

def _increment(self, data, verbose):
    self.precision = 0
    if (self.graph.n_edges == 0):
        if self.sparse:
            constructor = _increment_sparse_diagonal_precision
        else:
            constructor = _increment_dense_diagonal_precision
    elif self.sparse:
        constructor = partial(_increment_sparse_precision, mode=self.mode)
    else:
        constructor = partial(_increment_dense_precision, mode=self.mode)
    (constructor.precision, self._covariance_matrices) = constructor(data, self.mean_vector, self._covariance_matrices, self.n_samples, self.graph, self.n_features, self.n_features_per_vertex, dtype=self.dtype, n_components=self.n_components, bias=self.bias, verbose=verbose)
    self.mean_vector = _increment_multivariate_gaussian_mean(data, self.mean_vector, self.n_samples)
    self.n_samples += data.shape[0]

dataset/ETHPy150Open menpo/menpo/menpo/model/gmrf.py GMRFVectorModel._increment/VarMisuse@95/119 `self`->`constructor`