This upload contains all the python codes used in the paper titled "Phenomenological Dark Energy model with hybrid dynamic Cosmological Constant" [1] in pdfLaTeX format. There are five codes in the upload overall. A short description of what the codes do is given below – The code files named “Standard model test code” and “Hubble diagram code” fit supernova data from Union 2.1 collaboration [2] to the standard ΛCDM model and hybrid dynamic Cosmological Constant model (the model of the concerned paper) for estimating the relevant model parameters for flat Universe. The fitting procedure uses emcee [3] within the Lmfit module [4] of python which implements the Affine Invariant Markov Chain Monte Carlo (MCMC) method for extracting the model parameters. Publicly available Union 2.1 data has been presented in a .txt file named “union 2.1 sorted” for convenience and the codes are written to read data directly from the .txt file. (The tab-separated columns of union 2.1 sorted.txt stands for Redshift, Distance Modulus, and Distance Modulus Error respectively of union 2.1 Supernova data). The code files “Scale factor evolution code” and “Deceleration parameter evolution code” plot the evolution of scale factor and deceleration parameter for both – standard ΛCDM model and hybrid dynamic Cosmological Constant model using the fitted values of parameters. The code file “Derived Parameters code” calculates the derived Cosmological parameters - present-day deceleration parameter, transition redshift, and Age of the Universe for standard ΛCDM model and hybrid dynamic Cosmological Constant model. Parts of the code that calculates Cosmic Age has been adapted from Fatima et al. [5]

{"references": ["[1] A. Anonymous, Phenomenological Dark Energy model with hybrid dynamic Cosmological Constant", "[2] N. Suzuki et al., Union2.1 Compilation Magnitude vs. Redshift Table (for your own cosmology fitter). http://supernova.lbl.gov/Union/", "[3] D. Mackey, D. Hogg, D. Lang and J. Goodman, Publ. Astron. Soc. Pac. 125, 306 (2013).", "[4] M. Newville, T. Stensitzki, D.Allen and A.Ingargiola, Lmfit Code, Zenodo (2014).", "[5] H. Fatima, M. Mushtaq and S. Rahman, arXiv:1609.02480"]}

The manuscript related to the codes has been accepted and is currently available online at https://doi.org/10.1088/1361-6382/ac35ed A new version of the codes will be uploaded soon which will include new codes used in the paper due to revision during the peer-review process.