Solving Linear ODE using Python

Improving the Efficiency

I took a hint from manual solution and implemented the following custom function InvLaplace to improve the efficiency by splitting expression using partial fractions and then finding inverse transforms term by term. Here we go:

from sympy import *
from sympy.integrals.transforms import laplace_transform, inverse_laplace_transform

s, L = symbols('s, L')
t= symbols ('t', positive =True)

def InvLaplace(expr):
	ans = 0
	part_frac = expr.apart()	# find partial fractions
	for term in part_frac.args:
		inv_term = inverse_laplace_transform(term,s,t,noconds=True)
		ans = ans + inv_term
	return(ans.simplify())

y0  = 2
y10 = 1	# storing y(0) and y’(0)

Ly2 = s**2*L-s*y0-y10
Ly1= s*L-y0
Ly = L

algeq = Eq(Ly2 - Ly, laplace_transform(cos(t), t, s, noconds = True))

algsoln = solve(algeq, L)[0]
soln = InvLaplace(algsoln)
print("Solution: y(t) = ", soln)

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