def seed_method(method,File,stack,outFile,corFile=''): SeedingDone = 'no' next_method = method_default M = stack != 0 if method == 'manual': SeedingDone = seed_manual(File,stack,outFile) if SeedingDone == 'no': next_method = method_default print_warning(next_method) elif method == 'max_coherence': try: SeedingDone = seed_max_coherence(File,M,outFile,corFile) except: SeedingDone = seed_max_coherence(File,M,outFile) if SeedingDone == 'no': next_method = 'random' print_warning(next_method) elif method == 'random': y,x = random_selection(stack) seed_xy(File,x,y,outFile) SeedingDone = 'yes' elif method == 'global_average': print '\n---------------------------------------------------------' print 'Automatically Seeding using Global Spatial Average Value ' print '---------------------------------------------------------' print 'Calculating the global spatial average value for each epoch'+\ ' of all valid pixels ...' box = (0,0,width,length) meanList = ut.spatial_mean(File,M,box) seed_file(File,outFile,meanList,'','') SeedingDone = 'yes' return SeedingDone, next_method
def seed_xy(File,x,y,outName=''): ## Seed Input File with reference on point (y,x) print 'Referencing input file to pixel: (%d, %d)'%(y,x) ##4-tuple defining the left, upper, right, and lower pixel coordinate [optional] box = (x,y,x+1,y+1) ##### IO Info atr = readfile.read_attributes(File) k = atr['FILE_TYPE'] if outName == '': outName = 'Seeded_'+os.path.basename(File) ##### Mask length = int(atr['FILE_LENGTH']) width = int(atr['WIDTH']) mask = np.ones((length,width)) ## Read refernce value refList = ut.spatial_mean(File,mask,box) ## Seeding seed_file(File,outName,refList,x,y) return 1