Partial symbolic derivative in Python

问题

I need to partially derivate my equation and form a matrix out of the derivatives. My equation is: While this conditions must be met: For doing this I've used the sympy module and its diff() function. My code so far is:

from sympy import*
import numpy as np
init_printing() #delete if you dont have LaTeX installed

logt_r, logt_a, T, T_a, a_0, a_1, a_2, logS, Taa_0, Taa_1, Taa_2  = symbols('logt_r, logt_a, T, T_a, a_0, a_1, a_2, logS, Taa_0, Taa_1, Taa_2')

A = (logt_r - logt_a - (T - T_a) * (a_0 + a_1 * logS + a_2 * logS**2) )**2
parametri = [logt_a, a_0, Taa_0, a_1, Taa_1, a_2, Taa_2]

M = expand(A)
M = M.subs(T_a*a_0, Taa_0)
M = M.subs(T_a*a_1, Taa_1)
M = M.subs(T_a*a_2, Taa_2)

K = zeros(len(parametri), len(parametri))
O = []

def odv(par):
    for j in range(len(par)):
        for i in range(len(par)):
            P = diff(M, par[i])/2
            B = P.coeff(par[j])
            K[i,j] = B
    return K 

odv(parametri)

My result:

My problem

The problem that I'm having is in the partial derivatives of products (T_aa_0, T_aa_1 and T_a*a_2), because by using the diff() function, you cannot derivate a function with a product (obviously), else you get an error:

ValueError: 
Can't calculate 1-th derivative wrt T_a*a_0.

To solve this I substitued this products with coefficients, like:

M = M.subs(T_a*a_0, Taa_0)
M = M.subs(T_a*a_1, Taa_1)
M = M.subs(T_a*a_2, Taa_2)

But as you can see in the final result, this works only in some cases. I would like to know if there is a better way of doing this where I wouldn't need to substitude the products and that it would work in all cases.

ADDITIONAL INFORMATION

Let me rephrase my question. Is it possible to symbolically derive an equation with a function by using python or in that matter, to use the sympy module?

回答1:

So I've managed to solve my problem on my own. The main question was how to symbolically derive a function or equation with another function. As I've gone again slowly over the sympy documentation, I saw a little detail, that I've missed before. In order to derive a function with a function you need to change the settings of the function, that will be used to derive. For example:

x, y, z = symbols('x, y, z')
A = x*y*z
B = x*y

# This is the detail:
type(B)._diff_wrt = True
diff(A, B)

Or in my case, the code looks like:

koef = [logt_a, a_0, T_a*a_0, a_1, T_a*a_1, a_2, T_a*a_2]
M = expand(A)
K = zeros(len(koef), len(koef))
def odvod_mat(par):
    for j in range(len(par)):
        for i in range(len(par)):
            type(par[i])._diff_wrt = True
            P = diff(M, par[i])/2
            B = P.coeff(par[j])
            K[i,j] = B

            #Removal of T_a
            K[i,j] = K[i,j].subs(T_a, 0)
    return K  
odvod_mat(koef)

Thanks again to all that were taking their time to read this. I hope this helps to anyone, who will have the same problem as I did.

来源：https://stackoverflow.com/questions/37136697/partial-symbolic-derivative-in-python