This script provides an embedded dataset of redshift and comoving distance measurements from Type Ia supernovae and a minimal Python class to load and parse the data in memory.
These measurements can be used for studying cosmic expansion, Hubble's law, and dark energy models.
The dataset is embedded directly in the script as a multi-line string using CSV format. The class CosmologicalExpansionAnalyzer reads and parses this data on instantiation.
Each data entry contains:
redshift(z): Dimensionless, derived from supernova light spectra.distance_mpc: Comoving distance in megaparsecs (Mpc), assuming a cosmological model.
- Zero I/O: Data is embedded in the script—no need for external files.
- Lightweight: Pure Python solution with no required dependencies.
- Ready for analysis: Converts the dataset into a pandas
DataFramefor easy manipulation and plotting.
After installing the package, simply type the following command in your terminal:
cosmoexpThis will automatically load the dataset and display a Hubble diagram, showcasing the relationship between redshift and comoving distance.
No additional setup or coding is required except anything that you might contribute.