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)

        # TRANSFORMATION IN SEARCH SPACE
        x = 2 * self.arrsigns * x # makes the below boundary handling effective for coordinates
        try:
            x[:, 1:] = x[:, 1:] + .25 * (x[:, :-1] - self.arrxopt[:, :-1])
        except IndexError:
            x[1:] = x[1:] + .25 * (x[:-1] - self.arrxopt[:-1])
        x = 100. * (self.arrscales * (x - self.arrxopt) + self.arrxopt)

        # BOUNDARY HANDLING
        xoutside = np.maximum(0., np.abs(x) - 500.) * sign(x) # in [-500, 500]
        fpen = 0.01 * np.sum(xoutside ** 2, -1)
        fadd = fadd + fpen

        # COMPUTATION core
        ftrue = 0.01 * ((418.9828872724339) - np.mean(x * np.sin(np.sqrt(np.abs(x))), -1))
        fval = self.noise(ftrue)

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