for s, sbj_id in enumerate(sbj_id_all): consistency_date = [] dates = dates_all[s] video_loc = "D:\\NancyStudyData\\ecog\\raw\\" + sbj_id + "\\" label_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\manual_annotations\\tracks\\" #Save_locations extracted_label_loc = "C:\\Users\\wangnxr\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_reduced\\" label_accuracy_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" + sbj_id + "\\" label_consistency_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" for date in dates: automated_label_loc = "E:\\sound\\" + sbj_id + "\\" + str(date) + "\\" #automated_label_loc="E:\\mvmt\\" + sbj_id + "\\" consistency_file = [] extract_labeller_reduced_labels(sbj_id, date, label_loc, video_loc, extracted_label_loc, 'sk') for file in glob.glob(extracted_label_loc + "\\" + sbj_id + "_" + str(date) + "_*_" + 'sk' + ".p"): filename = file.split("\\")[-1] name, ext = file.split(".") filenum = file.split("_")[-2] if os.path.isfile(automated_label_loc + sbj_id + "_" + str(date) + "_" + filenum + ".p"): auto_label_temp = pickle.load( open( automated_label_loc + sbj_id + "_" + str(date) + "_" + filenum + ".p", "rb")) #plt.plot(auto_label_temp) #plt.show() #print filename labels1 = pickle.load(open(file, "rb"))
label_num=0 consistency_all = [] for s, sbj_id in enumerate(sbj_id_all): consistency_date=[] dates=dates_all[s] video_loc="D:\\NancyStudyData\\ecog\\raw\\" + sbj_id + "\\" label_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\manual_annotations\\tracks\\" #Save_locations extracted_label_loc="C:\\Users\\wangnxr\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_reduced\\" label_accuracy_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" + sbj_id + "\\" label_consistency_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" for date in dates: consistency_file=[] extract_labeller_reduced_labels(sbj_id, date, label_loc, video_loc, extracted_label_loc, labellers[0]) extract_labeller_reduced_labels(sbj_id, date, label_loc, video_loc, extracted_label_loc, labellers[1]) for file in glob.glob(extracted_label_loc + "\\" + sbj_id + "_" + str(date) + "_*_" + labellers[0] + ".p"): filename = file.split("\\")[-1] name, ext = file.split(".") filenum = file.split("_")[-2] file_alt = (extracted_label_loc + "\\" + sbj_id + "_" + str(date) + "_" + filenum + "_" + labellers[1] + ".p") if os.path.exists(file_alt): labels1 = pickle.load(open(file, "rb")) labels2 = pickle.load(open(file_alt, "rb")) accuracy_mat = np.zeros(len(labels1["labels_array"])) for l in xrange(len(labels1["labels_array"])): correct = np.where(labels1["labels_array"][l]==labels2["labels_array"][l])[0].shape[0] label1_yes += np.where(labels1["labels_array"][l]==1)[0].shape[0] label2_yes += np.where(labels2["labels_array"][l]==1)[0].shape[0]
for s, sbj_id in enumerate(sbj_id_all): consistency_date=[] dates=dates_all[s] video_loc="D:\\NancyStudyData\\ecog\\raw\\" + sbj_id + "\\" label_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\manual_annotations\\tracks\\" #Save_locations extracted_label_loc="C:\\Users\\wangnxr\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_reduced\\" label_accuracy_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" + sbj_id + "\\" label_consistency_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" for date in dates: automated_label_loc="E:\\sound\\" + sbj_id + "\\" + str(date) + "\\" #automated_label_loc="E:\\mvmt\\" + sbj_id + "\\" consistency_file=[] extract_labeller_reduced_labels(sbj_id, date, label_loc, video_loc, extracted_label_loc, 'sk') for file in glob.glob(extracted_label_loc + "\\" + sbj_id + "_" + str(date) + "_*_" + 'sk' + ".p"): filename = file.split("\\")[-1] name, ext = file.split(".") filenum = file.split("_")[-2] if os.path.isfile(automated_label_loc + sbj_id + "_" + str(date) + "_" + filenum + ".p"): auto_label_temp = pickle.load(open(automated_label_loc + sbj_id + "_" + str(date) + "_" + filenum + ".p", "rb")) #plt.plot(auto_label_temp) #plt.show() #print filename labels1 = pickle.load(open(file, "rb")) l = labels1["tracks"].index(type) o = labels1["tracks"].index("Other") auto_label = np.zeros(len(labels1["labels_array"][l])) for i in xrange(len(auto_label)): if np.where(auto_label_temp[(i-1)*sr:(i+2)*sr] > threshold)[0].shape[0] > 30: