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