pypet/parameter.py
def _values_of_same_type(self, val1, val2):
        """Checks if two values agree in type.

        Raises a TypeError if both values are not supported by the parameter.
        Returns false if only one of the two values is supported by the parameter.

        Example usage:

        >>>param._values_of_same_type(42,43)
        True

        >>>param._values_of_same_type(42,'43')
        False

        :raises: TypeError

        """
        if self.f_supports(val1) != self.f_supports(val2):
            return False

        if not self.f_supports(val1) and not self.f_supports(val2):
            raise TypeError('I do not support the types of both inputs (`%s` and `%s`),'
                            ' therefore I cannot judge whether the two are of same type.' %
                            str(type(val1)), str(type(val2)))

        if not type(val1) is type(val2):
            return False

        # Numpy arrays must agree in data type and shape
        if type(val1) is np.array:
            if not val1.dtype is val2.dtype:
                return False

            if not np.shape(val1) == np.shape(val2):
                return False

        # For tuples we now from earlier checks that the data is homogeneous.
        # Thus, only the type of the first item and the length must agree.
        if type(val1) is tuple:
            return (type(val1[0]) is type(val2[0])) and (len(val1) == len(val2))

        return True
def _values_of_same_type(self, val1, val2):
        """Checks if two values agree in type.

        Raises a TypeError if both values are not supported by the parameter.
        Returns false if only one of the two values is supported by the parameter.

        Example usage:

        >>>param._values_of_same_type(42,43)
        True

        >>>param._values_of_same_type(42,'43')
        False

        :raises: TypeError

        """
        if self.f_supports(val1) != self.f_supports(val2):
            return False

        if not self.f_supports(val1) and not self.f_supports(val2):
            raise TypeError('I do not support the types of both inputs (`%s` and `%s`),'
                            ' therefore I cannot judge whether the two are of same type.' %
                            str(type(val1)), str(type(val2)))

        if not type(val1) is type(val2):
            return False

        # Numpy arrays must agree in data type and shape
        if type(val1) is np.array:
            if not val1.dtype is val2.dtype:
                return False

            if not np.shape(val1) == np.shape(val2):
                return False

        # For tuples we now from earlier checks that the data is homogeneous.
        # Thus, only the type of the first item and the length must agree.
        if type(val1) is tuple:
            return (type(val1[0]) is type(val2[0])) and (len(val1) == len(val2))

        return True
Checks if two values agree in type.

        Raises a TypeError if both values are not supported by the parameter.
        Returns false if only one of the two values is supported by the parameter.

        Example usage:

        >>>param._values_of_same_type(42,43)
        True

        >>>param._values_of_same_type(42,'43')
        False

        :raises: TypeError