Question

我想在bokeh中显示相关热图。我正在初始化一个空图：

p2 = figure(x_range=[], y_range=[], plot_width=1200,plot_height=1200)

选择并加载数据源后（单击按钮），我会这样做

p2.x_range.factors = corr["TABLE1"].unique().tolist()
p2.y_range.factors = corr["TABLE2"].unique().tolist()
source_heat_map.data = corr.to_dict('list')
p2.rect(
        x="TABLE1",
        y="TABLE2",
        width=1,
        height=1,
        source=source_heat_map,
        line_color=None,
        fill_color=bokeh_transform('value', mapper)
    )

出现热图，但是x_range.factors和y_range.factors保持空白。

如果我使用以下命令初始化图p2：

test = pd.read_csv("Heatmap.csv")
source_heat_map.data = test.to_dict('list')
name_a = test.columns[0]
name_b = test.columns[1]
p2 = figure(x_range=b, y_range=a, plot_width=1200,plot_height=1200)
p2.rect(
        x=name_b,
        y=name_a,
        width=1,
        height=1,
        source=source_heat_map,
        line_color=None,
        fill_color=bokeh_transform('value', mapper)
    )

，然后选择另一个数据源，然后单击按钮，它会起作用，并且x_range.factors和y_range.factors会更新。我该怎么做才能更新空的FactorRanges？

编辑：

这是一个最低限度的工作示例。如果将if True:更改为if False:并将p2 = figure(x_range=[], y_range=[], plot_width=1200,plot_height=1200)的x_range.factors和y_range.factors初始化为空列表，它将不再起作用。

from bokeh.io import curdoc
from bokeh.layouts import column,row, widgetbox, Spacer
from bokeh.models import ColumnDataSource, Paragraph, LinearColorMapper, ColorBar, BasicTicker, TapTool, CustomJS,BoxSelectTool, Rect, FactorRange
from bokeh.models.widgets import Slider, TextInput, Div, Button, Dropdown, TableColumn, DataTable, CheckboxButtonGroup
from bokeh.models.annotations import Title
from bokeh.plotting import figure,show
from bokeh.client import push_session

from bokeh.transform import transform as bokeh_transform
from bokeh import events

from math import pi
import pandas as pd


def compute_corr():
    global matches
    corr = pd.DataFrame.from_dict({'TABLE1': {0: 'G', 1: 'L', 2: 'M', 3: 'N', 4: 'H', 5: 'T'}, 'value': {0: 1.0, 1: 0.5493847383480001, 2: 0.14649061756799993, 3: 0.39124820471999999, 4: 0.325265107675299999, 5: 0.668616128290099998}, 'TABLE2': {0: 'G', 1: 'G', 2: 'G', 3: 'G', 4: 'G', 5: 'G'}})

    p2.x_range.factors = corr["TABLE2"].unique().tolist()
    p2.y_range.factors = corr["TABLE1"].unique().tolist()
    source_heat_map.data = corr.to_dict('list')
    p2.rect(
            x="TABLE2",
            y="TABLE1",
            width=1,
            height=1,
            source=source_heat_map,
            line_color=None,
            fill_color=bokeh_transform('value', mapper)
        )

# You can use your own palette here
colors = ['#d7191c', '#fdae61', '#ffffbf', '#a6d96a', '#1a9641']


source_heat_map = ColumnDataSource(data = {})


b1 = Button(label="create", width=200, height=100)
b1.on_click(compute_corr)

mapper = LinearColorMapper(
        palette=colors, low=0, high=1)

if True:
    test = pd.DataFrame.from_dict({'TABLE1': {0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E', 5: 'F'}, 'value': {0: 1.0, 1: 0.8493847383480001, 2: 0.84649061756799993, 3: 0.89124820471999999, 4: 0.15265107675299999, 5: 0.068616128290099998}, 'TABLE2': {0: 'A', 1: 'A', 2: 'A', 3: 'A', 4: 'A', 5: 'A'}})
    source_heat_map.data = test.to_dict('list')
    name_a = 'TABLE1'
    name_b = 'TABLE2'
    a = list(set(test["TABLE1"].values))
    b = list(set(test["TABLE2"].values))
    print a,b
    p2 = figure(x_range=b, y_range=a, plot_width=1200,plot_height=1200)
    p2.rect(
            x=name_b,
            y=name_a,
            width=1,
            height=1,
            source=source_heat_map,
            line_color=None,
            fill_color=bokeh_transform('value', mapper)
        )
else:
    p2 = figure(x_range=[], y_range=[], plot_width=1200,plot_height=1200)

color_bar = ColorBar(
            color_mapper=mapper,
            location=(0, 0),
            ticker=BasicTicker(desired_num_ticks=len(colors)))

p2.add_layout(color_bar, 'right')
p2.toolbar.logo = None
p2.toolbar_location = None
p2.xaxis.major_label_orientation = pi / 3

curdoc().add_root(row(b1,p2))
curdoc().title = "Correlations"

Answer 1

升级到Bokeh版本0.13.0可以解决此问题。

散景：更新矩形中的空FactorRange

1 个答案: