https://github.com/coldmayo/annreweight
Using Neural Networks for Geant4 Reweighting
https://github.com/coldmayo/annreweight
Last synced: 5 months ago
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Using Neural Networks for Geant4 Reweighting
- Host: GitHub
- URL: https://github.com/coldmayo/annreweight
- Owner: coldmayo
- Created: 2024-07-09T13:57:33.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-13T04:59:28.000Z (almost 2 years ago)
- Last Synced: 2025-05-13T01:37:10.003Z (about 1 year ago)
- Language: Python
- Size: 30 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Reweighting using Neural Networks
In this project, I will be reweighting Geant4 histograms using Machine Learning. For more information check out this web page.
## Directory breakdown
- data/
- As the name suggests, this is where data is stored. From root to csv files
- model/
- Where all of the code relating to building, training, and testing of the models takes place
- saved_models/
- This directory is created once the user trains their first model. Information about the trained model is stored here (weights, bias, etc)
- useful_papers/
- Papers referenced for this project (helpful for writing references for a paper)
- output/
- Shows the output of the model (loss function, reweighted plots, etc)
## Important Links
Data:
- Zenodo
## Running the code
### Linux
1. Create Virtual Envirement
```bash
$ python -m venv .venv
```
2. Install packages
```bash
$ pip install -r requirements.txt
```
3. Use run.sh for running files
```bash
$ cd model
$ ./run.sh train.py 10
```
### Windows
1. Create Virtual Envirement
```bash
$ python -m venv .venv
```
2. Install packages
```bash
$ pip install -r requirements.txt
```
3. Run files
```bash
$ .venv\Scripts\activate.bat
$ cd model
$ python -u train.py 10
```