merge conflict

Author: pbrubeck

demos/saddle_point_pc/saddle_point_systems.py.rst

@@ -180,7 +180,7 @@ Finally, at each mesh size, we print out the number of cells in the
 mesh and the number of iterations the solver took to converge ::
 
     #
-        print(w.function_space().mesh().num_cells(), solver.snes.ksp.getIterationNumber())
+        print(w.function_space().mesh().unique().num_cells(), solver.snes.ksp.getIterationNumber())
 
 The resulting convergence is unimpressive:
 
@@ -282,7 +282,7 @@ applying the action of blocks, so we can use a block matrix format. ::
     for n in range(8):
         solver, w = build_problem(n, parameters, block_matrix=True)
         solver.solve()
-        print(w.function_space().mesh().num_cells(), solver.snes.ksp.getIterationNumber())
+        print(w.function_space().mesh().unique().num_cells(), solver.snes.ksp.getIterationNumber())
 
 The resulting convergence is algorithmically good, however, the larger
 problems still take a long time.
@@ -367,7 +367,7 @@ Let's see what happens. ::
     for n in range(8):
         solver, w = build_problem(n, parameters, block_matrix=True)
         solver.solve()
-        print(w.function_space().mesh().num_cells(), solver.snes.ksp.getIterationNumber())
+        print(w.function_space().mesh().unique().num_cells(), solver.snes.ksp.getIterationNumber())
 
 This is much better, the problem takes much less time to solve and
 when observing the iteration counts for inverting :math:`S` we can see
@@ -422,7 +422,7 @@ and so we no longer need a flexible Krylov method. ::
     for n in range(8):
         solver, w = build_problem(n, parameters, block_matrix=True)
         solver.solve()
-        print(w.function_space().mesh().num_cells(), solver.snes.ksp.getIterationNumber())
+        print(w.function_space().mesh().unique().num_cells(), solver.snes.ksp.getIterationNumber())
 
 This results in the following GMRES iteration counts
 
@@ -487,7 +487,7 @@ variable. We can provide it as an :class:`~.AuxiliaryOperatorPC` via a python pr
     for n in range(8):
         solver, w = build_problem(n, parameters, aP=None, block_matrix=False)
         solver.solve()
-        print(w.function_space().mesh().num_cells(), solver.snes.ksp.getIterationNumber())
+        print(w.function_space().mesh().unique().num_cells(), solver.snes.ksp.getIterationNumber())
 
 This actually results in slightly worse convergence than the diagonal
 approximation we used above.
@@ -571,7 +571,7 @@ Let's see what the iteration count looks like now. ::
     for n in range(8):
         solver, w = build_problem(n, parameters, aP=riesz, block_matrix=True)
         solver.solve()
-        print(w.function_space().mesh().num_cells(), solver.snes.ksp.getIterationNumber())
+        print(w.function_space().mesh().unique().num_cells(), solver.snes.ksp.getIterationNumber())
 
 ============== ==================
  Mesh elements  GMRES iterations

docs/source/conf.py

@@ -172,6 +172,8 @@
     r'https://www.hilton.com/en/hotels/leehnhn-hilton-leeds-city/',
     r'https://www.radissonhotels.com/en-us/hotels/park-plaza-leeds',
     r'https://www.radissonhotels.com/en-us/hotels/radisson-blu-leeds'
+    r'https://www.radissonhotels.com/en-us/hotels/radisson-blu-leeds',
+    r'https://all.accor.com/hotel/*',
 ]
 linkcheck_timeout = 30
 
@@ -413,10 +415,8 @@
 
 intersphinx_mapping = {
     'pyop2': ('https://op2.github.io/PyOP2', None),
-    'ufl': ('https://fenics.readthedocs.io/projects/ufl/en/latest/', None),
     'ufl': ('https://docs.fenicsproject.org/ufl/main/', None),
-    'FIAT': ('https://fenics.readthedocs.io/projects/fiat/en/latest/', None),
-    'FInAT': ('https://finat.github.io/FInAT/', None),
+    'FIAT': ('https://firedrakeproject.org/fiat', None),
     'petsctools': ('https://firedrakeproject.org/petsctools/', None),
     'mpi4py': ('https://mpi4py.readthedocs.io/en/stable/', None),
     'h5py': ('http://docs.h5py.org/en/latest/', None),

docs/source/install.rst

@@ -590,7 +590,7 @@ should be followed:
 
 #. Install Firedrake in editable mode without build isolation::
 
-   $ pip install --no-build-isolation --no-binary h5py --editable './firedrake[check]'
+   $ pip install --no-build-isolation --no-binary h5py --editable './firedrake[check,docs]'
 
 
 Editing subpackages

firedrake/adjoint_utils/blocks/solving.py

@@ -163,6 +163,13 @@ def _should_compute_boundary_adjoint(self, relevant_dependencies):
     def adj_sol(self):
         return self.adj_state
 
+    @adj_sol.setter
+    def adj_sol(self, value):
+        if self.adj_state is None:
+            self.adj_state = value.copy(deepcopy=True)
+        else:
+            self.adj_state.assign(value)
+
     def prepare_evaluate_adj(self, inputs, adj_inputs, relevant_dependencies):
         fwd_block_variable = self.get_outputs()[0]
         u = fwd_block_variable.output
@@ -187,7 +194,7 @@ def prepare_evaluate_adj(self, inputs, adj_inputs, relevant_dependencies):
         adj_sol, adj_sol_bdy = self._assemble_and_solve_adj_eq(
             dFdu_form, dJdu, compute_bdy
         )
-        self.adj_state = adj_sol
+        self.adj_sol = adj_sol
         if self.adj_cb is not None:
             self.adj_cb(adj_sol)
         if self.adj_bdy_cb is not None and compute_bdy:
@@ -408,7 +415,7 @@ def prepare_evaluate_hessian(self, inputs, hessian_inputs, adj_inputs,
             firedrake.derivative(dFdu_form, fwd_block_variable.saved_output,
                                  tlm_output))
 
-        adj_sol = self.adj_state
+        adj_sol = self.adj_sol
         if adj_sol is None:
             raise RuntimeError("Hessian computation was run before adjoint.")
         bdy = self._should_compute_boundary_adjoint(relevant_dependencies)
@@ -726,7 +733,7 @@ def prepare_evaluate_adj(self, inputs, adj_inputs, relevant_dependencies):
             relevant_dependencies
         )
         adj_sol, adj_sol_bdy = self._adjoint_solve(adj_inputs[0], compute_bdy)
-        self.adj_state = adj_sol
+        self.adj_sol = adj_sol
         if self.adj_cb is not None:
             self.adj_cb(adj_sol)
         if self.adj_bdy_cb is not None and compute_bdy:

firedrake/adjoint_utils/variational_solver.py

@@ -27,7 +27,7 @@ def wrapper(self, *args, **kwargs):
                     # Try again without expanding derivatives,
                     # as dFdu might have been simplied to an empty Form
                     self._ad_adj_F = adjoint(dFdu, derivatives_expanded=True)
-            except (TypeError, NotImplementedError):
+            except (ValueError, TypeError, NotImplementedError):
                 self._ad_adj_F = None
             self._ad_kwargs = {'Jp': self.Jp, 'form_compiler_parameters': self.form_compiler_parameters, 'is_linear': self.is_linear}
             self._ad_count_map = {}