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.
Science Score: 44.0%
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Low similarity (7.3%) to scientific vocabulary
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
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- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files
README.md
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
- Website: https://ovlasovets.netlify.app/
- Twitter: ovlasovets
- Repositories: 5
- Profile: https://github.com/Vlasovets
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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