更新旧 Python 代码
Updation of Old Python Code
非常菜鸟的问题所以请耐心等待，因为我是 Python 的新手。下面给出的代码是关于常微分方程生成 ODE 的自动组合。我尝试在 Python 3.6.3 和 Spider(Pyton 3.6) 上执行此代码但没有结果。我花了很多天让它在 Python 的新版本上可执行，但我无法执行它，因为正在生成更多错误。所以我照原样复制了代码。
from scipy import*
from scipy.integrate import odeint
from operator import itemgetter
import matplotlib
matplotlib.use('Agg')
from matplotlib.ticker import FormatStrFormatter
from pylab import *
from itertools import product, islice
from numpy import zeros_like
from string import ascii_lowercase
import operator
import sys
t_range = arange(0.0, 20.0, 0.1)
# initial_condi = []
# VarList = []
# ParamsList = []
ops = "+-"
opsdict = { "+": operator.add, "-": operator.sub }
# if len(initial_condi)!=len(VarList):
# sys.exit('error: the number of initional conditions do not equal to the number of variables')
def odeFunc(Y, t, model, K):
return GenModel(Y, model, K)
def GenModel(Y, model, K):
# New array of floating-point zeros the size of Y
dydt = zeros_like(Y)
for i, derivative in enumerate(model):
for j, operator in enumerate(derivative):
# Sequentially compute dy/dt for each variable in Y
dydt[i] = opsdict[operator](dydt[i],K[j]*Y[j])
return dydt
# Returns a nicer-looking string for a derivative expression given the encoding
def derivString(vars, deriv):
result = ""
for i, v in enumerate(vars):
if i == 0 and deriv[i] == '+':
result += v
else:
result += deriv[i]+v
return result
# main
numvars = int(raw_input("Enter number of variables\n> "))
VarList = ascii_lowercase[:numvars]
nummodels = (2**numvars)**numvars
# begin looping
input = ""
while input != "quit":
print "\n%d possible models" % nummodels
input = raw_input("Enter model ID (zero-indexed) or 'quit'\n> ")
# Basic input filtering
if input == "quit":
continue
elif not input.isdigit():
print "Input must be a non-negative integer"
continue
ID = int(input)
if ID >= nummodels or ID < 0:
print "Invalid ID"
continue
# itertools.product creates a generator for all possible combinations of +-
derivatives = product(ops, repeat=numvars)
# We take the product again to generate all models
models = product(derivatives, repeat=numvars)
# islice takes the specified model
model = next(islice(models, ID, None))
# Display dy/dt for each variable
print "Model %d:" % ID
IDtitle = []
for i, variable in enumerate(VarList):
tempstring = "d%c/dt = %s" % (variable, derivString(VarList, model[i]))
IDtitle.append(tempstring)
print "\t" + tempstring
# User specifies the initial values of all variables.
# This process can be automated but this is to demonstrate that the progam
# accepts any input
init_cons = []
params = []
confirm = ""
while confirm not in ("y", "n"):
confirm = raw_input("Run this model? (y/n)\n> ")
if confirm == "n":
continue
print "\nEnter <initial value, parameter> pairs separated by ','"
for i, variable in enumerate(VarList):
iv_param = map(float, raw_input("> %c: " % variable).split(','))
init_cons.append(iv_param[0])
params.append(iv_param[1])
print "\nRunning ODEint...",
result = odeint(odeFunc, init_cons, t_range, args=(model,params))
print " done."
print "Plotting results...",
f = figure(ID)
title(", ".join(IDtitle))
for i, variable in enumerate(VarList):
plot(t_range, result[:,i], label=variable)
legend()
axhline(0, color='k')
savefig("model"+str(ID))
close(f)
print "done."
print " -- Bye --"
raw_input 现在在 Python3 中称为 input。您还有一个名为 input 的变量，这可能引起了混淆。
from scipy import *
from scipy.integrate import odeint
from operator import itemgetter
import matplotlib
matplotlib.use('Agg')
from matplotlib.ticker import FormatStrFormatter
from pylab import *
from itertools import product, islice
from numpy import zeros_like
from string import ascii_lowercase
import operator
import sys
t_range = arange(0.0, 20.0, 0.1)
# initial_condi = []
# VarList = []
# ParamsList = []
ops = "+-"
opsdict = { "+": operator.add, "-": operator.sub }
# if len(initial_condi)!=len(VarList):
# sys.exit('error: the number of initional conditions do not equal to the number of variables')
def odeFunc(Y, t, model, K):
return GenModel(Y, model, K)
def GenModel(Y, model, K):
# New array of floating-point zeros the size of Y
dydt = zeros_like(Y)
for i, derivative in enumerate(model):
for j, operator in enumerate(derivative):
# Sequentially compute dy/dt for each variable in Y
dydt[i] = opsdict[operator](dydt[i],K[j]*Y[j])
return dydt
# Returns a nicer-looking string for a derivative expression given the encoding
def derivString(vars, deriv):
result = ""
for i, v in enumerate(vars):
if i == 0 and deriv[i] == '+':
result += v
else:
result += deriv[i]+v
return result
# main
numvars = int(input("Enter number of variables\n> "))
VarList = ascii_lowercase[:numvars]
nummodels = (2**numvars)**numvars
# begin looping
input_ = ""
while input_ != "quit":
print("\n%d possible models" % nummodels)
input_ = input("Enter model ID (zero-indexed) or 'quit'\n> ")
# Basic input filtering
if input_ == "quit":
continue
elif not input_.isdigit():
print("Input must be a non-negative integer")
continue
ID = int(input_)
if ID >= nummodels or ID < 0:
print("Invalid ID")
continue
# itertools.product creates a generator for all possible combinations of +-
derivatives = product(ops, repeat=numvars)
# We take the product again to generate all models
models = product(derivatives, repeat=numvars)
# islice takes the specified model
model = next(islice(models, ID, None))
# Display dy/dt for each variable
print("Model %d:" % ID)
IDtitle = []
for i, variable in enumerate(VarList):
tempstring = "d%c/dt = %s" % (variable, derivString(VarList, model[i]))
IDtitle.append(tempstring)
print("\t" + tempstring)
# User specifies the initial values of all variables.
# This process can be automated but this is to demonstrate that the progam
# accepts any input
init_cons = []
params = []
confirm = ""
while confirm not in ("y", "n"):
confirm = input("Run this model? (y/n)\n> ")
if confirm == "n":
continue
print("\nEnter <initial value, parameter> pairs separated by ','")
for i, variable in enumerate(VarList):
iv_param = list(map(float, input("> %c: " % variable).split(',')))
init_cons.append(iv_param[0])
params.append(iv_param[1])
print("\nRunning ODEint...", end='')
result = odeint(odeFunc, init_cons, t_range, args=(model,params))
print(" done.")
print("Plotting results...", end='')
f = figure(ID)
title(", ".join(IDtitle))
for i, variable in enumerate(VarList):
plot(t_range, result[:,i], label=variable)
legend()
axhline(0, color='k')
savefig("model"+str(ID))
close(f)
print("done.")
print(" -- Bye --")
非常菜鸟的问题所以请耐心等待，因为我是 Python 的新手。下面给出的代码是关于常微分方程生成 ODE 的自动组合。我尝试在 Python 3.6.3 和 Spider(Pyton 3.6) 上执行此代码但没有结果。我花了很多天让它在 Python 的新版本上可执行，但我无法执行它，因为正在生成更多错误。所以我照原样复制了代码。
from scipy import*
from scipy.integrate import odeint
from operator import itemgetter
import matplotlib
matplotlib.use('Agg')
from matplotlib.ticker import FormatStrFormatter
from pylab import *
from itertools import product, islice
from numpy import zeros_like
from string import ascii_lowercase
import operator
import sys
t_range = arange(0.0, 20.0, 0.1)
# initial_condi = []
# VarList = []
# ParamsList = []
ops = "+-"
opsdict = { "+": operator.add, "-": operator.sub }
# if len(initial_condi)!=len(VarList):
# sys.exit('error: the number of initional conditions do not equal to the number of variables')
def odeFunc(Y, t, model, K):
return GenModel(Y, model, K)
def GenModel(Y, model, K):
# New array of floating-point zeros the size of Y
dydt = zeros_like(Y)
for i, derivative in enumerate(model):
for j, operator in enumerate(derivative):
# Sequentially compute dy/dt for each variable in Y
dydt[i] = opsdict[operator](dydt[i],K[j]*Y[j])
return dydt
# Returns a nicer-looking string for a derivative expression given the encoding
def derivString(vars, deriv):
result = ""
for i, v in enumerate(vars):
if i == 0 and deriv[i] == '+':
result += v
else:
result += deriv[i]+v
return result
# main
numvars = int(raw_input("Enter number of variables\n> "))
VarList = ascii_lowercase[:numvars]
nummodels = (2**numvars)**numvars
# begin looping
input = ""
while input != "quit":
print "\n%d possible models" % nummodels
input = raw_input("Enter model ID (zero-indexed) or 'quit'\n> ")
# Basic input filtering
if input == "quit":
continue
elif not input.isdigit():
print "Input must be a non-negative integer"
continue
ID = int(input)
if ID >= nummodels or ID < 0:
print "Invalid ID"
continue
# itertools.product creates a generator for all possible combinations of +-
derivatives = product(ops, repeat=numvars)
# We take the product again to generate all models
models = product(derivatives, repeat=numvars)
# islice takes the specified model
model = next(islice(models, ID, None))
# Display dy/dt for each variable
print "Model %d:" % ID
IDtitle = []
for i, variable in enumerate(VarList):
tempstring = "d%c/dt = %s" % (variable, derivString(VarList, model[i]))
IDtitle.append(tempstring)
print "\t" + tempstring
# User specifies the initial values of all variables.
# This process can be automated but this is to demonstrate that the progam
# accepts any input
init_cons = []
params = []
confirm = ""
while confirm not in ("y", "n"):
confirm = raw_input("Run this model? (y/n)\n> ")
if confirm == "n":
continue
print "\nEnter <initial value, parameter> pairs separated by ','"
for i, variable in enumerate(VarList):
iv_param = map(float, raw_input("> %c: " % variable).split(','))
init_cons.append(iv_param[0])
params.append(iv_param[1])
print "\nRunning ODEint...",
result = odeint(odeFunc, init_cons, t_range, args=(model,params))
print " done."
print "Plotting results...",
f = figure(ID)
title(", ".join(IDtitle))
for i, variable in enumerate(VarList):
plot(t_range, result[:,i], label=variable)
legend()
axhline(0, color='k')
savefig("model"+str(ID))
close(f)
print "done."
print " -- Bye --"
raw_input 现在在 Python3 中称为 input。您还有一个名为 input 的变量，这可能引起了混淆。
from scipy import *
from scipy.integrate import odeint
from operator import itemgetter
import matplotlib
matplotlib.use('Agg')
from matplotlib.ticker import FormatStrFormatter
from pylab import *
from itertools import product, islice
from numpy import zeros_like
from string import ascii_lowercase
import operator
import sys
t_range = arange(0.0, 20.0, 0.1)
# initial_condi = []
# VarList = []
# ParamsList = []
ops = "+-"
opsdict = { "+": operator.add, "-": operator.sub }
# if len(initial_condi)!=len(VarList):
# sys.exit('error: the number of initional conditions do not equal to the number of variables')
def odeFunc(Y, t, model, K):
return GenModel(Y, model, K)
def GenModel(Y, model, K):
# New array of floating-point zeros the size of Y
dydt = zeros_like(Y)
for i, derivative in enumerate(model):
for j, operator in enumerate(derivative):
# Sequentially compute dy/dt for each variable in Y
dydt[i] = opsdict[operator](dydt[i],K[j]*Y[j])
return dydt
# Returns a nicer-looking string for a derivative expression given the encoding
def derivString(vars, deriv):
result = ""
for i, v in enumerate(vars):
if i == 0 and deriv[i] == '+':
result += v
else:
result += deriv[i]+v
return result
# main
numvars = int(input("Enter number of variables\n> "))
VarList = ascii_lowercase[:numvars]
nummodels = (2**numvars)**numvars
# begin looping
input_ = ""
while input_ != "quit":
print("\n%d possible models" % nummodels)
input_ = input("Enter model ID (zero-indexed) or 'quit'\n> ")
# Basic input filtering
if input_ == "quit":
continue
elif not input_.isdigit():
print("Input must be a non-negative integer")
continue
ID = int(input_)
if ID >= nummodels or ID < 0:
print("Invalid ID")
continue
# itertools.product creates a generator for all possible combinations of +-
derivatives = product(ops, repeat=numvars)
# We take the product again to generate all models
models = product(derivatives, repeat=numvars)
# islice takes the specified model
model = next(islice(models, ID, None))
# Display dy/dt for each variable
print("Model %d:" % ID)
IDtitle = []
for i, variable in enumerate(VarList):
tempstring = "d%c/dt = %s" % (variable, derivString(VarList, model[i]))
IDtitle.append(tempstring)
print("\t" + tempstring)
# User specifies the initial values of all variables.
# This process can be automated but this is to demonstrate that the progam
# accepts any input
init_cons = []
params = []
confirm = ""
while confirm not in ("y", "n"):
confirm = input("Run this model? (y/n)\n> ")
if confirm == "n":
continue
print("\nEnter <initial value, parameter> pairs separated by ','")
for i, variable in enumerate(VarList):
iv_param = list(map(float, input("> %c: " % variable).split(',')))
init_cons.append(iv_param[0])
params.append(iv_param[1])
print("\nRunning ODEint...", end='')
result = odeint(odeFunc, init_cons, t_range, args=(model,params))
print(" done.")
print("Plotting results...", end='')
f = figure(ID)
title(", ".join(IDtitle))
for i, variable in enumerate(VarList):
plot(t_range, result[:,i], label=variable)
legend()
axhline(0, color='k')
savefig("model"+str(ID))
close(f)
print("done.")
print(" -- Bye --")