Python Module Index

p
 
p
- pgmuvi
    pgmuvi.constraints
    pgmuvi.gps
    pgmuvi.initialization
    pgmuvi.kernels
    pgmuvi.lightcurve
    pgmuvi.multiband_ls_significance
    pgmuvi.preprocess
    pgmuvi.preprocess.quality
    pgmuvi.preprocess.variability
    pgmuvi.priors
    pgmuvi.synthetic
    pgmuvi.trainers

pgmuvi

Navigation

  • Background
  • Key Concepts
  • Glossary
  • Preamble
  • The Lightcurve object
  • In this notebook, we will demonstrate some features available for Lightcurve objects to manipulate 1D and 2D light curve data.
  • Data structure and invariants
  • Missing and non-finite data
  • Generating synthetic data
  • Visualization using the .plot() method
  • Input/output to CSV
  • The band attribute; selecting, dropping, merging, and concatenating light curves.
  • Subsampling light curves
  • Statistical tests for variability
  • Preamble
  • Return modes of fit_LS()
  • Key points to keep in mind
  • Frequencies vs periods
  • Ordering of peaks
  • Meaning of the significance mask
  • Practical takeaway
  • Joint analysis across bands
  • Sensitivity to heterogeneous sampling
  • Interpretation of peaks
  • Significance in the multiband case
  • Practical takeaway
  • Why this matters
  • What use_best_band_init=True does
  • When to use it
  • Dominant component (~150 d)
  • Secondary component (~66 d)
  • Short-period region
  • Overall interpretation
  • Single-band case
  • Multiband case
  • Practical implication
  • Different roles of LS and GP models
  • Using LS to initialize GP models
  • Important caveat
  • Practical takeaway
  • What fit_LS() does well
  • Key points about interpretation
  • Multiband-specific considerations
  • Role of sampling
  • Relationship to GP modeling
  • Final takeaway
  • Gaussian-process fitting in pgmuvi
  • GP model families available in pgmuvi
  • A practical way to choose a GP model
  • Basic GP-fitting workflow in pgmuvi
  • Comparing GP packages on synthetic light curves
  • How to use pgmuvi - a brief introduction
  • Tutorial: Preprocessing and Data Quality Assessment
  • Tutorial: Generating Synthetic Light Curves
  • Tutorial: Model Selection
  • How-To Guides
  • Frequently Asked Questions
  • API reference

Related Topics

  • Documentation overview
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