scverse / scverse/spatialdata-plot

Additive RGB color blending for render_shapes / render_labels (and render_points)

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まだ誰も着手していません。

主要言語
Python
スター
86
フォーク
21
平均マージ
14時間 50分
マージ済み PR(30日)
3

説明

Motivation

Spun out from #321 (the thread there mixes two unrelated asks — this issue is the second one, originally raised by @brainfo).

`render_images` already supports multi-channel additive compositing: you pass several channels with per-channel colormaps and they blend into a single RGB image, mirroring napari / ImageJ / FIJI for fluorescence microscopy. The same idiom is useful for sequencing-based spatial data, where a user wants to visualize co-expression of 2–3 genes per cell/spot/region on a single axis — red for gene A, green for gene B, blue for gene C, additively blended so co-expressing cells appear yellow/cyan/white.

Today this requires manual post-processing (the user in #321 mentions doing it in Illustrator).

Proposed API

Mirror the existing `render_images` multi-channel convention by letting `color` accept a list of obs/var columns on `render_shapes`, `render_labels`, and `render_points`:

```python
sdata.pl.render_shapes(
color=["Sox2", "Pax6", "Tbr2"],
palette=["red", "green", "blue"], # one color per channel
channels_as_legend=True,
).pl.show()

sdata.pl.render_labels(
color=["Sox2", "Pax6"],
palette=["red", "green"],
).pl.show()

sdata.pl.render_points(
color=["Sox2", "Pax6"],
).pl.show()
```

Output: a single axis (no multi-panel grid). Each shape / label / point gets one composited color derived from its per-column values blended via per-channel colormaps, identical in spirit to the additive multi-channel path already in `render_images`.

Why this is feasible

  • The additive-blending machinery already exists in `pl/render.py` for the multi-channel image path (see `render_images` branches 2A/2B/2C). The same per-channel cmap + sum + clip logic applies.
  • Single-axis output sidesteps the hierarchy-of-axes complexity that made multi-panel `color=[...]` (the other ask from #321) undesirable.
  • `channels_as_legend` already exists for `render_images`; can extend.

Scope

  • In scope: 2–3-column color lists on `render_shapes`, `render_labels`, `render_points`. Per-channel `cmap` or `palette`. Additive blend on a single axis.
  • Out of scope (defer or decline):
    • Multi-panel grids (`sc.pl.umap`-style) — already declined in #321.
    • Arbitrary blend modes beyond additive — start with the existing `render_images` semantics.
    • PCA-based or learned color reductions for >3 channels.

Edge cases to design for

  • Length mismatch between `color` list and `palette` list.
  • Mixing categorical and continuous columns in the same `color` list (probably reject with a clear error).
  • NaN handling per column (skip vs zero vs error — likely error, matching the recent `render_images` NaN rejection).
  • Per-column `norm` / `vmin` / `vmax` — accept a list, parallel to the per-channel `norm` already supported on `render_images`.
  • `groups` semantics when `color` is a list — likely ignored with a warning.

Relation to #321

#321 conflates two asks under "plotting multiple genes":

  1. Multi-panel grid for several genes — declined; possibly hosted in a future Squidpy 2.0 wrapper.
  2. Single-axis additive blend for co-expression visualization — this issue.

The documentation sub-tasks in #321 (`save`, `ncols` on `pl.show()`) are already resolved.

コントリビューションガイド

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はじめの一歩

  1. issue を最後まで読み、次にプロジェクトのコントリビューションガイドを読みます。
  2. 着手することを issue にコメントします — 二人が同じ作業をするのを防げます。
  3. リポジトリをフォークし、ブランチを切って変更します。
  4. issue 番号を参照したプルリクエストを送ります。

調査の方向性

pl/render.py で既存のマルチチャネルの render_images ブランチ 2A/2B/2C を読むことから始め、次に render_shapes、render_labels、render_points を追跡します。完了条件は、1 つの軸上で 2~3 個の連続値カラムをチャネルごとの色として加算ブレンディングでサポートし、指定されたパレット長、混合型、NaN、正規化、groups の動作を定義することです。

索引モデルが issue の本文から書いたものです。

評価

技術スタック
python
領域
data-visualization
issue の種類
機能追加
難易度
5/5
見積もり時間
1週間以上
活発さ
静か
明瞭さ
おおむね明確
初心者へのやさしさ
45/100

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