33a33b24185e45478c4758ac14cab8ae5234c44b,pgmpy/inference/base_continuous.py,GradientLogPDF,__init__,#GradientLogPDF#Any#Any#,112

Before Change

    def __init__(self, theta, model):
        // TODO: Take model as parameter instead of precision_matrix

        if not isinstance(theta, np.matrix):
            if isinstance(theta, (np.ndarray, list, tuple, set, frozenset)):
                length = len(theta)
                theta = np.matrix(theta)
                theta = np.reshape(theta, (1, length))
            else:
                raise TypeError("theta should be a 1d array type object")
            theta = np.reshape(theta, (len(theta), 1))

        if theta.shape[1] != model.precision_matrix.shape[0]:
            raise ValueError("shape of theta vector should be 1 X d if shape" +
                             " of precision matrix of model is d X d")
        self.theta = theta

After Change

    def __init__(self, theta, model):
        // TODO: Take model as parameter instead of precision_matrix

        if isinstance(theta, (np.matrix, np.ndarray, list, tuple, set, frozenset)):
            theta = np.array(theta).flatten()
            theta = np.matrix(np.reshape(theta, (len(theta), 1)))
        else:
            raise TypeError("theta should be a 1d array type object")

        if theta.shape[0] != model.precision_matrix.shape[0]:
            raise ValueError("shape of theta vector should be 1 X d if shape" +
                             " of precision matrix of model is d X d")
        self.theta = theta

Instances