Create and manipulate OpenFOAM cases
Project description
This module is a addition to PyFoam and can automatically setup OpenFOAM cases with varying conditions.
Getting started
Installing CaseFOAM
In order to use the Python module you need the PyFoam package.
install the package after cloning the repository with:
$ pip install .
or via pypi by executing:
$ pip install casefoam
User’s Guide
For a full documentation change into doc and build the documentation for example as html.
$ cd doc/
$ make html
$ firefox build/html/index.html
Example
CaseFoam offers two main features: the easy generation of parameter studies and the analysis of these. In the example, we want to change the intial height of the column and perform a grid study for the damBreak test case:
parameter studies
The first step is the generation of the cases. We want to generate three column heights where each case has three grids with a differnt cell size.
cat genCases.py:
import casefoam
baseCase = 'damBreak'
caseStructure = [['height_02', 'height_03', 'height_04'],
['grid1', 'grid2', 'grid3']
]
def update_grid(a,b,c,d,e):
return {
'system/blockMeshDict': {'#!stringManipulation': {'varA': '%s' %a,
'varB': '%s' %b,
'varC': '%s' %c,
'varD': '%s' %d,
'varE': '%s' %e
}
}
}
def update_height(height):
return {
'system/setFieldsDict': {'#!stringManipulation':
{'var_height': '%s' %height}}
}
caseData = {
'height_02': update_height(0.2),
'height_03': update_height(0.3),
'height_04': update_height(0.4),
'grid1': update_grid(23,8,19,42,4),
'grid2': update_grid(23*2,8*2,19*2,42*2,4*2),
'grid3': update_grid(23*3,8*3,19*3,42*3,4*3)
}
# generate cases
casefoam.mkCases(baseCase, caseStructure, caseData, hierarchy='tree',writeDir='Cases')
There a three different options how the cases can be manipulated:
replacing a string inside the specified files
executing a bash script
by specifying a dictionary
for details please see the user manual.
The script is executed by:
python genCases.py
This will the generate the following structure:
The cases can be started by running the newly created Allrun script
./Allrun
postProcessing
Three functions are avaiable for the postProcessing:
time_series
positional_field
posField_to_timeSeries
For the damBreak test case we want to plot the freesurface position at a given time. For that, we use the positional_field function and get a pandas dataframe which we plot with holoviews
import casefoam
import matplotlib.pyplot as plt
import pandas as pd
import holoviews as hv
hv.extension('bokeh')
caseStructure = [['height_02', 'height_03', 'height_04'],
['grid1', 'grid2', 'grid3']]
baseCase = 'Cases'
surfaceDir = 'freeSurface'
surface = casefoam.positional_field(surfaceDir,'U_freeSurface.raw',0.3,caseStructure,baseCase)
surface.columns = ['x','y','z','Ux','Uy','Uz','col_height','res']
surface_ds = hv.Dataset(surface, [ 'col_height','res'], ['x','y','z','Ux','Uy','Uz'])
holoviews is optimized for the use for the jupyter notebooks. The %%opts arguments are used to modify the layout of the plot. holoviews renders an interactive plot which can be exported as html:
%%opts Scatter [width=600,height=600,title='freeSurface at 0.3s',tools=['hover']]
%%opts (muted_alpha=0.0)
surface_ds.to(hv.Scatter,'x','y').overlay('res')
version 0.0.1
0.0.1 (2021-04-14)
First release on PyPI.
version 0.0.2
0.0.2 (2021-04-14)
First release on PyPI.
version 0.0.3
0.0.3 (2021-04-14)
First release on PyPI.
version 0.0.4
0.0.4 (2021-04-14)
First release on PyPI.
version 0.1.0
0.1.0 (2022-02-16)
added CI
replaced append with concat
version 0.1.1
0.1.1 (2022-05-18)
new Function: of_cases finds all OpenFOAM cases in folder
version 0.2.0
0.2.0 (2022-05-18)
new Function: profiling allows to load profiling data from OpenFOAM
add profiling to system controlDict:
profiling
{
active true;
cpuInfo false;
memInfo false;
sysInfo false;
}
prof = casefoam.profiling(time=0,processorDir="", caseStructure=caseStructure,baseCase=baseCase)
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