Honor cmap for numeric scatter colors#616
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cvanelteren merged 5 commits intomainfrom Mar 17, 2026
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Treat 1D numeric scatter c arrays matching the point count as scalar data for colormapping instead of literal RGBA colors. This preserves Nx3/Nx4 explicit color support, keeps the Matplotlib-compatible cmap behavior for numeric values, and adds a regression test for issue #615.
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Annotate the scatter-specific color parsing helpers touched by the cmap compatibility fix so the intent of the new parameters and return values is explicit without broadening the typing changes beyond the affected code path.
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Reminder: review this later today. |
Document the scatter color ambiguity resolved by the PR: one-dimensional numeric arrays matching the point count are treated as scalar colormap data, while explicit RGB(A) colors should be passed as N x 3 / N x 4 arrays or via color=.
Replace the loose Any annotations on the scatter color parsing helpers with explicit data and color input aliases based on ArrayLike and color tuples. This keeps the typing aligned with the actual ambiguity being resolved by the cmap fix while staying practical for plotting inputs.
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This fixes a Matplotlib-compatibility bug in
ax.scatter(...)whencis a 1D numeric array. UltraPlot was treating short numeric sequences like[0.1, 0.2, 0.3, 0.4]as literal colors too early, which causedcmapto be dropped as unused instead of applying colormapping. The fix keeps explicitN x 3/N x 4RGB(A) handling intact, but treats 1D numeric arrays matching the point count as scalar data for colormapping, which is the behavior users expect from Matplotlib. A regression test covering the reportedc=[...], cmap="turbo"case is included.Closes #615.