Wed Apr 29 09:30:26 2020

dpg_laplace_adapt_test:
  Python version: 3.6.9
  FENICS version 2019.1.0
  Adaptive refinement procedure applied to
  Discontinuous Petrov Galerkin method for the Poisson problem
  on a unit square with 0 boundary conditions.
Calling FFC just-in-time (JIT) compiler, this may take some time.
Calling FFC just-in-time (JIT) compiler, this may take some time.
Calling FFC just-in-time (JIT) compiler, this may take some time.
Calling FFC just-in-time (JIT) compiler, this may take some time.
Calling FFC just-in-time (JIT) compiler, this may take some time.
Calling FFC just-in-time (JIT) compiler, this may take some time.
Calling FFC just-in-time (JIT) compiler, this may take some time.
Level 0: Estimated error E = 0.0040681 (TOL = 0.0001)
Graphics: mesh0.png
Graphics: u0.png
Level 1: Estimated error E = 0.00207633 (TOL = 0.0001)
Graphics: mesh1.png
Graphics: u1.png
Level 2: Estimated error E = 0.001022 (TOL = 0.0001)
Graphics: mesh2.png
Graphics: u2.png
Level 3: Estimated error E = 0.000797214 (TOL = 0.0001)
Graphics: mesh3.png
Graphics: u3.png
Level 4: Estimated error E = 0.000451917 (TOL = 0.0001)
Graphics: mesh4.png
Graphics: u4.png
Level 5: Estimated error E = 0.000235863 (TOL = 0.0001)
Graphics: mesh5.png
Graphics: u5.png
Level 6: Estimated error E = 0.000120111 (TOL = 0.0001)
Graphics: mesh6.png
Graphics: u6.png
Level 7: Estimated error E = 6.12682e-05 (TOL = 0.0001)
Success, solution converged after 7 iterations

dpg_laplace_adapt_test:
  Normal end of execution.

Wed Apr 29 09:31:14 2020