frbmclust

Getting Started

Clusterize FRB profiles using hierarchical clustering, plot corresponding parameters distributions. Input files (waterfall data, CHIME catalog) are stored in the resources/ directory, output files are stored in the plots/ directory.

Data used in the clustering belongs to the CHIME/FRB collaboration, CHIME/FRB Catalog 1 Paper.

Prerequisites

• Python 3.7+

• The vos Python module for downloading waterfall data: CANFAR storage system

  • pip install vos --upgrade --user

• Python code related to DM calculations, estimations, and analysis: FRB

  • For FRB dependencies see: Installing FRB

    git clone https://github.com/FRBs/FRB.git
    cd FRB ; python setup.py install --user ; cd ..
    

    git clone https://github.com/FRBs/ne2001.git
    cd ne2001 ; python setup.py install --user ; cd ..
    

• astropy v4.3+

  pip install --upgrade pip 
  pip install astropy
  

• Installation/upgrade of side packages, which might be required for the version compatibility

  • pip install --user --upgrade lxml pandas ipython scipy matplotlib seaborn h5py

• cosmocalc

  We download cosmocalc v0.1.2 and refactor it to be able to run under Python 3 (2to3 software is used and should be installed via package manager):

  curl https://files.pythonhosted.org/packages/ca/61/df95b65cd3cf3abdffcbeea6c77a6d8964a8fb625a88eccd9c73d2bfdbf0/cosmocalc-0.1.2.tar.gz | tar -x
  cd cosmocalc-0.1.2 ; 2to3 -w cosmocalc.py ; python setup.py install --user ; cd ..
  

Configuration

For the fast reproduction of the main results one can run python frb_profiles_clustering.py --use-preprocessed --use-precalculated-z.

Instead of preprocessed signal data, waterfall data can also be used, which is located in CANFAR storage and which can be downloaded with the -d flag. For the data to be used, it shoud be in the resources/ folder and have a following name: {frb_name}_waterfall.h5

To obtain preprocessed signals, run python repack_waterfall.py. It would download waterfall data from CANFAR storage one at a time and save only calibrated profiles – mean of calibrated waterfall data over each frequency channel.

When calling python frb_profiles_clustering.py several flags are available:

• -d, --download: download waterfall data from CANFAR storage
• -ef, --emission_freq: set emission frequency (MHz) used in brightness temperature calculations. Default value is 600 MHz
• --use-preprocessed: use preprocessed signal profiles
• --use-precalculated-z: use precalculated red-shift values
• --use-latex: enable LaTeX support for plots