def evalfun(self, inputx):
        """
        This is like self.f.evalfun(), i.e. evaluating the benchmark
        function, but without incrementing usage counters.  This may be
        used only for re-evaluating a function at a point we already
        obtained but simply cannot conveniently retrieve right now;
        i.e. a value returned from the method black-box.
        """
        if self.f._is_rowformat:
            x = np.asarray(inputx)
        else:
            x = np.transpose(inputx)
        out = self.f._fun_evalfull(x)
        try:
            return out[0]
        except __HOLE__:
            return out
dataset/ETHPy150Open pasky/cocopf/experiment.py/FInstance.evalfun