def tomography_callback(self):
'''
Real image acquisition-routine for tomographd mode.
'''
# parameters
nbr_steps = fg.config['tomo']['steps']+1
fg.config['tomo']['done'] = False
# get update (motor-movement direction)
fg.config['tomo']['direction'] = -1 if fg.config['tomo']['posSTART'] >= fg.config['tomo']['posEND'] else 1
if fg.config['tomo']['posSTART'] == fg.config['tomo']['posEND']:
logger.warning("Start and END-Pos are the same hence the system will take {} images at the same position.".format(nbr_steps))
# iterate through tomography stack
for imnbr in range(fg.config['tomo']['steps']+1):
# actualize global number
fg.config['tomo']['step_number'] = imnbr
# to update measurement numbers indirectly
if imnbr == fg.config['tomo']['steps']:
fg.config['tomo']['done'] = True
# take image with selected method
toolbox.take_image(self)
# move to next position
toolbox.move_motor(self, instance=None, motor_sel=fg.config['tomo']['motor'],
motor_stepsize=fg.config['tomo']['stepsize'])
def autofocus_take_image(self, image_name_template, method):
imvar = 0
mythresh = 0.005 #has to be adjusted again
myc = 0
eps = 0.00001
image_stack = []
imvar_stack = []
# neutralize with prior image to have more averaging? -> NOT IMPLEMENTED
# take again if variance is too small until limit
while (imvar < mythresh or myc == 4):
image = toolbox.take_image(self, 'autofocus', image_name_template)
# normalize image to reside in [0,1]
help_image = image - np.min(image)
help_image[help_image == 0] = eps
help_image /= np.max(help_image)
imvar = np.var(help_image)
myc += 1
image_stack = [
image_stack,
image,
]
imvar_stack = [
imvar_stack,
imvar,
]
# calc_image_quality -> TENENGRAD for now
print("autofocus_take_image -> myc={}".format(myc))
if myc == 4:
image = image_stack[np.argmax(
imvar_stack
)] #note: stack was created as list of arrays! -> so: access array
imqual_res = imqual_metric(image, method=method)
return image, imqual_res