cmbscat 0.0.0

A package for scattering covariance synthesis on datasets of Healpix maps, based on the HealpixML package.

CMBSCAT: fast map-based emulator for CMB systematics

cmbscat is a pip installable package that can synthesize new map samples (called emulations) which are both visually and statistically similar to the ones found in an (eventually) small dataset of simulations.

Install with pip

You can install it simply doing:

pip install cmbscat

Usage

You can then set generate a new dataset of CMB systematics maps by doing:

from cmbscat import cmbscat_pipe

# Set emulator parameters
params = {
    'NNN'          : 10,             # Number of input reference maps
    'gauss_real'   : True,             # Generate new input data as Gaussian realizations from pixel covariance of original data
    'NGEN'         : 10,               # Batch size for gradient descent
    'n_samples'    : 10,               # Samples in the input dataset
    'nside'        : 16,               # N_side of input maps
    'NORIENT'      : 4,                # Orientations in the SC
    'nstep'        : 50,              # Steps in gradient descent
    'KERNELSZ'     : 3,                # Wavelet kernel size
    'outname'      : 'example',        # Output name
    'outpath'      : './data/',        # Output path
    'data'         : 'variable_gain_sims.npy'  # Input data path
}

# Initialize pipeline...
pipeline = cmbscat_pipe(params)

#...and run! This generates NGEN new maps for each of the n_samples input maps
pipeline.run()

Tutorial Notebook

You can find an introductory notebook explaining all features of the cmbscat package here