Prerequisites
Download the PROFFASTpylot repository
Get PROFFAST and copy it to proffastpylot
Create a virtual environment in python
Install PROFFASTpylot
Resulting folder structure
Test the installation by running an example dataset
Getting Updates
For using PROFFASTpylot you need Python 3.7 or newer. The PROFFAST and PROFFASTpylot can be used in Windows and Linux environments. A step-by-step installation instruction for both environments is given in the following. We did not test the software for Mac environments.
We recommend downloading the files using git (https://www.git-scm.com).
It will make future updates easier.
git clone https://gitlab.eudat.eu/coccon-kit/proffastpylot.git
A folder proffastpylot containing all program files will be created.
If you don’t want to use git, you can instead download and unpack the zip file https://gitlab.eudat.eu/coccon-kit/proffastpylot/-/archive/master/proffastpylot-master.zip
Extracting it will create the folder proffastpylot.
Download PROFFAST Version 2.4 from the KIT website:
https://www.imk-asf.kit.edu/english/3225.php
For Windows users, the executables are already provided, on Linux systems you need to create them from source.
If not present on your system, first install the gfortan compiler.
Secondly, run the installation script for compilation from the prf folder.
cd prf/
bash install_proffast_linux.sh
Copy the prf folder that was extracted from the zip file into proffastpylot.
We recommend using a virtual environment (venv) to avoid conflicts between any other packages or Python modules.
(Only first time) Navigate to the proffastpylot folder using a terminal.
(Only first time) Enter python -m venv prf_venv.
This command will create a folder named prf_venv which contains the virtual environment
Activate the virtual environment every time you run PROFFASTpylot with
Windows PowerShell: .\prf_venv\Scripts\Activate.ps1
Windows Commandline: .\prf_venv\Scripts\activate
Linux: source prf_venv/bin/activate
To deactivate the virtual environment you can run deactivate
Note that all packages to be installed with pip install will only affect the virtual environment and not the local Python installation.
In case of a problem, take a look at the Troubleshooting article of this documentation.
You need to activate the virtual environment before each run of PROFFASTpylot by executing the command in step 3, the other steps need to be executed only the first time.
Activate the virtual environment (see above).
Navigate to proffastpylot and enter
pip install --editable .
If you follow exactly the installation guide your folder structure should look like the following:
proffastpylot
├── prf_venv
│ ├── ...
├── docs
│ ├── ...
├── example
│ ├── input_sodankyla_example.yml
│ ├── log_type_pressure.yml
│ └── run.py
├── prf
│ ├── docs
│ ├── inp_fast
│ ├── inp_fwd
│ ├── preprocess
│ ├── source
│ ├── out_fast
│ └── wrk_fast
├── prfpylot
│ ├── ...
└── setup.py
To test the installation, we provide example raw data and a reference result file to compare the file to.
The example can be executed by navigating to the example folder and execute python run.py
(please ensure that your virtual environment is activated).
When first running the program, it will ask you to download the example file data to your local computer.
After the run is complete, please compare your results to the data given in example\Reference_Output_Example_Sodankyla.csv.
The deviations should be less than 0.1 ppm for XCO2, 0.1 ppb for XCH4 and 0.1 ppb for XCO.
If you used git during installation, you can easily get updates by entering
git pull
in a git bash or in a Terminal in your proffastpylot folder. This command will download all available updates.
If you downloaded PROFFASTpylot as zip file, you need to redo all steps of this installation script.