[LSST|dm-users 641] Re: Detection and Measurement of Postage Stamp
Will Dawson
will at dawsonresearch.com
Mon May 11 15:50:20 PDT 2015
Jim / Robert,
I’ve been running everything from python so I guess I will stick to help(). Is there a way that I can help edit the documentation as I learn things? For example I could help add some meat to things like:
reEstimateBackground
| Estimate the background again after final source detection?
Although I completely understand if you don’t want people who are just learning things to be editing the help documentation.
Thanks again,
Will
> On May 11, 2015, at 3:13 PM, Jim Bosch <jbosch at astro.princeton.edu> wrote:
>
> 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 <mailto: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 <mailto: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 <mailto: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 <http://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 <http://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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