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I've been getting deeper into vega-lite via Altair and I wasn't able to locate any examples or documentation about creating custom axes transformations and scales beyond the bundled continuous scales.
To be specific, I wrote a library called mpl-probscale that implements probability scales in (wait for it...) matplotlib.
Short version: probability scales take a quantile plot and convert the quantiles to probabilities (and back) based on the CDF/PPF of some user-specified probability distribution (typically normal or weibull in my field).
Here's an example comparing three different probability scales and a linear scale all with the same tick locations:
(here's a link to the docs page, just scroll down a bit)
I'd love to be able to do something like this in vega-lite (and eventually Altair), but I'm getting a little lost in the internals. Can anyone point me in the right direction?
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Hey folks,
I've been getting deeper into vega-lite via Altair and I wasn't able to locate any examples or documentation about creating custom axes transformations and scales beyond the bundled continuous scales.
To be specific, I wrote a library called mpl-probscale that implements probability scales in (wait for it...) matplotlib.
Short version: probability scales take a quantile plot and convert the quantiles to probabilities (and back) based on the CDF/PPF of some user-specified probability distribution (typically normal or weibull in my field).
Here's an example comparing three different probability scales and a linear scale all with the same tick locations:
(here's a link to the docs page, just scroll down a bit)
I'd love to be able to do something like this in vega-lite (and eventually Altair), but I'm getting a little lost in the internals. Can anyone point me in the right direction?
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