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materials_data_analytics

Data analytics software for materials characterization

https://github.com/nicholas9182/materials_data_analytics

Science Score: 44.0%

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    Low similarity (11.0%) to scientific vocabulary
Last synced: 9 months ago · JSON representation ·

Repository

Data analytics software for materials characterization

Basic Info
  • Host: GitHub
  • Owner: nicholas9182
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 463 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 3
  • Releases: 5
Created over 3 years ago · Last pushed 10 months ago
Metadata Files
Readme Citation

README.md

MaterialsDataAnalytics

A python package for the handling and analysis of a wide range of synthetic and experimental data for the development of next-generation energy materials. Its modular, method-chainable design makes it easy for researchers to analyze complex datasets efficiently, promoting reproducibility and extensibility.

Authors

  • Dr. Nicholas Siemons (GitHub) (nsiemons@stanford.edu)
  • Dr. Arianna Magni (GitHub) (amagni@stanford.edu)
  • Srikant Sagireddy (GitHub) (srikant@stanford.edu)

Why

The package was developed to streamline the analysis of a wide range of materials data, with a focus on the development of next-generation energy materials. The package is designed to be as user-friendly as possible, with a focus on ease of use, readability and distributility. The package is designed to be as modular as possible, with the aim of allowing users to easily extend the package to suit their own needs.

This package looks to keep many aspects of materials data analysis in one place. In doing so it allows for complex analysis to be done in a single environment, and for the results of that analysis to be easily compared. Furthermore, it will allow for analysis involving data from a variety of sources.

Philosophy

The package is designed to be as user-friendly as possible, with a focus on ease of use, readability and distributility. The package is designed to be as modular as possible, with the aim of allowing users to easily extend the package to suit their own needs. Wherever suitable, the code has been written so as to be method chainable, allowing for more concise and readable code.

Generally any class methods will do one of four things - - modify the self of the object in place - return a pandas dataframe, which can then be method chained with the usual pandas methods - return a plotly.express figure, which can then be modified with the usual plotly methods. In these cases, arguments can be passed to the method to modify the figure according with the plotly documentation through the use of **kwargs. - display a plotly figure

Additionally, the creation of almost all objects can be done by parsing a metadata dictionary to the object. This means that, for example, measurements corresponding to different systems can easily be compared by calculating their properties along with their metadata into a long-format dataframe, and then comparing those properties using the usual pandas and plotly methods. Finally, internally this package leverages the power of pandas and plotly for the handling and visualization of data.

Key Analysis Types

  • Cyclic Voltammetry: Analyze and visualize electrochemical measurements for battery and fuel cell development.
  • GIWAXS Analysis: Interpret grazing-incidence wide-angle X-ray scattering data to understand material structures.
  • Gaussian Quantum Chemistry: Analyze and visualize results from quantum chemistry calculations.
  • Gromacs+Plumed Metadynamics: Analyze and visualize results from metadynamics simulations.

Installation

To install the package, clone the repository and run the following command:

sh pip install ./path/to/Materials_Data_Analytics

or alternatively to install the most recent version from PyPi, run

sh pip install Materials_Data_Analytics

For usage instructions, see the README.md files in the module folders.

Dependencies

  • scipy
  • pandas
  • plotly
  • matplotlib
  • typer
  • click
  • numpy
  • networkx
  • MDAnalysis
  • dash
  • kaleido
  • pyFAI
  • pygix
  • Datetime

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Owner

  • Name: Nicholas Siemons
  • Login: nicholas9182
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.0.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: Siemons
    given-names: Nicholas
    orcid: https://orcid.org/0000-0002-0755-3981
  - family-names: Magni
    given-names: Arianna
    orcid: https://orcid.org/0000-0002-9376-4522
  - family-names: Sagireddy
    given-names: Srikant
  - family-names: Shad
    given-names: Alison
title: "Materials_Data_Analytics"
version: 6.2.10
doi: 10.5281/zenodo.15366819
date-released: 2024-09-13

GitHub Events

Total
  • Release event: 3
  • Delete event: 53
  • Member event: 7
  • Push event: 91
  • Pull request review comment event: 6
  • Pull request review event: 20
  • Pull request event: 111
  • Create event: 59
Last Year
  • Release event: 3
  • Delete event: 53
  • Member event: 7
  • Push event: 91
  • Pull request review comment event: 6
  • Pull request review event: 20
  • Pull request event: 111
  • Create event: 59

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 1
  • Total pull requests: 20
  • Average time to close issues: N/A
  • Average time to close pull requests: 8 days
  • Total issue authors: 1
  • Total pull request authors: 4
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 15
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 20
  • Average time to close issues: N/A
  • Average time to close pull requests: 8 days
  • Issue authors: 1
  • Pull request authors: 4
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 15
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • nicholas9182 (2)
Pull Request Authors
  • nicholas9182 (42)
  • magaris (12)
  • acshad (4)
  • ljmele (3)
  • kmasalk (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 186 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 24
  • Total maintainers: 1
pypi.org: materials-data-analytics

Data analysis package for materials characterisation at Stanford University

  • Versions: 24
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 186 Last month
Rankings
Dependent packages count: 10.3%
Average: 34.3%
Dependent repos count: 58.2%
Maintainers (1)
nsiemons
Last synced: 10 months ago

Dependencies

requirements.txt pypi
  • MDAnalysis ==2.3.0
  • click ==8.1.3
  • matplotlib ==3.6.2
  • numpy ==1.23.3
  • pandas ==1.5.1
  • plotly ==5.11.0
  • plumed ==2.8.0
  • typer ==0.7.0
setup.py pypi