The Multi-Mission Maximum Likelihood framework Logo
  • Installation
  • Intro
  • Configuration
  • Logging and Verbosity
  • Notes for XSPEC Users
  • Minimization
  • Bayesian Posterior Sampling
  • Plugins
    • Building Custom Plugins
    • Spectrum Plugins
    • Constructing plugins from TimeSeries
    • Background Modeling
    • Photometric Plugin
    • HAL (HAWC Accelerated Likelihood) plugin
  • Modeling
  • Frequently Asked Questions
  • API
  • threeML
  • Release Notes

Features and examples:

  • Analyzing GRB 080916C
  • Example joint fit between GBM and Swift BAT
  • Joint fitting XRT and GBM data with XSPEC models
  • Point Source Fluxes and Multiple Sources
  • Time-energy fit
  • Analysis Results
  • Random Variates
  • Point source plotting basics
  • Generating Synthetic Data
  • Goodness of Fit and Model Comparison
The Multi-Mission Maximum Likelihood framework
  • »
  • Plugins
  • Edit on GitHub

PluginsΒΆ

3ML is based on a plugin system. This means that For each instrument/datum, there is a plugin that holds the data, reads a model, and returns a likelihood. This is how we achieve the multi-messenger paradigm. A plugin handles its likelihood call internally and the likelhoods are combined within 3ML during a fit.

Contents:

  • Building Custom Plugins
    • The PluginPrototype class
      • Basic Properties
        • name
        • nuisance parameters
      • Unique Properties
        • set_model
        • get_log_like
        • inner_fit
    • Making a custom plugin
  • Spectrum Plugins
    • SpectrumLike
      • The count spectrum
        • Selection
      • Rebinning
      • Fitting
    • DispersionSpectrumLike
    • OGIPLike
  • Constructing plugins from TimeSeries
    • Constructing time series objects from different data types
      • GBM Data
      • LAT LLE data
    • Viewing Lightcurves and selecting source intervals
    • Fitting a polynomial background
    • Saving the background fit
    • Creating a plugin
    • Time-resolved binning and plugin creation
      • Constant Cadence
      • Custom
      • Significance
      • Bayesian Blocks
      • Working with bins
  • Background Modeling
    • Using a profile likelihood
    • Modeling the background
  • Photometric Plugin
    • Setup
      • Simple example of building a filter
    • 3ML filter library
    • Build your own filters
    • GROND Example
      • Model specification
  • HAL (HAWC Accelerated Likelihood) plugin
    • Download
    • Exploratory analysis
    • Simple model fit
    • Assessing the Fit Quality
    • Visualizing the Fit Results
Next Previous

© Copyright 2017--2020, G.Vianello, J. M. Burgess, N. Di Lalla, N. Omodei. Revision dccecb0e.

Built with Sphinx using a theme provided by Read the Docs.
Read the Docs v: latest
Versions
latest
stable
v2.1.3
v2.1.2
v2.1.1
v2.1.0
v2.0.3
v2.0.2
v2.0.1
v2.0.0
v1.2.0
v1.1.1
v1.0.9
Downloads
On Read the Docs
Project Home
Builds