Comparing the Python vs. R version below, I wonder whether we could support:
- Showing values as is, with a
scale_color_gradientn() type of legend where colors can be specified by the user.
- Inverting the image such that
col="black" would give auto-contrasted black intensities over white background.
Not sure how trivial this is to implement, but leaving the thought here...
- Somewhat related, there is currently no way to drop the legend, since there is a
new_scale() call after rendering the image layer. Perhaps a legend=T/F argument in plotImage() would suffice to address this.
(screenshots from https://helenalc.github.io/SpatialData.demo/code/csama.html)
Comparing the Python vs. R version below, I wonder whether we could support:
scale_color_gradientn()type of legend wherecolorscan be specified by the user.col="black"would give auto-contrasted black intensities over white background.Not sure how trivial this is to implement, but leaving the thought here...
new_scale()call after rendering the image layer. Perhaps alegend=T/Fargument inplotImage()would suffice to address this.(screenshots from https://helenalc.github.io/SpatialData.demo/code/csama.html)