aframosp/analysis_diagism

In this repository we found all the information for the analysis of the DiagISM web app

Reproduction repository for "Diagnosing the interstellar medium of galaxies with far-infrared emission lines III. Physical parameters of observed galaxies"

This repository contains data and code to reproduce the results of the research "Diagnosing the interstellar medium of galaxies with far-infrared emission lines III. Physical parameters of observed galaxies". Each step of the work is described in a step-by-step file with their respective Jupyter notebooks.

Software requirements

The most important software packages to work with the files in this repository are in environment.yml. This file is also used to launch a Binder to open the Jupyter notebooks interactively. We print all the packages in a given notebook using the IPython magic extension watermark. We also use autotpep8 to format the code to the PEP 8 style guide.

Repository Organization

The following is the organization of the repository with a simple description of the files or folder contents

.
├── CITATION.cff       <- Metadata for citation
├── LICENSE            <- License file
├── environment.yml    <- File containing the required software
├── README.md          <- This file
├── StepByStep.md      <- File describing the steps taken in this work
├── data
│   ├── interim        <- Intermediate data that has been transformed
│   ├── processed      <- Results from DiagISM and final data
│   └── raw            <- Original data from Paper II
├── notebooks          <- Jupyter notebooks
└── figures            <- Figures created from the Jupyter notebooks

Estimated physical parameters

The file containing the estimated physical parameters from the observational sample can be found in the predictions_DiagISM_obsSample.csv file.

Missing data

Unfortunately not all the raw data is available in the repository. Data from the SIDES lightcone catalog is ~2Gb, then we decided not to included in this repository, but if you want to use it you can check the webpage to obtain the catalogue.

Beside this, the mock_sample.csv file is not stored in Github (~100Mb) and need to be stored locally by running the notebook AppA_Predictions_newlinreg.