joss-dev

INSTALL.md

@@ -11,12 +11,11 @@
  - PETSc dependencies: `parmetis`, `scotch`, `suitesparse`, `superlu_dist`, `ml`, `hypre`
  - (optional): `gmsh`, `mshr`, `jupyter`
 
-
 ## Recommended installation using Anaconda 
 ### Installation with pip 
 1. Create an environment with `FEniCS` and appropriate dependencies and activate environment
 ```
-conda create -n soupy -c conda-forge fenics==2019.1.0 matplotlib scipy jupyter
+conda create -n soupy -c conda-forge python=3.11 fenics==2019.1.0 petsc4py==3.19 matplotlib scipy jupyter
 conda activate soupy
 ```
 
@@ -40,7 +39,7 @@ Examples in the `applications` directory can now be run. We refer to the full `F
 ### Installation for developers 
 1. Create an environment with `FEniCS` with appropriate dependencies
 ```
-conda create -n soupy -c conda-forge fenics==2019.1.0 matplotlib scipy jupyter
+conda create -n soupy -c conda-forge python=3.11 fenics==2019.1.0 petsc4py==3.19 matplotlib scipy jupyter
 ```
 
 2. Clone the `hIPPYlib` [repository](https://github.com/hippylib/hippylib). 

examples/hyperelasticity/driver_hyperelasticity.py

@@ -154,7 +154,7 @@
     plt.savefig("%s/u_soft.png" %(save_dir))
 
     plt.figure()
-    ax = dl.plot(hp.vector2Function(x[soupy.CONTROL], Vh[soupy.CONTROL]))
+    ax = dl.plot(hp.vector2Function(x[soupy.CONTROL], Vh[soupy.CONTROL]), vmin=0.0, vmax=1.0, extend='max')
     plt.colorbar(ax)
     plt.title("Optimal design")
     plt.savefig("%s/z_opt.png" %(save_dir))

examples/hyperelasticity/hyperelasticityControlPDE.py

@@ -126,7 +126,7 @@ def __init__(self, Vh, varf_handler, bc, bc0, load_steps=[1.0], max_newton_iter=
         self.max_newton_iter_increment = max_newton_iter_increment
         self.backtrack = backtrack
 
-        default_solver_parameters = {'newton_solver': {'linear_solver' : 'lu', 'maximum_iterations': self.max_newton_iter}}
+        default_solver_parameters = {'newton_solver': {'linear_solver' : 'lu', 'maximum_iterations': self.max_newton_iter, 'error_on_nonconvergence' : False}}
         self.default_newton_solver = soupy.NonlinearVariationalSolver(default_solver_parameters)
 
         self.backtrack_newton_solver = soupy.NewtonBacktrackSolver()
@@ -141,25 +141,24 @@ def solveFwd(self, state, x):
             Do load increments using backtracking newton if full solve fails
         """
         self.n_calls["forward"] += 1
-        try:
-            print("Process %d: Try immediate solve" %(MPI.COMM_WORLD.Get_rank()))
-            # Make functions 
-            u = hp.vector2Function(x[soupy.STATE], self.Vh[soupy.STATE])
-            m = hp.vector2Function(x[soupy.PARAMETER], self.Vh[soupy.PARAMETER])
-            p = dl.TestFunction(self.Vh[soupy.ADJOINT])
-            z = hp.vector2Function(x[soupy.CONTROL], self.Vh[soupy.CONTROL])
+        print("Process %d: Try immediate solve" %(MPI.COMM_WORLD.Get_rank()))
+        # Make functions 
+        u = hp.vector2Function(x[soupy.STATE], self.Vh[soupy.STATE])
+        m = hp.vector2Function(x[soupy.PARAMETER], self.Vh[soupy.PARAMETER])
+        p = dl.TestFunction(self.Vh[soupy.ADJOINT])
+        z = hp.vector2Function(x[soupy.CONTROL], self.Vh[soupy.CONTROL])
 
-            # Define full nonlinear problem
-            res_form = self.varf_handler(u, m, p, z)
-            jacobian_form = dl.derivative(res_form, u) 
+        # Define full nonlinear problem
+        res_form = self.varf_handler(u, m, p, z)
+        jacobian_form = dl.derivative(res_form, u) 
 
-            num_iters, converged = self.default_newton_solver.solve(res_form, u, self.bc, jacobian_form)
-            self.n_linear_solves += num_iters
+        num_iters, converged = self.default_newton_solver.solve(res_form, u, self.bc, jacobian_form)
+        self.n_linear_solves += num_iters
 
-            if converged:
-                print("Process %d: Immediate solve succeeded" %(MPI.COMM_WORLD.Get_rank()))
+        if converged:
+            print("Process %d: Immediate solve succeeded" %(MPI.COMM_WORLD.Get_rank()))
 
-        except:
+        else:
             print("Process %d: Increment load instead starting form zero with backtracking" %(MPI.COMM_WORLD.Get_rank()))
 
             # Start with zero initial guess

paper/paper.md

@@ -16,7 +16,7 @@ authors:
   - name: Umberto Villa 
     affiliation: 1
   - name: Omar Ghattas
-    affiliation: "1 3"
+    affiliation: "1, 3"
 affiliations:
  - name: Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, USA 
    index: 1