嗨，您尝试了将 beta 和 gamma 设置为 2/7 的代码，但 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 我得到：
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)
但是得到了ValueError: could not convert string to float: '2/7'
为readbeta = float(getbeta.get())
使用 eval 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?
这里的代码更新了：
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()
它使用getbeta = StringVar() 和
getgamma = StringVar() 然后是 readbeta = eval(getbeta.get(),{"builtins": {}}) 和 readgamma = eval(getgamma.get(), {"builtins": {}})
我在某处读到eval 在 python 中的使用是不安全的，所以如果有人作为更好的解决方案，请与我们分享
最后设法在将输入发送到eval 函数之前验证输入，因此代码应该是安全的（或者不是？？请在此处提供帮助）；
这里是新代码：
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()
允许 beta 和 gamma 插入浮点数（即 0.28）或分数（即 2/7）作为输入小部件框
开始享受 Tkinter，这里是另一个改进版本，其中 RadioButtons 控制允许的输入类型：
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(),
'\nN : ', intN,
'\niO : ',inti0,
'\nr0 : ',intr0,
'\nbeta : ',getbeta.get(),
'\ngamma : ',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()