- Part of the DRAGONS package that defines the abstraction layer for observational datasets. The astrodata abstraction and its associated grammar is used extensively by the Recipe System to effect correct processing.
- Not to be confused with
astrodata, this is the base class for instrument-specific AstroData classes, and the one most users and developers will interact with at a programmatic level.
- Is a method on an
AstroDatainstance. A descriptor represents a high-level metadata name and provides access to essential metadata through a uniform, instrument-agnostic interface to the FITS headers. E.g.,
- A suite of packages comprising
gempy, all of which provide the full functionality needed to run recipe pipelines on observational datasets.
DRAGONSpackage comprising gemini specific functional utilities.
- A function defined within a data reduction instrument package (a “dr” package)
that performs actual work on the passed dataset. Primitives observe controlled
interfaces in support of re-use of primitives and recipes for different types
of data, when possible. For example, all primitives called
flatCorrectmust apply the flat field correction appropriate for the data’s current astrodata tag set, and must have the same set of input parameters. This is a Gemini Coding Standard; it is not enforced by the Recipe System.
- A function defined in a recipe library (module), which defines a sequence
of function calls. A recipe is a simple python function that recieves an
instance of the appropriate primitive class and calls the available methods
that are to be done for a given recipe function. A recipe is the
high-level pipeline definition. Users can pass recipe names directly to
reduce.Essentially, a recipe is a pipeline.
- Recipe System
- The gemin_python framework that accommodates defined recipes and primitives classes. The Recipe System defines a set of classes that exploit attributes on an astrodata instance of a dataset to locate recipes and primitives appropriate to that dataset.
- The command line interface to the Recipe System and associated recipes/pipelines.
Represent a data classification. A dataset will be classified by a number of tags that describe both the data and its processing state. For example, a typical unprocessed GMOS image taken at Gemini-South would have the following tagset:
set(['RAW', 'GMOS', 'GEMINI', 'SIDEREAL', 'UNPREPARED', 'IMAGE', 'SOUTH'])
Instrument packages define tagsets, which are sets of string literals that describe and the kind of observational data that the package, primitive, or library has been defined to accommodate and process. As an example:
set(['GMOS', 'MOS', 'NODANDSHUFFLE')]