Source Finding¶
find_sources()
is an iterative
source-finding 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 log-likelihood surface around the peak maximum. After adding each source, re-fit 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 source-finding 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: - free_params (list) – (default : None)
- max_iter (int) – Maximum number of source finding iterations. The source finder will continue adding sources until no additional peaks are found or the number of iterations exceeds this number. (default : 5)
- min_separation (float) – Minimum separation in degrees between sources detected in each iteration. The source finder will look for the maximum peak in the TS map within a circular region of this radius. (default : 1.0)
- model (dict) – Dictionary defining the spatial/spectral properties of the test source. If model is None the test source will be a PointSource with an Index 2 power-law spectrum. (default : None)
- multithread (bool) – Split the calculation across all available cores. (default : False)
- sources_per_iter (int) – Maximum number of sources that will be added in each iteration. If the number of detected peaks in a given iteration is larger than this number, only the N peaks with the largest TS will be used as seeds for the current iteration. (default : 4)
- sqrt_ts_threshold (float) – Source threshold in sqrt(TS). Only peaks with sqrt(TS) exceeding this threshold will be used as seeds for new sources. (default : 5.0)
- tsmap_fitter (str) – Set the method for generating the TS map. Valid options are tsmap or tscube. (default : tsmap)
- tsmap (dict) – Keyword arguments dictionary for tsmap method.
- tscube (dict) – Keyword arguments dictionary for tscube method.
Returns: - peaks (list) – List of peak objects.
- sources (list) – List of source objects.