散景等效于Matplotlib scatter_matrix [英] Bokeh equivalent of Matplotlib scatter_matrix

问题描述

在Bokeh中，是否有比下面的代码更好的方法来再现matplotlibs scatter_matrix(将所有数据绘制成所有数据):

Is there a better way of reproducing matplotlibs scatter_matrix (plot all data against all data) in Bokeh than the code below:

    defaults.width = 100
    defaults.height = 100
    scatter_plots = []
    y_max = len(dataset.columns)-1
    for i, y_col in enumerate(dataset):
        for j, x_col in enumerate(dataset):
            df = pd.DataFrame({x_col: dataset[x_col].tolist(), y_col: dataset[y_col].tolist()})
            p = Scatter(df, x=x_col, y=y_col)
            if j > 0:
                p.yaxis.axis_label = ""
                p.yaxis.visible = False
            if i < y_max:
                p.xaxis.axis_label = ""
                p.xaxis.visible = False
            scatter_plots.append(p)
    grid = gridplot(scatter_plots, ncols = len(dataset.columns))
    show(grid)

特别是，我希望能够缩放和平移整个网格图作为一个实体，而不是缩放/平移鼠标悬停的子图.

In particular I would like to be able to zoom and pan the entire grid of plots as a single entity rather than zoom/pan the subplot the mouse is hovering over.

推荐答案

通常，要链接平移/缩放，您需要共享要在图之间链接的范围.《用户指南》中对此进行了说明:

In general, to have linked panning/zooming, you share the ranges that you want to be linked between plots. This is described here in the Users Guide:

https://docs.bokeh.org/en/latest/docs/user_guide/interaction/linking.html

您还可以查看此链接的SPLOM示例:

You can also check out this linked SPLOM example:

https://github.com/bokeh/bokeh/blob/master/examples/models/iris_splom.py

该示例冗长/冗长，因为它使用了低级的 bokeh.models API.重要的部分是在创建的任何绘图上重新使用范围 xdr 和 ydr .

That example is longer/more verbose because it uses the low level bokeh.models API. The important part is where it re-uses the ranges xdr and ydr on ever plot that gets created.

在您的特定情况下，由于高级图表不预先接受范围参数(IIRC)，因此我认为您必须在事后"修复图表，因此可能类似:

In your particular case, since high level charts don't accept range parameters up front (IIRC), I think you'll have to fix up the charts "after the fact", so maybe something like:

xr = scatter_plots[0].x_range
yr = scatter_plots[0].y_range
for p in scatter_plots:
    p.x_range = xr
    p.y_range = yr

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