Sample fgout results

Sample fgout results#

From the GeoClaw Tsunami Tutorial

The directory $GTT/CopalisBeach/example2 contains a GeoClaw example that produces results on fgout and fgmax grids.

See also

  • Copalis Beach example2 for more about this example, and general discussion of fgout and fgmax grids.

  • Plot fgout results is a Jupyter notebook that plots the fgout results.

  • chile2010_fgmax-fgout shows results from the example included with GeoClaw in $CLAW/geoclaw/examples/tsunami/chile2010_fgmax-fgout, which also illustrates how to make fgout animations, similar to what is described here, using the Chile 2010 event in the offshore region.

The script fetch_sample_results.py can be used to fetch some sample results if you want to run the post-processing script or notebook in this directory without running the GeoClaw code.

Plotting fgout results using setplot.py#

One approach to plotting fgout grid results is to specify a setplot function (in this example, there is one in setplot_fgout.py) that has the same form as a setplot function for plotting standard GeoClaw/Clawpack output frames, but we set:

plotdata.file_prefix = 'fgout0001'  # for fgout grid fgno==1

to indicate that instead of the usual output files with names like fort.t* and fort.q* (and also fort.b* in the case of binary output), as described at Clawpack output styles, the data is in files named fgout0001.t*, etc. The fgout results are written with the same format as AMR frame data, the only difference is that each frame has only one grid (the fgout grid) at a single AMR level (which is denoted by AMR level 0 in the fgout0001.t* files, to remind us that this is not one of the computational grids and is based on data at all levels).

Executing:

$ make plots SETPLOT_FILE=setplot_fgout.py PLOTDIR=_plots_fgout

will use this setplot_fgout.py file to create a set of plots in _plots_fgout that includes all of the fgout snapshots at the fgout times that were specified in setrun.py.

Loading and plotting one or more fgout snapshots directly#

Alternatively, since every fgout frame consists of only a single uniform grid of data, it is much easier to manipulate or plot directly than general AMR data. The clawpack.geoclaw.fgout_tools module described at fgout tools provides tools for reading frames and producing arrays that can then be worked with directly.

One example of how this might be done is provided in the Jupyter notebook Plot fgout results. This shows how a single frame of fgout results can be loaded, and then you can do any sort of plotting or other manipulations you please on this data, which is stored as a single numpy array.

Making an animation#

The sample code in make_fgout_animation.py reads in all the frames of fgout data and produces an animation as stand-alone mp4 and/or html files. To run this code, do::

python make_fgout_animation.py

The use of fgout grids provides a way to produce frequent outputs on a fixed grid resolution, as often desired for making smooth animations of a portion of the computational domain.

The code produces this animation:

(Right click and select “Show all controls” to find the Play button.)

Contents