanceCOMP] or [https://www.smashingmagazine.com/2015/06/efficient-image-resizing-with-imagemagick/ ImageMagick]
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* Exporting to LaTeX
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** Recommended approach:
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*** export as pdf
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*** optionally use pdfcrop (usually installed with LaTeX) to cut unecessary white space
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*** in case only eps export is supported, use epstopdf (usually installed with LaTeX)
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** For direct inclusion in LaTeX, use the following scripts to create PGF/Ti''k''Z files:
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*** Python: https://github.com/nschloe/tikzplotlib
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*** R: https://github.com/daqana/tikzDevice
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*** Matlab/Octave: https://github.com/matlab2tikz/matlab2tikz
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*** 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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* 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 12:58, 4 April 2024

Contents

Videos

  • For sharing videos with the thesis: figshare

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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