Quick Start Guide

This guide will get you started with CosmoForge’s main packages quickly.

CosmoForge Architecture

CosmoForge is organized as a namespace package with three main components:

  • cosmoforge.cosmocore: Core mathematical and computational utilities

  • cosmoforge.qube: QML estimation and Fisher matrix analysis

  • cosmoforge.meta: Metadata and project-wide utilities

Getting Started with CosmoCore

Parameter Management

CosmoCore uses a centralized parameter system:

from cosmoforge.cosmocore.cosmocore.settings import InputParams

# Create with defaults
params = InputParams()

# Check key parameters
print(f"HEALPix nside: {params.nside}")
print(f"Maximum l: {params.lmax}")
print(f"Field labels: {params.labels}")
print(f"Number of pixels: {params.npix}")

Configuration Files

Use YAML files for configuration:

# config.yaml
nside: 32
lmax: 128
labels: ["T", "E", "B"]          # Analysis field labels
physical_labels: ["T", "Q", "U"] # Map field labels (or "TQU", "T1_T2")
input_convention: Dl              # "Cl" (default) or "Dl" for input files
fwhmarcmin: 5.0
apply_pixwin: true

# Load configuration
params = InputParams.read_parameter_file('config.yaml')

Field Expansion

CosmoForge supports automatic field label expansion:

# Concatenated single-character fields
physical_labels: ["QU"]      # Expands to ["Q", "U"]
labels: ["TEB"]              # Expands to ["T", "E", "B"]

# Underscore-separated multi-character fields
labels: ["T1_T2"]            # Expands to ["T1", "T2"]
physical_labels: ["LOW_HIGH"] # Expands to ["LOW", "HIGH"]

# Mixed configurations
labels: ["T", "QU", "E1_E2"]  # Expands to ["T", "Q", "U", "E1", "E2"]

Mathematical Utilities

Access optimized mathematical functions:

from cosmoforge.cosmocore.cosmocore.basics import legendre_00, scalar_prod
import numpy as np

# Compute Legendre polynomials
x = 0.5
lmax = 10
legendre_values = legendre_00(x, lmax)

# Vector operations
vec1 = np.array([1.0, 0.0, 0.0])
vec2 = np.array([0.0, 1.0, 0.0])
dot_product = scalar_prod(vec1, vec2)

Getting Started with QUBE

Fisher Matrix Analysis

from cosmoforge.qube import Fisher

# Initialize Fisher analysis
fisher = Fisher("config/fisher_config.yaml")
fisher.run()

if fisher.rank == 0:
    errors = fisher.get_error_bars()

QML Power Spectrum Estimation

from cosmoforge.qube import Spectra

# Initialize QML analysis
spectra = Spectra("config/qml_config.yaml")
spectra.run()

if spectra.rank == 0:
    # Default: deconvolved estimates of true C_ell
    cl = spectra.get_power_spectra()
    # Other modes: "decorrelated", "convolved"
    cl_decorr = spectra.get_power_spectra(mode="decorrelated")

Next Steps