def simulate(scene):
"""Sweep the scene."""
last_step_coarse = True
f_cur, f_prev, f_prev2 = scene.get_focus_values([0, 0, 0])
position = 1
output = []
while position < scene.step_count:
f_prev2, f_prev, f_cur = f_prev, f_cur, scene.fvalues[position]
if last_step_coarse:
step_coarse = coarsefine.coarse_if_previously_coarse(
f_prev2, f_prev, f_cur)
else:
step_coarse = coarsefine.coarse_if_previously_fine(
f_prev2, f_prev, f_cur)
if step_coarse:
output.append((position, 0))
position += 8
else:
output.append((position, 1))
position += 1
last_step_coarse = step_coarse
return output
def search_sweep(scenes, always_coarse):
print ("Search for a peak by sweeping from the first lens position, stop\n"
"when a peak is found.")
if always_coarse:
print "Sweeping is done with coarse steps only."
else:
print "Sweeping is done using ml-based heuristics."
data_rows = [("filename", "status", "steps")]
for scene in scenes:
last_step_coarse = True
max_val = scene.fvalues[0]
f_cur, f_prev, f_prev2 = scene.get_focus_values([0, 0, 0])
current_pos = 1
step_count = 1
# Sweep in search of a maxima.
while current_pos < scene.step_count - 1:
# Size of the next step.
if always_coarse:
step_coarse = True
else:
f_prev2, f_prev, f_cur = \
f_prev, f_cur, scene.fvalues[current_pos]
# Decide on size of the next step using the right decision tree
if last_step_coarse:
step_coarse = coarsefine.coarse_if_previously_coarse(
f_prev2, f_prev, f_cur)
else:
step_coarse = coarsefine.coarse_if_previously_fine(
f_prev2, f_prev, f_cur)
if step_coarse:
current_pos = min(scene.step_count - 1, current_pos + 8)
else:
current_pos = min(scene.step_count - 1, current_pos + 1)
step_count += 1
max_val = max(max_val, scene.fvalues[current_pos])
if scene.fvalues[current_pos] < 0.7 * max_val:
break
last_step_coarse = step_coarse
# Go back to peak using local search hillclimbing.
while current_pos > 0:
if scene.fvalues[current_pos] < scene.fvalues[current_pos - 1]:
current_pos -= 1
step_count += 1
elif (current_pos > 1 and
scene.fvalues[current_pos] < scene.fvalues[current_pos - 2]):
# Tolerance of two fine steps.
current_pos -= 2
step_count += 2
else:
# Number of steps to move forward and back,
# due to two step tolerance
step_count += 4
break
first_column = "%s (%d)" % (scene.filename, len(scene.maxima))
if scene.distance_to_closest_peak(current_pos) < 1:
if scene.distance_to_highest_peak(current_pos) <= 1:
line = (first_column, "found highest", str(step_count))
else:
line = (first_column, "found a peak", str(step_count))
else:
line = (first_column, "failed", str(step_count))
data_rows.append(line)
print_aligned_data_rows(data_rows)
