AMRClawΒΆ
The AMRClaw version of Clawpack provides Adaptive Mesh Refinement (AMR) capabilities in 2 and 3 space dimensions. (The two-dimensional code can also be used for 1-dimensional problems, see AMRClaw for 1d problems.)
See also:
Block-structured AMR is implemented, in which rectangular patches of the grid at level L are refined to level L+1. See Specifying AMRClaw run-time parameters in setrun.py for a list of the input parameters that can be specified to help control how refinement is done. The general algorithms are described in [BergerLeVeque98].
See ClawPlotItem for a list of 2d plot types that can be used to create a setplot function to control plotting of two-dimensional results. Some of the attribute names start with the string amr_, indicating that a list of different values can be specified for each AMR level. See Plotting with Visclaw and Using setplot.py to specify the desired plots for more about plotting.
Python plotting tools for 3d are still under development. For now, the Matlab tools from Clawpack 4.3 can still be used, see Plotting using Matlab.
- Demo of running AMRClaw Fortran code and plotting results
- Module with functions used to execute system commands and capture output:
- Compile the code:
- Make documentation files:
- Run the code and plot results using the setrun.py and setplot.py files in this directory:
- Display the animation inline:
- Illustrate how to adjust some parameters and rerun the code:
- Write the data out (for the Fortran code to read in) and run the code:
- Changing plot parameters and plotting inline
- AMRClaw for 1d problems
- Specifying AMRClaw run-time parameters in setrun.py
- Sample setrun.py module for AMRClaw
- Adaptive mesh refinement (AMR) algorithms
- AMR refinement criteria
- Gauges
