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(How to Export Figures)
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** Blender (free and open-source)
** Blender (free and open-source)
** Autodesk Maya
** Autodesk Maya
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** see also [https://robin.wiki.ifi.uio.no/3D-software here]
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=== Plotting in ===
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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, uses Matplotlib internally, see for example [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 (PGF/Ti''k''Z; https://github.com/nschloe/tikzplotlib)
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*** check the [https://github.com/matplotlib/cheatsheets cheat sheets]
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** Seaborn (statistical data visualization; uses Matplotlib internally. See for example this [https://elitedatascience.com/python-seaborn-tutorial tutorial])
* R
* R
** ggplot2 (with Rstudio)
** ggplot2 (with Rstudio)
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** Export to LaTeX (PGF/Ti''k''Z; https://github.com/daqana/tikzDevice)
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* Matlab (available at UiO)
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* Matlab (available at uio)
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** Export to Latex (PGF/Ti''k''Z; https://github.com/matlab2tikz/matlab2tikz)
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* Octave (free alternative to matlab)
* Octave (free alternative to matlab)
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** Export to LaTeX (PGF/Ti''k''Z; https://github.com/matlab2tikz/matlab2tikz)
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* Gnuplot
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* Gnuplot (free)
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* Desmos.com (web based)
* Desmos.com (web based)
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* javaFX
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* excel (UiO)
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* excel (uio)
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=== Digitalize Figures ===
=== Digitalize Figures ===
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* External App: [https://automeris.io/WebPlotDigitizer/ WebPlotDigitizer]
* External App: [https://automeris.io/WebPlotDigitizer/ WebPlotDigitizer]
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=== Tips When Exporting Figures  ===
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=== Tips on Exporting Figures  ===
* Before saving the graphics in the respective programs  
* Before saving the graphics in the respective programs  
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** Check 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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** Avoid bitmap graphics if possible and especially jpg!
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** Check font size, font type and line widths
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** Preferably use vector graphics such as svg, pdf or eps (can be edited with vector graphics editors)
** Preferably use vector graphics such as svg, pdf or eps (can be edited with vector graphics editors)
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** Avoid bitmap graphics if possible and especially jpg!
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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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* For LaTeX
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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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** Recommended approach: export as pdf, use pdfcrop
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** Example plots with mostly default (left) and adapted (right) plotting parameters.
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*** epstopdf - usually installed with LaTeX
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** [[Fil:TestT .png|400px|middle]][[Fil:Test.png|250px|middle]]
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*** pdfcrop - usually installed with LaTeX
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** Make sure that your figures are still readable when printing them in grayscale
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** For direct inclusion in LaTeX use the scripts linked above to create PGF/Ti''k''Z files
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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)
* 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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** 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 [https://pngquant.org/ pngquant], [http://www.advancemame.it/comp-readme AdvanceCOMP] or [https://www.smashingmagazine.com/2015/06/efficient-image-resizing-with-imagemagick/ ImageMagick]
** 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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Add more info here
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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.

Nåværende revisjon fra 28. mar 2022 kl. 09:09

Innhold

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
    • Matplotlib
    • Seaborn (statistical data visualization; uses Matplotlib internally. See for example this tutorial)
  • 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
    • Avoid bitmap graphics if possible and especially jpg!
    • Preferably use vector graphics such as svg, pdf or eps (can be edited with vector graphics editors)
    • Check your colour maps! (see https://www.nature.com/articles/s41467-020-19160-7 or https://matplotlib.org/stable/tutorials/colors/colormaps.html)
    • 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!
    • Example plots with mostly default (left) and adapted (right) plotting parameters.
    • Make sure that your figures are still readable when printing them in grayscale
  • 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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