def predict(self, x):

        super(ResponseSurface, self).predict(x)

        n = x.size

        X = zeros(((self.n + 1) * (self.n + 2)) // 2)

        # Modify X to include constant, squared terms and cross terms

        # Constant Terms
        X[0] = 1.0

        # Linear Terms
        X[1:n + 1] = x

        # Quadratic Terms
        X_offset = X[n + 1:]
        for i in range(n):
            X_offset[:n - i] = x[i] * x[i:]
            X_offset = X_offset[n - i:]

        # Predict new_y using X and betas
        return X.dot(self.betas)
Look up a species from the index and return contents of species
dataset/ETHPy150Open OpenMDAO/OpenMDAO/openmdao/surrogate_models/response_surface.py/ResponseSurface.predict--crossover with--dataset/ETHPy150Open wizzomafizzo/starcheat/starcheat/assets/species.py/Species.get_species