如何在 Jupyter Notebook 中添加交互式绘图？

Question

我已经为基本 SIR 模型绘制了一个图。我对我的情节很满意，但是，我希望能够有一个交互式滑块来调整我的参数 beta 和 gamma。我希望它们的范围都在 0 到 1 之间，并且用户能够将它们递增 0.01。有人可以帮我在我的代码中实现这个吗？感谢您提前抽出时间。这是我的代码：# # Solving SIR Model in Python (INTERACTIVE)# \# Importing packages:# In[10]:# Display in LaTeX style.from sympy.interactive import printingprinting.init_printing(use_latex = True)# For integration.import scipy.integrate # For arrays (Python does not have native arrays).import numpy as np# For graphing.import matplotlib.pyplot as plt # Prevents the pop-up graphs in a separate window.get_ipython().run_line_magic('matplotlib', 'inline')# Allows for an interactive widget bar.from ipywidgets import interactive # \# Defining differential equations:# In[11]:def SIR_model(y, t, beta, gamma):    S, I, R = y        dS_dt = -beta*S*I    dI_dt = beta*S*I - gamma*I    dR_dt = gamma*I        return([dS_dt, dI_dt, dR_dt,])# \# Defining initial conditions:# In[12]:S0 = 0.95I0 = 0.05R0 = 0.0beta = 0.35gamma = 0.1# \# Defining time vector:# In[13]:# Graph from 0 to 100, include 10000 points.t = np.linspace(0, 100, 10000) # \# Defining solution:# In[14]:# Resultsolution = scipy.integrate.odeint(SIR_model, [S0, I0, R0], t, args=(beta, gamma))solution = np.array(solution)# \# Plotting the result:# In[20]:plt.figure(figsize=[8, 5])plt.plot(t, solution[:, 0], label="S(t)")plt.plot(t, solution[:, 1], label="I(t)")plt.plot(t, solution[:, 2], label="R(t)")plt.grid()plt.legend()plt.title("SIR Model")plt.xlabel("Time")plt.ylabel("Proportions of Populations")# THIS DOES NOT WORK !!!#interactive_plot = interactive(SIR_model, betta=(0.35,1,0.01), gamma=(0.1,1,0.01))#interactive_plotplt.show()这是输出。

Answer 1

您需要创建一个函数来一次性处理输入、积分和绘图 ( sir_interactive_func)，见下文：

# For integration.

import scipy.integrate 

# For arrays (Python does not have native arrays).

import numpy as np

# For graphing.

import matplotlib.pyplot as plt 

# Prevents the pop-up graphs in a separate window.

get_ipython().run_line_magic('matplotlib', 'inline')

# Allows for an interactive widget bar.

from ipywidgets import interactive 

S0 = 0.95

I0 = 0.05

R0 = 0.0

def SIR_model(y, t, beta, gamma):

    S, I, R = y

    

    dS_dt = -beta*S*I

    dI_dt = beta*S*I - gamma*I

    dR_dt = gamma*I

    

    return([dS_dt, dI_dt, dR_dt,])

    

def sir_interactive_func(beta, gamma):

    

    # Graph from 0 to 100, include 10000 points.

    t = np.linspace(0, 100, 10000) 

    

    solution = scipy.integrate.odeint(SIR_model, [S0, I0, R0], t, args=(beta, gamma))

    solution = np.array(solution)

    plt.figure(figsize=[8, 5])

    plt.plot(t, solution[:, 0], label="S(t)")

    plt.plot(t, solution[:, 1], label="I(t)")

    plt.plot(t, solution[:, 2], label="R(t)")

    plt.grid()

    plt.legend()

    plt.title("SIR Model")

    plt.xlabel("Time")

    plt.ylabel("Proportions of Populations")

    

interactive_plot = interactive(sir_interactive_func, beta=(0.35,1,0.01), gamma=(0.1,1,0.01))

interactive_plot