The difference between scipy.optimize.fsolve and sympy's solve functions

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I am trying to figure out the differences between Optimize.fsolve and SymPys solve function? **Is there a difference in computation or are the constraints as to which method to use?**Is Scipy fsolve more accurate than Numpy solve function?

The obvious difference I found is that Scipy.Optimize.Fsolve can solve non linear equations given a guess value, whereas SymPys solve function can be used to solve equations and expressions that contion symbolic math variables.

Any reference literature or website which you can share will be much appreciated.

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