3. Create Virtual Environment

The following steps create a virtual Python environment to ensure the model is run with the correct Python libraries. These steps are identical regardless of operating system.

  1. Create a virtual Python environment.
python3 -m venv .
  1. Activate the virtual environment.
source bin/activate 
  • If this worked successfully, you should see the directory name in parentheses before your terminal input.

Screenshot of the directory after we activate virtual environment

  1. Add Python libraries to the new virtual environment using the requirements file that was downloaded when the Github was cloned.
    python3 -m pip install -r requirements.txt
    
    • You may be prompted to say Y or N. Respond Y to all prompts.
    • Note: your requirements may differ on a supercomputing cluster such as UC Berkeley’s savio cluster. A copy of the requirements.txt file that works on UC Berkeley’s Savio is copied below.
  1. To confirm that the libraries are installed properly, run the following code. If you get a help message, the installation has worked properly.
    python3 run_echo_air.py -h
    
    • An example of the help message is below.

Screenshot of help message

– Next Step –>


Requirements for Savio

If you are using UC Berkeley’s Savio supercomputer, the following text should be copied over your requirements.txt file prior to step 3 above.

attrs==22.2.0
certifi==2021.10.8
click==8.0.3
click-plugins==1.1.1
cligj==0.7.2
cycler==0.11.0
DateTime==4.5
Fiona==1.8.21
fonttools==4.27.1
geopandas==0.9.0
importlib-metadata==4.8.3
kiwisolver==1.3.1
matplotlib==3.3.4
munch==2.5.0
numpy==1.19.5
packaging==21.3
pandas==1.1.5
pathlib==1.0.1
Pillow==8.4.0
pyarrow==6.0.1
pyparsing==3.0.8
pyproj==3.0.1
python-dateutil==2.8.2
pytz==2022.1
Rtree==0.9.7
scipy==1.5.4
seaborn==0.11.2
Shapely==1.8.1.post1
six==1.16.0
typing_extensions==4.1.1
zipp==3.6.0
zope.interface==5.4.0