Jupyter Bokeh：字形渲染器中不存在的列名

Question

我有一个GlyphRenderer其data_source.data是

{'index': [0, 1, 2, 3, 4, 5, 6, 7],
 'color': ['#3288bd', '#66c2a5', '#abdda4', '#e6f598', '#fee08b', '#fdae61', '#f46d43', '#d53e4f']}

渲染器的字形是

Oval(height=0.1, width=0.2, fill_color="color")

渲染时，我看到

E-1001 (BAD_COLUMN_NAME): Glyph refers to nonexistent column name: color [renderer: GlyphRenderer(id='1d1031f5-6ee3-4744-a0f7-22309798e313', ...)]

我显然缺少了一些东西，但是从已发布的示例中可以明显看出这一点。我在调试器中验证了data_source.column_namesjust ['index']; 我不明白的是，为什么该'color'列没有出现在数据源的column_names，或者为什么Bokeh发出此警告（图形似乎正确呈现）。

完整的资源可在https://pastebin.com/HXAEEujP获得

Answer 1

通常最好在构造对象时提供所有相关的参数，而不要在对象创建后对其进行变异。对于Bokeh尤其如此-在许多情况下，它会根据传递给的参数做一些额外的工作__init__。

看一下这段代码：

import math

from bokeh.io import show
from bokeh.models import GraphRenderer, StaticLayoutProvider, Oval, GlyphRenderer, ColumnDataSource, MultiLine
from bokeh.palettes import Spectral8
from bokeh.plotting import figure

N = 8
node_indices = list(range(N))

plot = figure(title="Graph Layout Demonstration", x_range=(-1.1, 1.1), y_range=(-1.1, 1.1),
              plot_width=250, plot_height=250,
              tools="", toolbar_location=None)

node_ds = ColumnDataSource(data=dict(index=node_indices,
                                     color=Spectral8),
                           name="Node Renderer")
edge_ds = ColumnDataSource(data=dict(start=[0] * N,
                                     end=node_indices),
                           name="Edge Renderer")
### start of layout code
circ = [i * 2 * math.pi / 8 for i in node_indices]
x = [math.cos(i) for i in circ]
y = [math.sin(i) for i in circ]
graph_layout = dict(zip(node_indices, zip(x, y)))
graph = GraphRenderer(node_renderer=GlyphRenderer(glyph=Oval(height=0.1, width=0.2, fill_color="color"),
                                                  data_source=node_ds),
                      edge_renderer=GlyphRenderer(glyph=MultiLine(),
                                                  data_source=edge_ds),
                      layout_provider=StaticLayoutProvider(graph_layout=graph_layout))

plot.renderers.append(graph)

show(plot)