Numerical solution

my goal is to solve this equation numerically on python $0=\int_{0}^{s} f(x) dx$(assuming that a solution exists). I initially attempted it through sympy however it's quite limited in what functions it can solve, for example it fails for f(x)=1+sin(x).

I searched a bit online and it seems scipy.optimise.fsolve is a feasible solution? my issue is that the upper bound of the integral is symbolic so script.integrate doesn't work?

How do I go about implementing the code for this

my goal is to solve this equation numerically on python $0=\int_{0}^{s} f(x) dx$(assuming that a solution exists). I initially attempted it through sympy however it's quite limited in what functions it can solve, for example it fails for f(x)=1+sin(x).

I searched a bit online and it seems scipy.optimise.fsolve is a feasible solution? my issue is that the upper bound of the integral is symbolic so script.integrate doesn't work?

How do I go about implementing the code for this

Assuming a solution exists limits you to a particular class of functions $f$ ... your example of $1 + \sin x$ is not in this class so of course it failed. There is no solution to find for this choice of function.

Test it for something like $f(x) = 1-x$ where you know the solution must be $s = 2$.

Are you after a numerical or symbolic solution? Not used sympy but combining integrate and solve should do what yorue after?

I'm after a numerical solution, I attempted it on python but it gives an error. The issue is that scipy doesn't accept symbolic bounds in the integral compared to sympy.

My code that I attempted is this:

scipy.optimize.fsolve(lambda x: scipy.integrate.quad(lambda x: x+1, 0, x), 0.1)

(for when f(x)=x+1)

Does integrate() and solve() work for a sympbolic solution? Integrate() allows you to put a variable in as an upper bound which I presume could be used in solve() to get the value.

Also, I would have thought that x=0 would be the solution to your previous example?

Also I shouldn't have put 0 on the lefthand side, it should be positive, a realisation from $Z\sim exp(1)$.

I already implemented the code in sympy, it works for polynomials and other singular term functions that are easy to invert. But when I ran it for $z=\int_{0}^{s} f(x)$ it comes up with the error saying there's no algorithm to solve it in sympy hence now I'm looking for a numerical solution for more complicated equations that sympy can't handle

Like in wolfram
https://www.wolframalpha.com/input?i=solve+integrate+from+0+to+x+%281%2Bsin%28t%29%29+dt+%3D+e%5E1
youd not get a symbolic solution from
1 + x - cos(x) = e
But Id be surprised if you couldnt combine the symbolic integral (1+x-cos(x)) and evaluate it numerically and combine it with a numerical search. So something like combine it with subs() or evalf() and put a simple wrapper function round it?

When you say wrapper function is it like a while loop that iterates x until you're a certain tolerance away from 0?

fsolve calls a function, so if that function contains subs/feval/... and the symbolic integral then it shouldnt need a loop. If you dont use the symbolic integral, then youd need to do a numerical integral yourself or ... Depends on what you want to do.

would you mind providing an example for your first suggestion?

Probably not. Havent got python on this machine and not used sympy (but used others). But Id guess its a combination of
* Defining your function for fsolve
https://www.youtube.com/watch?v=nnCDaHCulAU&ab_channel=APMonitor.com
* Evaluating the symbolic expression for the integral (upper limit is x say)
https://www.tutorialspoint.com/sympy/sympy_integration.htm
* Use something like lambidfy() to get the numeric value of the definite integral
https://www.tutorialspoint.com/sympy/sympy_lambdify_function.htm#:~:text=The%20lambdify%20function%20translates%20SymPy,given%20numerical%20library%2C%20usually%20NumPy.
The function should just be a couple of lines

Ideally, the symbolic integration should be evaluated one and either hard coded or passed into the function as it doesnt change, but whatever is easiest to get it working first. You could even just pass the function handle returned by lambidfy into the function fsolve calls (possibly/somehow).