Getting Started

This guide will help you install gen_surv and generate your first survival dataset.

Installation

From PyPI (Recommended)

pip install gen-surv

From Source

git clone https://github.com/DiogoRibeiro7/genSurvPy.git
cd genSurvPy
poetry install

Note

Some features and tests rely on optional packages such as scikit-survival. Install them with poetry install --with dev or pip install scikit-survival (additional system libraries may be required).

Basic Usage

The main entry point is the generate() function:

from gen_surv import generate

# Generate Cox proportional hazards data
 df = generate(
     model="cphm",      # Model type
     n=100,             # Sample size
    beta=0.5,          # Covariate effect
    covariate_range=2.0,  # Covariate range
     model_cens="uniform",  # Censoring type
     cens_par=3.0       # Censoring parameter
 )

print(df.head())

Understanding the Output

All models return a pandas DataFrame with at least these columns:

time: Observed event or censoring time
status: Event indicator (1 = event, 0 = censored)
Additional columns depend on the specific model

Command Line Usage

Generate datasets directly from the terminal:

# Generate CPHM data and save to CSV
python -m gen_surv dataset cphm --n 1000 -o survival_data.csv

# Print AFT data to stdout
python -m gen_surv dataset aft_ln --n 500

Next Steps

Explore the Tutorials for detailed examples
Check the API Reference for complete function documentation
Read about the 📘 Mathematical Foundations of gen_surv behind each model

Building the Documentation

To preview the documentation locally run:

cd docs
make html

More details about our Read the Docs configuration can be found in Read the Docs.