Comments (7)
Actually it would be nice to just have them as static np.arrays
, not as functions, too. Saves a lot of typing.
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I think it would be great if we could also define a default color palette.
We could also use the default of matplotlib
or seaborn
, but I would prefer a custom one. A custom color palette would make our plots look much more recognizable. I guess @philipphennig you would have a preference for main, second, third, ... colors?
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I mean, the obvious choice is the Uni-TUE color palette. It works well for plots with up to three lines. But I realise that it may not be everyone's cup of tea. We could keep the default color palette as the default and offer the unitue
palette as a replacement.
For what it's worth, I'm not a fan of seaborn
. It's too heavy-handed for my taste.
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thanks for the great inputs! :)
The original reasoning behind using functions was that I dont really like a bunch of constants lying around the source. But I guess constants are more practical anyway -- let's see how far we get with that!
The original reasoning behind using tuples was that this way, the source is dependency-free. However, if we depend on matplotlib anyway (which has a numpy dependency, too), there is no real reason to avoid numpy arrays. So yes, we can change them into arrays.
Regarding the color palette: I think it is a great idea to add color palettes. How about not adding a default color palette, but a range of palettes so a user can choose freely without us imposing our tastes? I have some color cycles lying around (tue, probnum, tufte, etc.) which I can turn into rcParams inputs.
I suppose then it would make sense to branch out the color module:
color/
rgb/ # for RGB constants
cycles/ # for color cycles
from where on one can expand.
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See #5.
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Ok, great!
I think static constants are fine if they are within the namespace of the package. Numpy
has np.pi
, so it can't be that bad :)
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#13 introduces color constants.
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Related Issues (20)
- Whitespace around figures when saving
- Readme images not displayed on PyPi
- ICLR 2023 bundle HOT 2
- Can this project be more general? HOT 3
- ICML 2023
- ICLR 2024
- ICML style updates
- Figure sizes
- Readme vs Documentation
- Font seems off HOT 4
- Font types HOT 1
- UAI style
- Implement quality assurance for Jupyter notebooks HOT 1
- _Inches_per_Point is inverted HOT 1
- Explain `overfull hbox` in troubleshooting section
- Neurips 2022 style
- Inconsistency in font-family defaults
- Windows compatibility and doctests HOT 1
- mathit in beamer_moml is too fat HOT 2
- Fontsize flexibility HOT 1
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