In scipy.optimize.differential_evolution, the convergence criteria are that:
the solving stops when
np.std(population_energies) <=
atol + tol * np.abs(np.mean(population_energies))
where atol and tol are the
absolute and relative tolerance respectively.
This begs the question, what are 'population energies' please?
This could be a follow up question to: Explain the intuition for the tol paramer in scipy differential evolution
I tried looking in the code, but I got:
self.population_energies = np.ones(popsize * parameter_count) * np.inf
self.population_energies[index] = self.func(parameters,*self.args)
So a follow up question would be what does that do please?