Question

从下拉列表中选择新值时，我在更新基础ColumnDataSource时遇到问题。在“ update_data”部分中，我正在更改绘图的基础ColumnDataSource的值。误差线在绘图上更新，但绘图数据不变。我简化了下面的代码。知道如何更新所有数据，而不仅仅是错误栏吗？

from bokeh.layouts import row, column
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Slider, TextInput
from bokeh.plotting import figure
from bokeh.io import output_file, show
from bokeh.models.widgets import Dropdown
import pandas as pd
import numpy as np
from bokeh.io import output_file, show, curdoc
from bokeh.layouts import row, column, widgetbox
from bokeh.models import (
    ColumnDataSource,
    HoverTool,
    LinearColorMapper,
    BasicTicker,
    PrintfTickFormatter,
    ColorBar,
    Legend,
    Whisker,
)
from bokeh.models.widgets import PreText, Select, RadioGroup, TextInput
from bokeh.plotting import figure
from bokeh.transform import dodge, factor_cmap
import bokeh.plotting
from bokeh.models import ColumnDataSource, CustomJS
from bokeh.models.widgets import Button
import io
import base64
import random
import statistics as stat
from bokeh.models.tickers import SingleIntervalTicker
from bokeh.plotting import figure, show




def sectionize(df, rows, cols):
    rowWise = df.stack()
    colWise = df.transpose().stack()
    rowData = []
    colData = []
    for x in rows:
        rowData.append(list(rowWise[x]))
    for x in range(1, (cols + 1)):
        colData.append(list(colWise[x]))
    print("sectionize has occured")
    return rowData, colData

def getLowerUpper(data):
    lower, upper = [], []
    for x in data:
        if x:
            mean = stat.mean(x)
            std = stat.stdev(x)
            lower.append(mean - std)
            upper.append(mean + std)
        else:
            lower.append(0)
            upper.append(0)
    return lower, upper

def sectionizePlot(source, source_error, type, base):
    print("sectionize plot created with typ: " + type)
    colors = []
    for x in range(0, len(base)):
        colors.append(getRandomColor())
    title = type + "-wise Intensity Distribution"
    p = figure(plot_width=600, plot_height=300, title=title)
    p.add_layout(
        Whisker(source=source_error, base="base", upper="upper", lower="lower"))
    for i, sec in enumerate(source.data['base']):
        p.circle(x=source_error.data["base"][i], y=sec, color=colors[i])
    p.xaxis.axis_label = type
    p.yaxis.axis_label = "Intensity"
    if (type.split()[-1] == "Row"):
        print("hit a row")
        conv = dict(enumerate(list("nABCDEFGHIJKLMNOP")))
        conv.pop(0)
        p.xaxis.major_label_overrides = conv
    p.xaxis.ticker = SingleIntervalTicker(interval=1)
    print("sectionizePlot changed")
    return p

def getRandomColor():
    colors = ['aqua', 'aquamarine', 'black', 'blue', 'blueviolet', 'brown', 'burlywood', 'cadetblue', 'chartreuse', 'chocolate',
         'coral', 'cornflowerblue', 'crimson', 'cyan', 'darkblue', 'darkcyan', 'darkgoldenrod', 'darkgray', 'darkgreen',
         'darkgrey', 'darkkhaki', 'darkmagenta', 'darkolivegreen', 'darkorange', 'darkorchid', 'darkred', 'darksalmon',
         'darkseagreen', 'darkslateblue', 'darkslategray', 'darkslategrey', 'darkturquoise', 'darkviolet', 'deeppink',
         'deepskyblue', 'dimgray', 'dimgrey', 'dodgerblue', 'firebrick', 'forestgreen', 'fuchsia', 'gold', 'goldenrod',
         'gray', 'green', 'greenyellow', 'grey', 'hotpink', 'indianred', 'indigo', 'khaki', 'lavender', 'lawngreen', 'lime',
         'limegreen', 'magenta', 'maroon', 'mediumaquamarine', 'mediumblue', 'mediumorchid', 'mediumpurple',
         'mediumseagreen', 'mediumslateblue', 'mediumspringgreen', 'mediumturquoise', 'mediumvioletred', 'midnightblue',
         'navy', 'olive', 'olivedrab', 'orange', 'orangered', 'orchid', 'peachpuff', 'peru', 'pink', 'plum', 'powderblue',
         'purple', 'red', 'rosybrown', 'royalblue', 'saddlebrown', 'salmon', 'sandybrown', 'seagreen', 'sienna', 'silver',
         'skyblue', 'slateblue', 'slategray', 'slategrey', 'springgreen', 'steelblue', 'tan', 'teal', 'thistle', 'tomato',
              'turquoise', 'violet', 'yellow', 'yellowgreen']
    return colors[random.randint(0, 101)]


colBase = list(range(1, 3))
colData = [[1,2,3,4,5,6], [7, 8, 9, 10, 11, 12]]
colData_lower, colData_upper = getLowerUpper(colData)
colSectTotSource = ColumnDataSource(data=dict(base=[]))
colSectTotSource_error = ColumnDataSource(data=dict(base=[], lower=[], upper=[]))
colSectTotSource.data = dict(base=colData)
colSectTotSource_error.data = dict(base=colBase, lower=colData_lower, upper=colData_upper)

menu = [("A", "A"), ("B", "B")]
dropdown = Dropdown(label="Dropdown button", button_type="warning", menu=menu)
colPlot = sectionizePlot(colSectTotSource, colSectTotSource_error, "Column", colBase)

def update_data(attrname, old, new):
    d = dropdown.value
    if(d == "B"):
        colData = [[11,12,13,14,15,16], [17,18,19,20,21,22]]
    else:
        colData = [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]]

    colData_lower, colData_upper = getLowerUpper(colData)
    #colSectTotSource = ColumnDataSource(data=dict(base=[]))
    colSectTotSource.data = dict(base=colData)
    colSectTotSource_error.data = dict(base=colBase, lower=colData_lower, upper=colData_upper)

for w in [dropdown]:
    w.on_change('value', update_data)

inputs = column(dropdown)
curdoc().add_root(row(inputs, colPlot, width=800))

Answer 1

圈子没有更新，因为您实际上并未将呼叫配置为使用来源：

p.circle(x=source_error.data["base"][i], y=sec, color=colors[i])

当您像上面所做的那样以x，y等形式传递实际的列表/数组时，Bokeh会创建一个新的CDS在内部使用。如果希望字形利用传入的源，则实际上必须将其传递，并且坐标应仅引用该源的列名：

my_source = ColumnDataSource(data=dict(foo=[...], bar=[...]))
p.circle(x="foo", y="bar", source=my_source)

此外，CDS中的数据格式对于这种用法不正确：

{'base': [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]]}

顾名思义，ColumnDataSource包含列。每列的值必须是一个一维数组或列表，而不是这里的列表列表（少数“多”字形可以接受此值，但圆形不能接受，等等）。即您将需要为每个圆圈创建一个单独的列，而不是为每个圆圈添加一个带有“子列表”的列。

散景-下拉菜单更改后无法更新ColumnDataSource

1 个答案: