import graphs
import read_write as rw
import non_linear_measures as nlm
import classification_functions as cl
output_folder = "/home/ubuntu/Documents/Thesis_work/results/19_oct_results/non_linear/sodp_analysis/afib_normal_data_generation/filtered_patient_afpdb_plot/quo_filt_patient_afpdb/"
db_name = "afpdb"
initial_rec_array = []
rec_name_array = []
annotator_array = []
wo_continuation_recs = []
recs_to_remove = ['n24', 'n27', 'n28']
annotator_array = ws.dload_annotator_names(db_name)
for ann_name in annotator_array:
print ann_name
if ann_name == "qrs":
annotation = ann_name
if ann_name == "atr":
annotation = ann_name
print("annotators for this database are: " + str(annotator_array) +
" we are choosing " + str(annotation))
initial_rec_array = ws.dload_rec_names(db_name)
wo_continuation_recs = ws.rmv_continuation_rec(initial_rec_array)
rec_name_array = ws.rmv_test_rec(wo_continuation_recs)
#rec_name_array=ws.rmv_even_rec(wo_continuation_recs)
print str(rec_name_array)
import classification_functions as cl
import process_ecg as pecg
output_folder = "/home/ubuntu/Documents/Thesis_work/results/thesis_images/chapter_5/"
db_name = "afpdb"
initial_rec_array = []
rec_name_array = []
annotator_array = []
wo_continuation_recs = []
# recs_to_remove=['n24','n27','n28'];
annotator_array = ws.dload_annotator_names(db_name)
for ann_name in annotator_array:
print ann_name
if ann_name == "atr":
annotation = ann_name
elif ann_name == "qrs":
annotation = ann_name
elif ann_name == "ecg":
annotation = ann_name
# if db_name == 'afdb':
# annotation='atr'
print ("annotators for this database are: " + str(annotator_array) + " we are choosing " + str(annotation))
initial_rec_array = ws.dload_rec_names(db_name)