Highlight of trace adds duplicate legend item.
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- 主要语言
- R
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描述
The current implementation for a selection highlighting adds duplicate legend entries.
For example in the below screenshot I clicked on trace "Alpha" and a new legend item "Alpha" got added while the existing "Alpha" legend is now dimmed but is still present. Resulting in 2 "Alpha" entries.
The core problem is that the current javascript code handling crosstalk selection, simply adds a duplicate selection traces here and dims all other traces here.
Since the original 'Alpha' trace was not removed and only dimmed and since a new trace also named "Alpha" was added to the legend. It results in the above legend.
Would it be possible to update the javascript logic to just dim the non-selected traces and update the selected trace to the desired highlight color (and other aspects set by the user). This would the have the desired effect on the legend.
Or to set the selected trace with showLegend=FALSE in the restyle for all the traces that got highlighted?
Edit it is not so easy as first thought:
I guess where my above described solution fails is when the selection is only a subset the trace data and only partially covers it. In that case the original legend entry would still need to be visible.
However, in theory it is possible to detect at creation time of the plot if the crosstalk key selection is equal to the legend entries. Eg. if the crosstalk key and the aesthetic property for the legend are equal.
That said this detection would then fail if one constructs a plotly object by manually adding traces. Or if the plotly graph has other traces added from a different dataset.
So to achieve what we want, we somehow need to determine if selection data fully covers the trace data. Not sure how we could smartly do it without having and extreme impact on the performance.
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调研方向
从 inst/htmlwidgets/plotly.js 中第 733 行和第 815 行附近的 crosstalk 选择逻辑开始。重现重复的“Alpha”图例条目,然后跟踪已选择和未选择的 trace 是如何被添加或调暗的,包括 issue 中描述的部分选择情况。当高亮不会创建重复的图例条目,并且在选择只覆盖 trace 的一部分时保留原始图例,就算完成。
由索引模型根据 Issue 内容生成。
评估
- 技术栈
- javascript, r
- 领域
- data-visualization, frontend
- Issue 类型
- 缺陷
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 活跃度
- 停滞
- 描述清晰度
- 基本清楚
- 新手友好度
- 25/100