prodg

a Python library for generating synthetic data based on different probability distributions. It's specifically designed for prokaryotic data but can be used for any zero-inflated compositional data.

https://github.com/vlasovets/prodg

Science Score: 44.0%

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Repository

a Python library for generating synthetic data based on different probability distributions. It's specifically designed for prokaryotic data but can be used for any zero-inflated compositional data.

Basic Info
  • Host: GitHub
  • Owner: Vlasovets
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 27.3 KB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

Python version License: MIT

ProDG: Prokaryotic Data Generator

ProDG is a Python library for generating synthetic data based on different probability distributions. It's specifically designed for prokaryotic data but can be used for any zero-inflated compositional data.

Installation

You can install ProDG using:

bash git clone https://github.com/Vlasovets/microbe-data-gen.git

Usage

Here is a basic example of how to use ProDG:

```python from prodg import DataGenerator

create a sample data where rows are bacterial species names and columns are sample names

df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=['Sample1', 'Sample2', 'Sample3', 'Sample4'])

call generator instance

prodg = DataGenerator()

Fit the models to the data

prodg.fit(df)

Generate new data

synthetic_data = prodg.generate(df)

Print the synthetic data

print(synthetic_data) ```

License

ProDG is licensed under the MIT License.

Owner

  • Name: Oleg
  • Login: Vlasovets
  • Kind: user
  • Location: Munich
  • Company: Helmholtz Munich

Citation (CITATION.cff)

format: https://doi.org
title: Prokaryotic Data Generator
version: 0.1
authors:
  - Last Names: Vlasovets
    First Names: Oleg
    orcid: 0000-0001-5259-9674
date-released: 2024-03-08

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Dependencies

requirements.txt pypi
setup.py pypi