Fix quadrature rule hash

FIAT/reference_element.py

@@ -26,6 +26,7 @@
 from math import factorial
 
 import numpy
+from gem.utils import safe_repr
 from recursivenodes.nodes import _decode_family, _recursive
 
 from FIAT.orientation_utils import (
@@ -126,7 +127,7 @@ def linalg_subspace_intersection(A, B):
     return U[:, :rank_c]
 
 
-class Cell(object):
+class Cell:
     """Abstract class for a reference cell.  Provides accessors for
     geometry (vertex coordinates) as well as topology (orderings of
     vertices that make up edges, faces, etc."""
@@ -184,6 +185,9 @@ def __init__(self, shape, vertices, topology):
         # Dictionary with derived cells
         self._split_cache = {}
 
+    def __repr__(self):
+        return f"{type(self).__name__}({self.shape!r}, {safe_repr(self.vertices)}, {self.topology!r})"
+
     def _key(self):
         """Hashable object key data (excluding type)."""
         # Default: only type matters
@@ -1130,6 +1134,9 @@ def __init__(self, *cells):
         super().__init__(TENSORPRODUCT, vertices, topology)
         self.cells = tuple(cells)
 
+    def __repr__(self):
+        return f"{type(self).__name__}({self.cells!r})"
+
     def _key(self):
         return self.cells
 

finat/point_set.py

@@ -1,22 +1,31 @@
-from abc import ABCMeta, abstractproperty
+import abc
+import hashlib
+from functools import cached_property
 from itertools import chain, product
 
 import numpy
 
 import gem
-from gem.utils import cached_property
+from gem.utils import safe_repr
 
 
-class AbstractPointSet(metaclass=ABCMeta):
+class AbstractPointSet(abc.ABC):
     """A way of specifying a known set of points, perhaps with some
     (tensor) structure.
 
     Points, when stored, have shape point_set_shape + (point_dimension,)
     where point_set_shape is () for scalar, (N,) for N element vector,
     (N, M) for N x M matrix etc.
     """
+    def __hash__(self):
+        return int.from_bytes(hashlib.md5(repr(self).encode()).digest(), byteorder="big")
 
-    @abstractproperty
+    @abc.abstractmethod
+    def __repr__(self):
+        pass
+
+    @property
+    @abc.abstractmethod
     def points(self):
         """A flattened numpy array of points or ``UnknownPointsArray``
         object with shape (# of points, point dimension)."""
@@ -27,12 +36,14 @@ def dimension(self):
         _, dim = self.points.shape
         return dim
 
-    @abstractproperty
+    @property
+    @abc.abstractmethod
     def indices(self):
         """GEM indices with matching shape and extent to the structure of the
         point set."""
 
-    @abstractproperty
+    @property
+    @abc.abstractmethod
     def expression(self):
         """GEM expression describing the points, with free indices
         ``self.indices`` and shape (point dimension,)."""
@@ -53,6 +64,9 @@ def __init__(self, point):
         assert len(point.shape) == 1
         self.point = point
 
+    def __repr__(self):
+        return f"{type(self).__name__}({safe_repr(self.point)})"
+
     @cached_property
     def points(self):
         # Make sure we conform to the expected (# of points, point dimension)
@@ -106,6 +120,9 @@ def __init__(self, points_expr):
         assert len(points_expr.shape) == 2
         self._points_expr = points_expr
 
+    def __repr__(self):
+        return f"{type(self).__name__}({self._points_expr!r})"
+
     @cached_property
     def points(self):
         return UnknownPointsArray(self._points_expr.shape)
@@ -133,6 +150,9 @@ def __init__(self, points):
         assert len(points.shape) == 2
         self.points = points
 
+    def __repr__(self):
+        return f"{type(self).__name__}({self.points!r})"
+
     @cached_property
     def points(self):
         pass  # set at initialisation
@@ -177,6 +197,9 @@ class TensorPointSet(AbstractPointSet):
     def __init__(self, factors):
         self.factors = tuple(factors)
 
+    def __repr__(self):
+        return f"{type(self).__name__}({self.factors!r})"
+
     @cached_property
     def points(self):
         return numpy.array([list(chain(*pt_tuple))

finat/quadrature.py

@@ -1,12 +1,13 @@
-from abc import ABCMeta, abstractproperty
-from functools import reduce
+import hashlib
+from abc import ABCMeta, abstractmethod
+from functools import cached_property, reduce
 
 import gem
 import numpy
 from FIAT.quadrature import GaussLegendreQuadratureLineRule
 from FIAT.quadrature_schemes import create_quadrature as fiat_scheme
 from FIAT.reference_element import LINE, QUADRILATERAL, TENSORPRODUCT
-from gem.utils import cached_property
+from gem.utils import safe_repr
 
 from finat.point_set import GaussLegendrePointSet, PointSet, TensorPointSet
 
@@ -60,11 +61,23 @@ class AbstractQuadratureRule(metaclass=ABCMeta):
     """Abstract class representing a quadrature rule as point set and a
     corresponding set of weights."""
 
-    @abstractproperty
+    def __hash__(self):
+        return int.from_bytes(hashlib.md5(repr(self).encode()).digest(), byteorder="big")
+
+    def __eq__(self, other):
+        return type(other) is type(self) and repr(other) == repr(self)
+
+    @abstractmethod
+    def __repr__(self):
+        pass
+
+    @property
+    @abstractmethod
     def point_set(self):
         """Point set object representing the quadrature points."""
 
-    @abstractproperty
+    @property
+    @abstractmethod
     def weight_expression(self):
         """GEM expression describing the weights, with the same free indices
         as the point set."""
@@ -110,6 +123,16 @@ def __init__(self, point_set, weights, ref_el=None, io_ornt_map_tuple=(None, )):
         self.weights = numpy.asarray(weights)
         self._intrinsic_orientation_permutation_map_tuple = io_ornt_map_tuple
 
+    def __repr__(self):
+        return (
+            f"{type(self).__name__}("
+            f"{self.point_set!r}, "
+            f"{safe_repr(self.weights)}, "
+            f"{self.ref_el!r}, "
+            f"{self._intrinsic_orientation_permutation_map_tuple!r}"
+            ")"
+        )
+
     @cached_property
     def point_set(self):
         pass  # set at initialisation
@@ -131,6 +154,9 @@ def __init__(self, factors, ref_el=None):
             for m in factor._intrinsic_orientation_permutation_map_tuple
         )
 
+    def __repr__(self):
+        return f"{type(self).__name__}({self.factors!r}, {self.ref_el!r})"
+
     @cached_property
     def point_set(self):
         return TensorPointSet(q.point_set for q in self.factors)

gem/utils.py

@@ -1,5 +1,11 @@
 import collections
+import functools
+import numbers
 from functools import cached_property  # noqa: F401
+from typing import Any
+
+import numpy as np
+from ufl.constantvalue import format_float
 
 
 def groupby(iterable, key=None):
@@ -88,3 +94,51 @@ def __exit__(self, exc_type, exc_value, traceback):
         assert self.state is variable._head
         value, variable._head = variable._head
         self.state = None
+
+
+@functools.singledispatch
+def safe_repr(obj: Any) -> str:
+    """Return a 'safe' repr for an object, accounting for floating point error.
+
+    Parameters
+    ----------
+    obj :
+        The object to produce a repr for.
+
+    Returns
+    -------
+    str :
+        A repr for the object.
+
+    """
+    raise TypeError(f"Cannot provide a safe repr for {type(obj).__name__}")
+
+
+@safe_repr.register(str)
+def _(text: str) -> str:
+    return text
+
+
+@safe_repr.register(numbers.Integral)
+def _(num: numbers.Integral) -> str:
+    return repr(num)
+
+
+@safe_repr.register(numbers.Real)
+def _(num: numbers.Real) -> str:
+    return format_float(num)
+
+
+@safe_repr.register(np.ndarray)
+def _(array: np.ndarray) -> str:
+    return f"{type(array).__name__}([{', '.join(map(safe_repr, array))}])"
+
+
+@safe_repr.register(list)
+def _(list_: list) -> str:
+    return f"[{', '.join(map(safe_repr, list_))}]"
+
+
+@safe_repr.register(tuple)
+def _(tuple_: tuple) -> str:
+    return f"({', '.join(map(safe_repr, tuple_))})"

test/finat/test_create_fiat_element.py

@@ -59,6 +59,11 @@ def tensor_name(request):
                 ids=lambda x: x.cellname(),
                 scope="module")
 def ufl_A(request, tensor_name):
+    if request.param == ufl.quadrilateral:
+        if tensor_name == "DG":
+            tensor_name = "DQ"
+        elif tensor_name == "DG L2":
+            tensor_name = "DQ L2"
     return finat.ufl.FiniteElement(tensor_name, request.param, 1)
 
 

test/finat/test_quadrature.py

@@ -0,0 +1,19 @@
+import pytest
+
+from FIAT import ufc_cell
+from finat.quadrature import make_quadrature
+
+
+@pytest.mark.parametrize(
+    "cell_name",
+    ["interval", "triangle", "interval * interval", "triangle * interval"]
+)
+def test_quadrature_rules_are_hashable(cell_name):
+    ref_cell = ufc_cell(cell_name)
+    quadrature1 = make_quadrature(ref_cell, 3)
+    quadrature2 = make_quadrature(ref_cell, 3)
+
+    assert quadrature1 is not quadrature2
+    assert hash(quadrature1) == hash(quadrature2)
+    assert repr(quadrature1) == repr(quadrature2)
+    assert quadrature1 == quadrature2