Plotly：对多个 CONTOUR 图使用一个颜色条

Question

我希望我的等高线图网格指的是同一个颜色条，但我得到了四个堆叠在一起的颜色条。我怎样才能只有一个颜色条，其数值引用所有图中的数据？或者，换句话说，我的绘图的颜色如何引用相同的颜色条？

这里是测试代码：

import plotly.graph_objects as go
from plotly.subplots import make_subplots

z1 =   [[2, 4, 7, 12, 13, 14, 15, 16],
        [3, 1, 6, 11, 12, 13, 16, 17],
        [4, 2, 7, 7, 11, 14, 17, 18],
        [5, 3, 8, 8, 13, 15, 18, 19],
        [7, 4, 10, 9, 16, 18, 20, 19],
        [9, 10, 5, 27, 23, 21, 21, 21],
        [11, 14, 17, 26, 25, 24, 23, 22]]

z2 =   [[20, 44, 7, 120, 1, 1, 5, 16],
         [3, 10, 6, 110, 12, 135, 162, 17],
         [4, 2, 77, 77, 11, 14, 172, 18],
         [54, 34, 8, 8, 13, 1, 1, 19],
         [7, 4, 10, 96, 16, 18, 20, 19],
         [9, 10, 55, 27, 2, 21, 2, 2],
         [11, 1, 17, 26, 2, 24, 23, 22]]

z3 =   [[205, 44, 7, 120, 1, 1, 5, 16],
         [3, 10, 6, 110, 12, 135, 162, 17],
         [4, 2, 77, 77, 11, 144, 172, 18],
         [54, 34, 8, 8, 13, 1, 1, 19],
         [7, 42, 10, 96, 16, 18, 20, 19],
         [9, 10, 55, 27, 2, 25, 2, 2],
         [11, 13, 17, 26, 2, 24, 23, 22]]

z4 =   [[203, 44, 7, 120, 1, 1, 5, 16],
         [3, 10, 6, 110, 126, 135, 162, 17],
         [4, 2, 77, 7, 11, 144, 172, 18],
         [54, 34, 8, 8, 13, 1, 1, 19],
         [7, 42, 10, 96, 16, 18, 20, 19],
         [9, 10, 55, 27, 2, 253, 2, 2],
         [11, 1, 17, 26, 2, 24, 23, 22]]

figc1=make_subplots(rows=2, cols=2, shared_xaxes=True, shared_yaxes=True, vertical_spacing=0.05, horizontal_spacing=0.05)
figc1.add_trace(go.Contour(z=z1, coloraxis='coloraxis'), row=1, col=1)
figc1.add_trace(go.Contour(z=z2, coloraxis='coloraxis'), row=1, col=2)
figc1.add_trace(go.Contour(z=z3, coloraxis='coloraxis'), row=2, col=1)
figc1.add_trace(go.Contour(z=z4, coloraxis='coloraxis'), row=2, col=2)
figc1.update_layout(coloraxis=dict(colorscale='Viridis'), showlegend=False)
figc1.show()

如果你运行这段代码，你会看到颜色条显示为 z1 的最大值，它应该显示 z1、z2、z3 和 z4 的最大值。

Answer 1

您必须使用单个最小+最大范围配置单独的轮廓设置，并在所有轮廓中重复使用它。

maxval = max(max(sum(z1, [])), max(sum(z2, [])), max(sum(z3, [])), max(sum(z4, [])))

contours=dict(
    start=0,
    end=maxval,
)

figc1=make_subplots(rows=2, cols=2, shared_xaxes=True, shared_yaxes=True, vertical_spacing=0.05, horizontal_spacing=0.05)
figc1.add_trace(go.Contour(z=z1, contours=contours, coloraxis='coloraxis'), row=1, col=1)
figc1.add_trace(go.Contour(z=z2, contours=contours, coloraxis='coloraxis'), row=1, col=2)
figc1.add_trace(go.Contour(z=z3, contours=contours, coloraxis='coloraxis'), row=2, col=1)
figc1.add_trace(go.Contour(z=z4, contours=contours, coloraxis='coloraxis'), row=2, col=2)
figc1.update_layout(coloraxis=dict(colorscale='Viridis'), showlegend=False)
figc1.update_coloraxes(colorscale='Viridis')

figc1.show()

但请注意，各个等高线图看起来会有些不同，因为所有等高线图都将重新缩放到最大比例。

这是 Deepnote 中的 example of the code。

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