def step_one(self, i):
        """
        Perform a single minimization step with member i.
        Returns an (x,y) tuple.
        """
        for retry in [0,1]: # retry once if StopIteration
            try:
                # Step by a single iteration of the minimizer
                self.points[i] = self.minimizers[i].next()
                x = self.points[i]
                break
            except StopIteration:
                # Local optimum, pick a new random point
                x = self.points[i]
                self.restart_one(i)
                # We did no computation for [i] yet in this iteration
                # so make a step right away
                continue

        # Get the value at this point
        y = self.fi.evalfun(x)
        self.values[i] = y
        self.iters[i] += 1
        self.total_steps += 1
        self.data.record(i, self.minimizers[i].minmethod.name, self.iters[i], self.fi.f.fopt - self.values[i], self.points[i])
        return (x, y)
dataset/ETHPy150Open pasky/cocopf/population.py/Population.step_one/swapped operands of `-`