如何对齐数据点和刻度标签？

Question

我想画一个带圆圈的网格并标记每一行和每一列。虽然我可以绘制数据点，但我无法正确对齐数据点及其各自的标签，所以绘图如下所示：

如何正确完成，使刻度标签与数据点对齐？

代码：

import numpy as np
import itertools
from bokeh.models import Circle, ColumnDataSource
from bokeh.plotting import figure, show

space = 0.5
row_ind = np.arange(0, 2, space)
col_ind = np.arange(0, 1.5, space)

data_points = list(itertools.product(row_ind, col_ind))

rows = [dp[0] for dp in data_points] 
cols = [dp[1] for dp in data_points]
size = 10
sizes = [size] * len(data_points)
source = ColumnDataSource(dict(columns=cols, rows=rows, size=sizes))

plot = figure(
    plot_width=400,
    plot_height=300,
    x_range=["1", "2", "3"],
    y_range=list("ABCD")
)
plot.circle(
    x="columns",
    y="rows",
    size="size",
    line_color="black",
    fill_color="white",
    line_width=2,
    source=source
)
show(plot)

Answer 1

您应该使用散景中的默认范围，然后使用plot.xaxis.ticker、plot.yaxis.ticker 和plot.yaxis.major_label_overrides 更改刻度。

完整示例

import numpy as np
import itertools
from bokeh.models import Circle, ColumnDataSource
from bokeh.plotting import figure, show, output_notebook
output_notebook()
row_ind = np.arange(0, 2, 0.5)
col_ind = np.arange(0, 1.5, 0.5)

data_points = list(itertools.product(row_ind, col_ind))
rows = [dp[0] for dp in data_points] 
cols = [dp[1] for dp in data_points]
sizes = [10] * len(data_points)

source = ColumnDataSource(dict(columns=cols, rows=rows, size=sizes))
plot = figure(
    plot_width=400,
    plot_height=300
)
plot.circle(
    x="columns",
    y="rows",
    size="size",
    line_color="black",
    fill_color="white",
    line_width=2,
    source=source
)
plot.xaxis.ticker, plot.yaxis.ticker = col_ind, row_ind
plot.yaxis.major_label_overrides = dict(zip(
    [int(i) if i.is_integer() else i for i in row_ind], 
    list('ABCD'))
   )
show(plot)

输出