bbobbenchmarks.py 文件源码

def _evalfull(self, x):
        fadd = self.fopt
        curshape, dim = self.shape_(x)
        # it is assumed x are row vectors

        if self.lastshape != curshape:
            self.initwithsize(curshape, dim)

        # BOUNDARY HANDLING

        # TRANSFORMATION IN SEARCH SPACE
        x = x - self.arrxopt
        x = monotoneTFosc(x)
        idx = (x > 0)
        x[idx] = x[idx] ** (1 + self.arrexpo[idx] * np.sqrt(x[idx]))
        x = self.arrscales * x

        # COMPUTATION core
        ftrue = 10 * (self.dim - np.sum(np.cos(2 * np.pi * x), -1)) + np.sum(x ** 2, -1)
        fval = self.noise(ftrue) # without noise

        # FINALIZE
        ftrue += fadd
        fval += fadd
        return fval, ftrue