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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 import commands 00005 import numpy 00006 from __main__ import default 00007 from tasks import * 00008 from taskinit import * 00009 import unittest 00010 00011 ''' 00012 Unit tests for task clean. It tests the following parameters: 00013 vis: wrong and correct values 00014 imagename: if output exists 00015 field: wrong field type; non-default value 00016 spw: wrong value; non-default value 00017 mode: empty value; non-default values 00018 gridmode: unsupported value; non-default values 00019 niter: wrong type; non-default values 00020 psfmode: unsupported value; non-default values 00021 imagermode: unsupported value; non-default values 00022 imsize: zero value; non-default value 00023 stokes: unsupported value; non-default value 00024 weighting: unsupported value; non-default values 00025 selectdata: True; subparameters: 00026 timerange: non-default value 00027 antenna: unsupported value; non-default value 00028 00029 Other tests: check the value of a pixel. 00030 ''' 00031 class clean_test1(unittest.TestCase): 00032 00033 # Input and output names 00034 # msfile = 'ngc7538_ut.ms' 00035 msfile = 'ngc7538_ut1.ms' 00036 res = None 00037 img = 'cleantest1' 00038 img2 = '0-cleantest1' 00039 msk = 'cleantest1.in.mask' 00040 boxmsk = 'cleantest1.box' 00041 00042 def setUp(self): 00043 self.res = None 00044 default(clean) 00045 if (os.path.exists(self.msfile)): 00046 os.system('rm -rf ' + self.msfile) 00047 00048 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00049 shutil.copytree(datapath+self.msfile, self.msfile) 00050 00051 def tearDown(self): 00052 if (os.path.exists(self.msfile)): 00053 os.system('rm -rf ' + self.msfile) 00054 00055 os.system('rm -rf ' + self.img+'*') 00056 00057 def getpixval(self,img,pixel): 00058 ia.open(img) 00059 px = ia.pixelvalue(pixel) 00060 ia.close() 00061 return px['value']['value'] 00062 00063 def compareimages(self,inimage,refimage): 00064 """ 00065 compare the input image with reference image 00066 return true if pix values are identical 00067 usually useful for mask images 00068 """ 00069 ia.open(inimage) 00070 invals = ia.getchunk() 00071 ia.close() 00072 ia.open(refimage) 00073 refvals= ia.getchunk() 00074 ia.close() 00075 diff = refvals - invals 00076 return (numpy.all(diff==0)) 00077 00078 def test1(self): 00079 '''Clean 1: Default values''' 00080 self.res = clean() 00081 self.assertFalse(self.res) 00082 00083 def test2(self): 00084 """Clean 2: Wrong input should return False""" 00085 msfile = 'badfilename' 00086 self.res = clean(vis=msfile, imagename=self.img, imagermode='') 00087 self.assertFalse(self.res) 00088 00089 def test3(self): 00090 """Clean 3: Good input should return None""" 00091 self.res = clean(vis=self.msfile,imagename=self.img, imagermode='') 00092 self.assertEqual(self.res,None) 00093 00094 def test4(self): 00095 """Clean 4: Check if output exists""" 00096 self.res = clean(vis=self.msfile,imagename=self.img) 00097 self.assertTrue(os.path.exists(self.img+'.image')) 00098 00099 def test5(self): 00100 """Clean 5: Wrong field type""" 00101 self.res = clean(vis=self.msfile,imagename=self.img,field=0) 00102 self.assertFalse(self.res) 00103 00104 def test6(self): 00105 """Clean 6: Non-default field value""" 00106 self.res = clean(vis=self.msfile,imagename=self.img,field='0~1', imagermode='') 00107 self.assertEqual(self.res, None) 00108 self.assertTrue(os.path.exists(self.img+'.image')) 00109 00110 def test7(self): 00111 """Clean 7: Wrong spw value""" 00112 self.res = clean(vis=self.msfile,imagename=self.img,spw='10') 00113 self.assertFalse(os.path.exists(self.img+'.image')) 00114 00115 def test8(self): 00116 """Clean 8: Non-default spw value""" 00117 self.res = clean(vis=self.msfile,imagename=self.img,spw='0', imagermode='') 00118 self.assertTrue(os.path.exists(self.img+'.image')) 00119 00120 def test9(self): 00121 """Clean 9: Empty mode value""" 00122 self.res = clean(vis=self.msfile,imagename=self.img,mode='') 00123 self.assertFalse(self.res) 00124 00125 # FIXME: CHANGE SUBPARAMETERS FOR DIFFERENT MODES 00126 def test10(self): 00127 """Clean 10: Non-default mode channel""" 00128 self.res = clean(vis=self.msfile,imagename=self.img,mode='channel',imagermode='') 00129 self.assertEqual(self.res,None) 00130 self.assertTrue(os.path.exists(self.img+'.image'),'Image %s does not exist'%self.img) 00131 00132 def test11(self): 00133 """Clean 11: Non-default mode velocity""" 00134 retValue = {'success': True, 'msgs': "", 'error_msgs': '' } 00135 # The introduction of a new image frequency gridding method 00136 # in imager (CAS-2576) causes the image channel width 00137 # to change (wider, since the velocity width was calculated from lower 00138 # frequency side) for the default velocity mode. This cause the last 00139 # channel image to be blank. To avoid this use nearest interpolation. 00140 res = clean(vis=self.msfile,imagename=self.img,mode='velocity',restfreq='23600MHz', interpolation='nearest',imagermode='') 00141 if(res != None): 00142 retValue['success']=False 00143 retValue['error_msgs']=retValue['error_msgs']\ 00144 +"\nError: Failed to run in velocity mode." 00145 if(not os.path.exists(self.img+'.image')): 00146 retValue['success']=False 00147 retValue['error_msgs']=retValue['error_msgs']\ 00148 +"\nError: Failed to create output image." 00149 00150 # Verify if there are blank planes at the edges 00151 vals = imval(self.img+'.image') 00152 size = len(vals['data']) 00153 00154 if (vals['data'][0]==0 or vals['data'][size-1]==0): 00155 retValue['success']=False 00156 retValue['error_msgs']=retValue['error_msgs']\ 00157 +"\nError: There are blank planes in the edges of the image." 00158 00159 00160 self.assertTrue(retValue['success'],retValue['error_msgs']) 00161 00162 def test12(self): 00163 """Clean 12: Non-default mode frequency""" 00164 self.res = clean(vis=self.msfile,imagename=self.img,mode='frequency',imagermode='') 00165 self.assertEqual(self.res,None) 00166 self.assertTrue(os.path.exists(self.img+'.image'),'Image %s does not exist'%self.img) 00167 00168 def test13(self): 00169 """Clean 13: Unsupported gridmode""" 00170 self.res = clean(vis=self.msfile,imagename=self.img,gridmode='grid') 00171 self.assertFalse(self.res) 00172 00173 def test14(self): 00174 """Clean 14: Non-default gridmode widefield""" 00175 self.res = clean(vis=self.msfile,imagename=self.img,gridmode='widefield',imsize=[20],imagermode='') 00176 self.assertEqual(self.res, None) 00177 self.assertTrue(os.path.exists(self.img+'.image'),'Image %s does not exist'%self.img) 00178 00179 # Takes too long!!! 00180 # def test11(self): 00181 # """Clean 11: Non-default gridmode aprojection""" 00182 # self.res = clean(vis=self.msfile,imagename=self.img,gridmode='aprojection',imsize=[10],niter=1) 00183 # self.assertEqual(self.res, None) 00184 # self.assertTrue(os.path.exists(self.img+'.image'),'Image %s does not exist'%self.img) 00185 00186 def test15(self): 00187 """Clean 15: Wrong niter type""" 00188 self.res = clean(vis=self.msfile,imagename=self.img,niter='1') 00189 self.assertFalse(self.res) 00190 00191 def test16(self): 00192 """Clean 16: Non-default niter values""" 00193 for n in range(10,400,50): 00194 self.res = clean(vis=self.msfile,imagename=self.img,niter=n, imagermode='') 00195 self.assertEqual(self.res,None,'Failed for niter = %s' %n) 00196 00197 def test17(self): 00198 """Clean 17: Unsupported psfmode""" 00199 self.res = clean(vis=self.msfile,imagename=self.img,psfmode='psf') 00200 self.assertFalse(self.res) 00201 00202 def test18(self): 00203 """Clean 18: Non-default psfmode hogbom""" 00204 self.res = clean(vis=self.msfile,imagename=self.img,psfmode='hogbom',imagermode='') 00205 self.assertEqual(self.res, None) 00206 self.assertTrue(os.path.exists(self.img+'.image')) 00207 00208 def test19(self): 00209 """Clean 19: Non-default psfmode clarkstokes""" 00210 self.res = clean(vis=self.msfile,imagename=self.img,psfmode='clarkstokes',imagermode='') 00211 self.assertEqual(self.res, None) 00212 self.assertTrue(os.path.exists(self.img+'.image')) 00213 00214 def test20(self): 00215 """Clean 20: Unsupported imagermode""" 00216 self.res = clean(vis=self.msfile,imagename=self.img,imagermode='clark') 00217 self.assertFalse(self.res) 00218 00219 def test21(self): 00220 '''Clean 21: Non-default imagermode csclean''' 00221 # now csclean is the default 00222 self.res = clean(vis=self.msfile,imagename=self.img,imagermode='csclean') 00223 self.assertEqual(self.res, None) 00224 self.assertTrue(os.path.exists(self.img+'.image')) 00225 00226 def test22(self): 00227 '''Clean 22: Non-default imagermode mosaic''' 00228 self.res = clean(vis=self.msfile,imagename=self.img,imagermode='mosaic',imsize=[20]) 00229 self.assertEqual(self.res, None) 00230 self.assertTrue(os.path.exists(self.img+'.image')) 00231 00232 def test23(self): 00233 """Clean 23: Zero value of imsize""" 00234 self.res = clean(vis=self.msfile,imagename=self.img,imsize=0) 00235 self.assertFalse(os.path.exists(self.img+'.image')) 00236 00237 def test24(self): 00238 '''Clean 24: Non-default imsize values''' 00239 self.res = clean(vis=self.msfile,imagename=self.img,imsize=[80,80], imagermode='') 00240 self.assertEqual(self.res,None) 00241 self.assertTrue(os.path.exists(self.img+'.image'),'Image %s does not exist' %self.img) 00242 00243 def test25(self): 00244 """Clean 25: Non-default cell values""" 00245 self.res = clean(vis=self.msfile,imagename=self.img, cell=12.5, imagermode='') 00246 self.assertEqual(self.res, None) 00247 self.assertTrue(os.path.exists(self.img+'.image')) 00248 00249 def test26(self): 00250 """Clean 26: Unsupported Stokes parameter""" 00251 self.res = clean(vis=self.msfile,imagename=self.img, stokes='V') 00252 self.assertFalse(self.res) 00253 00254 def test27(self): 00255 """Clean 27: Non-default Stokes parameter""" 00256 self.res = clean(vis=self.msfile,imagename=self.img, stokes='RR', imagermode='') 00257 self.assertEqual(self.res, None) 00258 self.assertTrue(os.path.exists(self.img+'.image')) 00259 00260 def test28(self): 00261 '''Clean 28: Unsupported weighting mode''' 00262 self.res = clean(vis=self.msfile,imagename=self.img, weighting='median') 00263 self.assertFalse(self.res) 00264 00265 def test29(self): 00266 '''Clean 29: Non-default weighting uniform''' 00267 self.res = clean(vis=self.msfile,imagename=self.img, weighting='uniform', imagermode='') 00268 self.assertEqual(self.res, None) 00269 self.assertTrue(os.path.exists(self.img+'.image')) 00270 00271 def test30(self): 00272 '''Clean 30: Non-default weighting briggs''' 00273 self.res = clean(vis=self.msfile,imagename=self.img, weighting='briggs', imagermode='') 00274 self.assertEqual(self.res, None) 00275 self.assertTrue(os.path.exists(self.img+'.image')) 00276 00277 def test31(self): 00278 '''Clean 31: Non-default weighting radial''' 00279 self.res = clean(vis=self.msfile,imagename=self.img, weighting='radial', imagermode='') 00280 self.assertEqual(self.res, None) 00281 self.assertTrue(os.path.exists(self.img+'.image')) 00282 00283 def test32(self): 00284 '''Clean 32: Non-default subparameters of selectdata''' 00285 # self.res = clean(vis=self.msfile,imagename=self.img,selectdata=True, 00286 # timerange='>11:30:00',antenna='VA12') 00287 self.res = clean(vis=self.msfile,imagename=self.img,selectdata=True, 00288 timerange='>11:30:00',antenna='VA01', imagermode='') 00289 self.assertEqual(self.res, None) 00290 self.assertTrue(os.path.exists(self.img+'.image')) 00291 00292 def test33(self): 00293 '''Clean 33: Wrong antenna subparameter of selectdata''' 00294 self.res = clean(vis=self.msfile,imagename=self.img,selectdata=True, 00295 antenna='88') 00296 self.assertFalse(os.path.exists(self.img+'.image')) 00297 00298 def test34(self): 00299 '''Clean 34: Verify the value of pixel 50''' 00300 #run clean with some parameters 00301 self.res = clean(vis=self.msfile,imagename=self.img,selectdata=True, 00302 timerange='>11:28:00',field='0~2',imsize=[100,100],niter=10,imagermode='') 00303 00304 os.system('cp -r ' + self.img + '.image' + ' myimage.im') 00305 self.assertEqual(self.res, None) 00306 self.assertTrue(os.path.exists(self.img + '.image')) 00307 # ref = 0.007161217276006937 00308 ref = 0.011824539862573147 00309 # ref = 0.009637 # active rev. 12908 00310 ref = 0.011824540793895721 # active rec. 19307+ (after change to image bandwidth and reffreq) 00311 value = self.getpixval(self.img+'.image', 50) 00312 diff = abs(ref - value) 00313 self.assertTrue(diff < 10e-4, 00314 'Something changed the pixel brightness. ref_val=%s, new_val=%s' 00315 %(ref,value)) 00316 00317 def test35(self): 00318 '''Clean 35: Wrong type of phasecenter''' 00319 self.res=clean(vis=self.msfile,imagename=self.img,phasecenter=4.5) 00320 self.assertFalse(os.path.exists(self.img+'.image')) 00321 00322 def test36(self): 00323 '''Clean 36: Non-default value of phasecenter''' 00324 self.res=clean(vis=self.msfile,imagename=self.img,phasecenter=2,imagermode='') 00325 self.assertTrue(os.path.exists(self.img+'.image')) 00326 00327 def test37(self): 00328 '''Clean 37: Test box mask''' 00329 self.res=clean(vis=self.msfile,imagename=self.img,mask=[115,115,145,145],imagermode='') 00330 self.assertTrue(os.path.exists(self.img+'.image') and 00331 os.path.exists(self.img+'.mask')) 00332 00333 def test38(self): 00334 '''Clean 38: Test freeing of resource for mask (checks CAS-954)''' 00335 self.res=clean(vis=self.msfile,imagename=self.img,mask=[115,115,145,145],imagermode='') 00336 cmd='/usr/sbin/lsof|grep %s' % self.img+'.mask' 00337 output=commands.getoutput(cmd) 00338 ret=output.find(self.img+'.mask') 00339 self.assertTrue(ret==-1) 00340 00341 def test39(self): 00342 '''Clean 39: Input mask image specified''' 00343 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00344 shutil.copytree(datapath+self.msk, '1_'+self.msk) 00345 self.res=clean(vis=self.msfile,imagename=self.img2,mask='1_'+self.msk, imagermode='') 00346 self.assertEqual(self.res, None) 00347 self.assertTrue(os.path.exists(self.img2+'.image')) 00348 # cleanup 00349 os.system('rm -rf ' + '1_'+self.msk+ ' ' + self.img2+'*') 00350 00351 def test40(self): 00352 '''Clean 40: Test chaniter=T clean with flagged channels''' 00353 # test CAS-2369 bug fix 00354 flagdata(vis=self.msfile,mode='manualflag',spw='0:0~0') 00355 self.res=clean(vis=self.msfile,imagename=self.img,mode='channel',chaniter=True, spw='0', imagermode='') 00356 self.assertEqual(self.res, None) 00357 self.assertTrue(os.path.exists(self.img+'.image')) 00358 00359 def test41(self): 00360 '''Clean 41: Test nterms=2 and ref-freq > maximum-frequency''' 00361 # This tests if negative-weights are being correctly allowed through the gridders 00362 self.res=clean(vis=self.msfile,imagename=self.img,nterms=2,reffreq='25.0GHz',niter=5,imagermode=''); 00363 self.assertEqual(self.res,None); 00364 00365 def test42(self): 00366 '''Clean42: Test nterms=2, with only one channel whose frequency is same as ref-freq''' 00367 # This tests if a numerical failure-mode is detected and returned without fuss. 00368 self.res=clean(vis=self.msfile,imagename=self.img,nterms=2,reffreq='23691.4682MHz',spw='0:0',imagermode=''); 00369 self.assertFalse(self.res); 00370 00371 def test43(self): 00372 '''Clean 43: Test user input mask from a boxfile''' 00373 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00374 refpath=datapath+'reference/' 00375 shutil.copyfile(datapath+self.boxmsk, self.boxmsk) 00376 self.res=clean(vis=self.msfile,imagename=self.img,mode='channel', mask=self.boxmsk,imagermode='') 00377 self.assertEqual(self.res, None) 00378 self.assertTrue(os.path.exists(self.img+'.image')) 00379 self.assertTrue(self.compareimages(self.img+'.mask', refpath+'ref_cleantest1boxfile.mask')) 00380 00381 def test44(self): 00382 '''Clean 44: Test input mask image of different channel ranges''' 00383 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00384 refpath=datapath+'reference/' 00385 shutil.copyfile(datapath+self.boxmsk, self.boxmsk) 00386 # wider channel range mask 00387 self.res=clean(vis=self.msfile,imagename=self.img,mode='channel', mask=[115,115,145,145], niter=10,imagermode='') 00388 self.assertEqual(self.res, None) 00389 # apply to narrower channel range 00390 self.res=clean(vis=self.msfile,imagename=self.img+'.narrow',mode='channel', 00391 nchan=3, start=2, mask=self.img+'.mask', niter=10,imagermode='') 00392 self.assertEqual(self.res, None) 00393 # apply the narrower channel range mask to wider channel range clean 00394 self.res=clean(vis=self.msfile,imagename=self.img+'.wide',mode='channel',mask=self.img+'.narrow.mask', niter=10,imagermode='') 00395 00396 # make sub-image from masks for comparison 00397 ia.open(self.img+'.mask') 00398 r1=rg.box([0,0,0,2],[256,256,0,4]) 00399 sbim=ia.subimage(outfile=self.img+'.subim.mask', region=r1) 00400 ia.close() 00401 sbim.close() 00402 # 00403 os.system('cp -r '+self.img+'.mask '+self.img+'.ref.mask') 00404 ia.open(self.img+'.narrow.mask') 00405 # note: narrow mask made with a single spw does not exactly 00406 # match with the wider cube with 2 spws in width 00407 pixs = ia.getchunk(blc=[0,0,0,0],trc=[256,256,0,1]) 00408 r1=rg.box([0,0,0,0],[256,256,0,1]) 00409 ia.close() 00410 ia.open(self.img+'.ref.mask') 00411 ia.set(pixelmask=False) 00412 ia.set(pixelmask=True, region=r1) 00413 ia.putchunk(pixels=pixs,blc=[0,0,0,2]) 00414 ia.close() 00415 00416 self.assertTrue(os.path.exists(self.img+'.narrow.image')) 00417 self.assertTrue(os.path.exists(self.img+'.wide.image')) 00418 self.assertTrue(self.compareimages(self.img+'.narrow.mask', self.img+'.subim.mask'), 00419 "mask mismatch for applying a wider chan. range mask to narrower chan. range clean") 00420 self.assertTrue(self.compareimages(self.img+'.wide.mask', self.img+'.ref.mask'), 00421 "mask mismatch for applying a narrower chan. range mask to wider chan. range clean") 00422 00423 def test45(self): 00424 """Clean 45: Test selection of obs ID 0 (present)""" 00425 self.res = clean(vis=self.msfile, imagename=self.img + '0', 00426 selectdata=True, observation='0', niter=10, imagermode='') 00427 self.assertTrue(os.path.exists(self.img + '0.image')) 00428 00429 def test46(self): 00430 """Clean 46: Test selection of obs ID 2 (absent)""" 00431 self.res = clean(vis=self.msfile, imagename=self.img + '2', 00432 selectdata=True, observation='2', niter=10) 00433 self.assertFalse(os.path.exists(self.img + '2.image')) 00434 00435 00436 class clean_test2(unittest.TestCase): 00437 00438 # Input and output names 00439 msfile = 'split1scan.ms' 00440 res = None 00441 img = 'cleantest2' 00442 00443 def setUp(self): 00444 self.res = None 00445 default(clean) 00446 if (os.path.exists(self.msfile)): 00447 os.system('rm -rf ' + self.msfile) 00448 00449 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00450 shutil.copytree(datapath+self.msfile, self.msfile) 00451 00452 def tearDown(self): 00453 if (os.path.exists(self.msfile)): 00454 os.system('rm -rf ' + self.msfile) 00455 00456 def test1a(self): 00457 """Clean 1a: Non-default mode velocity""" 00458 retValue = {'success': True, 'msgs': "", 'error_msgs': '' } 00459 res = clean(vis=self.msfile,imagename=self.img,mode='velocity',restfreq='231901MHz') 00460 if(res != None): 00461 retValue['success']=False 00462 retValue['error_msgs']=retValue['error_msgs']\ 00463 +"\nError: Failed to run in velocity mode." 00464 if(not os.path.exists(self.img+'.image')): 00465 retValue['success']=False 00466 retValue['error_msgs']=retValue['error_msgs']\ 00467 +"\nError: Failed to create output image." 00468 00469 # Verify if there are blank planes at the edges 00470 vals = imval(self.img+'.image') 00471 size = len(vals['data']) 00472 if (vals['data'][0]==0.0 or vals['data'][size-1]==0.0): 00473 retValue['success']=False 00474 retValue['error_msgs']=retValue['error_msgs']\ 00475 +"\nError: There are blank planes in the edges of the image." 00476 00477 00478 self.assertTrue(retValue['success'],retValue['error_msgs']) 00479 00480 class clean_multifield_test(unittest.TestCase): 00481 00482 # Input and output names# msfile = 'ngc7538_ut.ms' 00483 #msfile = '0556kf.ms' 00484 msfile = 'outlier_ut.ms' 00485 res = None 00486 img = ['cleantest3a','cleantest3b'] 00487 newoutlierfile='newoutlier4cleantest.txt' 00488 inmodel = 'cleantest3in.model' 00489 00490 def setUp(self): 00491 self.res = None 00492 default(clean) 00493 if (os.path.exists(self.msfile)): 00494 os.system('rm -rf ' + self.msfile) 00495 00496 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00497 shutil.copytree(datapath+self.msfile, self.msfile) 00498 00499 def tearDown(self): 00500 if (os.path.exists(self.msfile)): 00501 os.system('rm -rf ' + self.msfile) 00502 00503 #os.system('rm -rf ' + self.img[0]+'* ') 00504 #os.system('rm -rf ' + self.img[1]+'* ') 00505 for imext in ['.image','.model','.residual','.psf']: 00506 if (os.path.exists(self.img[0]+imext)): 00507 shutil.rmtree(self.img[0]+imext) 00508 if (os.path.exists(self.img[1]+imext)): 00509 shutil.rmtree(self.img[1]+imext) 00510 00511 #def testCAS1972(self): 00512 # """Clean test3:test bug fixes: CAS-1972""" 00513 # self.res= clean(vis=self.msfile,imagename=self.img,mode="mfs",interpolation="linear", 00514 # niter=100, psfmode="clark", 00515 # imsize=[[512, 512], [512, 512]], 00516 # cell="0.0001arcsec", phasecenter=['J2000 05h59m32.03313 23d53m53.9267', 00517 # 'J2000 05h59m32.03313 23d53m53.9263'], 00518 # weighting="natural",pbcor=False,minpb=0.1) 00519 # 00520 # self.assertEqual(self.res,None) 00521 # for im in self.img: 00522 # self.assertTrue(os.path.exists(im+'.image')) 00523 # stat0 = imstat(self.img[0]+'.model') 00524 # stat1 = imstat(self.img[1]+'.model') 00525 # self.assertEqual(stat0['max'],stat1['max']) 00526 # self.assertTrue(all(stat0['maxpos']==numpy.array([256,256,0,0])) and 00527 # all(stat1['maxpos']==numpy.array([256,260,0,0]))) 00528 00529 def testCAS1972(self): 00530 """Clean test3:test CAS-1972 bug fixes ver2 (with smaller dataset)""" 00531 self.res= clean(vis=self.msfile, 00532 imagename=self.img, 00533 mode="mfs", 00534 interpolation="linear", 00535 niter=100, psfmode="clark", 00536 imagermode='', 00537 #mask=[[250, 250, 262, 262], [250, 350, 262, 362]], 00538 # use (new) CASA region 00539 mask=['box[ [250pix, 250pix], [262pix, 262pix]]', 'box[ [250pix, 350pix], [262pix, 362pix]]'], 00540 imsize=[[512, 512], [512, 512]], 00541 cell="0.0001arcsec", 00542 phasecenter=['J2000 05h59m32.03313 23d53m53.9267', 'J2000 05h59m32.03313 23d53m53.9167'], 00543 weighting="natural", 00544 pbcor=False, 00545 minpb=0.1) 00546 00547 self.assertEqual(self.res,None) 00548 # quick check on the peaks apear at the location as expected 00549 for img in self.img: 00550 self.assertTrue(os.path.exists(img+".image")) 00551 stat0 = imstat(self.img[0]+'.model') 00552 stat1 = imstat(self.img[1]+'.model') 00553 #self.assertEqual(stat0['max'],stat1['max']) 00554 self.assertTrue(all(stat0['maxpos']==numpy.array([256,256,0,0])) and 00555 all(stat1['maxpos']==numpy.array([256,356,0,0]))) 00556 00557 def testOutlier2(self): 00558 """Clean test3:test task parm input with outlier file (CAS-3221)""" 00559 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00560 shutil.copy(datapath+self.newoutlierfile,self.newoutlierfile) 00561 self.res= clean(vis=self.msfile, 00562 imagename=self.img[0], 00563 outlierfile=self.newoutlierfile, 00564 mode="mfs", 00565 interpolation="linear", 00566 niter=100, psfmode="clark", 00567 imagermode='', 00568 mask=[250, 250, 262, 262], 00569 imsize=[512, 512], 00570 cell="0.0001arcsec", 00571 phasecenter='J2000 05h59m32.03313 23d53m53.9267', 00572 weighting="natural", 00573 pbcor=False, 00574 minpb=0.1) 00575 00576 #print "DONE clean" 00577 self.assertEqual(self.res,None) 00578 # quick check on the peaks apear at the location as expected 00579 for img in self.img: 00580 self.assertTrue(os.path.exists(img+".image")) 00581 stat0 = imstat(self.img[0]+'.model') 00582 stat1 = imstat(self.img[1]+'.model') 00583 #self.assertEqual(stat0['max'],stat1['max']) 00584 self.assertTrue(all(stat0['maxpos']==numpy.array([256,256,0,0])) and 00585 all(stat1['maxpos']==numpy.array([256,356,0,0]))) 00586 00587 def testOutlier3(self): 00588 """Clean test3:test task parm input with outlier file and with user-specified mask and model""" 00589 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00590 shutil.copy(datapath+self.newoutlierfile,self.newoutlierfile) 00591 shutil.copytree(datapath+self.inmodel, self.inmodel) 00592 self.res= clean(vis=self.msfile, 00593 imagename=self.img[0], 00594 outlierfile=self.newoutlierfile, 00595 mode="mfs", 00596 interpolation="linear", 00597 niter=100, psfmode="clark", 00598 imagermode='', 00599 mask='box [[250pix, 250pix], [262pix, 262pix]]', 00600 imsize=[512, 512], 00601 cell="0.0001arcsec", 00602 phasecenter='J2000 05h59m32.03313 23d53m53.9267', 00603 weighting="natural", 00604 pbcor=False, 00605 minpb=0.1) 00606 00607 #print "DONE clean" 00608 self.assertEqual(self.res,None) 00609 # quick check on the peaks apear at the location as expected 00610 for img in self.img: 00611 self.assertTrue(os.path.exists(img+".image")) 00612 stat0 = imstat(self.img[0]+'.model') 00613 stat1 = imstat(self.img[1]+'.model') 00614 #self.assertEqual(stat0['max'],stat1['max']) 00615 self.assertTrue(all(stat0['maxpos']==numpy.array([256,256,0,0])) and 00616 all(stat1['maxpos']==numpy.array([256,356,0,0]))) 00617 00618 class clean_multiterm_multifield_test(unittest.TestCase): 00619 00620 msfile = 'tpts_2chan_split.ms' 00621 #msfile = 'tpts_2chan.ms' 00622 res = None 00623 img = ['mtmf1','mtmf2'] 00624 outlierfile = 'mtmf_outlier_withmodel.txt' 00625 inmodeldir = 'testmodels'; 00626 modim2=['testmodels/inmodel0.model.tt0','testmodels/inmodel1.model.tt1'] 00627 00628 # Check which data cols exist on disk 00629 def checkdatacols(self,vis=''): 00630 tb.open(vis) 00631 colnames = tb.colnames() 00632 print 'data : ', colnames.count('DATA'), ' model : ', colnames.count('MODEL_DATA'), ' corrected : ', colnames.count('CORRECTED_DATA') 00633 #os.system('du -khs '+vis) 00634 return [ colnames.count('DATA') , colnames.count('MODEL_DATA') , colnames.count('CORRECTED_DATA') ] 00635 00636 # Delete model and corrected columns. 00637 def delmodelcorrcols(self,vis=''): 00638 tb.open(vis, nomodify=False); 00639 colnames = tb.colnames() 00640 remcols = [] 00641 if colnames.count('CORRECTED_DATA'): 00642 remcols.append('CORRECTED_DATA') 00643 00644 if colnames.count('MODEL_DATA'): 00645 remcols.append('MODEL_DATA') 00646 00647 tb.removecols(remcols); 00648 tb.close(); 00649 00650 def setUp(self): 00651 self.res = None 00652 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/multiterm_multifield_data/' 00653 ## datapath = '/home/vega/rurvashi/CASAtrees/DATATree/clean/multiterm_multifield_data/' 00654 default(clean) 00655 if (os.path.exists(self.msfile)): 00656 os.system('rm -rf ' + self.msfile) 00657 00658 shutil.copytree(datapath+self.msfile, self.msfile) 00659 shutil.copy(datapath+self.outlierfile,self.outlierfile) 00660 shutil.copytree(datapath+self.inmodeldir, self.inmodeldir) 00661 00662 def tearDown(self): 00663 if (os.path.exists(self.msfile)): 00664 os.system('rm -rf ' + self.msfile) 00665 if (os.path.exists(self.inmodeldir)): 00666 os.system('rm -rf ' + self.inmodeldir) 00667 if (os.path.exists(self.outlierfile)): 00668 os.system('rm -rf ' + self.outlierfile) 00669 00670 for imext in ['.image.tt0','.image.tt1','.model.tt0','.model.tt1','.residual.tt0','.residual.tt1','.psf.tt0','.psf.tt1','.image.alpha','.flux','.mask']: 00671 if (os.path.exists(self.img[0]+imext)): 00672 shutil.rmtree(self.img[0]+imext) 00673 if (os.path.exists(self.img[1]+imext)): 00674 shutil.rmtree(self.img[1]+imext) 00675 00676 def testMultiTermOutlier(self): 00677 """Clean testMTOutlier1 (multi-term+multi-field : CAS-2664) : test task param input with nterms=2 and outlier file and with user-specified mask and model""" 00678 00679 # Run clean with outlier file 00680 self.res= clean(vis=self.msfile, 00681 imagename=self.img[0], 00682 outlierfile=self.outlierfile, 00683 mode="mfs", 00684 nterms=2, 00685 niter=10, 00686 imagermode='', 00687 mask='circle[[50pix , 50pix] ,15pix ]', 00688 modelimage=['testmodels/inmodel0.model.tt0','testmodels/inmodel0.model.tt1'], 00689 imsize=[100, 100], 00690 interactive=False, 00691 npercycle=10, 00692 cell="8.0arcsec", 00693 weighting="briggs", 00694 pbcor=False, 00695 minpb=0.1) 00696 00697 self.assertEqual(self.res,None) 00698 00699 # quick check on the peaks apear at the location as expected 00700 for img in self.img: 00701 self.assertTrue(os.path.exists(img+".image.tt0")) 00702 self.assertTrue(os.path.exists(img+".image.tt1")) 00703 stat00 = imstat(self.img[0]+'.model.tt0') 00704 stat10 = imstat(self.img[1]+'.model.tt0') 00705 stat01 = imstat(self.img[0]+'.model.tt1') 00706 stat11 = imstat(self.img[1]+'.model.tt1') 00707 00708 self.assertTrue(all(stat00['maxpos']==numpy.array([50,50,0,0])) and 00709 all(stat10['maxpos']==numpy.array([15,15,0,0]))) 00710 self.assertTrue(all(stat01['minpos']==numpy.array([50,50,0,0])) and 00711 all(stat11['minpos']==numpy.array([15,15,0,0]))) 00712 00713 ## Uncomment after CAS-3688 gets fixed, so that this can run in the same casapy session. 00714 ## It will test re-running clean twice, in different ways. 00715 def testMultiTermLists(self): 00716 """Clean testMTOutlier2 (multi-term+multi-field) : test task param input with nterms=2 and inline lists for modelimages and masks""" 00717 00718 # Run clean with inline lists 00719 self.res= clean(vis=self.msfile, 00720 imagename=self.img, 00721 mode="mfs", 00722 nterms=2, 00723 niter=10, 00724 mask=[ 'circle[[50pix , 50pix] ,15pix ]' , 'circle[[15pix , 15pix] ,8pix ]' ], 00725 modelimage=[ ['testmodels/inmodel0.model.tt0','testmodels/inmodel0.model.tt1'] , ['testmodels/inmodel1.model.tt0','testmodels/inmodel1.model.tt1' ] ], 00726 imsize=[ [100,100] , [50,50] ], 00727 phasecenter = [0 ,'J2000 19h58m34.032 +40d57m20.763' ], 00728 interactive=False, 00729 npercycle=10, 00730 cell="8.0arcsec", 00731 weighting="briggs", 00732 pbcor=False, 00733 minpb=0.1) 00734 00735 self.assertEqual(self.res,None) 00736 00737 # quick check on the peaks apear at the location as expected 00738 for img in self.img: 00739 self.assertTrue(os.path.exists(img+".image.tt0")) 00740 self.assertTrue(os.path.exists(img+".image.tt1")) 00741 stat00 = imstat(self.img[0]+'.model.tt0') 00742 stat10 = imstat(self.img[1]+'.model.tt0') 00743 stat01 = imstat(self.img[0]+'.model.tt1') 00744 stat11 = imstat(self.img[1]+'.model.tt1') 00745 00746 self.assertTrue(all(stat00['maxpos']==numpy.array([50,50,0,0])) and 00747 all(stat10['maxpos']==numpy.array([15,15,0,0]))) 00748 self.assertTrue(all(stat01['minpos']==numpy.array([50,50,0,0])) and 00749 all(stat11['minpos']==numpy.array([15,15,0,0]))) 00750 00751 def testMultiTermOutlierUvsub(self): 00752 """Clean testMTOutlier3 (multi-term+multi-field+uvsub) : test task param input with nterms=2, inline lists for outlier fields, clean with niter=0 to predict a model, and uvsub to subtract outliers. 00753 """ 00754 00755 msname = self.msfile 00756 00757 usescratch = False 00758 testmschange = True # Calculate models on one ms, subtract from another 00759 00760 # State-checker... 00761 rstate = True 00762 00763 print '(0) Start with only data column' 00764 self.delmodelcorrcols(msname); 00765 rstate = rstate & ( self.checkdatacols(msname) == [1,0,0] ) 00766 00767 ## (1) Run clean with imsize=100, one field, 2 terms. 00768 os.system('rm -rf try_uvsub_1*'); 00769 clean(vis = msname, \ 00770 imagename = 'try_uvsub_1', \ 00771 imsize=100,\ 00772 mask = 'circle[[50pix , 50pix] ,8pix ]',\ 00773 cell='8.0arcsec',\ 00774 niter=10, \ 00775 gain=0.5, \ 00776 interactive=False, \ 00777 npercycle=5,\ 00778 psfmode='hogbom',\ 00779 weighting='briggs',\ 00780 nterms=2,\ 00781 usescratch=usescratch); 00782 00783 print '(1) After first run' 00784 rstate = rstate & ( self.checkdatacols(msname) == [1,int(usescratch),0] ) 00785 if rstate==False: 00786 print 'FAIL : usescratch=', usescratch, ' in clean' 00787 self.assertTrue( rstate ) 00788 00789 ## (2) Run clean with two fields, 100, 50, both with 2 terms 00790 os.system('rm -rf try_uvsub_2*'); 00791 clean(vis = msname, \ 00792 imagename = [ 'try_uvsub_2_main', 'try_uvsub_2_outlier' ], \ 00793 imsize=[ [100,100], [50,50] ], \ 00794 phasecenter = [ 0 , 'J2000 19h58m34.032 +40d57m20.763' ], \ 00795 mask = ['circle[[50pix , 50pix] ,8pix ]' , 'circle[[15pix , 15pix] ,8pix ]'],\ 00796 cell=['8.0arcsec'],\ 00797 niter=10, \ 00798 gain=0.5, \ 00799 interactive=False, \ 00800 npercycle=5,\ 00801 psfmode='hogbom',\ 00802 weighting='briggs',\ 00803 nterms=2,\ 00804 usescratch=usescratch); 00805 00806 print '(2) After the multi-field run' 00807 rstate = rstate & ( self.checkdatacols(msname) == [1,int(usescratch),0] ) 00808 if rstate==False: 00809 print 'FAIL : usescratch=', usescratch, ' in clean' 00810 self.assertTrue( rstate ) 00811 00812 if testmschange == True: 00813 self.delmodelcorrcols(msname); 00814 print '(2.5) Deleting model col again' 00815 rstate = rstate & ( self.checkdatacols(msname) == [1,0,0] ) 00816 if rstate==False: 00817 print 'FAIL : Error in deleting columns' 00818 00819 ## (3) Run clean with niter=0 and only the second field model (2 terms) 00820 clean(vis = msname, \ 00821 imagename = 'try_uvsub_2_outlier', \ 00822 imsize=[50,50],\ 00823 phasecenter='J2000 19h58m34.032 +40d57m20.763' ,\ 00824 mask = 'circle[[15pix , 15pix] ,8pix ]',\ 00825 cell=['8.0arcsec'],\ 00826 niter=0, \ 00827 weighting='briggs',\ 00828 nterms=2,\ 00829 usescratch=usescratch); 00830 00831 print '(3) After the niter=0 prediction run with usescratch=', usescratch 00832 rstate = rstate & ( self.checkdatacols(msname) == [1,int(usescratch),0] ) 00833 if rstate==False: 00834 print 'FAIL : usescratch=', usescratch, ' in clean' 00835 self.assertTrue( rstate ) 00836 00837 ## (4) uvsub 00838 uvsub(vis = msname) 00839 00840 print '(4) After uvsub' 00841 rstate = rstate & ( self.checkdatacols(msname) == [1,int(usescratch),1] ) 00842 if rstate==False: 00843 print 'FAIL : uvsub scratch-column construction. Should be ', [1,int(usescratch),1] 00844 self.assertTrue( rstate ) 00845 00846 ## (5) Repeat (1) and sidelobes from the faraway source should have gone. 00847 os.system('rm -rf try_uvsub_3*'); 00848 clean(vis = msname, \ 00849 imagename = 'try_uvsub_3', \ 00850 imsize=100,\ 00851 mask = 'circle[[50pix , 50pix] ,8pix ]',\ 00852 cell='8.0arcsec',\ 00853 niter=10, \ 00854 gain=0.5, \ 00855 interactive=False, \ 00856 npercycle=5,\ 00857 psfmode='hogbom',\ 00858 weighting='briggs',\ 00859 nterms=2,\ 00860 usescratch=usescratch); 00861 00862 print '(5) Finished second clean run' 00863 rstate = rstate & ( self.checkdatacols(msname) == [1,int(usescratch),1] ) 00864 if rstate==False: 00865 print 'FAIL : usescratch in clean' 00866 self.assertTrue( rstate ) 00867 00868 print '(6) Check that try_uvsub_3.image.tt0 looks like try_uvsub_2_main.image.tt0 and not have huge circles of try_uvsub_1.image.tt0 in the top right corner' 00869 00870 stat1 = imstat('try_uvsub_1.image.tt0') 00871 stat2 = imstat('try_uvsub_2_main.image.tt0') 00872 stat3 = imstat('try_uvsub_3.image.tt0') 00873 00874 print "Peak positions : ", stat1['maxpos'] , stat2['maxpos'] , stat3 ['maxpos'] 00875 00876 rstate = rstate & all(stat1['maxpos']==numpy.array([50,50,0,0])) 00877 rstate = rstate & all(stat1['maxpos']==numpy.array([50,50,0,0])) 00878 rstate = rstate & all(stat1['maxpos']==numpy.array([50,50,0,0])) 00879 00880 statcorner1 = imstat('try_uvsub_1.image.tt0', box='70,70,99,99') 00881 statcorner2 = imstat('try_uvsub_2_main.image.tt0', box='70,70,99,99') 00882 statcorner3 = imstat('try_uvsub_3.image.tt0', box='70,70,99,99') 00883 00884 print "Corner RMS : ", statcorner1['rms'] , statcorner2['rms'] , statcorner3 ['rms'] 00885 00886 rstate = rstate & (statcorner1['rms'] > 0.049 and statcorner1['rms'] < 0.05) 00887 rstate = rstate & (statcorner2['rms'] > 0.0021 and statcorner2['rms'] < 0.0022) 00888 rstate = rstate & (statcorner3['rms'] > 0.0021 and statcorner3['rms'] < 0.0022) 00889 00890 self.assertTrue( rstate ) 00891 00892 ######################################################### 00893 00894 class clean_multims_test(unittest.TestCase): 00895 # unit tests for multiple ms inputs 00896 msfiles = ['point_spw1.ms', 'point_spw2.ms'] 00897 res = None 00898 img = 'cleantest_multims' 00899 mask = 'multims-mfs.topo.mask' 00900 00901 def setUp(self): 00902 self.res = None 00903 default(clean) 00904 for msfile in self.msfiles: 00905 if (os.path.exists(msfile)): 00906 os.system('rm -rf ' + msfile) 00907 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00908 #datapath = '../' 00909 shutil.copytree(datapath+msfile, msfile) 00910 00911 def tearDown(self): 00912 for msfile in self.msfiles: 00913 if (os.path.exists(msfile)): 00914 os.system('rm -rf ' + msfile) 00915 00916 for imext in ['.image','.model','.residual','.psf','.flux','.mask']: 00917 if (os.path.exists(self.img+imext)): 00918 shutil.rmtree(self.img+imext) 00919 00920 def test_multims1(self): 00921 '''Clean multims test1: Test two cases with wrong numbers of spw or field given)''' 00922 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00923 resfail1=clean(vis=self.msfiles,spw=['0~1','0~1','0'],field=['0~2','0~2'],imagename=self.img,imagermode='') 00924 resfail2=clean(vis=self.msfiles,spw=['0~1','0~1'],field=['0~2','0~2','0~2'],imagename=self.img,imagermode='') 00925 self.res=clean(vis=self.msfiles,spw=['0~1','0~1'],field=['0~2','0~2'],imagename=self.img,imagermode='') 00926 self.assertFalse(resfail1) 00927 self.assertFalse(resfail2) 00928 self.assertEqual(self.res,None) 00929 00930 def test_multims2(self): 00931 '''Clean multims test2: Test multiple MSes input in mfs mode''' 00932 # expected reference values on r.15199 00933 #refimbandw=1.0e+09 00934 #refimfreq=1.49e+09 00935 #refimmax=1.198562 00936 # expected reference values for r19307+ (change to defineimage bandwidth and reffreq) 00937 refimbandw=1.019991294e+09 00938 refimfreq=1.489984788e+09 00939 refimmax=1.19856226444 00940 00941 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00942 self.res=clean(vis=self.msfiles,mode='mfs', spw='', field='',imsize=[200], 00943 cell=['4.0arcsec', '4.0arcsec'], imagename=self.img,imagermode='') 00944 self.assertEqual(self.res,None) 00945 imhout=imhead(imagename=self.img+'.image',mode='list') 00946 #print "imhout['cdelt4']=", imhout['cdelt4'], " imhout['crval4']=", imhout['crval4'], " imhout['datamax']=",imhout['datamax'] 00947 imbwrdiff = abs(refimbandw-float(imhout['cdelt4']))/refimbandw 00948 imfreqrdiff = abs(refimfreq-float(imhout['crval4']))/refimfreq 00949 maxrdiff = abs(refimmax-float(imhout['datamax']))/refimmax 00950 # should exactly match for bandwidth and center frequency 00951 self.assertTrue(imbwrdiff < 1.0e-9) 00952 self.assertTrue(imfreqrdiff < 1.0e-9) 00953 self.assertTrue(maxrdiff < 0.01) 00954 00955 def test_multims3(self): 00956 '''Clean multims test3: Test multiple MSes input in mfs mode with spw channel selection''' 00957 # expected reference values on r.15199 00958 #refimbandw=9.2e+08 00959 #refimfreq=1.45e+09 00960 #refimmax=1.25990 00961 # expected reference values for r19307+ (change to defineimage bandwidth and reffreq) 00962 refimbandw=9.59991881e+08 00963 refimfreq=1.459985082e+09 00964 refimmax=1.2438338995 00965 00966 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00967 self.res=clean(vis=self.msfiles,mode='mfs', spw=['0:0~19','0:0~16'], field='',imsize=[200], 00968 cell=['4.0arcsec', '4.0arcsec'], imagename=self.img, imagermode='') 00969 self.assertEqual(self.res,None) 00970 imhout=imhead(imagename=self.img+'.image',mode='list') 00971 imbwrdiff = abs(refimbandw-float(imhout['cdelt4']))/refimbandw 00972 imfreqrdiff = abs(refimfreq-float(imhout['crval4']))/refimfreq 00973 maxrdiff = abs(refimmax-float(imhout['datamax']))/refimmax 00974 # should exactly match for bandwidth and center frequency 00975 #print "imhout['cdelt4']=", imhout['cdelt4'], " imhout['crval4']=", imhout['crval4'], " imhout['datamax']=",imhout['datamax'] 00976 self.assertTrue(imbwrdiff < 1.0e-9) 00977 self.assertTrue(imfreqrdiff < 1.0e-9) 00978 self.assertTrue(maxrdiff < 0.01) 00979 00980 def test_multims4(self): 00981 '''Clean multims test4: Test multiple MSes input in frequency mode, make a single fat bw image''' 00982 # expected reference values on r.15199 00983 refimbandw=1.0e+09 00984 refimmax=1.19717 00985 refimfreq=1.5e+09 00986 00987 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 00988 self.res=clean(vis=self.msfiles,mode='frequency', spw='', field='',imsize=[200], 00989 cell=['4.0arcsec', '4.0arcsec'], imagename=self.img, start='1.5GHz', width='1GHz', nchan=1, imagermode='') 00990 self.assertEqual(self.res,None) 00991 imhout=imhead(imagename=self.img+'.image',mode='list') 00992 imbwrdiff = abs(refimbandw-float(imhout['cdelt4']))/refimbandw 00993 imfreqrdiff = abs(refimfreq-float(imhout['crval4']))/refimfreq 00994 maxrdiff = abs(refimmax-float(imhout['datamax']))/refimmax 00995 # should exactly match for bandwidth and center frequency 00996 #print "imhout['cdelt4']=", imhout['cdelt4'], " imhout['crval4']=", imhout['crval4'], " imhout['datamax']=",imhout['datamax'] 00997 self.assertTrue(imbwrdiff < 1.0e-9) 00998 self.assertTrue(imfreqrdiff < 1.0e-9) 00999 self.assertTrue(maxrdiff < 0.01) 01000 01001 def test_multims5(self): 01002 '''Clean multims test5: Test multiple MSes input with a mask in different spectral frame (mfs mode)''' 01003 # expected reference values on r.16164 01004 refimbandw=1.0e+09 01005 refimmax=1.19606661797 01006 refimfreq=1.49e+09 01007 01008 datapath = os.environ.get('CASAPATH').split()[0] + '/data/regression/unittest/clean/' 01009 if not os.path.exists(self.mask): 01010 shutil.copytree(datapath+self.mask, self.mask) 01011 self.res=clean(vis=self.msfiles,mode='mfs', spw='', field='',imsize=[200], 01012 cell=['4.0arcsec', '4.0arcsec'], imagename=self.img, mask=self.mask,imagermode='') 01013 self.assertEqual(self.res,None) 01014 imhout=imhead(imagename=self.img+'.image',mode='list') 01015 imbwrdiff = abs(refimbandw-float(imhout['cdelt4']))/refimbandw 01016 imfreqrdiff = abs(refimfreq-float(imhout['crval4']))/refimfreq 01017 maxrdiff = abs(refimmax-float(imhout['datamax']))/refimmax 01018 # 01019 shutil.rmtree(self.mask) 01020 01021 01022 def suite(): 01023 #return [clean_test1] 01024 return [clean_test1,clean_multifield_test,clean_multims_test,clean_multiterm_multifield_test] 01025
1.8.0
