independent "auto-multithresh" functionality

[schiebel]

The auto masking functionality seems to be completely implemented in C++ with the only access available through deconvolve/tclean (see below). This functionality is needed outside of these tasks. It would be nice to implement this as a stand-alone tool (since casa tools can use other casa tools) or provide an API in Python which allows for running the automasking routines (even if the implementation just uses the deconvolve task underneath).

This is not needed for iclean, but it is needed to allow for automasking in a stand-alone createmask task based on the iclean GUI framework.

---

    frame #0: 0x000000013ef1a871 libcasatools.cpython-310-darwin.dylib`casa::SDMaskHandler::autoMaskByMultiThreshold(this=0x00007fa045a34150, mask=0x00007fa0453c8200, posmask=0x00007fa0473b9200, res=0x00007fa0473b8200, psf=0x00007fa0453c5200, stats=0x00007ffee84cd0e8, robuststats=0x00007ffee84ccc68, iterdone=0, chanFlag=0x00007ffee84d1b18, minPercentChange=0x00007ffee84d1b0c, sidelobeLevel=0x00007fa045a34160, sidelobeThresholdFactor=0x00007ffee84d1ae4, noiseThresholdFactor=0x00007ffee84d1ae8, lowNoiseThresholdFactor=0x00007ffee84d1aec, negativeThresholdFactor=0x00007ffee84d1af0, cutThreshold=0x00007ffee84d1afc, smoothFactor=0x00007ffee84d1af4, minBeamFrac=0x00007ffee84d1af8, growIterations=75, doGrowPrune=true, verbose=false, isthresholdreached=false) at SDMaskHandler.cc:2228:25
    frame #1: 0x000000013ef10bd7 libcasatools.cpython-310-darwin.dylib`casa::SDMaskHandler::autoMask(this=0x00007fa045a34150, imstore=std::__1::shared_ptr<casa::SIImageStore>::element_type @ 0x00007f9ff5bed800 strong=3 weak=1, posmask=0x00007fa0473b9200, iterdone=0, chanflag=0x00007ffee84d1b18, robuststatsrec=0x00007ffee84d1c18, alg=0x00007ffee84d1a88, threshold=0x00007ffee84d1aa0, fracofpeak=0x00007ffee84d1ab8, resolution=0x00007ffee84d1ac0, resbybeam=0x00007ffee84d1ad8, nmask=0, autoadjust=false, sidelobethreshold=0x00007ffee84d1ae4, noisethreshold=0x00007ffee84d1ae8, lownoisethreshold=0x00007ffee84d1aec, negativethreshold=0x00007ffee84d1af0, cutthreshold=0x00007ffee84d1afc, smoothfactor=0x00007ffee84d1af4, minbeamfrac=0x00007ffee84d1af8, growiterations=75, dogrowprune=true, minpercentchange=0x00007ffee84d1b0c, verbose=false, fastnoise=true, isthresholdreached=false, pblimit=0) at SDMaskHandler.cc:1266:7
    frame #2: 0x000000013f031079 libcasatools.cpython-310-darwin.dylib`casa::SynthesisDeconvolver::setAutoMask(this=0x00007ffee84d1550) at SynthesisDeconvolver.cc:1122:25
    frame #3: 0x000000013eea01d6 libcasatools.cpython-310-darwin.dylib`casa::CubeMinorCycleAlgorithm::task(this=0x00007ffee84d3ee0) at CubeMinorCycleAlgorithm.cc:136:18
    frame #4: 0x000000013fd2f7fa libcasatools.cpython-310-darwin.dylib`casa::Algorithm::apply(this=0x00007ffee84d3ee0) at Algorithm.h:96:18
    frame #5: 0x000000013fd2ffe6 libcasatools.cpython-310-darwin.dylib`casa::Applicator::apply(this=0x0000000140f89dc8, a=0x00007ffee84d3ee0) at Applicator.cc:394:7
    frame #6: 0x000000013f02af1e libcasatools.cpython-310-darwin.dylib`casa::SynthesisDeconvolver::executeCubeMinorCycle(this=0x00007fa050d80800, minorCycleControlRec=0x00007ffee84d4ec8, AutoMaskFlag=1) at SynthesisDeconvolver.cc:773:24
    frame #7: 0x000000013f02fb0e libcasatools.cpython-310-darwin.dylib`casa::SynthesisDeconvolver::setupMask(this=0x00007fa050d80800) at SynthesisDeconvolver.cc:1020:6
    frame #8: 0x0000000155cce81f _synthesisdeconvolver.cpython-310-darwin.so`casac::synthesisdeconvolver::setupmask(this=0x00007fa0158de390) at synthesisdeconvolver_cmpt.cc:79:29
    frame #9: 0x0000000155cc3fca _synthesisdeconvolver.cpython-310-darwin.so`_wrap_synthesisdeconvolver_setupmask((null)=0x00000001522532e0, args=0x000000015e4be740) at synthesisdeconvolver_wrap.cpp:3296:32
    frame #10: 0x00000001077e806e python3.10`cfunction_call + 94
    frame #11: 0x00000001078b0f0a python3.10`_PyEval_EvalFrameDefault + 71658
    frame #12: 0x0000000107789870 python3.10`_PyFunction_Vectorcall + 560
    frame #13: 0x000000010778e697 python3.10`method_vectorcall + 151
    frame #14: 0x00000001078aab80 python3.10`_PyEval_EvalFrameDefault + 46176
    frame #15: 0x0000000107789870 python3.10`_PyFunction_Vectorcall + 560
    frame #16: 0x00000001078a82a5 python3.10`_PyEval_EvalFrameDefault + 35717
[...]
    frame #76: 0x00000001078aef4c python3.10`_PyEval_EvalFrameDefault + 63532
    frame #77: 0x0000000107789870 python3.10`_PyFunction_Vectorcall + 560
    frame #78: 0x00000001078cce33 python3.10`call_function + 179
    frame #79: 0x00000001078a8301 python3.10`_PyEval_EvalFrameDefault + 35809
    frame #80: 0x000000010789d8e0 python3.10`_PyEval_Vector + 544
    frame #81: 0x0000000107922530 python3.10`run_mod + 240
    frame #82: 0x00000001079222f5 python3.10`pyrun_file + 133
    frame #83: 0x0000000107921dff python3.10`_PyRun_SimpleFileObject + 319
    frame #84: 0x000000010792177f python3.10`_PyRun_AnyFileObject + 143
    frame #85: 0x0000000107946e48 python3.10`pymain_run_file_obj + 216
    frame #86: 0x00000001079468d5 python3.10`pymain_run_file + 85
    frame #87: 0x0000000107946018 python3.10`pymain_run_python + 376
    frame #88: 0x0000000107945e55 python3.10`Py_RunMain + 37
    frame #89: 0x0000000107725708 python3.10`main + 56
    frame #90: 0x00007fff6ac88cc9 libdyld.dylib`start + 1
    frame #91: 0x00007fff6ac88cc9 libdyld.dylib`start + 1