[LSST|dm-users 640] Re: Detection and Measurement of Postage Stamp

Mon May 11 15:13:10 PDT 2015

The Doxygen is good for some things, but the configuration of Python code
isn't one of them.  If you're running a command-line task, then Robert's
suggestion is the way to go.  If not, I recommend just using Python's
help() function on the config object - that should get you the list of
options and some documentation for each of them.

Jim

On Mon, May 11, 2015 at 6:10 PM, Robert Lupton the Good <
rhl at astro.princeton.edu> wrote:

> I don't know how you are running your task, but if it's using
> commandLineTask then
>    --show=*[Bb]ackground*
> should show all configuration parameters matching the glob. (Benighted
> [t]csh users will need to quote the pattern)
>
>         R
>
> On 11 May 2015, at 18:00, Jim Bosch <jbosch at astro.princeton.edu> wrote:
>
> I think this should be just a matter of setting
>
> detectSourcesConfig.reEstimateBackground = False
>
>
>
> Jim
>
>
>
> On Mon, May 11, 2015 at 5:41 PM, Will Dawson <will at dawsonresearch.com>
> wrote:
>
>> I am trying to use DM Stack detect and analyze in object in a small
>> postage stamp (see attached example, log scale). I know I can use
>> lsst.afw.detection.Threshold() with lsst.afw.detection.FootprintSet() to
>> create a footprint for the detected object. But I also (first) tried
>> lsst.meas.algorithms.SourceDetectionTask(config=detectSourcesConfig, "other
>> args") with config set as:
>>
>> detectSourcesConfig   =
>> measAlg.SourceDetectionConfig(thresholdType='value’)
>> or
>> detectSourcesConfig   =
>> measAlg.SourceDetectionConfig(thresholdType='value',thresholdValue=0)
>>
>> and got the error at the end of this email. I am not entirely sure how to
>> parse this error statement, but if I had to guess: no objects are being
>> detected because it is trying to estimate the background based on this
>> stamp which contains primary just the object thus when it does image -
>> background there is nothing above threshold left to detect. Or it chokes
>> when trying to estimate the background.
>>
>> Is there an option to run lsst.meas.algorithms.SourceDetectionTask with
>> the background estimation/ subtraction process turned off? For example when
>> detecting objects on an image that already has the background subtracted.
>> Perhaps the only option is to stick with the detection.FootprintSet method.
>>
>> Thanks,
>> Will
>>
>>
>>  <28x28stamp.png>
>>
>> ---------------------------------------------------------------------------InvalidParameterError                     Traceback (most recent call last)<ipython-input-66-d08d86b9540f> in <module>()      2 # catalog atually stores stuff)      3 table   = afwTable.SourceTable.make(schema)----> 4 catalog = detect.makeSourceCatalog(table, exposure, sigma=3)
>> /Users/dawson/lsst/DarwinX86/pipe_base/10.0+2/python/lsst/pipe/base/timer.pyc in wrapper(self, *args, **keyArgs)    116         logInfo(obj = self, prefix = func.__name__ + "Start")    117         try:--> 118             res = func(self, *args, **keyArgs)    119         finally:    120             logInfo(obj = self, prefix = func.__name__ + "End")
>> /Users/dawson/lsst/DarwinX86/meas_algorithms/10.0+2/python/lsst/meas/algorithms/detection.pyc in run(self, table, exposure, doSmooth, sigma, clearMask)    313             raise ValueError("Table has incorrect Schema")    314         fpSets = self.detectFootprints(exposure=exposure, doSmooth=doSmooth, sigma=sigma,--> 315                                        clearMask=clearMask)    316         sources = afwTable.SourceCatalog(table)    317         table.preallocate(fpSets.numPos + fpSets.numNeg) # not required, but nice
>> /Users/dawson/lsst/DarwinX86/pipe_base/10.0+2/python/lsst/pipe/base/timer.pyc in wrapper(self, *args, **keyArgs)    116         logInfo(obj = self, prefix = func.__name__ + "Start")    117         try:--> 118             res = func(self, *args, **keyArgs)    119         finally:    120             logInfo(obj = self, prefix = func.__name__ + "End")
>> /Users/dawson/lsst/DarwinX86/meas_algorithms/10.0+2/python/lsst/meas/algorithms/detection.pyc in detectFootprints(self, exposure, doSmooth, sigma, clearMask)    443             fpSets.background = bkgd    444             self.log.log(self.log.INFO, "Resubtracting the background after object detection")--> 445             mi -= bkgd.getImageF()    446             del mi    447
>> /Users/dawson/lsst/DarwinX86/afw/10.0+3/python/lsst/afw/math/mathLib.pyc in getImageF(self, *args)   5736         getImageF(Background self) -> boost::shared_ptr< lsst::afw::image::Image< float > >   5737         """-> 5738         return _mathLib.Background_getImageF(self, *args)   5739    5740     def getImageI(self, *args):
>> InvalidParameterError:
>>   File "src/math/Interpolate.cc", line 60, in std::pair<std::vector<double>, std::vector<double> > lsst::afw::math::(anonymous namespace)::recenter(const std::vector<double> &, const std::vector<double> &)
>>     You must provide at least 1 point {0}
>>   File "src/math/BackgroundMI.cc", line 196, in void lsst::afw::math::BackgroundMI::_setGridColumns(const Interpolate::Style, const lsst::afw::math::UndersampleStyle, const int, const std::vector<int> &) const
>>     setting _gridcolumns {1}
>> lsst::pex::exceptions::InvalidParameterError: 'You must provide at least 1 point {0}; setting _gridcolumns {1}'
>>
>>
>>
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>
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