def _compute_input_activations(self, X):

        n_samples = X.shape[0]

        mlp_acts = np.zeros((n_samples, self.n_hidden))
        if (self._use_mlp_input):
            b = self.components_['biases']
            w = self.components_['weights']
            mlp_acts = self.alpha * (safe_sparse_dot(X, w) + b)

        rbf_acts = np.zeros((n_samples, self.n_hidden))
        if (self._use_rbf_input):
            radii = self.components_['radii']
            centers = self.components_['centers']
            scale = self.rbf_width * (1.0 - self.alpha)
            rbf_acts = scale * cdist(X, centers)/radii

        self.input_activations_ = mlp_acts + rbf_acts
Return a subview at the given location (default top left) and size (default maximum).
dataset/ETHPy150Open dclambert/Python-ELM/random_layer.py/RandomLayer._compute_input_activations--crossover with--dataset/ETHPy150Open adurdin/platformgen/tilemap.py/TileMap.subview