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)