matplotlib 平滑动画叠加在散点图上

Question

Jupyter 中的以下 Python 代码显示了一个示例，该示例显示了一些生成的散点图数据，它叠加了一条线，您可以交互地更改 y 截距和斜率，它还显示均方根误差。我的问题是：我怎样才能使它更具响应性？处理过程中存在滞后和累积变化，并且闪烁很多。能否更快、更灵敏、更流畅？

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%matplotlib inline

from ipywidgets import interactive
import matplotlib.pyplot as plt
import numpy as np

# Desired mean values of generated sample.
N = 50

# Desired mean values of generated sample.
mean = np.array([0, 0])

# Desired covariance matrix of generated sample.
cov = np.array([
        [ 10,  8],
        [  8, 10]
    ])

# Generate random data.
data = np.random.multivariate_normal(mean, cov, size=N)
xdata = data[:, 0]
ydata = data[:, 1]

# Plot linear regression line
def f(m, b):
    plt.figure()
    x = np.linspace(-10, 10, num=100)
    plt.plot(xdata, ydata, 'ro')
    plt.plot(x, m * x + b)
    plt.ylim(-10, 10)
    rmes = np.sqrt(np.mean(((xdata*m+b)-ydata)**2))
    print("Root Mean Square Error: ", rmes)

interactive_plot = interactive(f, m=(-10.0, 10.0), b=(-10, 10, 0.5))
output = interactive_plot.children[-1]
output.layout.height = '350px'
interactive_plot

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Answer 1

您需要在函数末尾添加plt.show()。有一个github issue about it

尝试使用FloatSlider 和continuous_update=False。 See here

interactive_plot = interactive(f, m=FloatSlider(min=-10.0, max=10.0,  continuous_update=False), 
                               b=FloatSlider(min=-10, max=10, step=.5, continuous_update=False))