python - 如何将 Bokeh 中的 slider 值传递回 Python 代码

Question

我想将 slider 值(我用 Bokeh 构建的)传递回我的 Python 代码。该代码在绘图上生成 2 条线，并允许我更改其中一条线的斜率和截距。但是当我引入回调 javascript 将 slider 值作为 "ff" 传递回我的 Python 代码时，它失败了。
你能帮助我使用回调语法来将 slider 值返回到Python(例如，参见代码的最后一行) - 我确实想做一些比仅仅打印它更有趣的事情最终出来!
回调的错误消息是:

ValueError: expected an element of Dict(String, Instance(Model)), got {'my_dict': {'s': 0.5}}

我的代码是:-

from ipywidgets import interact  
import numpy as np  
from bokeh.io import push_notebook, show, output_notebook  
from bokeh.plotting import figure  
from bokeh.models import ColumnDataSource  
from bokeh.models.callbacks import CustomJS  
output_notebook()  
x = np.linspace(0, 20, 200) # create equally spaced points.  
s = 0.5 # slope.  
i = 3 # intercept.  
y = s * x + i # straight line.  
my_dict = dict(s=s) # need to create a dict object to hold what gets passed in the callback.  

callback = CustomJS(args=dict(my_dict=my_dict), code="""  
  var ff = cb_obj.value  
  my_dict.change.emit()  
""")  
// ff should be the slider value.  

p = figure(title="simple line example", plot_height=300, plot_width=600, y_range=(-20,20),  
           background_fill_color='#efefef')  
r = p.line(x, y, color="#8888cc", line_width=1.5, alpha=0.8) # 1st line. This line can be controlled by sliders.  
q = p.line(x, 2*x+1.2, color="#0088cc", line_width=1.9, alpha=0.2) # 2nd line.  
def update(w=s, a=i):  
    r.data_source.data['y'] = w * x + a  # allow updates for the line r.  
    push_notebook()  
show(p, notebook_handle=True)  
interact(update, w=(-10,10), a=(-12,12) )  
print(ff)  # Return what the slider value is. I want ff accessible back in my python code.

Answer 1

我没有 Jupyter Notebook，所以这两个示例是纯 Bokeh 应用程序，第一个使用 JS 回调，第二个使用 Python 回调(Bokeh v1.0.4)。

import numpy as np
from bokeh.plotting import figure, show
from bokeh.models import ColumnDataSource, Slider, CustomJS, Range1d
from bokeh.layouts import column

slider_slope = Slider(start = 0, end = 1, value = 0.5, step = 0.1)
slider_intercept = Slider(start = 0, end = 20, value = 10, step = 1)

slider_code = '''   i = slider_intercept.value
                    s = slider_slope.value
                    x = r.data_source.data['x'];
                    y = [];

                    for (index = 0; index < x.length; index ++)
                        y.push((s * x[index]) + i);

                    r.data_source.data['y'] = y
                    r.data_source.change.emit(); '''

s = slider_slope.value  # slope.
i = slider_intercept.value  # intercept.

x = np.linspace(-40, 20, 200)
y = [(s * xx + i) for xx in x]

p = figure(title = "simple line example", plot_height = 500, plot_width = 600, y_range = Range1d(start = -80, end = 40), background_fill_color = '#efefef')
r = p.line(x, y, color = "red", line_width = 1.5, alpha = 0.8)  # 1st line. This line can be controlled by sliders.
q = p.line(x, 2 * x + 1.2, color = "blue", line_width = 1.9, alpha = 0.2)  # 2nd line.

slider_callback = CustomJS(args = dict(slider_slope = slider_slope,
                                slider_intercept = slider_intercept,
                                r = r), code = slider_code)

slider_slope.callback = slider_callback
slider_intercept.callback = slider_callback

layout = column(p, slider_slope, slider_intercept)
show(layout, notebook_handle = True)

您可以使用 Python 回调轻松将其转换为 Bokeh 服务器应用程序:

import numpy as np
from bokeh.plotting import figure, show, curdoc
from bokeh.models import Slider, CustomJS
from bokeh.layouts import column

slider_slope = Slider(title = 'Slope', start = 0, end = 1, value = 0.5, step = 0.1)
slider_intercept = Slider(title = 'Intercept', start = 0, end = 20, value = 10, step = 1)

s = slider_slope.value  # slope.
i = slider_intercept.value  # intercept.

x = np.linspace(-40, 20, 200)
y = [(s * xx + i) for xx in x]

p = figure(title = "simple line example", plot_height = 500, plot_width = 600, y_range = Range1d(start = -80, end = 40), background_fill_color = '#efefef')
r = p.line(x, y, color = "red", line_width = 1.5, alpha = 0.8)  # 1st line. This line can be controlled by sliders.
q = p.line(x, 2 * x + 1.2, color = "blue", line_width = 1.9, alpha = 0.2)  # 2nd line.

def update(attr, old, new):
    s = slider_slope.value  # slope.
    i = slider_intercept.value  # intercept
    x = r.data_source.data['x'];
    y = []

    for value in x:
        y.append((s * value) + i)

    r.data_source.data['y'] = y

slider_slope.on_change('value', update)
slider_intercept.on_change('value', update)

layout = column(p, slider_slope, slider_intercept)
curdoc().add_root(layout)

结果: