Dorado Documentation Overview

(Digitized Observatory Resources for Automated Data Operations)


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Digitized Observatory Resources for Automated Data Operations (DORADO) is a python based expansion of astropy (and affiliated packages) that aims to be a simple and common framework for data reduction tailored for life at the Allan I. Carswell Observatory at York university, Toronto, Ontario, Canada

☣⚠ DORADO is in beta ⚠☣

DORADO is in beta and as such is highly experimental and still a work in progress. While still in active development DORADO may still be used and experimented with; but a stable channel will not be created until DORADO enters a stable phase in the future.

Use of DORADO while in beta will not result in any risk to your computer or hardware, but may affect stability of software that are written with DORADO or the quality of data that is produced using DORADO.

During the beta, documentation and code commenting may be subpar as many things will being changing regularly with new code being written and rewritten and in-line testing appearing temporarily.

Getting started with dorado:

For help getting started see: Getting Started

Getting Started








Putting it Together


Install dorado by running: pip install dorado.


The dorado project on PyPI .


In the near future examples, tutorials, and pre-made use scripts will be located here. The first release of Dorado should ship with an example pipeline and data formatting tutorial.


dorado Package


delcacheObj(self, fname[, subcache])

delcacheObj is a convenience method that deletes a selected cache object given is file name.

getDateString(self, epoch[, utc])

getDateString computes the date string for the given ceres object.


get_night obtains a timestring for the most recent(previous) night based on local/hardware time provided by datetime.

mkcacheObj(self, object[, subcache])

mkcacheObj is a convenience function that creates a cache object for a .fits compatable object in the self.dordir/cache directory.

plate_solve(dirarray[, data, writearray])

plate_solve takes a dirarray pointing to a fits file to plate solve using astrometryNet.


Run the tests for the package.


Ceres([filters, data, bias, time, datestr])

The Ceres class encapsulates a set of astronomical data from a single night of observation.


Fournax(name[, epoch, period])

The Fournax class extends the TOI target class to provide a consistent simple, yet robust interface to targets with regular or semi-regular photometric variability for the purposes of lightcurve/timeseries fourier analysis.

Stack(data[, flat, filter, times, ...])

The Stack class encapsulates correlated stacks of image objects and their associated data.


The TOI class represents an astronomical target of interest (TOI) and handles the targets relevent attributes.



dracoPhot([limit_Mag, search_bounds])


readers need to have a dirscan method and a savewrok method.

timeSeries(times, flux[, name, exptimes, x, ...])

The timeSeries


We love contributions! dorado is open source, built on open source, and we’d love to have you hang out in our community.

Imposter syndrome disclaimer: We want your help. No, really.

There may be a little voice inside your head that is telling you that you’re not ready to be an open source contributor; that your skills aren’t nearly good enough to contribute. What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong. If you can write code at all, you can contribute code to open source. Contributing to open source projects is a fantastic way to advance one’s coding skills. Writing perfect code isn’t the measure of a good developer (that would disqualify all of us!); it’s trying to create something, making mistakes, and learning from those mistakes. That’s how we all improve, and we are happy to help others learn.

Being an open source contributor doesn’t just mean writing code, either. You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process). Some of these contributions may be the most valuable to the project as a whole, because you’re coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.


This disclaimer was originally written by Adrienne Lowe for a PyCon talk, and was adapted by dorado based on its use in the README file for the MetPy project.


If you have any questions or would like to contribute to DORADO, please contact @mucephie at <>. If you are interested in the Allan I. Carswell observatory at York university, you can find more information at our website.


This project is Copyright (c) Mucephie and licensed under the terms of the BSD 3-Clause license. This package is based upon the Astropy package template which is licensed under the BSD 3-clause license. See the licenses folder for more information.