Colormap norming about pyvista HOT 6 OPEN

LogNorm and SymLogNorm

Another point (along comments by @craigmillernz): Adding the possibility for LogNorm and SymLogNorm (as in matplotlib/discretize).

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Thanks for opening the issue. As I mentioned on Slack, the idea arose because you mentioned the interactive keyword, which I meant was about changing the colormap, but turned out to be about changing the appearance/location of the colorbar. Again as I said before, I think in general this is a bad idea (at least for static figures, for the exactly same reasons why jet etc are bad colormaps), but it can be very useful to explore the dataspace interactively.

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I like the idea of having an interactive way of exploring the colormap and I think this might be a cool side project we could implement for simply creating a matplotlib colormap which we could support linking to vtki plots.

Perhaps we could make a new module called icolormap under @OpenGeoVis?

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Maybe @mycarta, @kwinkunks has experienced already with something similar, maybe some stuff already exists?

They, quite rightly and as I do, tell everyone to use good colormaps. But by doing so, I think they've come along many tools, which might help here. As important as good colormaps are for static figures, I think such an interactive colormap could be very interesting indeed for playing around interactively.

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(The dangers of it are obvious and known. In the Oil & Gas company I worked years ago it was common that we presented an EM inversion result, just so that the commercial managers came over to play around with the colour-bar [not Matlab, but similar feature] until they were satisfied with what they saw. But then, every powerful tool has its dangers if it falls into the wrong hands.)

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I tried to implement the class MidpointNormalize ad hoc to center the color bar, alas without success. Did you get this to work or just an analogy to be implemented? Or has anyone found another solution to this?

I implemented another method adapted from here, but it weighs the smaller values too much, see figure.

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