Usage

dolfin-adjoint with FEniCS Docker

To Run the MIDBench API Code:

• Install midbench:

pip install midbench

• Create a session that has access to the current folder from the host:

• Linux Users:

$ cd /path/to/midbench
$ sudo docker run -it -p 8887:8887 -v $(pwd):/home/fenics/shared quay.io/dolfinadjoint/pyadjoint

• Windows and Mac Users: If running on Mac or Windows, make sure you run the above commands inside the Docker Quickstart Terminal.

• Open jupyter notebook or jupyter lab:

$ jupyter lab --no-browser --ip=0.0.0.0 --port=8887

• Run MIDBench 2D Heat Conduction Optimization Demo: In the midbench directory, there is an iPython notebook "example_usage.ipynb". Please open the notebook in jupyter lab or jupyter notebook. Please run the API demo code in the notebook cell by cell to check out the 2D Heat Conduction Optimization demo in your dolfin-adjoint FEniCS Docker container. The commands in the jupyter notebook are as follows:

# Optimization
from midbench.envs import make
Env, Design, Condition = make("HeatConduction2d-v0")

conditions = Condition(**{'volume':0.4,'length':0.5,'resolution':50})
designs = Design(**{'volume':0.4,'resolution':50}).output()
objectives = ['compliance']

compliance=Env.optimize(conditions, designs, objectives)