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vprd

Virtual Pulse Reconstruction Diagnostic

https://github.com/thawn/vprd

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: zenodo.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.4%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Virtual Pulse Reconstruction Diagnostic

Basic Info
  • Host: GitHub
  • Owner: thawn
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: main
  • Size: 3.79 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

Virtual Pulse Reconstruction Diagnostic

DOI

Code for the paper Harnessing Machine Learning for Single-Shot Measurement of Free Electron Laser Pulse Power

Installation

Download the code and install it with pip

Note: You need at least Python version 3.10

bash mkdir VPRD cd VPRD curl https://anonymous.4open.science/api/repo/VPRD-1146/zip -o VPRD.zip unzip VPRD.zip python3 -m venv vprd-env source vprd-env/bin/activate pip install .

First steps

Start jupyter lab (while vprd-env is still active):

bash jupyter lab

Now you can execute the notebooks to reproduce the results from the paper:

Train a model

Execute the notebook docs/notebooks/trainmlpmodel.ipynb

Reproduce data preprocessing

Please note that your computer needs a GPU that supports OpenCL in order to execute this notebook.

Execute the notebook docs/notebooks/data_merging.ipynb

Step-by-step image processing

Please note that your computer needs a GPU that supports OpenCL in order to execute this notebook

Execute the notebook docs/notebooks/imagetoelectron_power

Troubleshooting

In case of Runtime errors in th preprocessing and image processing notebooks, please follow the pyclesperanto GPU troubleshooting guidelines.

In that case the easies way is to create the environment with mamba (so you don't need to install OpenCl manually). Please use these installation instructions instead of the ones given above:

Installation with mamba

If you don't have mamba installed yet, we recommend to install miniforge

Download the code and create an environment

bash git clone https://github.com/thawn/VPRD.git cd VPRD mamba env create -f env.yml mamba activate vprd-env pip install .

MacOS users may need to install the following package:

bash mamba install -c conda-forge ocl_icd_wrapper_apple

Linux users may need to install the following package:

bash mamba install -c conda-forge ocl-icd-system

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Korten"
  given-names: "Till"
  orcid: "https://orcid.org/0000-0002-2315-9247"
- family-names: "Steinbach"
  given-names: "Peter"
  orcid: "https://orcid.org/0000-0002-4974-230X"
- family-names: "Mirian"
  given-names: "Najmeh Sadat"
  orcid: "https://orcid.org/0000-0002-6152-2721"
title: "Virtual Pulse Reconstruction Diagnostic"
version: 0.2.0
doi: 10.5281/zenodo.14179724
date-released: 2024-11-18
url: "https://github.com/thawn/VPRD"

GitHub Events

Total
  • Public event: 1
  • Push event: 4
  • Create event: 1
Last Year
  • Public event: 1
  • Push event: 4
  • Create event: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 1
  • Total pull requests: 1
  • Average time to close issues: 4 days
  • Average time to close pull requests: less than a minute
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 1
  • Average time to close issues: 4 days
  • Average time to close pull requests: less than a minute
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
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Top Authors
Issue Authors
  • thawn (1)
Pull Request Authors
  • thawn (1)
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Dependencies

pyproject.toml pypi
  • h5py *
  • jupyter *
  • lightning *
  • matplotlib *
  • numpy *
  • pandas *
  • pyclesperanto *
  • scikit-learn *
  • scipy *
  • seaborn *
  • statsmodels *
  • tables *
  • tensorboard *
  • torch *