Q: How to render xenium morphology image with original colors?

Hello @LucaMarconato!

Thank you very much for this tool. I want to plot a part of morphology image acquired with xenium + multimodal segmentation kit. It is loaded into spatialdata and plotted without errors, but the colors are dim and they are different from what I'd expected (DAPI - #0F73E6, Boundary - #F300A5, Interior RNA - #A4A400, interior protein - #008A00, reference values from Xenium Explorer). I tried passing a list of colors like this:

crop = lambda sdata: spatialdata.bounding_box_query(
    sdata,
    min_coordinate=[17_500, 55_000],
    max_coordinate=[19_500, 57_000],
    axes=("x", "y"),
    target_coordinate_system="global",
)

crop(sdata).pl.render_images("morphology_focus", ["#0F73E6", "#F300A5", "#A4A400", "#008A00"]).pl.show(
    ax=axes[0], title="Morphology image", coordinate_systems="global"
)

The code does not produce an error, it works twice as long, and it results in the same image with colors unchanged.

The key question is how to adjust the colors and saturation of the plot, so that it looked closer to what I see in Xenium Explorer?

Secondary question is how to translate physical coordinates into spatialdata's global coordinate system? Am I supposed to get transformation and then apply transformation to a single or a couple points to get min and max for cropping above? I can make a separate issue with this question, if necessary.

Best,
Vasily

Inizia dalla chiamata a render_images su morphology_focus e segui come i suoi argomenti relativi ai colori influenzano l’immagine tracciata. Confronta i colori renderizzati con i valori di riferimento di Xenium Explorer e verifica separatamente come bounding_box_query utilizza il sistema di coordinate globale per le coordinate fisiche fornite. Il lavoro è completato quando il comportamento dei colori e la conversione delle coordinate sono documentati o corretti con un esempio riproducibile.