allen_sec_begin, allen_sec_end = allen_sec_range[stack_id]
delta = allen_sec_end - allen_sec_begin
initial_allen_sec = int(allen_sec_begin + float(sec_num) / nsection * delta)
initial_allen_sec_index = argmin(abs(array(allen_secs) - initial_allen_sec))
initial_allen_sec = allen_secs[initial_allen_sec_index]
print 'initial_allen_sec:', initial_allen_sec
test_sections = allen_secs[max(0, initial_allen_sec_index - 10):min(initial_allen_sec_index + 10, len(allen_secs))]
print 'test_sections:', test_sections
image_from_name = '{0}_{1}.tif'.format(stack_id, sec_num)
image_from_fullname = SECTION_FOLDER + str(stack_id) + '/' + image_from_name
matchings, test_sections = \
util.conditional_load(image_from_name[:-4] + '_matchings', \
allen.get_allen_matching_multisections, \
(image_from_fullname, dataset_id, test_sections), \
regenerate=False, append_obj=test_sections)
# quit()
err_list = [m[-1] if m is not None else inf for m in matchings]
print 'err_list:', err_list
best_section = test_sections[argmin(err_list)]
print 'best_section:', best_section
chosen_secs_idx = [i for i, m in enumerate(matchings) if m is not None and m[-1] < RELEVANCY_THRESH]
chosen_secs = [test_sections[i] for i in chosen_secs_idx]
print 'chosen_secs:', chosen_secs
query_keypoints = [matchings[i][1] for i in chosen_secs_idx]
query_descriptors = [matchings[i][2] for i in chosen_secs_idx]
allen_keypoints = [matchings[i][3] for i in chosen_secs_idx]
import time
begin = time.time()
nsections = {3:0, 4:40, 5:32, 6:34, 9:28, 10:80}
stack_id = 4
nsection = nsections[stack_id]
start_sec = 0
# stack_id = 10
# nsection = 50
# start_sec = 30
sections = range(start_sec, start_sec + nsection)
d = util.conditional_load('_'.join(['d', 'stack',str(stack_id), 'start', str(start_sec)]), \
detect_keypoints, (stack_id, sections), regenerate=True)
A, err, skip = util.conditional_load('_'.join(['A', 'model', str(MODEL), 'stack', str(stack_id),\
'start', str(start_sec)]), \
find_transforms, [d], regenerate=True)
print 'skipped:', skip
# k = 5; sift.draw_registration(ims[k], H[k][:2, :], ims[0])
H, ims_reg = accumulate_transforms(d, A,reverse=False)
print time.time() - begin
# util.Plotter('Stack '+str(stack_id), ims_reg, 0)
