Repository for applying Machine-Learning techniques to multi-phase flows:
- Flow regime recognition
-
Clone the repo in the desired drectory
git clone [email protected]:pasassi/multiphaseML.git
-
Create a virtual environment (venv must be installed)
i. Create a virtual environment (here is named
.venv
)python3 -m venv .venv
ii. Activate it
source .venv/bin/activate
-
Install necessary dependencies via
requirements.txt
(I recommendpipenv
)pipenv install
This will read the
requirements.txt
file and generatePipfile
andPipfile.lock
files -
Add your virtual environment to Jupyter (the interactive IDE)
python -m ipykernel install --user --name=.venv
-
Add your virtual environment as preferred python interpret in VSC
i. Create a folder called
.vscode
in the repo root dir if you haven't already.mkdir .vscode
ii. Create the user settings file inside that folder
touch ./.vscode/settings.json
iii. Add this line to your
settings.json
file to set the default Python interpreter for VS Code.// Sets this project's .venv Python interpreter { "python.defaultInterpreterPath": "<path_to_multiphaseML>/multiphaseML/.venv/bin/python3", }
Where
<path_to_multiphaseML>
is the absolute path tomultiphaseML
repository.
Follow the installation guide for using TensorFlow with GPU