Sure, sorry about the image, I was unaware of how easy is to generate
python code with the print methods
from sympy import Symbol, Matrix,I
gamma_c = Symbol('gamma_c')
n_c = Symbol('n_c')
gamma_h = Symbol('gamma_h')
n_h = Symbol('n_h')
epsilon_c = Symbol('epsilon_c')
g = Symbol('g')
epsilon_h = Symbol('epsilon_h')
e = Matrix([[-gamma_c*(n_c + 1) - gamma_h*(n_h + 1), 0, 0, 0, 0,
gamma_c*n_c, 0, 0, 0, 0, gamma_h*n_h, 0, 0, 0, 0, 0], [0, -I*epsilon_c -
gamma_c*n_c/2 - gamma_c*(n_c + 1)/2 - gamma_h*(n_h + 1), I*g, 0, 0, 0, 0,
0, 0, 0, 0, gamma_h*n_h, 0, 0, 0, 0], [0, I*g, -I*epsilon_h - gamma_c*(n_c
+ 1) - gamma_h*n_h/2 - gamma_h*(n_h + 1)/2, 0, 0, 0, 0, gamma_c*n_c, 0, 0,
0, 0, 0, 0, 0, 0], [0, 0, 0, -gamma_c*n_c/2 - gamma_c*(n_c + 1)/2 -
gamma_h*n_h/2 - gamma_h*(n_h + 1)/2 - I*(epsilon_c + epsilon_h), 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, -gamma_c*n_c/2 - gamma_c*(n_c +
1)/2 - gamma_h*(n_h + 1) - I*(epsilon_h - (epsilon_c + epsilon_h)), 0, 0,
0, -I*g, 0, 0, 0, 0, 0, gamma_h*n_h, 0], [gamma_c*(n_c + 1) - gamma_h*n_h,
0, 0, 0, 0, -gamma_c*n_c - gamma_h*n_h - gamma_h*(n_h + 1), I*g, 0, 0,
-I*g, -gamma_h*n_h, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, I*g, -gamma_c*n_c/2 -
gamma_c*(n_c + 1)/2 - gamma_h*n_h/2 - gamma_h*(n_h + 1)/2 - I*(-epsilon_c +
epsilon_h), 0, 0, 0, -I*g, 0, 0, 0, 0, 0], [0, 0, gamma_c*(n_c + 1), 0, 0,
0, 0, -I*epsilon_h - gamma_c*n_c - gamma_h*n_h/2 - gamma_h*(n_h + 1)/2, 0,
0, 0, -I*g, 0, 0, 0, 0], [0, 0, 0, 0, -I*g, 0, 0, 0, -gamma_c*(n_c + 1) -
gamma_h*n_h/2 - gamma_h*(n_h + 1)/2 - I*(epsilon_c - (epsilon_c +
epsilon_h)), 0, 0, 0, 0, gamma_c*n_c, 0, 0], [0, 0, 0, 0, 0, -I*g, 0, 0, 0,
-gamma_c*n_c/2 - gamma_c*(n_c + 1)/2 - gamma_h*n_h/2 - gamma_h*(n_h + 1)/2
- I*(epsilon_c - epsilon_h), I*g, 0, 0, 0, 0, 0], [-gamma_c*n_c +
gamma_h*(n_h + 1), 0, 0, 0, 0, -gamma_c*n_c, -I*g, 0, 0, I*g, -gamma_c*n_c
- gamma_c*(n_c + 1) - gamma_h*n_h, 0, 0, 0, 0, 0], [0, gamma_h*(n_h + 1),
0, 0, 0, 0, 0, -I*g, 0, 0, 0, -I*epsilon_c - gamma_c*n_c/2 - gamma_c*(n_c +
1)/2 - gamma_h*n_h, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-gamma_c*n_c/2 - gamma_c*(n_c + 1)/2 - gamma_h*n_h/2 - gamma_h*(n_h + 1)/2
+ I*(epsilon_c + epsilon_h), 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0,
gamma_c*(n_c + 1), 0, 0, 0, 0, I*epsilon_h - gamma_c*n_c - gamma_h*n_h/2 -
gamma_h*(n_h + 1)/2, I*g, 0], [0, 0, 0, 0, gamma_h*(n_h + 1), 0, 0, 0, 0,
0, 0, 0, 0, I*g, I*epsilon_c - gamma_c*n_c/2 - gamma_c*(n_c + 1)/2 -
gamma_h*n_h, 0], [gamma_c*n_c + gamma_h*n_h, 0, 0, 0, 0, gamma_c*n_c +
gamma_h*n_h + gamma_h*(n_h + 1), 0, 0, 0, 0, gamma_c*n_c + gamma_c*(n_c +
1) + gamma_h*n_h, 0, 0, 0, 0, 0]])
However, I care more about how to speed up matrix inversion in general, as
it was terribly fast in Mathematica and it never finished in sympy. I guess
there is a more efficient way than using
e.inv()
El martes, 11 de enero de 2022 a las 3:21:33 UTC+1, Oscar escribió:
> On Monday, 10 January 2022 at 15:51:49 UTC [email protected] wrote:
>
>> Hi,
>>
>> So I was working in some problem and I had to switch to mathematica due
>> to the time the inverse of a matrix was taking, in mathematica it was
>> solved in less than a second while the computation in sympy has been
>> running for a day and hasn't finished.
>>
>> Is there anyway to speed up matrix inversion in sympy?
>>
>> Given that it is so much faster in mathematica is there any interest in
>> implementing some method (maybe theirs) that yields the inverse of a matrix
>> faster? if so I'd like to do it maybe someone could give me some pointers
>> to get me started
>>
>> The matrix is 15*15 and attached as an image, but any example of how to
>> speed things up will do. Thanks a lot!
>>
>
> The image is not a useful way to share this. Can you show simple code to
> make this matrix?
>
> (i.e. just the code to make the symbols and then something like the repr()
> of the matrix but make sure it's fully runnable code without any missing
> bits)
>
> --
> Oscar
>
--
You received this message because you are subscribed to the Google Groups
"sympy" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to [email protected].
To view this discussion on the web visit
https://groups.google.com/d/msgid/sympy/5fb279aa-81e9-49ca-bbed-0a65e184c507n%40googlegroups.com.
