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Software modes

Running as a script

When running the software, pySYD will look in the following paths:

  • INFDIR : '~/path/to/local/pysyd/directory/info'
  • INPDIR : '~/path/to/local/pysyd/directory/data'
  • OUTDIR : '~/path/to/local/pysyd/directory/results'

which by default, is the absolute path of the current working directory (or wherever you ran setup from). We will eventually add an option to save the example data and files as package data (since it is easier to load in)

Important: when running pysyd as a script, there is one positional argument for the pipeline "mode".

Importing as a module

Pipeline overview

The software generally operates in four main steps:
  1. :ref:`Loads in parameters and data <quickstart/stepone>`
  2. :ref:`Gets initial values <quickstart/steptwo>`
  3. :ref:`Fits global parameters <quickstart/stepthree>`
  4. :ref:`Estimates uncertainties <quickstart/stepfour>`

Note

The software will process the pipeline on oversampled spectra for the first iterations but will always switch to critically-sampled spectra for estimating uncertainties. Calculating uncertainties with oversampled spectra can produce unreliable results and uncertainties!

A pySYD pipeline Target class object has two main function calls:

  1. The first module :
    • Summary: a crude, quick way to identify the power excess due to solar-like oscillations
    • This uses a heavy smoothing filter to divide out the background and then implements a frequency-resolved, collapsed autocorrelation function (ACF) using 3 different box sizes
    • The main purpose for this first module is to provide a good starting point for the second module. The output from this routine provides a rough estimate for numax, which is translated into a frequency range in the power spectrum that is believed to exhibit characteristics of p-mode oscillations
  2. The second module :
    • Summary: performs a more rigorous analysis to determine both the stellar background contribution as well as the global asteroseismic parameters.
    • Given the frequency range determined by the first module, this region is masked out to model the white- and red-noise contributions present in the power spectrum. The fitting procedure will test a series of models and select the best-fit stellar background model based on the BIC.
    • The power spectrum is corrected by dividing out this contribution, which also saves as an output text file.
    • Now that the background has been removed, the global parameters can be more accurately estimated. Numax is estimated by using a smoothing filter, where the peak of the heavily smoothed, background-corrected power spectrum is the first and the second fits a Gaussian to this same power spectrum. The smoothed numax has typically been adopted as the default numax value reported in the literature since it makes no assumptions about the shape of the power excess.
    • Using the masked power spectrum in the region centered around numax, an autocorrelation is computed to determine the large frequency spacing.

Note

By default, both modules will run and this is the recommended procedure if no other information is provided.

If stellar parameters like the radius, effective temperature and/or surface gravity are provided in the info/star_info.csv file, pySYD can estimate a value for numax using a scaling relation. Therefore the first module can be bypassed, and the second module will use the estimated numax as an initial starting point.

There is also an option to directly provide numax in the info/star_info.csv (or via command line, see :ref:`advanced usage<advanced>` for more details), which will override the value found in the first module. This option is recommended if you think that the value found in the first module is inaccurate, or if you have a visual estimate of numax from the power spectrum.

Introduction

This was initially created to be used with the command-line tool but has been expanded to include functions compatible with Python notebooks as well. This is still a work in progress!

Imports

Pipeline modes

There are currently four operational pySYD modes (and two under development):

  1. setup : Initializes pysyd.pipeline.setup for quick and easy setup of directories, files and examples. This mode only inherits higher level functionality and has limited CLI (see :ref:`parent parser<parentparse>` below). Using this feature will set up the paths and files consistent with what is recommended and discussed in more detail below.
  2. load : Loads in data for a single target through pysyd.pipeline.load. Because this does handle data, this has full access to both the :ref:`parent<parentparse>` and :ref:`main parser<mainparse>`.
  3. run : The main pySYD pipeline function is initialized through pysyd.pipeline.run and runs the two core modules (i.e. find_excess and fit_background) for each star consecutively. This mode operates using most CLI options, inheriting both the :ref:`parent<parentparse>` and :ref:`main parser<mainparse>` options.
  4. parallel : Operates the same way as the previous mode, but processes stars simultaneously in parallel. Based on the number of threads available, stars are separated into groups (where the number of groups is exactly equal to the number of threads). This mode uses all CLI options, including the number of threads to use for parallelization (:ref:`see here<parallel>`).
  5. display : will primarily be used for development and testing purposes as well, but
  6. test : Currently under development but intended for developers.

Examples

pysyd.pipeline API

.. automodule:: pysyd.pipeline
   :members: