如何简单地积分用 Sympy 编写的函数
How to simply integral a function written in Sympy
通过使用方法并获得Whosebug用户的帮助,我找到了一半的解决方案,我需要完成它。
通过使用 Sympy,我可以参数化地生成我的函数,它变成了 100 个类似于 0.03149536*exp(-4.56*s)*sin(2.33*s) 0.03446408*exp(-4.56*s)*sin(2.33*s)
的不同项目。通过使用 f = lambdify(s,f)
,我将它转换为 NumPy 函数,我需要对 in the different
sthat I already have. The upper limit of the integral is a constant value and the lower limit must be done through a
for 循环进行积分。
当我尝试执行此操作时,出现了一些错误,我在下面 post 进行了说明。我写的代码在下面,但为了成为一个可重现的问题,我必须放置一个生成的数据。 TypeError: cannot determine truth value of Relational
from sympy import exp, sin, symbols, integrate, lambdify
import pandas as pd
import matplotlib.pyplot as plt
from scipy import integrate
import numpy as np
S = np.linspace(0,1000,100)
C = np.linspace(0,1,100)
s, t = symbols('s t')
lanr = -4.56
lani = -2.33
ID = S[-1]
result=[]
f = C * exp(lanr * s) * sin (lani * s)
f = lambdify(s,f)
#vff = np.vectorize(f)
for i in (S):
I = integrate.quad(f,s,(i,ID))
result.append(I)
print(result)
编辑
- 我尝试在没有
Sympy
的情况下只使用Scipy
来做同样的事情,并在下面编写了代码,但我再次无法解决问题。
from scipy.integrate import quad
import numpy as np
lanr = -6.55
lani = -4.22
def integrand(c,s):
return c * np.exp(lanr * s) * np.sin (lani * s)
def self_integrate(c,s):
return quad(integrand,s,1003,1200)
import pandas as pd
file = pd.read_csv('1-100.csv',sep="\s+",header=None)
s = np.linspace(0,1000,100)
c = np.linspace(0,1,100)
ID = s[-1]
for i in s:
I = self_integrate(integrand,c,s)
print(I)
我得到了这个TypeError: self_integrate() takes 2 positional arguments but 3 were given
假设您要在 s
上集成,并使用 c
作为固定参数(对于给定的 quad
调用),定义:
In [198]: lanr = 1
...: lani = 2
...: def integrand(s, c):
...: return c * np.exp(lanr * s) * np.sin (lani * s)
...:
自行测试:
In [199]: integrand(10,1.23)
Out[199]: 24734.0175253505
并在quad
中进行测试:
In [200]: quad(integrand, 0, 10, args=(1.23,))
Out[200]: (524.9015616747192, 3.381048596651226e-08)
对一系列 c
值执行相同操作:
In [201]: alist = []
...: for c in range(0,10):
...: x,y = quad(integrand, 0, 10, args=(c,))
...: alist.append(x)
...:
In [202]: alist
Out[202]:
[0.0,
426.74923713391905,
853.4984742678381,
1280.2477114017531,
1706.9969485356762,
2133.7461856695877,
2560.4954228035062,
2987.244659937424,
3413.9938970713524,
3840.743134205258]
来自 quad
文档:
quad(func, a, b, args=(),...)
func : {function, scipy.LowLevelCallable}
A Python function or method to integrate. If `func` takes many
arguments, it is integrated along the axis corresponding to the
first argument.
还有一个例子:
>>> f = lambda x,a : a*x
>>> y, err = integrate.quad(f, 0, 1, args=(1,))
文档有点长,但基础知识应该很简单。
我想说你被卡在了 sympy
调用模式上,但第二个参数要么是积分符号,要么是元组。
>>> integrate(log(x), (x, 1, a))
a*log(a) - a + 1
所以我很困惑你为什么坚持使用
quad(integrand,s,1003,1200)
s
无论是sympy变量还是linspace数组都没有意义
通过使用方法并获得Whosebug用户的帮助,我找到了一半的解决方案,我需要完成它。
通过使用 Sympy,我可以参数化地生成我的函数,它变成了 100 个类似于 0.03149536*exp(-4.56*s)*sin(2.33*s) 0.03446408*exp(-4.56*s)*sin(2.33*s)
的不同项目。通过使用 f = lambdify(s,f)
,我将它转换为 NumPy 函数,我需要对 in the different
sthat I already have. The upper limit of the integral is a constant value and the lower limit must be done through a
for 循环进行积分。
当我尝试执行此操作时,出现了一些错误,我在下面 post 进行了说明。我写的代码在下面,但为了成为一个可重现的问题,我必须放置一个生成的数据。 TypeError: cannot determine truth value of Relational
from sympy import exp, sin, symbols, integrate, lambdify
import pandas as pd
import matplotlib.pyplot as plt
from scipy import integrate
import numpy as np
S = np.linspace(0,1000,100)
C = np.linspace(0,1,100)
s, t = symbols('s t')
lanr = -4.56
lani = -2.33
ID = S[-1]
result=[]
f = C * exp(lanr * s) * sin (lani * s)
f = lambdify(s,f)
#vff = np.vectorize(f)
for i in (S):
I = integrate.quad(f,s,(i,ID))
result.append(I)
print(result)
编辑
- 我尝试在没有
Sympy
的情况下只使用Scipy
来做同样的事情,并在下面编写了代码,但我再次无法解决问题。
from scipy.integrate import quad
import numpy as np
lanr = -6.55
lani = -4.22
def integrand(c,s):
return c * np.exp(lanr * s) * np.sin (lani * s)
def self_integrate(c,s):
return quad(integrand,s,1003,1200)
import pandas as pd
file = pd.read_csv('1-100.csv',sep="\s+",header=None)
s = np.linspace(0,1000,100)
c = np.linspace(0,1,100)
ID = s[-1]
for i in s:
I = self_integrate(integrand,c,s)
print(I)
我得到了这个TypeError: self_integrate() takes 2 positional arguments but 3 were given
假设您要在 s
上集成,并使用 c
作为固定参数(对于给定的 quad
调用),定义:
In [198]: lanr = 1
...: lani = 2
...: def integrand(s, c):
...: return c * np.exp(lanr * s) * np.sin (lani * s)
...:
自行测试:
In [199]: integrand(10,1.23)
Out[199]: 24734.0175253505
并在quad
中进行测试:
In [200]: quad(integrand, 0, 10, args=(1.23,))
Out[200]: (524.9015616747192, 3.381048596651226e-08)
对一系列 c
值执行相同操作:
In [201]: alist = []
...: for c in range(0,10):
...: x,y = quad(integrand, 0, 10, args=(c,))
...: alist.append(x)
...:
In [202]: alist
Out[202]:
[0.0,
426.74923713391905,
853.4984742678381,
1280.2477114017531,
1706.9969485356762,
2133.7461856695877,
2560.4954228035062,
2987.244659937424,
3413.9938970713524,
3840.743134205258]
来自 quad
文档:
quad(func, a, b, args=(),...)
func : {function, scipy.LowLevelCallable}
A Python function or method to integrate. If `func` takes many
arguments, it is integrated along the axis corresponding to the
first argument.
还有一个例子:
>>> f = lambda x,a : a*x
>>> y, err = integrate.quad(f, 0, 1, args=(1,))
文档有点长,但基础知识应该很简单。
我想说你被卡在了 sympy
调用模式上,但第二个参数要么是积分符号,要么是元组。
>>> integrate(log(x), (x, 1, a))
a*log(a) - a + 1
所以我很困惑你为什么坚持使用
quad(integrand,s,1003,1200)
s
无论是sympy变量还是linspace数组都没有意义