plots_post_processing

functions to allocate arrays that are used at run-time to postprocess data that is stored in the netcdf files

analyze_and_plot_data(prefix...; run_index=nothing)

Make some plots for the simulation at prefix. If more than one argument is passed to prefix, plot all the simulations together.

The strings passed to prefix should be either a directory (which contains run output) or the prefix of output files, like <directory>/<prefix> where the output files are <directory>/<prefix>.moments.h5 and <directory>/<prefix>.dfns.h5.

If a single value is passed for prefix the plots/movies are created in the same directory as the run, and given names based on the name of the run. If multiple values are passed, the plots/movies are given names beginning with compare_ and are created in the comparison_plots/ subdirectory.

By default plots output from all restarts in a directory. To select a single run, pass the run_index argument - the value corresponds to the _<i> suffix given to output files when restarting. run_index can be an integer (which is applied to all directories in prefix...), or a tuple of integers (which should have the same length as the number of directories passed to prefix...). Use run_index=-1 to get the most recent run (which does not have a _<i> suffix). Note that run_index is only used when a directory (rather than the prefix of a specific output file) is passed to prefix...

Find the maximum difference, as a function of time, between two or more outputs for each variable.

Add a thin, red, dashed line showing vparallel=(vth*wparallel+upar)=0 to a 2d plot with axes (z,vpa).

get_tuple_of_return_values(func, arg_tuples...)

Suppose func(args...) returns a tuple of return values, then get_tuple_of_return_values(func, arg_tuples...) returns a tuple (with an entry for each return value of func) of tuples (one for each argument in each of arg_tuples...) of return values.

plots various slices of the ion pdf (1d and 2d, stills and animations)

plots various slices of the neutral pdf (1d and 2d, stills and animations)

Make a 2d plot of an unnormalised f on unnormalised coordinates, as returned from getunnormalisedf_coords()

Note this function requires using the PyPlot backend to support 2d coordinates being passed to heatmap().

Read data which is a function of (r,t) or (r,species,t) and associated to one of the wall boundaries

run_names is a tuple. If it has more than one entry, this means that there are multiple restarts (which are sequential in time), so concatenate the data from each entry together.

Call gif, but catch the exception if there is an error

Call savefig, but catch the exception if there is an error