Downloading Repository

The first thing that needs to be done is to download the repository from Github:

git clone

This will download all of the necessary scripts to run the analysis on the SDSS DR7 catalogues.

Installing Environment & Dependencies

To use the scripts in this repository, you must have Anaconda installed on the system that will be running the scripts. This will simplify the process of installing all the dependencies.

For reference, see: Anaconda - Managing environments

The package counts with a Makefile with useful functions. You must use this Makefile to ensure that you have all the necessary dependencies, as well as the correct conda environment.

Once Anaconda has been installed, you can use the Makefile to

  • Install the Anaconda environment conformity.
  • Update the project environment conformity.
  • Install the src package via pip.

Makefile functions

  • Show all available functions in the Makefile
$:  make show-help

  1_halo_fracs_calc   1-halo Quenched Fractions - Calculations
  1_halo_mcf_calc     1-halo Marked Correlation Function - Calculations
  2_halo_fracs_calc   2-halo Quenched Fractions - Calculations
  2_halo_mcf_calc     2-halo Marked Correlation Function - Calculations
  clean               Deletes all build, test, coverage, and Python artifacts
  clean-build         Remove build artifacts
  clean-pyc           Removes Python file artifacts
  clean-test          Remove test and coverage artifacts
  cosmo_utils_install Installing cosmo-utils
  cosmo_utils_remove  Removing cosmo-utils
  cosmo_utils_upgrade Upgrading cosmo-utils
  download_dataset    Download required Dataset
  environment         Set up python interpreter environment - Using environment.yml
  lint                Lint using flake8
  plot_figures        Figures
  remove_calc_screens Remove Calc. screen session
  remove_catalogues   Remove downloaded catalogues
  remove_environment  Delete python interpreter environment
  remove_plot_screens Remove Plot screen session
  src_env             Import local source directory package
  src_remove          Remove local source directory package
  src_update          Updated local source directory package
  test_environment    Test python environment is setup correctly
  update_environment  Update python interpreter environment
  • Create the environment from the environment.yml file:
$:  make environment
  • Activate the new environment conformity.
$:  source activate conformity
  • To update the environment.yml file (when the required packages have changed):
$:  make update_environment
  • Deactivate the new environment:
$:  source deactivate

Auto-activate environment

To make it easier to activate the necessary environment, one can check out *conda-auto-env* which activates the necessary environment automatically.

Download Dataset

In order to be able to run the scripts in this repository, one needs to first download the required datasets. One can do that by running the following command from the main directory and using the Makefile:

$: make download_dataset

This command will download the required catalogues for the analysis to the data/external/ directory.

Depending on the variables used for the analysis, one can download different sets of catalogues, depending on what kind of catalogues they want to use it for.


In order to make use of this commands, one will need wget. If wget is not available, one can download the files from and put them in /data/external/SDSS.

Steps and Commands

By running the following commands, one is able to replicate the results found in Calderon et al. (2018).

git clone
cd SDSS_Conformity_Analysis/
make environment
source activate conformity
make download_dataset
make 1_halo_fracs_calc
make 1_halo_mcf_calc
make 2_halo_fracs_calc
make 2_halo_mcf_calc
make plot_figures
open /reports/figures/SDSS/Paper_Figures/

This is the sequence of commands used to create the results shown in Calderon et al. (2018). The scripts already have default values. If one wishes to perform the analysis using a different set of parameters, these can be changed in the Makefile, or by simply calling the functions in the Makefile as:

make SAMPLE="20" download_dataset

This command will download the datasets for the Mr20 galaxy and group galaxy catalogues.