feat: add a new wind rose chart operator#4224
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aglinxinyuan merged 4 commits intoapache:mainfrom Apr 17, 2026
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Ma77Ball
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Overall looks good. Look over the comments above and reply to them. After those are addressed, I can approve, and I think it's good to merge.
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@Ma77Ball After you approve this PR, please let me know so that I can review and approve it. |
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LGTM! @chenlica, please approve the workflows and merge if passed. |
Ma77Ball
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aglinxinyuan
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### What changes were proposed in this PR? <img width="3023" height="1714" alt="image" src="https://github.com/user-attachments/assets/dd6e94c0-70da-4c5d-bedb-27f78bab403b" /> This change adds a new wind rose chart operator, which visualizes how a magnitude (radial value) is distributed across different directions (angular values) and optionally grouped by a categorical variable (color). In a wind rose chart: - Each angular segment represents a direction (e.g., N, NE, E). - The length of each bar from the center represents the magnitude or frequency for that direction. - Color can optionally represent an additional grouping variable, such as strength or category. This visualization is useful for understanding directional distributions, identifying dominant directions, and comparing patterns across different groups or conditions. The operator takes in 2 or 3 inputs: the radial values, the angular values, and optionally a color/grouping variable. ### Any related issues, documentation, discussions? No related issues, documentation, or discussions. ### How was this PR tested? PR is tested with existing test cases. ### Was this PR authored or co-authored using generative AI tooling? No. --------- Co-authored-by: Xinyuan Lin <xinyual3@uci.edu>
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What changes were proposed in this PR?
This change adds a new wind rose chart operator, which visualizes how a magnitude (radial value) is distributed across different directions (angular values) and optionally grouped by a categorical variable (color).
In a wind rose chart:
This visualization is useful for understanding directional distributions, identifying dominant directions, and comparing patterns across different groups or conditions. The operator takes in 2 or 3 inputs: the radial values, the angular values, and optionally a color/grouping variable.
Any related issues, documentation, discussions?
No related issues, documentation, or discussions.
How was this PR tested?
PR is tested with existing test cases.
Was this PR authored or co-authored using generative AI tooling?
No.