Initializing Feel++

The core module provides the basic data structures to

  • setup and run Feel++ application in a parallel environment.

  • handle the command line options

  • download and upload data from and to GitHub and/or Girder

1. Setting up the Feel++ Environment

To set Feel++ environment, we create an environment and set the associated repository for the results. A Feel++ environment can be created only once. The repository can be global with respect to $HOME/.feelppconfig globalroot setting or local with respect to the current directory.

Set the Feel++ environment with local repository
import feelpp.core as fppc
import sys
app = fppc.Environment(["myapp"],config=fppc.localRepository(""))

Query the app about the current environment
print("pid:",app.worldComm().localRank() )
print("isMasterRank:",app.isMasterRank() )
print("is parallel: ",app.isParallel() )
pid: 0
isMasterRank: True
is parallel:  False

2. Downloading data

Feel++ can query data on GitHub and Girder. "github:{repo:feelpp,path:README.adoc}", worldComm=app.worldCommPtr() )[0]

print("downloaded Feel++ README.adoc from Github: ",readme)
downloaded Feel++ README.adoc from Github:  /nvme0/prudhomm/github-actions/actions-runner-4/_work/

The code will get the file README.adoc from the toplevel Feel++ github directory downloaded

A bit more interesting example: the following code will download a csv file from the Feel++ github repository and plot the data using the plotly library. "github:{repo:feelpp,path:toolboxes/fluid/cases/moving_body/gravity/cylinder_under_gravity/curve_comparison.csv}", worldComm=app.worldCommPtr() )[0] (1)
import pandas as pd (2)
df = pd.read_csv(acsv, sep=",") (3)
df.columns = df.columns.str.replace(' ', '')
       TIME      Y_CM
0  0.001538  3.991736
1  0.013846  3.983471
2  0.022432  3.959772
3  0.030984  3.925082
4  0.038925  3.881016
1 download the file curve_comparison.csv from the Feel++ github repository toolboxes/fluid/cases/moving_body/gravity/cylinder_under_gravity/curve_comparison.csv
2 use the pandas library to read the csv file
3 read the csv file and remove the spaces in the column names

We can now use plotly to plot the data

import as px
fig = px.scatter(df,x="TIME", y="Y_CM", title="y-displacement of the center of mass(CM) of the cylinder",labels={"TIME":"t (s)","Y_CM":r'y-displacement (m)'})