File size: 1,612 Bytes
a1b0d0f 34a423b a1b0d0f 34a423b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | ---
library_name: pytorch
license: other
tags:
- scientific-computing
- fluid-dynamics
- kinetic-theory
---
# Learning the Optimal Linear Hydrodynamic Closure
Code for generating spectral and time-evolution comparisons used in the paper *Learning the Optimal Linear Hydrodynamic Closure*. The main entry point is `Run.py`.
## Model Card
- **Model file:** `DSMC3ModelsExp/DSMC3LearnModelFull6.pt`
- **Type:** PyTorch checkpoint for a learned linear hydrodynamic closure.
- **Use case:** Reproduce spectra and time-evolution figures in this project.
- **Input dependencies:** `spectraV1_225_50_50_250000_5e_06_0_005_1_0_1_0.npz` and `Boltzmann3_macro_values_Adapt_FullExp.pkl`.
- **Limitations:** Intended for research reproduction; validate before use outside the reported setup.
## Setup
Create a fresh environment and install the dependencies:
```bash
conda create -n nc-code python=3.11
conda activate nc-code
pip install -r requirements.txt
```
If you prefer, you can use `venv` instead of Conda.
## Required Files
Before running `Run.py`, make sure these files are present:
- `spectraV1_225_50_50_250000_5e_06_0_005_1_0_1_0.npz`
- `Boltzmann3_macro_values_Adapt_FullExp.pkl`
- `DSMC3ModelsExp/DSMC3LearnModelFull6.pt`
## Run
Run from the repository root:
```bash
python Run.py
```
The script loads the precomputed data and trained model, then writes:
- `spectra.png`
- `dynamics.png`
## Notes
- `Run.py` uses relative paths, so run it from the repository root.
- JAX is set to CPU mode in the script.
- `jax` and `torch` may need platform-specific installation steps on some systems.
|