plotly / plotly/plotly.R

Using opacityscale with surface results in ordering by addition order, not depth

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R
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Descrizione

Hi, been using plotly with R for a while now and really loving it - thanks for assembling such a phenomenal program! I'd like to report a bug found while plotting multiple surface objects, which causes them to layer in the order they're added (using %>%) rather than the "depth" at which they should really render in the figure. See below for code and examples.

The "opacityscale" function is a new one from the dev branch (and I don't think problems with it have been reported on here before) so this question may be a better fit for https://github.com/plotly/plotly.js instead, where there's a bit more discussion about it and the original implementation, but I don't know JavaScript and can't provide a reprex there.

This is great:

image

This is not great (same figure rotated to look from below):

image

It only seems to show up if the opacityscale parameter is added, even if the opacity is set to 1 for all values.

Renders fine:
# devtools::install_github("ropensci/plotly")
library(plotly)
df <- data.frame(x=1:10, y=1:10)
surface_data <- matrix(1:100, nrow=10, ncol=10)
z_mat <- matrix(0, nrow = 10, ncol = 10)

plot_ly(df, x=~x, y=~y) %>%
  add_trace(type="surface",
            z=z_mat,
            surfacecolor=surface_data,
            colorscale=list(list(0, 1), list("red", "orange"))) %>%
  add_trace(type = "surface",
            z = z_mat+2,
            surfacecolor=surface_data,
            colorscale = list(list(0, 1), list("yellow", "green"))) %>%
  add_trace(type = "surface",
            z = z_mat+1,
            surfacecolor=surface_data,
            colorscale = list(list(0, 1), list("blue", "purple"))) 

image

Does not render fine:
plot_ly(df, x=~x, y=~y) %>%
  add_trace(type="surface",
            z=z_mat,
            surfacecolor=surface_data,
            opacityscale=list(list(0, 1), list(1, 1)),
            colorscale=list(list(0, 1), list("red", "orange"))) %>%
  add_trace(type = "surface",
            z = z_mat+1,
            surfacecolor=surface_data,
            opacityscale=list(list(0, 1), list(1, 1)),
            colorscale = list(list(0, 1), list("yellow", "green"))) %>%
  add_trace(type = "surface",
            z = z_mat+2,
            surfacecolor=surface_data,
            opacityscale=list(list(0, 1), list(1, 1)),
            colorscale = list(list(0, 1), list("blue", "purple")))

image

I've had a little trouble figuring out exactly how to best pass the opacityscale argument in R but I believe these settings should disable the opacity completely by setting every value between 0 and 1 to an opacity between 1 and 1 (i.e., always 1 and fully opaque).

Additionally, the surface that renders on "top" is the one that's added last in the piping order. If we alter the above code a little bit to render the purple/blue surface before the yellow/green one, we get some more interesting renders:

plot_ly(df, x=~x, y=~y) %>%
  add_trace(type="surface",
            z=z_mat,
            surfacecolor=surface_data,
            opacityscale=list(list(0, 1), list(1, 1)),
            colorscale=list(list(0, 1), list("red", "orange"))) %>%
  add_trace(type = "surface",
            z = z_mat+2,
            surfacecolor=surface_data,
            opacityscale=list(list(0, 1), list(1, 1)),
            colorscale = list(list(0, 1), list("blue", "purple"))) %>%
  add_trace(type = "surface",
            z = z_mat+1,
            surfacecolor=surface_data,
            opacityscale=list(list(0, 1), list(1, 1)),
            colorscale = list(list(0, 1), list("yellow", "green")))

image

image

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Direzione di ricerca

Riproduci il problema con gli esempi R forniti usando plot_ly(), add_trace(), trace surface e opacityscale, quindi confronta il rendering con e senza opacityscale. Segui il comportamento attraverso l’implementazione di plotly.js citata nell’issue 4331; il lavoro è completato quando l’ordinamento delle superfici segue la profondità invece dell’ordine di aggiunta delle trace quando è presente opacityscale.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
javascript, r
Ambito
data-visualization
Tipo di issue
Bug
Difficoltà
4/5
Tempo stimato
3-5 giorni
Stato di attività
Ferma
Chiarezza
Abbastanza chiara
Idoneità per principianti
30/100

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