You can simply clone the repo via git:
git clone https://github.com/Hiperwind/PhDSchool.git
We recommend the installation of a Python 3.10 virtual environment. You can do so via:
- Conda (recommended)
conda create -n "hiperwind" python=3.10
- venv (this option requires a prior Python installation)
python -m venv /path_to_new_virtual_environment
You can then pip install the required packages:
pip install -r requirements.txt
- Conda (recommended)
conda activate hiperwind
- venv
source /path_to_new_virtual_environment/bin/activate
The slides are available here.
The exercises and tutorials are available here.
A template containing all instructions necessary for the project is available here. You can complete the project at your own pace, though we suggest the following timeframe:
- Day 1: Intro, installation of the Python environment, data visualization.
- Day 2: Environmental data fitting.
- Day 3: Surrogate model construction and testing.
- Day 4: Limit state definition and reliability estimation.