Jupyter Bokeh:字形渲染器中不存在的列名

时间:2018-03-19 08:30:19

标签: python jupyter bokeh

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', ...)]

我显然遗漏了一些东西,但这几乎从发表的例子中解脱了。我在调试器中验证data_source.column_names只是['index'];我不明白为什么'color'列没有出现在数据源的column_names中,或者为什么Bokeh会产生此警告(图表看起来是正确的)呈现)。

完整的来源位于https://pastebin.com/HXAEEujP

1 个答案:

答案 0 :(得分:3)

在构造对象时提供所有相关参数通常更好,而不是在已经创建对象之后改变对象。对于Bokeh来说尤其如此 - 在许多情况下,它会根据传递给__init__的参数做一些额外的工作。

看看这个版本的代码:

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)