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casa
$Rev:20696$
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casa
$Rev:20696$
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00001 import os 00002 import sys 00003 import shutil 00004 from __main__ import default 00005 from tasks import * 00006 from taskinit import * 00007 import unittest 00008 import math 00009 import numpy 00010 00011 #run using 00012 # `which casapy` --nologger --log2term -c `echo $CASAPATH | awk '{print $1}'`/code/xmlcasa/scripts/regressions/admin/runUnitTest.py --mem test_imstat 00013 # 00014 00015 ''' 00016 Unit tests for task imstat. 00017 ''' 00018 class imstat_test(unittest.TestCase): 00019 00020 # Input and output names 00021 moment = 'moment_map.im' 00022 s150 = '150arcsec_pix.im' 00023 s15 = '15arcsec_pix.im' 00024 s0_015 = '0.015arcsec_pix.im' 00025 s0_0015 = '0.0015arcsec_pix.im' 00026 s0_00015 = '0.00015arcsec_pix.im' 00027 linear_coords = 'linearCoords.fits' 00028 fourdim = '4dim.im' 00029 res = None 00030 00031 def setUp(self): 00032 self.res = None 00033 self._myia = iatool() 00034 default(clean) 00035 self.datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/imstat/' 00036 00037 def tearDown(self): 00038 self._myia.done() 00039 for dir in [ 00040 self.moment, self.s150, self.s15, self.s0_015, self.s0_0015, 00041 self.s0_00015, self.linear_coords, self.fourdim 00042 ]: 00043 if os.path.isfile(dir): 00044 os.remove(dir) 00045 elif (os.path.exists(dir)): 00046 shutil.rmtree(dir) 00047 00048 def test001(self): 00049 """Test 1: verify moment maps can have flux densities computed in statistics""" 00050 shutil.copytree(self.datapath+self.moment, self.moment) 00051 stats = imstat(imagename=self.moment) 00052 mean = stats['mean'] 00053 npts = stats['npts'] 00054 00055 _myia = iatool() 00056 _myia.open(self.moment) 00057 summary = _myia.summary() 00058 _myia.close() 00059 rainc = qa.abs(qa.quantity(summary['incr'][0],'rad')) 00060 rainc = qa.convert(rainc,'arcsec') 00061 decinc = qa.abs(qa.quantity(summary['incr'][1],'rad')) 00062 decinc = qa.convert(decinc,'arcsec') 00063 beam = summary['restoringbeam'] 00064 major = beam['major'] 00065 minor = beam['minor'] 00066 pixperbeam = qa.div(qa.mul(major,minor),(qa.mul(rainc,decinc)))['value']*(math.pi/(4*math.log(2))) 00067 got = stats['flux'][0] 00068 expected = (mean*npts/pixperbeam)[0] 00069 self.assertTrue(abs(got - expected) < 1e-11) 00070 00071 def test002(self): 00072 """ Test 2: test position format for 150 arcsec pixel image is correct """ 00073 shutil.copytree(self.datapath+self.s150, self.s150) 00074 _myia = iatool() 00075 _myia.open(self.s150) 00076 stats = _myia.statistics() 00077 _myia.close() 00078 self.assertTrue(stats['blcf'] == '15:43:21.873, -00.17.47.274, I, 1.41332e+09Hz') 00079 self.assertTrue(stats['maxposf'] == '15:22:40.165, +05.11.29.923, I, 1.41332e+09Hz') 00080 self.assertTrue(stats['minposf'] == '15:43:25.618, +04.22.40.617, I, 1.41332e+09Hz') 00081 self.assertTrue(stats['trcf'] == '15:00:27.115, +10.20.37.699, I, 1.41332e+09Hz') 00082 00083 def test003(self): 00084 """ Test 3: test position format for 15 arcsec pixel image is correct """ 00085 shutil.copytree(self.datapath+self.s15, self.s15) 00086 _myia = iatool() 00087 _myia.open(self.s15) 00088 print "*** before " 00089 stats = _myia.statistics() 00090 print "*** after" 00091 _myia.close() 00092 self.assertTrue(stats['blcf'] == '15:24:08.404, +04.31.59.181, I, 1.41332e+09Hz') 00093 self.assertTrue(stats['maxposf'] == '15:22:04.016, +05.04.44.999, I, 1.41332e+09Hz') 00094 self.assertTrue(stats['minposf'] == '15:24:08.491, +04.59.59.208, I, 1.41332e+09Hz') 00095 self.assertTrue(stats['trcf'] == '15:19:52.390, +05.35.44.246, I, 1.41332e+09Hz') 00096 00097 def test004(self): 00098 """ Test 4: test position format for 0.015 arcsec pixel image is correct """ 00099 shutil.copytree(self.datapath+self.s0_015, self.s0_015) 00100 _myia = iatool() 00101 _myia.open(self.s0_015) 00102 stats = _myia.statistics() 00103 _myia.close() 00104 self.assertTrue(stats['blcf'] == '15:22:00.1285, +05.03.58.0800, I, 1.41332e+09Hz') 00105 self.assertTrue(stats['maxposf'] == '15:22:00.0040, +05.04.00.0450, I, 1.41332e+09Hz') 00106 self.assertTrue(stats['minposf'] == '15:22:00.1285, +05.03.59.7600, I, 1.41332e+09Hz') 00107 self.assertTrue(stats['trcf'] == '15:21:59.8725, +05.04.01.9050, I, 1.41332e+09Hz') 00108 00109 def test005(self): 00110 """ Test 5: test position format for 0.0015 arcsec pixel image is correct """ 00111 print "*** test 5" 00112 _myia = iatool() 00113 shutil.copytree(self.datapath+self.s0_0015, self.s0_0015) 00114 _myia.open(self.s0_0015) 00115 stats = _myia.statistics() 00116 _myia.close() 00117 print "*** blcf xxx " + str(stats['blcf']) 00118 self.assertTrue(stats['blcf'] == '15:22:00.01285, +05.03.59.80800, I, 1.41332e+09Hz') 00119 self.assertTrue(stats['maxposf'] == '15:22:00.00040, +05.04.00.00450, I, 1.41332e+09Hz') 00120 self.assertTrue(stats['minposf'] == '15:22:00.01285, +05.03.59.97600, I, 1.41332e+09Hz') 00121 self.assertTrue(stats['trcf'] == '15:21:59.98725, +05.04.00.19050, I, 1.41332e+09Hz') 00122 00123 def test006(self): 00124 """ Test 6: test position format for 0.00015 arcsec pixel image is correct """ 00125 shutil.copytree(self.datapath+self.s0_00015, self.s0_00015) 00126 _myia = iatool() 00127 _myia.open(self.s0_00015) 00128 stats = _myia.statistics() 00129 _myia.close() 00130 self.assertTrue(stats['blcf'] == '15:22:00.001285, +05.03.59.980800, I, 1.41332e+09Hz') 00131 self.assertTrue(stats['maxposf'] == '15:22:00.000040, +05.04.00.000450, I, 1.41332e+09Hz') 00132 self.assertTrue(stats['minposf'] == '15:22:00.001285, +05.03.59.997600, I, 1.41332e+09Hz') 00133 self.assertTrue(stats['trcf'] == '15:21:59.998725, +05.04.00.019050, I, 1.41332e+09Hz') 00134 00135 def test007(self): 00136 """ Test 7: test that box parameter can have spaces, CAS-2050 """ 00137 shutil.copytree(self.datapath+self.s0_00015, self.s0_00015) 00138 box = '0, 0, 1 , 1' 00139 stats = imstat(imagename=self.s0_00015, box=box) 00140 self.assertTrue(stats['npts'] == 4) 00141 00142 def test008(self): 00143 """ Test 8: verify fix for CAS-2195""" 00144 def test_statistics(image): 00145 _myia = iatool() 00146 _myia.open(myim) 00147 stats = _myia.statistics() 00148 _myia.done() 00149 return stats 00150 00151 def test_imstat(image): 00152 return imstat(image) 00153 00154 myim = self.linear_coords 00155 shutil.copy(self.datapath + myim, myim) 00156 expected_max = [3, 10] 00157 expected_min = [4, 0] 00158 for code in [test_statistics, test_imstat]: 00159 stats = code(myim) 00160 self.assertTrue((stats['maxpos'] == expected_max).all()) 00161 self.assertTrue((stats['minpos'] == expected_min).all()) 00162 00163 def test009(self): 00164 """ Test 9: choose axes works""" 00165 def test_statistics(image, axes): 00166 _myia = iatool() 00167 _myia.open(myim) 00168 stats = _myia.statistics(axes=axes) 00169 _myia.done() 00170 return stats 00171 00172 def test_imstat(image, axes): 00173 return imstat(image, axes=axes) 00174 00175 myim = self.fourdim 00176 shutil.copytree(self.datapath + myim, myim) 00177 axes = [-1, [0, 1, 2], [0, 1], 3] 00178 expected_mean = [ 00179 [59.5], [ 57.5, 58.5, 59.5, 60.5, 61.5], 00180 [ 00181 [50., 51., 52., 53., 54.], 00182 [55., 56., 57., 58., 59.], 00183 [60., 61., 62., 63., 64.], 00184 [65., 66., 67., 68., 69.] 00185 ], 00186 [ 00187 [ 00188 [2., 7., 12., 17.], 00189 [22., 27., 32., 37.], 00190 [42., 47., 52., 57.] 00191 ], 00192 [ 00193 [62., 67., 72., 77.], 00194 [ 82., 87., 92., 97.], 00195 [ 102., 107., 112., 117.] 00196 ] 00197 ] 00198 ] 00199 expected_sumsq = [ 00200 [568820], [ 108100., 110884., 113716., 116596., 119524.], 00201 [ 00202 [ 22000., 22606., 23224., 23854., 24496.], 00203 [ 25150., 25816., 26494., 27184., 27886.], 00204 [ 28600., 29326., 30064., 30814., 31576.], 00205 [ 32350., 33136., 33934., 34744., 35566.] 00206 ], 00207 [ 00208 [ 00209 [ 3.00000000e+01, 2.55000000e+02, 7.30000000e+02, 1.45500000e+03], 00210 [ 2.43000000e+03, 3.65500000e+03, 5.13000000e+03, 6.85500000e+03], 00211 [ 8.83000000e+03, 1.10550000e+04, 1.35300000e+04, 1.62550000e+04] 00212 ], 00213 [ 00214 [ 1.92300000e+04, 2.24550000e+04, 2.59300000e+04, 2.96550000e+04], 00215 [ 3.36300000e+04, 3.78550000e+04, 4.23300000e+04, 4.70550000e+04], 00216 [ 5.20300000e+04, 5.72550000e+04, 6.27300000e+04, 6.84550000e+04] 00217 ] 00218 ] 00219 ] 00220 for i in range(len(axes)): 00221 for code in [test_statistics, test_imstat]: 00222 stats = code(myim, axes[i]) 00223 self.assertTrue((stats['mean'] == expected_mean[i]).all()) 00224 self.assertTrue((stats['sumsq'] == expected_sumsq[i]).all()) 00225 00226 """ 00227 def test_robust(self): 00228 *"" Confirm robust parameter*"" 00229 def test_statistics(image, robust): 00230 _myia = iatool() 00231 _myia.open(myim) 00232 stats = _myia.statistics(robust=robust) 00233 _myia.done() 00234 return stats 00235 def test_imstat(image, robust): 00236 return imstat(image, robust=robust) 00237 myim = self.fourdim 00238 shutil.copytree(self.datapath + myim, myim) 00239 for robust in [True, False]: 00240 for code in [test_statistics, test_imstat]: 00241 stats = code(myim, robust) 00242 self.assertTrue(stats.has_key('median') == robust) 00243 self.assertTrue(stats.has_key('medabsdevmed') == robust) 00244 self.assertTrue(stats.has_key('quartile') == robust) 00245 00246 """ 00247 00248 def test_stretch(self): 00249 """ ia.statistics(): Test stretch parameter""" 00250 yy = iatool() 00251 mymask = "maskim" 00252 yy.fromshape(mymask, [200, 200, 1, 1]) 00253 yy.addnoise() 00254 yy.done() 00255 shape = [200,200,1,20] 00256 imagename = "tmp.im" 00257 yy.fromshape(imagename, shape) 00258 yy.addnoise() 00259 self.assertRaises( 00260 Exception, 00261 yy.statistics, 00262 mask=mymask + ">0", stretch=False 00263 ) 00264 zz = yy.statistics( 00265 mask=mymask + ">0", stretch=True 00266 ) 00267 self.assertTrue(zz and type(zz) == type({})) 00268 yy.done() 00269 00270 zz = imstat( 00271 imagename=imagename, mask=mymask + ">0", stretch=False 00272 ) 00273 self.assertTrue(type(zz) == type({}) and (zz == {})) 00274 00275 zz = imstat( 00276 imagename=imagename, mask=mymask + ">0", stretch=True 00277 ) 00278 self.assertTrue(type(zz) == type({}) and (not zz == {})) 00279 yy.done() 00280 00281 def test010(self): 00282 """test logfile """ 00283 def test_statistics(image, axes, logfile, append): 00284 _myia = iatool() 00285 _myia.open(image) 00286 stats = _myia.statistics( 00287 axes=axes, logfile=logfile, append=append 00288 ) 00289 _myia.done() 00290 return stats 00291 00292 def test_imstat(image, axes, logfile, append): 00293 return imstat(image, axes=axes, logfile=logfile, append=append) 00294 00295 logfile = "imstat.log" 00296 i = 1 00297 myim = self.fourdim 00298 shutil.copytree(self.datapath + myim, myim) 00299 for code in [test_statistics, test_imstat]: 00300 append = False 00301 if i == 2: 00302 append = True 00303 stats = code(myim, [0], logfile, append) 00304 size = os.path.getsize(logfile) 00305 print "size " + str(size) 00306 # appending, second time through size should double 00307 self.assertTrue(size > 1.2e4*i and size < 1.3e4*i ) 00308 i = i+1 00309 00310 00311 def test011(self): 00312 """ test multiple region support""" 00313 shape = [10, 10, 10] 00314 myia = self._myia 00315 myia.fromshape("test011.im", shape) 00316 box = "0, 0, 2, 2, 4, 4, 6, 6" 00317 chans = "0~4, 6, >8" 00318 reg = rg.frombcs( 00319 myia.coordsys().torecord(), shape, 00320 box=box, chans=chans 00321 ) 00322 bb = myia.statistics(region=reg) 00323 self.assertTrue(bb["npts"][0] == 126) 00324 bb = imstat(imagename=myia.name(), chans=chans, box=box) 00325 self.assertTrue(bb["npts"][0] == 126) 00326 00327 def test012(self): 00328 """ Test multi beam support""" 00329 myia = self._myia 00330 shape = [15, 20, 4, 10] 00331 myia.fromshape("", shape) 00332 xx = numpy.array(range(shape[0]*shape[1])) 00333 xx.resize(shape[0], shape[1]) 00334 myia.putchunk(xx, replicate=True) 00335 myia.setbrightnessunit("Jy/pixel") 00336 def check(myia, axes, exp): 00337 for i in range(shape[2]): 00338 for j in range(shape[3]): 00339 got = myia.statistics( 00340 axes=axes, 00341 region=rg.box( 00342 blc = [0, 0, i, j], 00343 trc=[shape[0]-1, shape[1]-1, i, j] 00344 ) 00345 ) 00346 self.assertTrue(len(got.keys()) == len(exp.keys())) 00347 for k in got.keys(): 00348 if (type(got[k]) == type(got["rms"])): 00349 if (k != "blc" and k != "trc"): 00350 self.assertTrue((got[k] == exp[k][0][0]).all()) 00351 00352 axes = [0, 1] 00353 exp = myia.statistics(axes=axes) 00354 self.assertFalse(exp.has_key("flux")) 00355 check(myia, axes, exp) 00356 myia.setbrightnessunit("Jy/beam") 00357 self.assertTrue(myia.brightnessunit() == "Jy/beam") 00358 major = qa.quantity("3arcmin") 00359 minor = qa.quantity("2.5arcmin") 00360 pa= qa.quantity("20deg") 00361 myia.setrestoringbeam( 00362 major=major, minor=minor, pa=pa 00363 ) 00364 self.assertTrue(myia.brightnessunit() == "Jy/beam") 00365 exp = myia.statistics(axes=axes) 00366 self.assertTrue(exp.has_key("flux")) 00367 check(myia, axes, exp) 00368 myia.setrestoringbeam(remove=True) 00369 self.assertTrue( 00370 myia.setrestoringbeam( 00371 major=major, minor=minor, pa=pa, 00372 channel=0, polarization=0 00373 ) 00374 ) 00375 exp = myia.statistics(axes=axes) 00376 self.assertTrue(exp.has_key("flux")) 00377 check(myia, axes, exp) 00378 nmajor = qa.add(major, qa.quantity("0.1arcmin")) 00379 self.assertTrue( 00380 myia.setrestoringbeam( 00381 major=nmajor, minor=minor, pa=pa, 00382 channel=1, polarization=1 00383 ) 00384 ) 00385 exp = myia.statistics(axes=axes) 00386 self.assertTrue(exp.has_key("flux")) 00387 self.assertTrue( 00388 abs(1 - qa.getvalue(nmajor)*exp["flux"][1][1]/(qa.getvalue(major)*exp["flux"][0][0])) 00389 < 1e-7 00390 ) 00391 00392 def test_CAS4545(self): 00393 """verify CAS-4545 fix: full support for >2Gpixel images""" 00394 myia = self._myia 00395 myia.fromshape("", [1290, 1290, 1290]) 00396 stats = myia.statistics() 00397 self.assertTrue(stats['npts'][0] == myia.shape().prod()) 00398 00399 def suite(): 00400 return [imstat_test] 00401 00402
1.8.0
