How about changing the default colour scheme to a scientifically-derived one?
A couple of suitable existing schemes are “inferno (matplotlib)” and “Viridis (matplotlib)”
The benefits (e.g. as discussed in The misuse of colour in science communication | Nature Communications) would be:
- They report true data variations.
- They reduce complexity.
- They are accessible for people with colour-vision deficiencies.
I’m afraid changing the default colormap is a no-go.
The current color map cool to warm, designed by Ken Moreland, reports true data variations, reduces complexity and is very color deficient/ color blind friendly. Thus, I believe these are not good reasons to change it.
The current color map does have one deficiency under certain conditions in my mind. It does not have as much discriminitive power as some of the other maps. That’s why we add a broad range of really good maps in the Color Editor/ Presets.
With regards to Cool to Warm, I would argue leaving it alone. It has stood up well over a lot of years, everyone knows about it, and again it’s a good map.
Thanks for the prompt replies!
I take your points.
In any case, as you say, we all have the freedom to select a colour scheme of our choice from the many available.
And easily make it permanent (for that user)!
If you haven’t looked at them yet, take a look at the color maps that include three colors. These are Blue-Green-Orange or Yellow-Gray-Blue. This is the work of Francesca Samsul, of TAC and LANL.
I had not looked at Blue-Green-Orange or Yellow-Gray-Blue, but I will.
In addition, if you don’t like ParaView’s default color map, you can set a custom one!
See this section in the ParaView Guide, last paragraph: 3. Color maps and transfer functions — ParaView Documentation 5.10.0 documentation
Side note: it would be nice to have linear colormaps “Cool” and “Warm” that correspond to their respective portions of the “Cool to Warm” colormap. I’m constantly creating custom “Cool” and “Warm” colormaps and “saving” them, but alas they don’t appear to persist between sessions. I’ve probably created my own “Cool” and “Warm” colormaps about 1K times now… pretty much every time I open a result in ParaView.
ImportPresets(filename='mycolorfile.json') which lets me use mycolorfile in new ParaView sessions.
For other readers of this thread in the future (to help inspire greater thought into colormap choice):
- One possible limitation (may depend on the data) of the default Cool to Warm scale is that the “lightness” is not linear: both extremes (red and blue) are dark, while the centre of the scale is light. If a Cool to Warm image was converted to greyscale then the colours would not be unique (red would look the same as blue). This figure gives a useful flowchart for choosing a scheme: https://www.nature.com/articles/s41467-020-19160-7/figures/6
Why not do this:
MinColor = (x1,y1,z1,a1)
MaxColor = (x2,y2,z2,a2)
SliderColorVal = (slider.max-slider.current)/(slider.max-slider.min)*(MaxColor - MinColor) + MimColor