The Elixir system includes a database system for storing and
manipulating measurements of objects in the sky. The database and the
associated tools make it easy to related objects measured from a
variety of sources.
Structure of the Database
The photometry database consists of several types of tables. One type
of table is used to store aggregate quantities for each object such as
the average position, average magnitudes for a certain filter, and
information about the number of specific measurements for each object.
A second set of tables provides all individual measurements for each
object, including the time of the measurement, the magnitude, offset
from the average postion, etc. A third type of table provides
information for each object about those images on which the object was
not detected, although it was in the field of view. A fourth table
contains additional average magnitude values. The final table
provides information about the images which supplied the individual
measurements in the rest of the database.
The object tables are organized as a collection of many separate file
representing a small region on the sky, with constant RA and DEC
boundaries. Each file contains all four of the object tables,
Average, Measure, Missing, Secondary Filters, for each region. This
organization into many distinct database tables allows searches which
depend on RA and DEC in some way (the vast majority of all searches)
to be extremely efficient.
Inserting Measurements in database
When the objects from an image are added to the photometry database,
the measurements are associated with existing objects, if available,
on the basis of the RA and DEC of the objects. All objects in the new
image are considered and for each object, a search is performed for
all objects in the database within a certain distance: a specified
factor times the standard deviations of the astrometric solution.
For any object in an image, there are four possible cases:
- no object in the database is within the given distance of the
object.
- a single object is within the given distance.
- more than one object in the database is within the given distance
of the new object.
- an object in the database is within the given distance of more than
one object in the input image.
The first two cases are trivial and require little explanation. In
the first case, and entry is created for the new object, and the
average values are initialized. In the second case, the new
measurement is added to the existing measurements and the average
position is updated.
In the third case, a flag is set to indicate that the object on the
image could be associated with more than one object, and the new
measurement is added to each of the existing objects.
In the fourth case, a different flag is set and both measurements are
added to the object in the database.
An additional point concerns the object non-detections. All
non-detections of an object are recorded in the database linked to the
average just as the measurements are linked. If an object is found on
an image, and no object had previously been found there, a pointer to
all images which overlap this location are added to the object's table
of missed measurements. Also, if an image overlaps an object in the
database and no measurement is found, it is included in the list of
missed measurements for that object.
Photcodes
Each measurement which is placed in the database has an associated
code which defines the photometry system for the measurement. For an
individual measurement, this code is unique for each combination of
filter, telescope, and detector. These codes are called `photcodes'
and allow the database to associate measurements in different filters
together in appropriate ways. For example, all measurements from
CFH12K using the R filter receive one of 12 possible photcodes
depending on which chip the measurement came from. Similarly, all
measurements from the Subaru Suprime camera in an R filter would have
one of 10 possible photcode values, and 8 for measurements from the
ESO WFI, etc. However, since all of these are R photometry
measurements, it is useful to be able to relate them together. They
are
[when are the color, airmass terms applied? do they use the B or
CFH12K.B.00 values?]
Magnitude Averaging - `nrphot'
In the Elixir photometry database, average magnitudes for objects are
not automatically updated when the objects are added to the database.
The database maintainer must make a decision when to update the
magnitude averages. This design choice has been made to allow a
complex, processing-intensive magnitude averaging system to be used
without locking up the database by this step.
The program `nrphot' is used to perform the update of magnitude
averages. Nrphot performs the magnitude averaging for a single
spatially contiugous portion of the database at one time. The
magnitude averaging process consists of two stages:
- select all images in a region
- select all objects on those images
- select a subset of measurements with good S/N
- associate measurements with images
- determine the best set of zero-point corrections for each image
- apply the zero-points to all objects
- `average' (find weighted average of inner 50%)
Searching the database - `status'
The `status' program provides a user interface to the photometry
database. The general usage of status is described elsewhere [REF];
here we focus on those aspects relevant to the photometry database.
Some of the general features of `status' include the ability to
manipulate and plot data in scalars, vectors, and arrays.
Status provides a variety of functions to extract data from the
photometry database and to visualize the results. Low level functions
include commands to extract any of the elements from the different
tables into vectors. These vectors may then be plotted as line or
point plots as needed. For example, to find the luminosity function
for a given region, all that is needed is to define the region, extract
the vector corresponding the magnitude of interest, and calculate the
histogram of this vector:
status: region 10 40 1.5
status: extract mag -photcode V
status: histogram mag Nm 0.0 30.0 0.1
status: create dm 0.0 30.0 0.1
status: lim dm Nm; clear; box; plot -x 1 dm Nm
Other low level commands will return the images which overlap a given
point (gimages RA DEC), objects within a certain radius of a given
point (gstars RA DEC radius).
In addition to these low-level commands, there are higher level
functions which allow for more complex plots or extractions. For
example, it is possible to plot all stars in a region by extracting
each of the vectors of RA, DEC, Mag, and plotting the points with the
point size scaled by the magnitude vector. However, a single function
also exists which performs exactly this task. Also, a single
function will plot the outlines of all images in a given region on a
plot of the sky.
Since `status' includes an interpreted programming language, it is
possible to define even more complex visualization functions. One
example is the `navigate' macro which allows the user to interactively
peruse the data by navigating through a plot of the sky.
* table of database-interaction commands
[these need to be clarified a bit....]
gcat
gstars
pmeasure
pcat
images
imlist
extract
mextract
imextract
cmd
cmdextract
ccd
ccdextract
...
- standard options:
-time
-trange
-photcode
- measurements of various speeds
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