Documentation for PyImfit

OVERVIEW AND SAMPLE USAGE:

• Installation of PyImfit
  • Standard Installation: macOS
  • Standard Installation: Linux
  • Conda Installations:
• Sample Usage
• Overview of PyImfit
  • For Those Already Familiar with Imfit
  • The Basics
    • Specify the model (and its parameters)
    • Fit a model to the data
    • Generate a model image (without fitting)
• Pixel Coordinate Conventions
  • Image Coordinates
  • Specifying Image Subsets for Fitting

USER DOCUMENTATION:

• Defining Models
  • Image Functions
  • More Information
• PSF Convolution
  • Requirements for PSF images
  • Basic PSF Convolution
  • Convolving with Oversampled PSFs
• Fitting an Image (Choosing Fit Statistics and Solvers)
  • Finding the best-fit solution by minimizing a fit statistic
  • Fit statistics (chi^2 and all that)
  • Minimizers/Solvers
  • More Information
• Bootstrap Resampling for Parameter Uncertainties
  • Bootstrap Resampling
  • Using MCMC
• Example of using PyImfit with Markov-Chain Monte Carlo code “emcee”
  • Create image-fitting model using PyImfit
  • Define log-probability functions for use with emcee
  • Set up and run Markov-Chain Monte Carlo using emcee
  • Corner plot of converged MCMC samples
• Example of using PyImfit to Estimate B/T Uncertainties
  • Introduction
• Acknowledgments
  • Imfit-related Acknowledgements

API DOCUMENTATION:

• PyImfit API
  • Description Classes
  • The Imfit class
  • Useful Functions

Imfit manual (PDF)