def __init__(self):
# set working directory
abspath = os.path.abspath(__file__)
dname = os.path.dirname(abspath)
os.chdir(dname)
print('Current directory: ' + subprocess.check_output('pwd').decode("utf-8"))
# setting up motors
print('Initializing motors')
ports = faulhaber_port_numbers()
self.motors = Motors(ports)
# seting up camera
print('Initializing camera')
self.camera = Camera(
starting_exposure = 2745,
color_mode = ids.ids_core.COLOR_BAYER_16
)
# setting up arduino communication
print('Initializing arduino connection')
#self.arduino_conn = arduino_connection()
self.cluster_size_threshold = 1000
self.by_size = False
self.nominal_laser_intensity = 41
self.correct_for_laser = True
print('Initializing mologram position control')
self.chip = Chip(self.motors)
print('Done')
print('System booted normally')
class Setup:
def __init__(self):
# set working directory
abspath = os.path.abspath(__file__)
dname = os.path.dirname(abspath)
os.chdir(dname)
print('Current directory: ' + subprocess.check_output('pwd').decode("utf-8"))
# setting up motors
print('Initializing motors')
ports = faulhaber_port_numbers()
self.motors = Motors(ports)
# seting up camera
print('Initializing camera')
self.camera = Camera(
starting_exposure = 2745,
color_mode = ids.ids_core.COLOR_BAYER_16
)
# setting up arduino communication
print('Initializing arduino connection')
#self.arduino_conn = arduino_connection()
self.cluster_size_threshold = 1000
self.by_size = False
self.nominal_laser_intensity = 41
self.correct_for_laser = True
print('Initializing mologram position control')
self.chip = Chip(self.motors)
print('Done')
print('System booted normally')
def photodiode_intensity(self):
val = self.arduino_conn.read()
val = ord(val)
return val
def calib(self):
self.motors.calib()
self.chip.move_to('B,1,1')
def binary_search(
self,
increment,
evaluate,
starting_step,
final_step,
starting_direction,
condition,
max_difference
):
# initialize search parameters
step = starting_step
direction = starting_direction
new_score, old_score, i = 0,0,0
# divide
while (abs(step) > final_step):
# initialize score
old_score = evaluate()
increment(direction*step)
new_score = evaluate()
print('Exposure: ' + str(self.camera.exposure) + ', step: ' + str(step))
print('New score: ' + str(new_score) + ', old score: ' + str(old_score))
# keep incrementing until reach a local extrema
while condition(old_score,new_score,direction,step):
increment(direction*step)
old_score = new_score
new_score = evaluate()
buffer_length = 3
for i in range(buffer_length-1):
new_scores[i] = old_scores[i+1]
new_scores[buffer_length-1] = new_score
print('Exposure: ' + str(self.camera.exposure) + ', step: ' + str(step))
print('New score: ' + str(new_score) + ', old score: ' + str(old_score))
# update search parameters
step *= 0.5
direction *= -1
i += 1
if i > 100:
return
def max_pixel(self):
num_pixels = 50
buffer_length = 5
values = np.empty(buffer_length)
for i in range(buffer_length):
img,retval = self.camera.get_raw_img()
values[i] = np.mean(heapq.nlargest(num_pixels, img.flatten()))
#values[i] = np.max(img.flatten())
value = np.mean(values)
return value
def adjust_exposure(self):
saturation_value = 255
margin = 1
final_step = 0.5
max_difference = 5
# condition = lambda old_score,new_score,direction: \
# (new_score >= old_score - margin) and not(new_score == 255 and direction == 1)
condition = lambda old_score,new_score,direction,step: \
(((new_score < saturation_value/2) and (direction == 1)) or \
((new_score > saturation_value/2) and (direction == -1))) and \
(abs(step) > final_step)
self.binary_search(
increment = lambda x: self.camera.set_exposure(self.camera.exposure + x),
evaluate = lambda: self.mologram_intensity(avg = True)[0],
starting_step = 64,
final_step = final_step,
starting_direction = -1,
condition = condition,
max_difference = 5
)
def adjust_focus(self):
saturation_value = 255
margin = 20000
max_difference = 5000
final_step = 1
starting_step = 40
evaluate = lambda: processing.image_score(self.camera.get_raw_img()[0])
increment = lambda x: self.motors.z.move_um(x)
init_eval = evaluate()
condition = lambda old_score,new_score,direction,step: \
(new_score <= old_score + margin) #and \
#((direction == 1) and (new_score >= saturation_value))
self.binary_search(
increment = increment,
evaluate = evaluate,
starting_step = starting_step,
final_step = final_step,
starting_direction = 1,
condition = condition,
max_difference = max_difference
)
if evaluate() < init_eval:
self.binary_search(
increment = increment,
evaluate = evaluate,
starting_step = starting_step,
final_step = final_step,
starting_direction = -1,
condition = condition,
max_difference = max_difference
)
def adjust_coupling(self):
saturation_value = 255
margin = 5
condition = lambda old_score,new_score,direction,step: \
(new_score >= old_score - margin) and \
((direction == 1) and (new_score >= saturation_value))
self.binary_search(
increment = lambda x: self.motors.TE.move_degrees(x),
evaluate = lambda: self.mologram_intensity(avg = True)[0],
starting_step = 0.1,
final_step = 0.01,
starting_direction = 1,
condition = condition,
max_difference = 1
)