本文介绍了在tkinter图形用户界面中解决简单的ODE系统的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我有一个用于SIR疾病模型的简单的ODE系统，它工作得很好，并产生了一个图形化的情节。但是，我正在尝试使用tkinter创建一个简单的弹出框，该框接受参数值，而不必通过脚本将参数值放入其中。
以下是原始代码。
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
#three compartments, Susceptible S, infected I, recovered R
#dS/dt, dI/dt, dR/dt
#susceptible sees birth rate coming in, deaths leaving and force of infection leaving
#infected sees FOI coming in, deaths leaving and recovery rates
#recovered sees recovery rate coming in, deaths leaving
#beta is tranmission coefficient, FOI is beta * (I/N) where N is total pop
#initially consider a model not accounting for births and deaths
# Total population, N.
N = 1000
# Initial number of infected and recovered individuals, I0 and R0.
I0, R0 = 1, 0
# Everyone else, S0, is susceptible to infection initially.
S0 = N - I0 - R0
# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).
beta, gamma = 2/7, 1/7
# A grid of time points (in days)
t = np.linspace(0, 160, 160)
# The SIR model differential equations.
def deriv(y, t, N, beta, gamma):
S, I, R = y
dS = ((-beta * S * I) / N)
dI = ((beta * S * I) / N) - (gamma * I)
dR = (gamma * I)
return dS, dI, dR
# Initial conditions are S0, I0, R0
# Integrate the SIR equations over the time grid, t.
solve = odeint(deriv, (S0, I0, R0), t, args=(N, beta, gamma))
S, I, R = solve.T
# Plot the data on three separate curves for S(t), I(t) and R(t)
fig = plt.figure(facecolor='w')
ax = fig.add_subplot(111, facecolor='#dddddd', axisbelow=True)
ax.plot(t, S/1000, 'b', alpha=1, lw=2, label='Susceptible')
ax.plot(t, I/1000, 'r', alpha=1, lw=2, label='Infected')
ax.plot(t, R/1000, 'black', alpha=1, lw=2, label='Recovered')
ax.set_xlabel('Time in days')
ax.set_ylabel('Number (1000s)')
ax.set_ylim(0,1.1)
#ax.yaxis.set_tick_params(length=0)
#ax.xaxis.set_tick_params(length=0)
ax.grid(b=True, which='major', c='w', lw=2, ls='-')
legend = ax.legend()
legend.get_frame().set_alpha(0.5)
#for spine in ('top', 'right', 'bottom', 'left'):
# ax.spines[spine].set_visible(False)
plt.show()
现在是带有一些图形用户界面的
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
import tkinter as tk
from tkinter import IntVar
###############################################################################
def mainwindow():
mainwindow = tk.Tk()
mainwindow.geometry('350x350')
tk.Label(mainwindow, text="enter parameters below").grid(row=1)
getN = IntVar()
geti0 = IntVar()
getr0 = IntVar()
getbeta = IntVar()
getgamma = IntVar()
tk.Label(mainwindow, text="N").grid(row=2)
tk.Label(mainwindow, text="i0").grid(row=3)
tk.Label(mainwindow, text="r0").grid(row=4)
tk.Label(mainwindow, text="beta").grid(row=5)
tk.Label(mainwindow, text="gamma").grid(row=6)
e1 = tk.Entry(mainwindow,textvariable = getN).grid(row=2, column=1)
e2 = tk.Entry(mainwindow,textvariable = geti0).grid(row=3, column=1)
e3 = tk.Entry(mainwindow,textvariable = getr0).grid(row=4, column=1)
e4 = tk.Entry(mainwindow,textvariable = getbeta).grid(row=5, column=1)
e5 = tk.Entry(mainwindow,textvariable = getgamma).grid(row=6, column=1)
solve = tk.Button(mainwindow, text='solve!', command=lambda: [values()]).grid(row=7, column=1, sticky=tk.W, pady=4)
def values():
readN = getN.get()
readi0 = geti0.get()
readr0 = getr0.get()
readbeta = getbeta.get()
readgamma = getgamma.get()
intN = int(readN)
inti0 = int(readi0)
intr0 = int(readr0)
intbeta = int(readbeta)
intgamma = int(readgamma)
# Total population, N.
N = readN
# Initial number of infected and recovered individuals, I0 and R0.
I0, R0 = readi0, readr0
# Everyone else, S0, is susceptible to infection initially.
S0 = N - I0 - R0
# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).
beta, gamma = readbeta, readgamma
# A grid of time points (in days)
t = np.linspace(0, 160, 160)
# The SIR model differential equations.
def deriv(y, t, N, beta, gamma):
S, I, R = y
dS = ((-beta * S * I) / N)
dI = ((beta * S * I) / N) - (gamma * I)
dR = (gamma * I)
return dS, dI, dR
# Initial conditions are S0, I0, R0
# Integrate the SIR equations over the time grid, t.
solve = odeint(deriv, (S0, I0, R0), t, args=(N, beta, gamma))
S, I, R = solve.T
# Plot the data on three separate curves for S(t), I(t) and R(t)
fig = plt.figure(facecolor='w')
ax = fig.add_subplot(111, facecolor='#dddddd', axisbelow=True)
ax.plot(t, S/1000, 'b', alpha=0.5, lw=2, label='Susceptible')
ax.plot(t, I/1000, 'r', alpha=0.5, lw=2, label='Infected')
ax.plot(t, R/1000, 'g', alpha=0.5, lw=2, label='Recovered with immunity')
ax.set_xlabel('Time /days')
ax.set_ylabel('Number (1000s)')
ax.set_ylim(0,1.2)
ax.yaxis.set_tick_params(length=0)
ax.xaxis.set_tick_params(length=0)
ax.grid(b=True, which='major', c='w', lw=2, ls='-')
legend = ax.legend()
legend.get_frame().set_alpha(0.5)
for spine in ('top', 'right', 'bottom', 'left'):
ax.spines[spine].set_visible(False)
plt.show()
mainwindow.mainloop()
mainwindow()
第一个给出预期的曲线图：
，但是对于图形用户界面，它提供了以下功能：
我的代码哪里出错了？解算系统的代码没有改变，我只是设置了它，以便参数采用我在弹出框中输入的值。Lambda函数是否出错？
推荐答案
我尝试使用Beta和Gamma作为2/7的代码，1/7无法使其工作。
使用：
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
import tkinter as tk
from tkinter import IntVar,StringVar,DoubleVar
###############################################################################
def mainwindow():
mainwindow = tk.Tk()
mainwindow.geometry('350x350')
tk.Label(mainwindow, text="enter parameters below").grid(row=1)
getN = IntVar()
geti0 = IntVar()
getr0 = IntVar()
# getbeta = StringVar()
# getgamma = StringVar()
getbeta = DoubleVar()
getgamma = DoubleVar()
tk.Label(mainwindow, text="N").grid(row=2)
tk.Label(mainwindow, text="i0").grid(row=3)
tk.Label(mainwindow, text="r0").grid(row=4)
tk.Label(mainwindow, text="beta").grid(row=5)
tk.Label(mainwindow, text="gamma").grid(row=6)
e1 = tk.Entry(mainwindow,textvariable = getN).grid(row=2, column=1)
e2 = tk.Entry(mainwindow,textvariable = geti0).grid(row=3, column=1)
e3 = tk.Entry(mainwindow,textvariable = getr0).grid(row=4, column=1)
e4 = tk.Entry(mainwindow,textvariable = getbeta).grid(row=5, column=1)
e5 = tk.Entry(mainwindow,textvariable = getgamma).grid(row=6, column=1)
solve = tk.Button(mainwindow, text='solve!', command=lambda: [values()]).grid(row=7, column=1, sticky=tk.W, pady=4)
def values():
readN = getN.get()
readi0 = geti0.get()
readr0 = getr0.get()
# readbeta = float(getbeta.get())
# readgamma = float(getgamma.get())
readbeta = (getbeta.get())
readgamma =(getgamma.get())
print('ppppppppppppp', readbeta,readgamma)
intN = int(readN)
inti0 = int(readi0)
intr0 = int(readr0)
intbeta = float(readbeta)
intgamma = float(readgamma)
# Total population, N.
N = readN
# Initial number of infected and recovered individuals, I0 and R0.
I0, R0 = readi0, readr0
# Everyone else, S0, is susceptible to infection initially.
S0 = N - I0 - R0
# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).
beta, gamma = readbeta, readgamma
# A grid of time points (in days)
t = np.linspace(0, 160, 160)
# The SIR model differential equations.
def deriv(y, t, N, beta, gamma):
S, I, R = y
dS = ((-beta * S * I) / N)
dI = ((beta * S * I) / N) - (gamma * I)
dR = (gamma * I)
return dS, dI, dR
# Initial conditions are S0, I0, R0
# Integrate the SIR equations over the time grid, t.
solve = odeint(deriv, (S0, I0, R0), t, args=(N, beta, gamma))
S, I, R = solve.T
# Plot the data on three separate curves for S(t), I(t) and R(t)
fig = plt.figure(facecolor='w')
ax = fig.add_subplot(111, facecolor='#dddddd', axisbelow=True)
ax.plot(t, S/1000, 'b', alpha=0.5, lw=2, label='Susceptible')
ax.plot(t, I/1000, 'r', alpha=0.5, lw=2, label='Infected')
ax.plot(t, R/1000, 'g', alpha=0.5, lw=2, label='Recovered with immunity')
ax.set_xlabel('Time /days')
ax.set_ylabel('Number (1000s)')
ax.set_ylim(0,1.2)
ax.yaxis.set_tick_params(length=0)
ax.xaxis.set_tick_params(length=0)
ax.grid(b=True, which='major', c='w', lw=2, ls='-')
legend = ax.legend()
legend.get_frame().set_alpha(0.5)
for spine in ('top', 'right', 'bottom', 'left'):
ax.spines[spine].set_visible(False)
plt.show()
mainwindow.mainloop()
mainwindow()
和0.28，0.14作为Beta和Gamma I：
希望知道如何使用分数作为输入的人会出现，
我尝试使用getbeta = StringVar()和getgamma = StringVar()
和readbeta = float(getbeta.get())和readgamma =float(getgamma.get())
或intbeta = float(readbeta)和intgamma = float(readgamma)
但收到ValueError: could not convert string to float: '2/7'
对于readbeta = float(getbeta.get())
遇到eval要允许输入‘2/7’和‘1/7’作为beta和Gamma，请参阅How can I get the data from Entry in tkinter that can be used as function?
此处代码更新：
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
import tkinter as tk
from tkinter import IntVar,StringVar,DoubleVar
###############################################################################
def mainwindow():
mainwindow = tk.Tk()
mainwindow.geometry('350x350')
tk.Label(mainwindow, text="enter parameters below").grid(row=1)
getN = IntVar()
geti0 = IntVar()
getr0 = IntVar()
getbeta = StringVar()
getgamma = StringVar()
# getbeta = DoubleVar()
# getgamma = DoubleVar()
tk.Label(mainwindow, text="N").grid(row=2)
tk.Label(mainwindow, text="i0").grid(row=3)
tk.Label(mainwindow, text="r0").grid(row=4)
tk.Label(mainwindow, text="beta").grid(row=5)
tk.Label(mainwindow, text="gamma").grid(row=6)
e1 = tk.Entry(mainwindow,textvariable = getN).grid(row=2, column=1)
e2 = tk.Entry(mainwindow,textvariable = geti0).grid(row=3, column=1)
e3 = tk.Entry(mainwindow,textvariable = getr0).grid(row=4, column=1)
e4 = tk.Entry(mainwindow,textvariable = getbeta).grid(row=5, column=1)
e5 = tk.Entry(mainwindow,textvariable = getgamma).grid(row=6, column=1)
solve = tk.Button(mainwindow, text='solve!', command=lambda: [values()]).grid(row=7, column=1, sticky=tk.W, pady=4)
def values():
readN = getN.get()
readi0 = geti0.get()
readr0 = getr0.get()
# readbeta = float(getbeta.get())
# readgamma = float(getgamma.get())
readbeta = eval(getbeta.get(),{"builtins": {}})
readgamma = eval(getgamma.get(), {"builtins": {}})
print('ppppppppppppp', readbeta,readgamma)
intN = int(readN)
inti0 = int(readi0)
intr0 = int(readr0)
intbeta = float(readbeta)
intgamma = float(readgamma)
# Total population, N.
N = readN
# Initial number of infected and recovered individuals, I0 and R0.
I0, R0 = readi0, readr0
# Everyone else, S0, is susceptible to infection initially.
S0 = N - I0 - R0
# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).
beta, gamma = readbeta, readgamma
# A grid of time points (in days)
t = np.linspace(0, 160, 160)
# The SIR model differential equations.
def deriv(y, t, N, beta, gamma):
S, I, R = y
dS = ((-beta * S * I) / N)
dI = ((beta * S * I) / N) - (gamma * I)
dR = (gamma * I)
return dS, dI, dR
# Initial conditions are S0, I0, R0
# Integrate the SIR equations over the time grid, t.
solve = odeint(deriv, (S0, I0, R0), t, args=(N, beta, gamma))
S, I, R = solve.T
# Plot the data on three separate curves for S(t), I(t) and R(t)
fig = plt.figure(facecolor='w')
ax = fig.add_subplot(111, facecolor='#dddddd', axisbelow=True)
ax.plot(t, S/1000, 'b', alpha=0.5, lw=2, label='Susceptible')
ax.plot(t, I/1000, 'r', alpha=0.5, lw=2, label='Infected')
ax.plot(t, R/1000, 'g', alpha=0.5, lw=2, label='Recovered with immunity')
ax.set_xlabel('Time /days')
ax.set_ylabel('Number (1000s)')
ax.set_ylim(0,1.2)
ax.yaxis.set_tick_params(length=0)
ax.xaxis.set_tick_params(length=0)
ax.grid(b=True, which='major', c='w', lw=2, ls='-')
legend = ax.legend()
legend.get_frame().set_alpha(0.5)
for spine in ('top', 'right', 'bottom', 'left'):
ax.spines[spine].set_visible(False)
plt.show()
mainwindow.mainloop()
mainwindow()
getbeta = StringVar()和
getgamma = StringVar()，然后readbeta = eval(getbeta.get(),{"builtins": {}})和readgamma = eval(getgamma.get(), {"builtins": {}})
我在某个地方读到，eval在Python中的使用是不安全的，所以如果有人想要更好的解决方案，请与我们分享
eval函数之前对其进行验证，因此代码应该是安全的(或不安全？？请在此帮助)；
新代码如下：
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
import tkinter as tk
from tkinter import IntVar,StringVar,DoubleVar
###############################################################################
def callback_int(input):
if input.isdigit():
print(input)
return True
elif input == "":
print(input)
return True
else:
print(input)
return False
def callback_str(input, typez=None):
if all([s.isdigit() or s =='/' for s in input]) and input.count('/') <= 1:
print([s.isdigit() or s =='/' for s in input])
# print(input)
return True
elif all([s.isdigit() or s =='.' for s in input]) and input.count('.') <= 1:
print([s.isdigit() or s =='.' for s in input])
# print(input)
return True
else:
print('no valid input : ',input)
return False
def mainwindow():
mainwindow = tk.Tk()
mainwindow.geometry('350x350')
tk.Label(mainwindow, text="enter parameters below").grid(row=1)
getN = IntVar()
geti0 = IntVar()
getr0 = IntVar()
getbeta = StringVar(mainwindow, value='0')
getgamma = StringVar(mainwindow, value='0')
# getbeta = DoubleVar()
# getgamma = DoubleVar()
tk.Label(mainwindow, text="N").grid(row=2)
tk.Label(mainwindow, text="i0").grid(row=3)
tk.Label(mainwindow, text="r0").grid(row=4)
tk.Label(mainwindow, text="beta").grid(row=5)
tk.Label(mainwindow, text="gamma").grid(row=6)
e1 = tk.Entry(mainwindow,textvariable = getN)
e1.grid(row=2, column=1)
e2 = tk.Entry(mainwindow,textvariable = geti0)
e2.grid(row=3, column=1)
e3 = tk.Entry(mainwindow,textvariable = getr0)
e3.grid(row=4, column=1)
e4 = tk.Entry(mainwindow,textvariable = getbeta)
e4.grid(row=5, column=1)
e5 = tk.Entry(mainwindow,textvariable = getgamma)
e5.grid(row=6, column=1)
reg_int = mainwindow.register(callback_int)
reg_str = mainwindow.register(callback_str)
print(type(e4))
e1.config(validate ="key", validatecommand =(reg_int, '%P'))
e2.config(validate ="key", validatecommand =(reg_int, '%P'))
e3.config(validate ="key", validatecommand =(reg_int, '%P'))
e4.config(validate ="key", validatecommand =(reg_str, '%P'))
e5.config(validate ="key", validatecommand =(reg_str, '%P'))
solve = tk.Button(mainwindow, text='solve!', command=lambda: [values()]).grid(row=7, column=1, sticky=tk.W, pady=4)
def values():
readN = getN.get()
readi0 = geti0.get()
readr0 = getr0.get()
# readbeta = float(getbeta.get())
# readgamma = float(getgamma.get())
readbeta = eval(getbeta.get(),{"builtins": {}})
readgamma = eval(getgamma.get(), {"builtins": {}})
print('ppppppppppppp', readbeta,readgamma)
intN = int(readN)
inti0 = int(readi0)
intr0 = int(readr0)
intbeta = float(readbeta)
intgamma = float(readgamma)
# Total population, N.
N = readN
# Initial number of infected and recovered individuals, I0 and R0.
I0, R0 = readi0, readr0
# Everyone else, S0, is susceptible to infection initially.
S0 = N - I0 - R0
# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).
beta, gamma = readbeta, readgamma
# A grid of time points (in days)
t = np.linspace(0, 160, 160)
# The SIR model differential equations.
def deriv(y, t, N, beta, gamma):
S, I, R = y
dS = ((-beta * S * I) / N)
dI = ((beta * S * I) / N) - (gamma * I)
dR = (gamma * I)
return dS, dI, dR
# Initial conditions are S0, I0, R0
# Integrate the SIR equations over the time grid, t.
solve = odeint(deriv, (S0, I0, R0), t, args=(N, beta, gamma))
S, I, R = solve.T
# Plot the data on three separate curves for S(t), I(t) and R(t)
fig = plt.figure(facecolor='w')
ax = fig.add_subplot(111, facecolor='#dddddd', axisbelow=True)
ax.plot(t, S/1000, 'b', alpha=0.5, lw=2, label='Susceptible')
ax.plot(t, I/1000, 'r', alpha=0.5, lw=2, label='Infected')
ax.plot(t, R/1000, 'g', alpha=0.5, lw=2, label='Recovered with immunity')
ax.set_xlabel('Time /days')
ax.set_ylabel('Number (1000s)')
ax.set_ylim(0,1.2)
ax.yaxis.set_tick_params(length=0)
ax.xaxis.set_tick_params(length=0)
ax.grid(b=True, which='major', c='w', lw=2, ls='-')
legend = ax.legend()
legend.get_frame().set_alpha(0.5)
for spine in ('top', 'right', 'bottom', 'left'):
ax.spines[spine].set_visible(False)
plt.show()
mainwindow.mainloop()
mainwindow()
这允许Beta和Gamma将浮点数(即0.28)或分数(即2/7)作为输入插入Entry Widget框
开始享受Tkinter，这里是允许单选按钮控制输入类型的另一个改进版本：
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
import tkinter as tk
from tkinter import IntVar,StringVar,DoubleVar
###############################################################################
def mainwindow():
def switch():
print(varb.get(), ' ') #,varbR)
# print(varbR)
getbeta.set('0')
getgamma.set('0')
return
def callback(input,typez=None, varb=None):
value = mainwindow.getvar(varb)
print(value)
# varb.get()=varb.get()
# uu = varb.get()
# print(varb, uu)
# print(varb.get())
if typez == "int":
if input.isdigit():
# print(input)
return True
elif input == "":
# print(input)
return True
else:
print(input, 'not allowed !!!!')
return False
if typez == "str":
if value =='frc':
if len(input) >=1 and input[0] == '/':
return False
if all([s.isdigit() or s =='/' for s in input]) and input.count('/') <= 1:
# print([s.isdigit() or s =='/' for s in input])
# print(input)
return True
else:
print('no valid input : ',input)
return False
elif value =='flt':
if all([s.isdigit() or s =='.' for s in input]) and input.count('.') <= 1:
# print([s.isdigit() or s =='.' for s in input])
# print(input)
return True
else:
print('no valid input : ',input)
return False
else:
return False
mainwindow = tk.Tk()
mainwindow.geometry('550x350')
tk.Label(mainwindow, text="enter parameters below").grid(row=1)
getN = IntVar()
geti0 = IntVar()
getr0 = IntVar()
getbeta = StringVar(mainwindow, value='0')
getgamma = StringVar(mainwindow, value='0')
# getbeta = DoubleVar()
# getgamma = DoubleVar()
tk.Label(mainwindow, text="N").grid(row=2)
tk.Label(mainwindow, text="i0").grid(row=3)
tk.Label(mainwindow, text="r0").grid(row=4)
tk.Label(mainwindow, text="beta").grid(row=5)
tk.Label(mainwindow, text="gamma").grid(row=6)
e1 = tk.Entry(mainwindow,textvariable = getN)
e1.grid(row=2, column=1)
e2 = tk.Entry(mainwindow,textvariable = geti0)
e2.grid(row=3, column=1)
e3 = tk.Entry(mainwindow,textvariable = getr0)
e3.grid(row=4, column=1)
e4 = tk.Entry(mainwindow,textvariable = getbeta)
e4.grid(row=5, column=1)
e5 = tk.Entry(mainwindow,textvariable = getgamma)
e5.grid(row=6, column=1)
varb = StringVar(mainwindow, value='flt')
# varbR=varb.get()
rb1 = tk.Radiobutton(mainwindow, borderwidth=8,height=1, text='float ' ,
variable = varb, value='flt', command=switch, justify="left")
rb1.grid(row=5,column =2, rowspan=1, sticky="w")
rb2 = tk.Radiobutton(mainwindow, borderwidth=8,height=1, text='fraction' ,
variable = varb, value='frc', command=switch ,justify="left")
rb2.grid(row=6,column =2, rowspan=1, sticky="w")
rb1.deselect() # finche non attivo radiobutton non prende parametri
reg = mainwindow.register(callback)
# e1.config(validate ="key", validatecommand =(reg, '%P', 'int',varbR))
# e2.config(validate ="key", validatecommand =(reg, '%P', 'int',varbR))
# e3.config(validate ="key", validatecommand =(reg, '%P', 'int',varbR))
# e4.config(validate ="key", validatecommand =(reg, '%P', 'str',varbR))
# e5.config(validate ="key", validatecommand =(reg, '%P', 'str',varbR))
# e1.config(validate ="key", validatecommand =(reg, '%P', 'int',varb.get()))
# e2.config(validate ="key", validatecommand =(reg, '%P', 'int',varb.get()))
# e3.config(validate ="key", validatecommand =(reg, '%P', 'int',varb.get()))
# e4.config(validate ="key", validatecommand =(reg, '%P', 'str',varb.get()))
# e5.config(validate ="key", validatecommand =(reg, '%P', 'str',varb.get()))
e1.config(validate ="key", validatecommand =(reg, '%P', 'int',varb))
e2.config(validate ="key", validatecommand =(reg, '%P', 'int',varb))
e3.config(validate ="key", validatecommand =(reg, '%P', 'int',varb))
e4.config(validate ="key", validatecommand =(reg, '%P', 'str',varb))
e5.config(validate ="key", validatecommand =(reg, '%P', 'str',varb))
solve = tk.Button(mainwindow, text='solve!', command=lambda: [values()]).grid(row=7, column=1, sticky=tk.W, pady=4)
def values():
try:
a = varb.get()
print(a)
readN = getN.get()
readi0 = geti0.get()
readr0 = getr0.get()
# readbeta = float(getbeta.get())
# readgamma = float(getgamma.get())
# readbeta_ = getbeta.get()
# if readbeta_[0] == '/':
# readbeta_ = readbeta_[1:]
# readbeta = eval(readbeta_,{"builtins": {}})
readbeta = eval(getbeta.get(),{"builtins": {}})
readgamma = eval(getgamma.get(), {"builtins": {}})
intN = int(readN)
inti0 = int(readi0)
intr0 = int(readr0)
intbeta = float(readbeta)
intgamma = float(readgamma)
print('varb : ', varb.get(),
'
N : ', intN,
'
iO : ',inti0,
'
r0 : ',intr0,
'
beta : ',getbeta.get(),
'
gamma : ',getgamma.get())
# Total population, N.
N = readN
# Initial number of infected and recovered individuals, I0 and R0.
I0, R0 = readi0, readr0
# Everyone else, S0, is susceptible to infection initially.
S0 = N - I0 - R0
# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).
beta, gamma = readbeta, readgamma
# A grid of time points (in days)
t = np.linspace(0, 160, 160)
# The SIR model differential equations.
def deriv(y, t, N, beta, gamma):
S, I, R = y
dS = ((-beta * S * I) / N)
dI = ((beta * S * I) / N) - (gamma * I)
dR = (gamma * I)
return dS, dI, dR
# Initial conditions are S0, I0, R0
# Integrate the SIR equations over the time grid, t.
solve = odeint(deriv, (S0, I0, R0), t, args=(N, beta, gamma))
S, I, R = solve.T
# Plot the data on three separate curves for S(t), I(t) and R(t)
fig = plt.figure(facecolor='w')
ax = fig.add_subplot(111, facecolor='#dddddd', axisbelow=True)
ax.plot(t, S/1000, 'b', alpha=0.5, lw=2, label='Susceptible')
ax.plot(t, I/1000, 'r', alpha=0.5, lw=2, label='Infected')
ax.plot(t, R/1000, 'g', alpha=0.5, lw=2, label='Recovered with immunity')
ax.set_xlabel('Time /days')
ax.set_ylabel('Number (1000s)')
ax.set_ylim(0,1.2)
ax.yaxis.set_tick_params(length=0)
ax.xaxis.set_tick_params(length=0)
ax.grid(b=True, which='major', c='w', lw=2, ls='-')
legend = ax.legend()
legend.get_frame().set_alpha(0.5)
for spine in ('top', 'right', 'bottom', 'left'):
ax.spines[spine].set_visible(False)
plt.show()
return
except:
print('maybe wrong values !!!!!!!!')
return
mainwindow.mainloop()
mainwindow()
这篇关于在tkinter图形用户界面中解决简单的ODE系统的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持编程学习网！
本站部分内容来源互联网,如果有图片或者内容侵犯您的权益请联系我们删除！