def instance_vectors(self, weights, normalized_weights=False):
        weights = np.asarray(weights)  # if eg a list is provided
        n_instances, n_weights = weights.shape
        if n_weights > self.n_active_components:
            raise ValueError(
                "Number of weightings cannot be greater than {}".format(
                    self.n_active_components))
        else:
            full_weights = np.zeros((n_instances, self.n_active_components),
                                    dtype=self._components.dtype)
            full_weights[..., :n_weights] = weights
            weights = full_weights

        if normalized_weights:
            # If the weights were normalized, then they are all relative to
            # to the scale of the eigenvalues and thus must be multiplied by
            # the sqrt of the eigenvalues.
            weights *= self.eigenvalues ** 0.5
        return self._instance_vectors_for_full_weights(weights)
Creates new vectorized instances of the model using the first
dataset/ETHPy150Open menpo/menpo/menpo/model/pca.py/PCAVectorModel.instance_vectors