pyop3: matnest

firedrake/assemble.py

@@ -1280,15 +1280,15 @@ def TwoFormAssembler(form, *args, **kwargs):
     assert isinstance(form, (ufl.form.Form, slate.TensorBase))
     mat_type = kwargs.pop('mat_type', None)
     sub_mat_type = kwargs.pop('sub_mat_type', None)
-    mat_type, sub_mat_type = _get_mat_type(mat_type, sub_mat_type, form.arguments())
+    mat_type, sub_mat_type, block_shape = _get_mat_type(mat_type, sub_mat_type, form.arguments())
     if mat_type == "matfree":
         # Arguably we should crash here, as we would be passing ignored arguments through
         kwargs.pop('needs_zeroing', None)
         kwargs.pop('weight', None)
         kwargs.pop('allocation_integral_types', None)
         return MatrixFreeAssembler(form, *args, **kwargs)
     else:
-        return ExplicitMatrixAssembler(form, *args, mat_type=mat_type, sub_mat_type=sub_mat_type, **kwargs)
+        return ExplicitMatrixAssembler(form, *args, mat_type=mat_type, sub_mat_type=sub_mat_type, block_shape=block_shape, **kwargs)
 
 
 def _get_mat_type(mat_type, sub_mat_type, arguments):
@@ -1332,6 +1332,8 @@ def _get_mat_type(mat_type, sub_mat_type, arguments):
 
     if mat_type == "nest":
         mat_type = {}
+        block_shape = dict()
+
         test, trial = arguments
         for test_subspace in test.function_space():
             for trial_subspace in trial.function_space():
@@ -1340,9 +1342,10 @@ def _get_mat_type(mat_type, sub_mat_type, arguments):
                     mat_type[subspace_key] = "dat"
                 else:
                     mat_type[subspace_key] = sub_mat_type
+                block_shape[subspace_key] = test_subspace.value_size, trial_subspace.value_size
 
     # sub_mat_type no longer used after this
-    return mat_type, sub_mat_type
+    return mat_type, sub_mat_type, block_shape
 
 
 class ExplicitMatrixAssembler(ParloopFormAssembler):
@@ -1369,14 +1372,16 @@ def _cache_key(cls, *args, **kwargs):
     @FormAssembler._skip_if_initialised
     def __init__(self, form, bcs=None, form_compiler_parameters=None, needs_zeroing=True,
                  mat_type=None, sub_mat_type=None, options_prefix=None, appctx=None, weight=1.0,
-                 allocation_integral_types=None):
+                 allocation_integral_types=None,
+                 block_shape=None):
         # The previous API was that the user would specify mat_type and sub_mat_type, now
         # mat_type can be a dict so convert to that here.
         # NOTE: This function is called in TwoFormAssembler, should it be?
         # mat_type, sub_mat_type = _get_mat_type(mat_type, sub_mat_type, form.arguments())
 
         super().__init__(form, bcs=bcs, form_compiler_parameters=form_compiler_parameters, needs_zeroing=needs_zeroing)
         self._mat_type = mat_type
+        self._block_shape = block_shape
         self._options_prefix = options_prefix
         self._appctx = appctx
         self.weight = weight
@@ -1389,6 +1394,7 @@ def allocate(self):
             trial,
             self._mat_type,
             self._make_maps_and_regions(),
+            block_shape=self._block_shape,
         )
         mat = op3.Mat.from_sparsity(sparsity)
         return matrix.Matrix(
@@ -1401,15 +1407,16 @@ def allocate(self):
         )
 
     @staticmethod
-    def _make_sparsity(test, trial, mat_type, maps_and_regions):
+    def _make_sparsity(test, trial, mat_type, maps_and_regions, block_shape=None):
         # Is this overly restrictive?
         if any(len(a.function_space()) > 1 for a in [test, trial]) and mat_type == "baij":
             raise ValueError("BAIJ matrix type makes no sense for mixed spaces, use 'aij'")
 
         sparsity = op3.Sparsity(
             test.function_space().axes,
             trial.function_space().axes,
-            mat_type=mat_type
+            mat_type=mat_type,
+            block_shape=block_shape,
         )
 
         # Pretend that we are doing assembly by looping over the right