def iterate_ellection_taxon_rank_representatives(self,
current_state,
taxon_rank='species'):
signal.signal(signal.SIGINT, self.signal_handler)
protDB = db_handling.ProteinDatabase()
latest_taxon_id = current_state[5]
taxon_id_list = protDB.get_taxon_ids_by_rank(taxon_rank)
taxon_rank_id_list = []
for taxon_id_tuple in taxon_id_list:
taxon_rank_id_list.append(taxon_id_tuple[0])
start = 0
if latest_taxon_id:
start = taxon_rank_id_list.index(latest_taxon_id)
taxon_rank_id_list = taxon_rank_id_list[start:]
print('ctrl + c will stop the process at appropriate timing')
sys.stdout.write("\n")
bar = Bar(taxon_rank + ' classifications:', max=len(taxon_id_list))
bar.index = start
for taxon_rank_id in taxon_rank_id_list:
bar.next()
not_depleted = True
while not_depleted:
sys.stdout.write("\n")
not_depleted = self.ellect_taxon_rank_representatives_step(
taxon_rank_id, taxon_rank)
sys.stdout.write("\033[F")
sys.stdout.write("\033[F")
if self.stop_process:
sys.exit('\nprocess terminated correctly')
protDB.update_representatives_taxon_id_by_abstence(
taxon_rank_id, taxon_rank)
protDB.update_state(
{'classifications_latest_taxon_id': taxon_rank_id},
taxon_rank),
bar.finish()
def dask_player(video, segmentation, optical_flow):
Cache(2e6).register() # Turn cache on globally
video = cv2.VideoCapture(video)
segmentation = da.from_npy_stack(segmentation)
optical_flow = da.from_npy_stack(optical_flow)
bar = Bar('Frame', max=video.get(cv2.CAP_PROP_FRAME_COUNT))
bar.index = OFFSET
video.set(cv2.CAP_PROP_POS_FRAMES, OFFSET)
while video.isOpened():
video_frame = video.read()[1]
optical_flow_frame = optical_flow[bar.index].compute()
segmentation_frame = segmentation[bar.index].compute()
cv2.imshow('video', video_frame)
cv2.imshow('segmentation', segmentation_frame)
cv2.imshow('optical_flow', visualize_optical_flow(optical_flow_frame))
import pdb
pdb.set_trace()
cv2.waitKey(27)
bar.next()
def compare_sequences_same_taxon_level(self, taxon_rank, current_state):
protDB = db_handling.ProteinDatabase()
paralell = Parallelization()
ncbi = ncbi_taxonomy.NCBITaxa()
latest_taxon_id = current_state[3]
latest_seq_a = current_state[7]
latest_seq_b = current_state[8]
taxon_rank_sequences = protDB.get_sequences_same_taxon_rank(taxon_rank)
max_len = len(taxon_rank_sequences)
start = 0
if latest_taxon_id:
for seq in taxon_rank_sequences:
if seq[2] == latest_taxon_id:
start = taxon_rank_sequences.index(seq)
break
taxon_rank_sequences = taxon_rank_sequences[start:]
print('ctrl + c will stop the process at appropriate timing')
sys.stdout.write("\n")
bar = Bar(taxon_rank + ' comparisons:', max=max_len)
bar.index = start
first_line = True
params_a, params_b, sorted_repres_list, taxon_id = self.populate_parameters_same_taxon_comparisons(
taxon_rank_sequences,
latest_seq_a,
latest_seq_b,
partial=True,
taxon_rank=taxon_rank)
while params_a:
taxon_name = ncbi.get_taxid_translator([taxon_id])[taxon_id]
sys.stdout.write("\n")
sys.stdout.write("\033[K")
bar_taxon = Bar(taxon_rank + ' ' + taxon_name, max=len(params_a))
paralell.parallelize_7(self.perform_needle_comparison,
[params_a, params_b],
log_param=taxon_rank,
bar=bar_taxon,
handle_signal=True)
bar_taxon.finish()
sys.stdout.write("\033[F")
sys.stdout.write("\033[F")
sys.stdout.write("\033[K")
bar.next()
protDB.update_state({'comparisons_latest_taxon_id': taxon_id},
taxon_rank)
params_a, params_b, sorted_repres_list, taxon_id = self.populate_parameters_same_taxon_comparisons(
sorted_repres_list, partial=True, taxon_rank=taxon_rank)
bar.finish()
protDB.assign_identity_paramters_comparisons()
protDB.update_state({'comparisons_done': 1}, taxon_rank)
