rms = np.sqrt(np.mean(arr[mask==1]**2))
arr.tofile(unwrapped_file,format='%f')
arr.resize(int(xsize),int(ysize))
mask.resize(int(xsize),int(ysize))
# Saves surface image
toimage(arr).save(image_file)
return (filename+','+str(rms))
if __name__ == '__main__':
# Get path
path = diropenbox('Pick directory to process',default=r'd:\phase')
path = win32api.GetShortPathName(path)
path_raw, path_images, filenames = get_path(path, filetype = 'unwrapped')
algorithm_exe = fileopenbox('Pick algorithm exe to use',default=r'd:\phase')
'''
# Check if qual or mcut, both require mode to be choosen
arg =''
algorithm_exe = fileopenbox('Pick algorithm exe to use',default=r'd:\phase')
if re.search('mcut',algorithm_exe) or re.search('qual',algorithm_exe):
mode = choicebox('mcut and qual need a mode, choose mode below','Choose mode',\
['min_grad','min_var','max_corr', 'max_pseu'])
arg = ' -mode '+mode
'''
# Setup dimensions of array from %path%/debug.csv in col x row format
xsize, ysize, data = unwrap_setup(path)
# Setup mask
from multiprocessing import Pool
#from Tkinter import *
# TFI
from calc_phase import calc_phase
from mask import get_mask
from wrapped_phase import get_phase, get_path
if __name__ == '__main__':
#path = diropenbox('Pick directory to process',default=r'c:\phase')
path = r'C:\Users\jsaredy\Desktop\4 1_20130710'
path = r'C:\Users\jsaredy\Desktop\run3'
path_raw, path_images, filenames = get_path(path, 'h5')
first_file = os.path.join(path,filenames[0])
mask,coord = get_mask(first_file, border=2)
mask = mask[coord[0]:coord[1],coord[2]:coord[3]]
#coord [0] = x_min, [1] = x_max, [2] = y_min, [3] = y_max
deb = ''
#for filename in filenames:
# deb = get_phase(filename, path, path_raw, path_images, mask, coord, deb)
pool = Pool()
A=[]
for filename in filenames:
A.append((filename, path, path_raw, path_images, mask, coord))
zz = time.clock()
imap1 = pool.imap(get_phase,A)
#imap1 = map(get_phase,A)
