如何在python bokeh中创建滑块播放按钮

Question

我已经从这里有了一个只是静态的滑块代码，必须手动滑动它，但是我想要一个上面带有播放按钮并且可以通过单击播放的东西。

这是我尝试具有播放和暂停按钮的操作， 这是获得此代码的来源

def animate_update():
    year = slider.value + 1
    if year > years[-1]:
        year = years[0]
    slider.value = year


def slider_update(attrname, old, new):
    year = slider.value
    label.text = str(year)
    source.data = data[year]

slider = Slider(start=years[0], end=years[-1], value=years[0], step=1, title="Year")
slider.on_change('value', slider_update)


def animate():
    if button.label == '► Play':
        button.label = '❚❚ Pause'
        curdoc().add_periodic_callback(animate_update, 200)
    else:
        button.label = '► Play'
        curdoc().remove_periodic_callback(animate_update)

button = Button(label='► Play', width=60)
button.on_click(animate)

但是当使用它给我错误

NameError                                 Traceback (most recent call last)
<ipython-input-15-f62f961b8000> in <module>()
     32         curdoc().remove_periodic_callback(animate_update)
     33 
---> 34 button = Button(label='► Play', width=60)
     35 button.on_click(animate)

NameError: name 'Button' is not defined

PS-我正在使用jupyter笔记本。

我在做什么错了。

任何帮助将非常感激。

谢谢

DOMNICK

Answer 1

这是带有本地Bokeh Server的滑块的播放按钮的示例（通过结合这两个链接： here和here ）。

在此之前，您需要安装bokeh 。

然后，您编写并运行以下脚本：

 from bokeh.server.server import Server
 from bokeh.application import Application
 from bokeh.application.handlers.function import FunctionHandler
 from bokeh.plotting import figure, ColumnDataSource
 from bokeh.core.properties import field
 from bokeh.models import (HoverTool, SingleIntervalTicker,
                           Slider, Button, Label, CategoricalColorMapper)
 from bokeh.palettes import Spectral6 
 import numpy as np
 import pandas as pd

def process_data():
    from bokeh.sampledata.gapminder import fertility, life_expectancy, population, regions

    # Make the column names ints not strings for handling
    columns = list(fertility.columns)
    years = list(range(int(columns[0]), int(columns[-1])))
    rename_dict = dict(zip(columns, years))

    fertility = fertility.rename(columns=rename_dict)
    life_expectancy = life_expectancy.rename(columns=rename_dict)
    population = population.rename(columns=rename_dict)
    regions = regions.rename(columns=rename_dict)

    regions_list = list(regions.Group.unique())

    # Turn population into bubble sizes. Use min_size and factor to tweak.
    scale_factor = 200
    population_size = np.sqrt(population / np.pi) / scale_factor
    min_size = 3
    population_size = population_size.where(population_size >= min_size).fillna(min_size)

    return fertility, life_expectancy, population_size, regions, years, regions_list


def make_document(doc):

    fertility_df, life_expectancy_df, population_df_size, regions_df, years, regions_list = process_data()

    df = pd.concat({'fertility': fertility_df,
                'life': life_expectancy_df,
                'population': population_df_size},
               axis=1)    
    data = {}

    regions_df.rename({'Group':'region'}, axis='columns', inplace=True)
    for year in years:
        df_year = df.iloc[:,df.columns.get_level_values(1)==year]
        df_year.columns = df_year.columns.droplevel(1)
        data[year] = df_year.join(regions_df.region).reset_index().to_dict('series')

    source = ColumnDataSource(data=data[years[0]])

    plot = figure(x_range=(1, 9), y_range=(20, 100), title='Gapminder Data', plot_height=300)
    plot.xaxis.ticker = SingleIntervalTicker(interval=1)
    plot.xaxis.axis_label = "Children per woman (total fertility)"
    plot.yaxis.ticker = SingleIntervalTicker(interval=20)
    plot.yaxis.axis_label = "Life expectancy at birth (years)"

    label = Label(x=1.1, y=18, text=str(years[0]), text_font_size='70pt', text_color='#eeeeee')
    plot.add_layout(label)

    color_mapper = CategoricalColorMapper(palette=Spectral6, factors=regions_list)
    plot.circle(
      x='fertility',
      y='life',
      size='population',
      source=source,
      fill_color={'field': 'region', 'transform': color_mapper},
      fill_alpha=0.8,
      line_color='#7c7e71',
      line_width=0.5,
      line_alpha=0.5,
      legend=field('region'),
    )
    plot.add_tools(HoverTool(tooltips="@Country", show_arrow=False,  point_policy='follow_mouse'))

    def animate_update():
        year = slider.value + 1
        if year > years[-1]:
            year = years[0]
        slider.value = year    

    def slider_update(attrname, old, new):
        year = slider.value
        label.text = str(year)
        source.data = data[year]

    slider = Slider(start=years[0], end=years[-1], value=years[0], step=1, title="Year")
    slider.on_change('value', slider_update)

    callback_id = None

    def animate():
        global callback_id
        if button.label == '► Play':
            button.label = '❚❚ Pause'
            callback_id = doc.add_periodic_callback(animate_update, 200)
        else:
            button.label = '► Play'
            doc.remove_periodic_callback(callback_id)

    button = Button(label='► Play', width=60)
    button.on_click(animate)    

    doc.add_root(button)
    doc.add_root(slider)
    doc.add_root(plot)

apps = {'/': Application(FunctionHandler(make_document))}

server = Server(apps, port=5000)
server.start()

然后，写一个导航器： http：// localhost：5000 /