使用 python 中的 "bokeh" 库更新绘图时拟合曲线

Question

我已经编写了一段代码来使用 bokeh 库可视化数据。我定义了一个简单的数据框 df 为：

      Y1     Y2  x_val
0   3.01   0.99      0
1   5.10   3.05      1
2   6.99   7.29      2
3   8.02  13.41      3
4  10.81  20.31      4

并使用以下代码，我可以交互式地绘制 x_val 与 Y1 和 Y2 的关系图。

import pandas as pd
from bokeh.io import curdoc
from bokeh.layouts import row, widgetbox
from bokeh.models import ColumnDataSource, Select
from bokeh.plotting import figure


dc = {'x_val':[0,1,2,3,4], 'Y1':[3.01, 5.10, 6.99, 8.02, 10.81],
     'Y2':[0.99, 3.05, 7.29, 13.41, 20.31]}
df = pd.DataFrame(dc)

source = ColumnDataSource(data={'x': df['x_val'], 'y': df['Y1'], 'y2':df['Y2']})

plot = figure(x_axis_label = 'x', y_axis_label = 'f(x)')
plot.circle('x', 'y', source=source)


def update_plot(attr, old, new):
        y = y_select.value
        new_data = {'x': df['x_val'], 'y': df[y]}
        source.data = new_data


y_select = Select(options=['Y1', 'Y2'],value='Y1',title='y-axis data')
y_select.on_change('value', update_plot)

# Create layout and add to current document
layout = row(widgetbox(y_select), plot)

# Add layout to current document
curdoc().add_root(layout)

现在，每当我更新绘图时，我都想在数据上拟合一条曲线，即，当我选择绘制 x_val 与 Y1 的关系时，也会绘制相关的拟合曲线，对于其他情况，即 x_val 与 Y2。为此，我将上面的代码扩展为如下一段：

import pandas as pd
import numpy as np
from bokeh.io import curdoc
from bokeh.layouts import row, widgetbox
from bokeh.models import ColumnDataSource, Select
from bokeh.plotting import figure
from scipy.optimize import curve_fit


def fit_func(xdata, ydata):

    def func(x,a,c):
        return a*(x**2)+a*x+c

    y = func(xdata, 1, 1)
    popt, pcov = curve_fit(func, xdata, ydata)
    new_x = np.arange(0,10,2)
    new_y = func(new_x,*popt)

    return (new_x, new_y)


dc = {'x_val':[0,1,2,3,4], 'Y1':[3.01, 5.10, 6.99, 8.02, 10.81],
     'Y2':[0.99, 3.05, 7.29, 13.41, 20.31]}
df = pd.DataFrame(dc)

dfit = pd.DataFrame({'x': fit_func(df['x_val'].values, df['Y1'].values)[0],
                     'y': fit_func(df['x_val'].values, df['Y1'].values)[1]})

source = ColumnDataSource(data={'x': df['x_val'], 'y': df['Y1'], 'y2':df['Y2']})
source_f = ColumnDataSource(data={'x': dfit['x'], 'y': dfit['y']})

plot = figure(x_axis_label = 'x', y_axis_label = 'f(x)')
plot.circle('x', 'y', source=source)
plot.line('x', 'y', source=source_f)    

def update_plot(attr, old, new):
        y = y_select.value
        new_data = {'x': df['x_val'], 'y': df[y]}
        source.data = new_data

        answ = fit_func(df['x_val'].values, df[y].values)
        new_fit = pd.DataFrame({'x': fit_func(df['x_val'].values, df['Y1'].values)[0],
                                'y': fit_func(df['x_val'].values, df['Y1'].values)[1]})
        source_f.data = new_fit


y_select = Select(options=['Y1', 'Y2'],value='Y1',title='y-axis data')
y_select.on_change('value', update_plot)

# Create layout and add to current document
layout = row(widgetbox(y_select), plot)

# Add layout to current document
curdoc().add_root(layout)

这次更新图是看不到拟合曲线的我的问题。另一个问题是：是否有任何优雅的方法可以仅在我们更新绘图时拟合曲线？

谢谢！

Answer 1

考虑到 Alex 的评论，我把我的问题的解决方案放在这里：

import pandas as pd
import numpy as np
from bokeh.io import curdoc
from bokeh.layouts import row, widgetbox
from bokeh.models import ColumnDataSource, Select
from bokeh.plotting import figure
from scipy.optimize import curve_fit

def fit_func(xdata, ydata):

    def func(x,a,c):
        return a*(x**2)+a*x+c

    y = func(xdata, 1, 1)
    popt, pcov = curve_fit(func, xdata, ydata)
    new_x = np.arange(0,10,2)
    new_y = func(new_x,*popt)

    return (new_x, new_y)

dc = {'x_val':[0,1,2,3,4], 'Y1':[3.01, 5.10, 6.99, 8.02, 10.81],
     'Y2':[0.99, 3.05, 7.29, 13.41, 20.31]}
df = pd.DataFrame(dc)

source = ColumnDataSource(data={'x': df['x_val'], 'y': df['Y1'], 'y2':df['Y2']})

xf, yf = fit_func(df['x_val'].values, df['Y1'].values)
source_f = ColumnDataSource(data={'x': xf, 'y': yf})

plot = figure(x_axis_label = 'x', y_axis_label = 'f(x)')
plot.circle('x', 'y', source=source)
plot.line('x', 'y', source=source_f)

def update_plot(attr, old, new):
        y = y_select.value
        new_data = {'x': df['x_val'], 'y': df[y]}
        source.data = new_data

        answ = fit_func(df['x_val'].values, df[y].values)
        new_fit = {'x':answ[0], 'y':answ[1]}
        source_f.data = new_fit

y_select = Select(options=['Y1', 'Y2'],value='Y1',title='y-axis data')
y_select.on_change('value', update_plot)

layout = row(widgetbox(y_select), plot)    
curdoc().add_root(layout)

使用 python 中的 "bokeh" 库更新绘图时拟合曲线

Fitting a curve while updating a plot using the "bokeh" library in python

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