Installation

pip

pip install prandtl-cfd             # base (numpy, scipy, torch)
pip install prandtl-cfd[gp]         # Gaussian Process backend (GPyTorch)
pip install prandtl-cfd[export]     # ONNX export support
pip install prandtl-cfd[tree]       # 树模型后端 (Random Forest / Gradient Boosting)
pip install prandtl-cfd[all]        # 全部功能 (gp + export + tree)

Extras

Extra	What it installs	When you need it
none	numpy, scipy, torch	Sampling + MLP training + metrics
[gp]	GPyTorch	Gaussian Process surrogates
[export]	onnx, onnxruntime	部署 MLP 代理模型
[tree]	scikit-learn	Random Forest / Gradient Boosting 后端
[all]	gp + export + tree	全部功能

Check installation

import prandtl as pr
print(pr.__version__)  # 0.3.0

# Verify GP backend
X, Y = pr.sample(pr.analytical.cl_flat_plate, bounds=[(0, 5), (0.01, 0.05)], n=20)
s = pr.Surrogate(params=["alpha", "camber"], outputs=["CL"], method="gp")
s.fit(X, Y)
print(s.validate(X, Y))  # should show R² ≈ 1.0