Source Finding¶
find_sources()
is an iterative
sourcefinding algorithm that uses peak detection on a TS map to find
new source candidates. The procedure for adding new sources at each
iteration is as follows:
 Generate a TS map for the test source model defined with the
model
argument.  Identify peaks with sqrt(TS) >
sqrt_ts_threshold
and an angular distance of at leastmin_separation
from a higher amplitude peak in the map.  Order the peaks by TS and add a source at each peak starting from the highest TS peak. Set the source position by fitting a 2D parabola to the loglikelihood surface around the peak maximum. After adding each source, refit its spectral parameters.
 Add sources at the N highest peaks up to N =
sources_per_iter
.
Source finding is repeated up to max_iter
iterations or until no
peaks are found in a given iteration. Sources found by the method are
added to the model and given designations PS JXXXX.X+XXXX according
to their position in celestial coordinates.
Examples¶
model = {'Index' : 2.0, 'SpatialModel' : 'PointSource'}
srcs = gta.find_sources(model=model, sqrt_ts_threshold=5.0,
min_separation=0.5)
The method for generating the TS maps can be controlled with the
tsmap_fitter
option. TS maps can be generated with either
tsmap()
or
tscube()
.
Reference/API¶

GTAnalysis.
find_sources
(prefix='', **kwargs) An iterative sourcefinding algorithm that uses likelihood ratio (TS) maps of the region of interest to find new sources. After each iteration a new TS map is generated incorporating sources found in the previous iteration. The method stops when the number of iterations exceeds
max_iter
or no sources exceedingsqrt_ts_threshold
are found.Parameters: Returns:  peaks (list) – List of peak objects.
 sources (list) – List of source objects.