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Changeset 510


Ignore:
Timestamp:
Apr 22, 2004, 6:06:00 PM (22 years ago)
Author:
Paul Price
Message:

Standardised "Pipelines" to "Analysis Stages".

File:
1 edited

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  • trunk/doc/design/design.tex

    r508 r510  
    1 %%% $Id: design.tex,v 1.7 2004-04-23 02:44:14 price Exp $
     1%%% $Id: design.tex,v 1.8 2004-04-23 04:06:00 price Exp $
    22\documentclass[panstarrs]{panstarrs}
    33
     
    191191\resizebox{8cm}{!}{\includegraphics{pics/overview}}
    192192\caption{ \label{overview} IPP System Overview. \tbd{``Processing
    193 Jobs'' should be renamed ``Analysis Pipelines''.} }
     193Jobs'' should be renamed ``Analysis Stages''.} }
    194194\end{center}
    195195\end{figure}
    196196
    197 \subsubsection{Analysis Pipelines}
    198 
    199 We now consider the collection of IPP analysis pipelines.  Depending
    200 on the particular pipeline, they may be run on individual images,
    201 collections of images, or on derived data products.  Because of the
    202 nature of the image data, many of the analysis pipelines can be run in
    203 parallel because, for example, the analysis of a chip in one image
    204 does not depend on the results from another chip.  We define the
    205 analysis pipelines to be the largest complete analysis task which may
    206 be performed on a single data item.  The data analysis tasks are
    207 divided into three categories, and further subdivided as follows:
    208 
    209 \begin{enumerate}
    210 \item Science Image Pipelines
     197\subsubsection{Analysis Stages}
     198
     199We now consider the collection of IPP analysis stages.  We define an
     200analysis stage to be the largest complete task which may be performed
     201in serial without interation between parallel threads.
     202
     203Depending on the particular analysis stage, it may process individual
     204images, collections of images, or on derived data products.  Because
     205of the nature of the image data, many of the analysis stages can be
     206run in parallel because, for example, the analysis of a chip in one
     207image does not depend on the results from another chip.
     208
     209The data analysis stages are divided into three categories as follows:
     210
     211\begin{enumerate}
     212\item Science Image Analysis Stages
    211213  \begin{enumerate}
    212   \item Phase 1: image processing preparation
    213   \item Phase 2: image reduction
    214   \item Phase 3: exposure analysis
    215   \item Phase 4: image combination
     214  \item Phase 1: image processing preparation --- estimates
     215    first-order astrometric and photometric solutions required to
     216    process each major frame.
     217  \item Phase 2: image reduction --- produces calibrated chips from
     218    raw chips.
     219  \item Phase 3: exposure analysis --- processes an FPA to produce
     220    unified and consistent backgrounds, photometry and astrometry for
     221    the component chips.
     222  \item Phase 4: image combination --- processes sky cells overlapped
     223    by a major frame.
    216224  \end{enumerate}
    217 \item Calibration Image Pipelines
     225\item Calibration Image Analysis Stages
    218226  \begin{enumerate}
    219   \item Calibration 1: basic master-detrend creation
    220   \item Calibration 2: Sky-model/fringe-mode generation
    221   \item Calibration 3: Flat-field correction image Creation
     227  \item Calibration 1: Basic master-detrend creation --- combination
     228    of simple detrend images.
     229  \item Calibration 2: Sky-model/fringe-mode generation ---
     230    combination of more-complicated detrend images.
     231  \item Calibration 3: Flat-field correction image creation ---
     232    analysis of photometry from multiple dithered FPAs.
    222233  \end{enumerate}
    223 \item Reference Catalog Pipelines
     234\item Reference Catalog Analysis Stages
    224235  \begin{enumerate}
    225   \item Astrometry reference catalog generation
    226   \item Photometry reference catalog generation
     236  \item Astrometry reference catalog generation --- processing of the
     237    astrometric data to determine and apply a consistent global
     238    solution.
     239  \item Photometry reference catalog generation --- processing of the
     240    photometric data to determine and apply a consistent global
     241    solution.
    227242  \end{enumerate}
    228243\end{enumerate}
    229244
    230 Figure~\ref{pipelines} shows the flow of data between the various IPP
    231 software systems and the different analysis tasks, each managed by the
    232 controller.  The thick lines represent the flow of pixel data, the
     245Figure~\ref{system} shows the flow of data between the various IPP
     246software systems and the different analysis stages, each managed by
     247the controller.  The thick lines represent the flow of pixel data, the
    233248thin lines represent the flow of metadata and object data, and the
    234249grey lines represent the flow of commands.  The hatched systems
     
    240255\begin{center}
    241256\resizebox{8cm}{!}{\includegraphics{pics/pipelines}}
    242 \caption{ \label{pipelines} IPP System Overview. \tbd{Small part at
     257\caption{ \label{system} IPP System Overview. \tbd{Small part at
    243258top is missing.} }
    244259\end{center}
     
    252267the pre-reduction analysis of the raw science images.  In addition, we
    253268have specified distinct machines to maintain the object and metadata
    254 databases.  This last aspect is largely theoretical until we have
     269databases.  \tbd{This last aspect is largely theoretical until we have
    255270defined the details of these databases; it may be more appropriate
    256271depending on the eventual solutions to distribute these database
    257 elements across the Detector and Static Sky subclusters.
     272elements across the Detector and Static Sky subclusters.}
    258273
    259274\begin{figure}
     
    274289frameworks.  In particular, the modules can be tied together with a
    275290simple framework (an `engine') or with detailed flow-control through
    276 the use of a high-level language such as Perl, Python, or Tcl.  For
    277 the high-level functions in the operational system, the IPP will make
    278 use of \tbd{Python} as the scripting language to tie the modules
    279 together.
     291the use of a high-level language such as Perl, Python, or Tcl
     292employing the SWIG interfaces.  For the high-level functions in the
     293operational system, the IPP will make use of \tbd{Python} as the
     294scripting language to provide the required flow-control to tie the
     295modules together.
    280296
    281297This approach satisfies the requirement that complicated low-level
     
    304320\subsubsection{Modules}
    305321
    306 The IPP analysis tasks are broken down into modules which represent
     322The IPP analysis stages are broken down into modules which represent
    307323specific functional operations.  The modules will be written in C
    308324using the \PS{} Library functions and will be grouped into a \PS{}
    309325Module Library.  The modules will be provided with SWIG interfaces to
    310 all public APIs for their use in processing stages.  Examples of modules
    311 are overscan subtraction and image combination.
     326all public APIs for their use in processing stages.  Examples of
     327modules are overscan subtraction and image combination.  Some modules
     328(e.g.\ find objects on an image) will be used by multiple stages.
    312329
    313330\subsubsection{Stages}
     
    334351external to the IPP, and for initiating the reduction appropriate for
    335352images as they are received.  An example of the scheduler
    336 functionality is ``I've just received exposure number 1234; run phase
    337 1--4 controllers on exposure 1234''.
     353functionality is ``Retrieve exposure number 1234; run phase 1--4
     354controllers on exposure 1234''.
    338355
    339356%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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