Fix format.

partitioned-heat-conduction/doConvergenceStudy.py

@@ -29,7 +29,7 @@ def render(precice_config_params):
         file.write(precice_config_template.render(precice_config_params))
 
 
-def do_run(dt, n_substeps = 1, polynomial_degree = 1, error_tol=10e-3, precice_config_params=default_precice_config_params):
+def do_run(dt, n_substeps=1, polynomial_degree=1, error_tol=10e-3, precice_config_params=default_precice_config_params):
     time_window_size = dt
     time_step_size = time_window_size / n_substeps
 
@@ -42,19 +42,27 @@ def do_run(dt, n_substeps = 1, polynomial_degree = 1, error_tol=10e-3, precice_c
     participants = [
         {
             "name": "Dirichlet",
-            "cmd":"-d",
+            "cmd": "-d",
         },
         {
             "name": "Neumann",
-            "cmd":"-n",
+            "cmd": "-n",
         },
     ]
 
-    for participant in participants: participant['logfile'] = f"stdout-{participant['name']}.log"
+    for participant in participants:
+        participant['logfile'] = f"stdout-{participant['name']}.log"
 
     for participant in participants:
         with open(fenics / participant['logfile'], "w") as outfile:
-            p = subprocess.Popen(["python3", fenics / "heat.py", participant["cmd"], f"-e {error_tol}", f"-s {n_substeps}", f"-p {polynomial_degree}"], cwd=fenics, stdout=outfile)
+            p = subprocess.Popen(["python3",
+                                  fenics / "heat.py",
+                                  participant["cmd"],
+                                  f"-e {error_tol}",
+                                  f"-s {n_substeps}",
+                                  f"-p {polynomial_degree}"],
+                                 cwd=fenics,
+                                 stdout=outfile)
             participant["proc"] = p
 
     for participant in participants:
@@ -97,7 +105,8 @@ def do_run(dt, n_substeps = 1, polynomial_degree = 1, error_tol=10e-3, precice_c
 
     for dt in dts:
         for n in substeps:
-            summary = do_run(dt, n_substeps=n, polynomial_degree=polynomial_degree, error_tol=10e10, precice_config_params=precice_config_params)
+            summary = do_run(dt, n_substeps=n, polynomial_degree=polynomial_degree,
+                             error_tol=10e10, precice_config_params=precice_config_params)
             df = pd.concat([df, pd.DataFrame(summary, index=[0])], ignore_index=True)
 
             print(f"Write preliminary output to {summary_file}")
@@ -119,7 +128,7 @@ def do_run(dt, n_substeps = 1, polynomial_degree = 1, error_tol=10e-3, precice_c
     if repo.is_dirty():
         chash += "-dirty"
 
-    metadata={
+    metadata = {
         "git repository": repo.remotes.origin.url,
         "git commit": chash,
         "precice_config_params": precice_config_params,
@@ -134,4 +143,4 @@ def do_run(dt, n_substeps = 1, polynomial_degree = 1, error_tol=10e-3, precice_c
 
     print('-' * term_size.columns)
     print(df)
-    print('-' * term_size.columns)
+    print('-' * term_size.columns)

partitioned-heat-conduction/fenics/heat.py

@@ -61,7 +61,12 @@ def determine_gradient(V_g, u, flux):
 command_group.add_argument("-d", "--dirichlet", help="create a dirichlet problem", dest="dirichlet",
                            action="store_true")
 command_group.add_argument("-n", "--neumann", help="create a neumann problem", dest="neumann", action="store_true")
-parser.add_argument("-s", "--n-substeps", help="Number of substeps in one window for this participant", type=int, default=1)
+parser.add_argument(
+    "-s",
+    "--n-substeps",
+    help="Number of substeps in one window for this participant",
+    type=int,
+    default=1)
 parser.add_argument("-p", "--polynomial-order", help="Polynomial order of manufactured solution", type=int, default=1)
 parser.add_argument("-e", "--error-tol", help="set error tolerance", type=float, default=10**-6,)
 
@@ -120,7 +125,12 @@ def determine_gradient(V_g, u, flux):
 # Define variational problem
 u = TrialFunction(V)
 v = TestFunction(V)
-f_manufactured = - sp.diff(sp.diff(u_manufactured, symbols['x']), symbols['x']) - sp.diff(sp.diff(u_manufactured, symbols['y']), symbols['y']) + sp.diff(u_manufactured, symbols['t'])
+f_manufactured = - sp.diff(sp.diff(u_manufactured,
+                                   symbols['x']),
+                           symbols['x']) - sp.diff(sp.diff(u_manufactured,
+                                                           symbols['y']),
+                                                   symbols['y']) + sp.diff(u_manufactured,
+                                                                           symbols['t'])
 f = Expression(sp.printing.ccode(f_manufactured), degree=2, t=0)
 F = u * v / dt * dx + dot(grad(u), grad(v)) * dx - (u_n / dt + f) * v * dx
 
@@ -256,4 +266,4 @@ def determine_gradient(V_g, u, flux):
 
 with open(errors_csv, 'a') as f:
     f.write(f"{metadata}")
-    df.to_csv(f)
+    df.to_csv(f)

partitioned-heat-conduction/fenics/problem_setup.py

@@ -56,7 +56,7 @@ def get_manufactured_solution(time_dependence, alpha, beta, p=-1):
     x, y, t = sp.symbols('x[0], x[1], t')
     # Define analytical solution
     if time_dependence == TimeDependence.POLYNOMIAL:
-        assert(p > -1)
+        assert (p > -1)
         g = (t + 1)**p
     elif time_dependence == TimeDependence.TRIGONOMETRIC:
         g = 1 + sp.sin(t)
@@ -65,4 +65,4 @@ def get_manufactured_solution(time_dependence, alpha, beta, p=-1):
 
     manufactured_solution = 1 + g * x**2 + alpha * y**2 + beta * t
     print("manufactured solution = {}".format(manufactured_solution))
-    return manufactured_solution, {'x':x, 'y':y, 't':t}
+    return manufactured_solution, {'x': x, 'y': y, 't': t}