# Source code for ufl.averaging

    """Averaging operations."""

    # Copyright (C) 2008-2016 Martin Sandve Alnæs
    #
    # This file is part of UFL (https://www.fenicsproject.org)
    #
    # SPDX-License-Identifier:    LGPL-3.0-or-later

    from ufl.constantvalue import ConstantValue
    from ufl.core.operator import Operator
    from ufl.core.ufl_type import ufl_type

    @ufl_type(
        inherit_shape_from_operand=0, inherit_indices_from_operand=0, num_ops=1, is_evaluation=True
    )
    class CellAvg(Operator):
        """Cell average."""

        __slots__ = ()

        def __new__(cls, f):
            """Create a new CellAvg."""
            if isinstance(f, ConstantValue):
                return f
            return super().__new__(cls)

        def __init__(self, f):
            """Initialise."""
            Operator.__init__(self, (f,))

        @property
        def ufl_shape(self):
            """Get the UFL shape."""
            return self.ufl_operands[0].ufl_shape

        def evaluate(self, x, mapping, component, index_values):
            """Performs an approximate symbolic evaluation, since we don't have a cell."""
            return self.ufl_operands[0].evaluate(x, mapping, component, index_values)

        def __str__(self):
            """Format as a string."""
            return f"cell_avg({self.ufl_operands[0]})"

    @ufl_type(
        inherit_shape_from_operand=0, inherit_indices_from_operand=0, num_ops=1, is_evaluation=True
    )
    class FacetAvg(Operator):
        """Facet average."""

        __slots__ = ()

        def __new__(cls, f):
            """Create a new FacetAvg."""
            if isinstance(f, ConstantValue):
                return f
            return super().__new__(cls)

        def __init__(self, f):
            """Initialise."""
            Operator.__init__(self, (f,))

        @property
        def ufl_shape(self):
            """Return the UFL shape."""
            return self.ufl_operands[0].ufl_shape

        def evaluate(self, x, mapping, component, index_values):
            """Performs an approximate symbolic evaluation, since we dont have a cell."""
            return self.ufl_operands[0].evaluate(x, mapping, component, index_values)

        def __str__(self):
            """Format as a string."""
            return f"facet_avg({self.ufl_operands[0]})"