Merge pull request #1 from aaronyicongfu/cython

Fix python code formatting

examples/egads/crm/dcel.py

@@ -1,6 +1,7 @@
 """
 Implementation of a DECL data structure
 """
+
 import numpy as np
 
 

examples/poisson/poisson_agg_error.py

@@ -2,6 +2,7 @@
 Plot the aggregation error as a function of rho for the KS and p-norm
 functionals
 """
+
 from __future__ import print_function
 import tikzplots as tkz
 import numpy as np

examples/pygeometryloader/plate/plate.py

@@ -3,6 +3,7 @@
 
 To run the defaults: mpirun -np 2 python plate.py
 """
+
 # imports
 import os
 from mpi4py import MPI

examples/pytacsadapt/plate/plate_adapt.py

@@ -13,6 +13,7 @@
 3. run `mpirun -np 4 python plate_adapt.py --niters 10 --strategy fixed_growth --ref_factor 0.1`
 4. compare the results of uniform and adaptive refinement between step 2 and 3
 """
+
 import os
 import argparse
 from mpi4py import MPI

examples/smooth/smooth_stl.py

@@ -1,6 +1,7 @@
 """
 Imports a STL file and applies a smoothing to it
 """
+
 from __future__ import print_function
 
 # Import the locate point code

examples/topology_optimization/eigenvalue/lbracket_eigenvalue.py

@@ -2,6 +2,7 @@
 Solve the eigenvalue-constrained optimization problem
 
 """
+
 from mpi4py import MPI
 from tmr import TMR, TopOptUtils
 from paropt import ParOpt, ParOptEig

examples/topology_optimization/qn-correction/compliance/comp-min.py

@@ -397,9 +397,9 @@ def evalObjConGrad(self, x, g, gcon):
                 prob.driver.opt_settings["Minor print level"] = 0
 
                 if max_iterations > 1 and step == max_iterations - 1:
-                    prob.driver.opt_settings[
-                        "Major iterations limit"
-                    ] = args.niter_finest
+                    prob.driver.opt_settings["Major iterations limit"] = (
+                        args.niter_finest
+                    )
                 else:
                     prob.driver.opt_settings["Major iterations limit"] = args.max_iter
 

examples/topology_optimization/qn-correction/eigenvalue/eig-max-lite.py

@@ -1,6 +1,7 @@
 """
 This script performs eigenvalue minimization with mass constraint
 """
+
 import numpy as np
 from mpi4py import MPI
 import argparse

examples/topology_optimization/qn-correction/frequency-baseline/baseline.py

@@ -1,6 +1,7 @@
 """
 Compute the base frequencies for different domains with concentrated mass
 """
+
 from tmr import TMR, TopOptUtils
 from tacs import TACS, constitutive
 

examples/topology_optimization/qn-correction/refactor_compfreq/compfreq.py

@@ -475,9 +475,9 @@ def evalObjConGrad(self, x, g, gcon):
                 omprob.driver.opt_settings["Minor print level"] = 0
 
                 if args.n_mesh_refine > 1 and step == args.n_mesh_refine - 1:
-                    omprob.driver.opt_settings[
-                        "Major iterations limit"
-                    ] = args.niter_finest
+                    omprob.driver.opt_settings["Major iterations limit"] = (
+                        args.niter_finest
+                    )
                 else:
                     omprob.driver.opt_settings["Major iterations limit"] = args.max_iter
 

examples/topology_optimization/qn-correction/refactor_frequency/refactor_frequency.py

@@ -447,9 +447,9 @@ def evalObjConGrad(self, x, g, gcon):
                 omprob.driver.opt_settings["Minor print level"] = 0
 
                 if n_refine_steps > 1 and step == n_refine_steps - 1:
-                    omprob.driver.opt_settings[
-                        "Major iterations limit"
-                    ] = args.niter_finest
+                    omprob.driver.opt_settings["Major iterations limit"] = (
+                        args.niter_finest
+                    )
                 else:
                     omprob.driver.opt_settings["Major iterations limit"] = args.max_iter
 

tmr/pytacsadapt.py

@@ -436,9 +436,9 @@ def setupModel(self, model_type, **kwargs):
 
         # record the number of degrees of freedom for this model
         nnodes = model.assembler.getNumOwnedNodes()
-        self.mesh_history[
-            model.prob_name
-        ] = model.assembler.getVarsPerNode() * model.comm.allreduce(nnodes, op=MPI.SUM)
+        self.mesh_history[model.prob_name] = (
+            model.assembler.getVarsPerNode() * model.comm.allreduce(nnodes, op=MPI.SUM)
+        )
         return
 
     def solvePrimal(self, model_type, writeSolution=False, **kwargs):
@@ -662,9 +662,9 @@ def estimateOutputError(self, writeSolution=False):
 
         # update histories
         self.error_history[f"adapt_iter_{self.fine.refine_iter}_error"] = error_estimate
-        self.error_history[
-            f"adapt_iter_{self.fine.refine_iter}_correction"
-        ] = output_correction
+        self.error_history[f"adapt_iter_{self.fine.refine_iter}_correction"] = (
+            output_correction
+        )
 
         # write out the nodal error field
         if writeSolution:
@@ -942,9 +942,9 @@ def writeModelHistory(self, filename=""):
                 for key, val in self.adaptation_history["element_errors"].items():
                     h5[f"adaptation_history/element_errors/{key}"] = val
                 if self.adapt_strategy:
-                    h5["adaptation_history"].attrs[
-                        "strategy"
-                    ] = self.adapt_strategy.replace("_", " ").lower()
+                    h5["adaptation_history"].attrs["strategy"] = (
+                        self.adapt_strategy.replace("_", " ").lower()
+                    )
                     h5["adaptation_history"].attrs["error_tolerance"] = self.error_tol
                     h5["adaptation_history"].attrs[
                         "max_refine_levels"