Getting started
This page provides a short roadmap for new users before diving into the more detailed reference sections.
Recommended reading order
Installation Guide to create a working environment.
Configuring BESTA to understand the runtime options and values files.
Pipeline Manager if you plan to run CosmoSIS-based fits.
Post-processing and Posterior Analysis to inspect results after a run completes.
Grid-Based Inference if your use case is better served by precomputed model grids.
Two main workflows
BESTA currently supports two complementary analysis modes:
- Sampler-based pipeline fitting with
besta.pipeline.MainPipeline. Use this when you need flexible forward modelling and continuous parameter inference, especially for spectroscopy or joint fits with nuisance parameters.
- Sampler-based pipeline fitting with
- Grid-based inference with
besta.grid.grid.GridFitter. Use this when you already have a finite model library and want high-throughput, repeatable inference over many objects.
- Grid-based inference with
Minimal pipeline example
The smallest CosmoSIS-based run usually contains:
a
runtimesection selecting the samplers,an
outputsection selecting the results filename,a
pipelinesection pointing to the active module and values file, andone module-specific section such as
FullSpectralFit.
The complete structure is documented in Configuring BESTA, and a full orchestration example is given in Pipeline Manager.
Tutorial material
The repository includes worked examples under tutorials/. In particular:
tutorials/fit_sdss_spectrademonstrates an end-to-end spectral fit,tutorials/fit_redshiftcontains redshift-oriented examples.
These tutorials complement the API reference by showing how the values file, input spectra, LSF information, and post-processing tools fit together in a single workflow.
Where to go next
For available fitting modules, see Pipeline Modules.
For API-level details, see API Reference.
For contributing fixes or documentation improvements, see the contributing page.