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casa
$Rev:20696$
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casa
$Rev:20696$
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00001 # 00002 # This file was generated using xslt from its XML file 00003 # 00004 # Copyright 2008, Associated Universities Inc., Washington DC 00005 # 00006 import sys 00007 import os 00008 #from casac import * 00009 import casac 00010 import string 00011 import time 00012 import inspect 00013 import gc 00014 import numpy 00015 from odict import odict 00016 from taskmanager import tm 00017 from task_feather import feather 00018 class feather_cli_: 00019 __name__ = "feather" 00020 __async__ = {} 00021 rkey = None 00022 i_am_a_casapy_task = None 00023 # The existence of the i_am_a_casapy_task attribute allows help() 00024 # (and other) to treat casapy tasks as a special case. 00025 00026 def __init__(self) : 00027 self.__bases__ = (feather_cli_,) 00028 self.__doc__ = self.__call__.__doc__ 00029 00030 self.parameters={'imagename':None, 'highres':None, 'lowres':None, 'sdfactor':None, 'effdishdiam':None, 'showplot':None, 'async':None} 00031 00032 00033 def result(self, key=None): 00034 #### here we will scan the task-ids in __async__ 00035 #### and add any that have completed... 00036 if key is not None and self.__async__.has_key(key) and self.__async__[key] is not None: 00037 ret = tm.retrieve(self.__async__[key]) 00038 if ret['state'] == "done" : 00039 self.__async__[key] = None 00040 elif ret['state'] == 'crashed' : 00041 self.__async__[key] = None 00042 return ret 00043 return None 00044 00045 00046 def __call__(self, imagename=None, highres=None, lowres=None, sdfactor=None, effdishdiam=None, showplot=None, async=None): 00047 00048 """Combine two images using their Fourier transforms 00049 00050 Feathering is a simple method for combining two images with different 00051 spatial resolution. The processing steps are: 00052 00053 1. Regrid the low-resolution image to a temporary copy matching the 00054 resolution of the high-resolution image, 00055 2. Transform each image to the spatial-frequency plane (gridded). 00056 3. Scale the low-resolution image (uv-grid) by the ratio of the 00057 volumes of the two 'clean beams' (high-res/low-res). 00058 4. Add to this, the uv-grid of the high-resolution image, scaled by 00059 (1-wt) where 'wt' is the Fourier transform of the 'clean beam' 00060 defined in the low-resolution image. 00061 5. Transform back to the image plane. 00062 00063 Both input images must have a well-defined beam shape for this task to work. 00064 This could be a 'clean beam' for interferometric images, and a 'primary-beam' 00065 for a single-dish image. 00066 00067 The two images must also have the same flux density normalization scale. 00068 00069 Keyword arguments: 00070 imagename -- Name of output feathered image 00071 default: none; example: imagename='orion_combined.im' 00072 highres -- Name of high resolution (interferometer) image 00073 default: none; example: highres='orion_vla.im' 00074 This image is often a clean image obtained from synthesis 00075 observations. 00076 lowres -- Name of low resolution (single dish) image 00077 default: none; example: lowres='orion_gbt.im' 00078 This image is often a image from a single-dish observations 00079 or a clean image obtained from lower resolution synthesis 00080 observations. 00081 sdfactor -- value by which to scale the Single Dish image. Default is 1.0 00082 Basically modifying the flux scale of the SD image 00083 effdishdiam -- New effective SingleDish diameter to use in m. Obviously one can only reduce the dish effective dish diameter in feathering. Default -1.0 means leave as is. 00084 showplot -- If True will plot the cuts across the feathring function 00085 00086 00087 Comments: 00088 00089 This task can be used as one method of combining single-dish and 00090 interferometric images after they have been separately made. 00091 00092 The clean task allows another method of combining single-dish and 00093 interferometric data. The single-dish image can be used as a starting 00094 model for the interferometric image-reconstruction. If there is 00095 some overlap between the spatial-frequencies contained in the 00096 single-dish image and the interferometer sampling function, then, 00097 such a starting model will help constrain the solutions on the 00098 short-baselines of the interferometric data. 00099 00100 00101 00102 """ 00103 if not hasattr(self, "__globals__") or self.__globals__ == None : 00104 self.__globals__=sys._getframe(len(inspect.stack())-1).f_globals 00105 #casac = self.__globals__['casac'] 00106 casalog = self.__globals__['casalog'] 00107 #casalog = casac.casac.logsink() 00108 self.__globals__['__last_task'] = 'feather' 00109 self.__globals__['taskname'] = 'feather' 00110 ### 00111 self.__globals__['update_params'](func=self.__globals__['taskname'],printtext=False,ipython_globals=self.__globals__) 00112 ### 00113 ### 00114 #Handle globals or user over-ride of arguments 00115 # 00116 function_signature_defaults=dict(zip(self.__call__.func_code.co_varnames,self.__call__.func_defaults)) 00117 useLocalDefaults = False 00118 00119 for item in function_signature_defaults.iteritems(): 00120 key,val = item 00121 keyVal = eval(key) 00122 if (keyVal == None): 00123 #user hasn't set it - use global/default 00124 pass 00125 else: 00126 #user has set it - use over-ride 00127 if (key != 'self') : 00128 useLocalDefaults = True 00129 00130 myparams = {} 00131 if useLocalDefaults : 00132 for item in function_signature_defaults.iteritems(): 00133 key,val = item 00134 keyVal = eval(key) 00135 exec('myparams[key] = keyVal') 00136 self.parameters[key] = keyVal 00137 if (keyVal == None): 00138 exec('myparams[key] = '+ key + ' = self.itsdefault(key)') 00139 keyVal = eval(key) 00140 if(type(keyVal) == dict) : 00141 if len(keyVal) > 0 : 00142 exec('myparams[key] = ' + key + ' = keyVal[len(keyVal)-1][\'value\']') 00143 else : 00144 exec('myparams[key] = ' + key + ' = {}') 00145 00146 else : 00147 async = self.parameters['async'] 00148 myparams['imagename'] = imagename = self.parameters['imagename'] 00149 myparams['highres'] = highres = self.parameters['highres'] 00150 myparams['lowres'] = lowres = self.parameters['lowres'] 00151 myparams['sdfactor'] = sdfactor = self.parameters['sdfactor'] 00152 myparams['effdishdiam'] = effdishdiam = self.parameters['effdishdiam'] 00153 myparams['showplot'] = showplot = self.parameters['showplot'] 00154 00155 00156 result = None 00157 00158 # 00159 # The following is work around to avoid a bug with current python translation 00160 # 00161 mytmp = {} 00162 00163 mytmp['imagename'] = imagename 00164 mytmp['highres'] = highres 00165 mytmp['lowres'] = lowres 00166 mytmp['sdfactor'] = sdfactor 00167 mytmp['effdishdiam'] = effdishdiam 00168 mytmp['showplot'] = showplot 00169 pathname='file:///'+os.environ.get('CASAPATH').split()[0]+'/share/xml/' 00170 trec = casac.casac.utils().torecord(pathname+'feather.xml') 00171 00172 casalog.origin('feather') 00173 try : 00174 #if not trec.has_key('feather') or not casac.casac.utils().verify(mytmp, trec['feather']) : 00175 #return False 00176 00177 casac.casac.utils().verify(mytmp, trec['feather'], True) 00178 scriptstr=[''] 00179 saveinputs = self.__globals__['saveinputs'] 00180 saveinputs('feather', 'feather.last', myparams, self.__globals__,scriptstr=scriptstr) 00181 if async : 00182 count = 0 00183 keybase = time.strftime("%y%m%d.%H%M%S") 00184 key = keybase + "_" + str(count) 00185 while self.__async__.has_key(key) : 00186 count += 1 00187 key = keybase + "_" + str(count) 00188 result = tm.execute('feather', imagename, highres, lowres, sdfactor, effdishdiam, showplot) 00189 print "Use: " 00190 print " tm.retrieve(return_value) # to retrieve the status" 00191 print 00192 self.rkey = key 00193 self.__async__[key] = result 00194 else : 00195 tname = 'feather' 00196 spaces = ' '*(18-len(tname)) 00197 casalog.post('\n##########################################'+ 00198 '\n##### Begin Task: ' + tname + spaces + ' #####') 00199 casalog.post(scriptstr[1][1:]+'\n', 'INFO') 00200 result = feather(imagename, highres, lowres, sdfactor, effdishdiam, showplot) 00201 casalog.post('##### End Task: ' + tname + ' ' + spaces + ' #####'+ 00202 '\n##########################################') 00203 00204 except Exception, instance: 00205 if(self.__globals__.has_key('__rethrow_casa_exceptions') and self.__globals__['__rethrow_casa_exceptions']) : 00206 raise 00207 else : 00208 #print '**** Error **** ',instance 00209 tname = 'feather' 00210 casalog.post('An error occurred running task '+tname+'.', 'ERROR') 00211 pass 00212 00213 gc.collect() 00214 return result 00215 # 00216 # 00217 # 00218 def paramgui(self, useGlobals=True, ipython_globals=None): 00219 """ 00220 Opens a parameter GUI for this task. If useGlobals is true, then any relevant global parameter settings are used. 00221 """ 00222 import paramgui 00223 if not hasattr(self, "__globals__") or self.__globals__ == None : 00224 self.__globals__=sys._getframe(len(inspect.stack())-1).f_globals 00225 00226 if useGlobals: 00227 if ipython_globals == None: 00228 myf=self.__globals__ 00229 else: 00230 myf=ipython_globals 00231 00232 paramgui.setGlobals(myf) 00233 else: 00234 paramgui.setGlobals({}) 00235 00236 paramgui.runTask('feather', myf['_ip']) 00237 paramgui.setGlobals({}) 00238 00239 # 00240 # 00241 # 00242 def defaults(self, param=None, ipython_globals=None, paramvalue=None, subparam=None): 00243 if not hasattr(self, "__globals__") or self.__globals__ == None : 00244 self.__globals__=sys._getframe(len(inspect.stack())-1).f_globals 00245 if ipython_globals == None: 00246 myf=self.__globals__ 00247 else: 00248 myf=ipython_globals 00249 00250 a = odict() 00251 a['imagename'] = '' 00252 a['highres'] = '' 00253 a['lowres'] = '' 00254 a['sdfactor'] = 1.0 00255 a['effdishdiam'] = -1.0 00256 a['showplot'] = False 00257 00258 a['async']=False 00259 00260 ### This function sets the default values but also will return the list of 00261 ### parameters or the default value of a given parameter 00262 if(param == None): 00263 myf['__set_default_parameters'](a) 00264 elif(param == 'paramkeys'): 00265 return a.keys() 00266 else: 00267 if(paramvalue==None and subparam==None): 00268 if(a.has_key(param)): 00269 return a[param] 00270 else: 00271 return self.itsdefault(param) 00272 else: 00273 retval=a[param] 00274 if(type(a[param])==dict): 00275 for k in range(len(a[param])): 00276 valornotval='value' 00277 if(a[param][k].has_key('notvalue')): 00278 valornotval='notvalue' 00279 if((a[param][k][valornotval])==paramvalue): 00280 retval=a[param][k].copy() 00281 retval.pop(valornotval) 00282 if(subparam != None): 00283 if(retval.has_key(subparam)): 00284 retval=retval[subparam] 00285 else: 00286 retval=self.itsdefault(subparam) 00287 else: 00288 retval=self.itsdefault(subparam) 00289 return retval 00290 00291 00292 # 00293 # 00294 def check_params(self, param=None, value=None, ipython_globals=None): 00295 if ipython_globals == None: 00296 myf=self.__globals__ 00297 else: 00298 myf=ipython_globals 00299 # print 'param:', param, 'value:', value 00300 try : 00301 if str(type(value)) != "<type 'instance'>" : 00302 value0 = value 00303 value = myf['cu'].expandparam(param, value) 00304 matchtype = False 00305 if(type(value) == numpy.ndarray): 00306 if(type(value) == type(value0)): 00307 myf[param] = value.tolist() 00308 else: 00309 #print 'value:', value, 'value0:', value0 00310 #print 'type(value):', type(value), 'type(value0):', type(value0) 00311 myf[param] = value0 00312 if type(value0) != list : 00313 matchtype = True 00314 else : 00315 myf[param] = value 00316 value = myf['cu'].verifyparam({param:value}) 00317 if matchtype: 00318 value = False 00319 except Exception, instance: 00320 #ignore the exception and just return it unchecked 00321 myf[param] = value 00322 return value 00323 # 00324 # 00325 def description(self, key='feather', subkey=None): 00326 desc={'feather': 'Combine two images using their Fourier transforms', 00327 'imagename': 'Name of output feathered image', 00328 'highres': 'Name of high resolution (interferometer) image', 00329 'lowres': 'Name of low resolution (single dish) image', 00330 'sdfactor': 'Scale factor to apply to Single Dish image', 00331 'effdishdiam': 'New effective SingleDish diameter to use in m ', 00332 'showplot': 'Show plot of feather function', 00333 00334 'async': 'If true the taskname must be started using feather(...)' 00335 } 00336 00337 if(desc.has_key(key)) : 00338 return desc[key] 00339 00340 def itsdefault(self, paramname) : 00341 a = {} 00342 a['imagename'] = '' 00343 a['highres'] = '' 00344 a['lowres'] = '' 00345 a['sdfactor'] = 1.0 00346 a['effdishdiam'] = -1.0 00347 a['showplot'] = False 00348 00349 #a = sys._getframe(len(inspect.stack())-1).f_globals 00350 00351 if a.has_key(paramname) : 00352 return a[paramname] 00353 feather_cli = feather_cli_()
1.8.0
