Preprocessing and postprocessing tools

This directory contains a collection of helpful preprocessing and postprocessing utilities.

Preprocessing scripts

naluwind2amrwind.py

The naluwind2amrwind.py python script allows you to convert a Nalu-wind input file to an amr-wind input file. To the best of its ability, it will try to take the parameters from Nalu-wind and map them to amr-wind.

The basic usage is given by:

usage: naluwind2amrwind.py [-h] [--outfile OUTFILE] yamlfile

Convert Nalu-Wind input file to AMR-wind input file

positional arguments:
  yamlfile

optional arguments:
  -h, --help         show this help message and exit
  --outfile OUTFILE  write output to this file

For instance, to convert the Nalu-wind input file naluwind.yaml, run

$ ./naluwind2amrwind.py naluwind.yaml

#---------------------------------------#
#            SIMULATION STOP            #
#---------------------------------------#
time.stop_time                 = 20000.0                        # Max (simulated) time to evolve
time.max_step                  = 40000                          # Max number of time steps

#---------------------------------------#
#         TIME STEP COMPUTATION         #
#---------------------------------------#
time.fixed_dt                  = 0.5                            # Use this constant dt if > 0
time.cfl                       = 0.95                           # CFL factor

#---------------------------------------#
#            INPUT AND OUTPUT           #
#---------------------------------------#
time.plot_interval             = 1000                           # Steps between plot files
time.checkpoint_interval       = 1000                           # Steps between checkpoint files
io.KE_int                      = 1                              
io.line_plot_int               = 1                              

[...snip...]

Use the --outfile option to write the output to a file instead. Note that the nalu_abl_mesh and nalu_preprocess section should be present in the yaml file for it to correctly extract the geometry and the inversion layer properties.

Postprocessing scripts

postproamrwind.py

The postproamrwind.py python provides a quick method to time-average and extract data from the line_plot.txt output.

The major functions in this code are:

• loadfile(filename, t1, t2, headerinfo=[]): Loads the line_plot.txt file given by filename, for all times between t1 and t2.
• timeaverage(dat, t1, t2, Ncells, Ncomp): Time averages the line_plot data given by dat, between times t1 and t2.
• avglineplot(filename, t1,t2, headerinfo=[]): Combines loadfile() and timeaverage(), so it loads the line_plot.txt given by filename, and averages it between t1 and t2.
• extractvars(dat, colheaders, varnames): Returns the variable(s) matching the variables in varnames

A short example of how to use the code is shown below. In this case, we load the line_plot.txt file, average from 0 to 100 seconds, and plot the averaged U velocity versus z.

import postproamrwind
import matplotlib.pylot as plt
avgdat, headers = postproamrwind.avglineplot('line_plot.txt',0,100)
amrvars         = postproamrwind.extractvars(avgdat, headers, ['z','u_avg'])
plt.plot(amrvars['u_avg'], amrvars['z'])
plt.show()