.. _api: Stingray API ************ Library of Time Series Methods For Astronomical X-ray Data. Data Classes ============ These classes define basic functionality related to common data types and typical methods that apply to these data types, including basic read/write functionality. Currently implemented are :class:`stingray.Lightcurve` and :class:`stingray.events.EventList`. Lightcurve ---------- .. autoclass:: stingray.Lightcurve :members: ---- EventList --------- .. autoclass:: stingray.events.EventList :members: ---- Fourier Products ================ These classes implement commonly used Fourier analysis products, most importantly :class:`Crossspectrum` and :class:`Powerspectrum`, along with the variants for averaged cross/power spectra. Crossspectrum ------------- .. autoclass:: stingray.Crossspectrum :members: ---- Coherence --------- Convenience function to compute the coherence between two :class:`stingray.Lightcurve` objects. .. autofunction:: stingray.coherence ---- Powerspectrum ------------- .. autoclass:: stingray.Powerspectrum :members: :private-members: :inherited-members: ---- AveragedCrossspectrum --------------------- .. autoclass:: stingray.AveragedCrossspectrum :members: :inherited-members: ---- AveragedPowerspectrum --------------------- .. autoclass:: stingray.AveragedPowerspectrum :members: :inherited-members: ---- Dynamical Powerspectrum ----------------------- .. autoclass:: stingray.DynamicalPowerspectrum :members: :inherited-members: ---- CrossCorrelation ---------------- .. autoclass:: stingray.CrossCorrelation :members: ---- AutoCorrelation --------------- .. autoclass:: stingray.AutoCorrelation :members: :inherited-members: ---- Dead-Time Corrections --------------------- .. automodule:: stingray.deadtime.fad :members: :imported-members: .. automodule:: stingray.deadtime.model :members: :imported-members: ---- Higher-Order Fourier and Spectral Timing Products ================================================= These classes implement higher-order Fourier analysis products (e.g. :class:`Bispectrum`) and Spectral Timing related methods taking advantage of both temporal and spectral information in modern data sets. Bispectrum ---------- .. autoclass:: stingray.bispectrum.Bispectrum :members: ---- Covariancespectrum ------------------ .. autoclass:: stingray.Covariancespectrum :members: ---- AveragedCovariancespectrum -------------------------- .. autoclass:: stingray.AveragedCovariancespectrum :members: :inherited-members: ---- VarEnergySpectrum ------------------ Abstract base class for spectral timing products including both variability and spectral information. .. autoclass:: stingray.varenergyspectrum.VarEnergySpectrum :members: ---- RmsEnergySpectrum ----------------- .. autoclass:: stingray.varenergyspectrum.RmsEnergySpectrum :members: :inherited-members: ---- LagEnergySpectrum ----------------- .. autoclass:: stingray.varenergyspectrum.LagEnergySpectrum :members: :inherited-members: ---- ExcessVarianceSpectrum ---------------------- .. autoclass:: stingray.varenergyspectrum.ExcessVarianceSpectrum :members: :inherited-members: ---- Utilities ========= Commonly used utility functionality, including Good Time Interval operations and input/output helper methods. Statistical Functions --------------------- .. automodule:: stingray.stats :members: :imported-members: GTI Functionality ----------------- .. automodule:: stingray.gti :members: :imported-members: I/O Functionality ----------------- .. automodule:: stingray.io :members: Other Utility Functions ----------------------- .. automodule:: stingray.utils :members: :imported-members: Modeling ======== This subpackage defines classes and functions related to parametric modelling of various types of data sets. Currently, most functionality is focused on modelling Fourier products (especially power spectra and averaged power spectra), but rudimentary functionality exists for modelling e.g. light curves. .. _loglikelihoods: Log-Likelihood Classes ---------------------- These classes define basic log-likelihoods for modelling time series and power spectra. :class:`stingray.modeling.LogLikelihood` is an abstract base class, i.e. a template for creating user-defined log-likelihoods and should not be instantiated itself. Based on this base class are several definitions for a :class:`stingray.modeling.GaussianLogLikelihood`, appropriate for data with normally distributed uncertainties, a :class:`stingray.modeling.PoissonLogLikelihood` appropriate for photon counting data, and a :class:`stingray.modeling.PSDLogLikelihood` appropriate for (averaged) power spectra. .. autoclass:: stingray.modeling.LogLikelihood :members: :inherited-members: .. autoclass:: stingray.modeling.GaussianLogLikelihood :members: :inherited-members: .. autoclass:: stingray.modeling.PoissonLogLikelihood :members: :inherited-members: .. autoclass:: stingray.modeling.PSDLogLikelihood :members: :inherited-members: .. autoclass:: stingray.modeling.LaplaceLogLikelihood :members: :inherited-members: ---- Posterior Classes ----------------- These classes define basic posteriors for parametric modelling of time series and power spectra, based on the log-likelihood classes defined in :ref:`loglikelihoods`. :class:`stingray.modeling.Posterior` is an abstract base class laying out a basic template for defining posteriors. As with the log-likelihood classes above, several posterior classes are defined for a variety of data types. Note that priors are **not** pre-defined in these classes, since they are problem dependent and should be set by the user. The convenience function :func:`stingray.modeling.set_logprior` can be useful to help set priors for these posterior classes. .. autoclass:: stingray.modeling.Posterior :members: :inherited-members: .. autoclass:: stingray.modeling.GaussianPosterior :members: :inherited-members: .. autoclass:: stingray.modeling.PoissonPosterior :members: :inherited-members: .. autoclass:: stingray.modeling.PSDPosterior :members: :inherited-members: .. autoclass:: stingray.modeling.LaplacePosterior :members: :inherited-members: ---- Parameter Estimation Classes ---------------------------- These classes implement functionality related to parameter estimation. They define basic ``fit`` and ``sample`` methods using ``scipy.optimize`` and ``emcee``, respectively, for optimization and Markov Chain Monte Carlo sampling. :class:`stingray.modeling.PSDParEst` implements some more advanced functionality for modelling power spectra, including both frequentist and Bayesian searches for (quasi-)periodic signals. .. autoclass:: stingray.modeling.ParameterEstimation :members: .. autoclass:: stingray.modeling.PSDParEst :members: :inherited-members: ---- Auxiliary Classes ----------------- These are helper classes instantiated by :class:`stingray.modeling.ParameterEstimation` and its subclasses to organize the results of model fitting and sampling in a more meaningful, easily accessible way. .. autoclass:: stingray.modeling.OptimizationResults :members: :private-members: .. autoclass:: stingray.modeling.SamplingResults :members: :private-members: ---- Convenience Functions --------------------- These functions are designed to help the user perform common tasks related to modelling and parameter estimation. In particular, the function :func:`stingray.modeling.set_logprior` is designed to help users set priors in their :class:`stingray.modeling.Posterior` subclass objects. .. autofunction:: stingray.modeling.set_logprior .. automodule:: stingray.modeling.scripts :members: :imported-members: ---- Pulsar ====== This submodule broadly defines functionality related to (X-ray) pulsar data analysis, especially periodicity searches. .. automodule:: stingray.pulse :members: :imported-members: Simulator ========= This submodule defines extensive functionality related to simulating spectral-timing data sets, including transfer and window functions, simulating light curves from power spectra for a range of stochastic processes. .. autoclass:: stingray.simulator.simulator.Simulator :members: :undoc-members: Exceptions ========== Some basic Stingray-related errors and exceptions. .. autoclass:: stingray.exceptions.StingrayError :members: :undoc-members: