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annsa

Artificial neural networks for spectral analysis.

https://github.com/arfc/annsa

Science Score: 18.0%

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

  • ✓
    CITATION.cff file
    Found CITATION.cff file
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    codemeta.json file
  • ○
    .zenodo.json file
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    DOI references
  • ○
    Academic publication links
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    Institutional organization owner
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  • ○
    Scientific vocabulary similarity
    Low similarity (5.4%) to scientific vocabulary

Keywords

artificial-neural-networks gamma-spectroscopy python-package
Last synced: 6 months ago · JSON representation ·

Repository

Artificial neural networks for spectral analysis.

Basic Info
  • Host: GitHub
  • Owner: arfc
  • License: bsd-3-clause
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 23.5 MB
Statistics
  • Stars: 12
  • Watchers: 5
  • Forks: 4
  • Open Issues: 8
  • Releases: 0
Topics
artificial-neural-networks gamma-spectroscopy python-package
Created over 7 years ago · Last pushed 11 months ago
Metadata Files
Readme Contributing License Citation

README.md

annsa

Artificial neural networks for spectroscopic analysis (annsa) is a python package can quickly prototype gamma-ray spectra datasets and machine learning and data science experiments for these datasets.

Install

To install, either git clone the annsa repo or download and unzip the zip file. In your command line run:

cd annsa python setup.py install

Standard Naming Convention for Spectrum Files

Ex. "99MTc_500.0_50.0_lead_0.0_2.0.spe"

This is for a spectrum taken with the following parameters
Technetium-99, metastable
500cm away from detector
50cm above ground
Lead shielding
'Areal' density of shielding
Full width half max of 2.0
File type: .spe

Owner

  • Name: Advanced Reactors and Fuel Cycles
  • Login: arfc
  • Kind: organization
  • Email: arfc@groups.google.com
  • Location: University of Illinois at Urbana-Champaign

A research group focused on modeling and simulation of advanced nuclear reactors and fuel cycles.

Citation (citation.md) 

Mark Kamuda, annsa, (2018), GitHub repository, https://github.com/kamuda1/annsa



```latex
@misc{kamuda2018,
  author = {Kamuda, Mark},
  title = {annsa},
  year = {2018},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/kamuda1/annsa}}
}
```

GitHub Events

Total
  • Watch event: 1
  • Issue comment event: 1
  • Push event: 1
  • Pull request event: 1
Last Year
  • Watch event: 1
  • Issue comment event: 1
  • Push event: 1
  • Pull request event: 1

Dependencies

requirements.txt pypi
  • matplotlib *
  • numpy *
  • pandas *
  • scikit-learn *
  • scipy *
  • tensorflow *
setup.py pypi
  • numpy *
  • scipy *
  • tensorflow *
test-requirements.txt pypi
  • pytest * test
  • pytest-flake8 * test