vid_start_end = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\vid_real_time\\" #Save_locations ecog_cluster_loc= "E:\\cluster_results_fewer_frequencies2\\" + sbj_id + "\\" extracted_label_loc="C:\\Users\\wangnxr\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_reduced\\" extracted_random_label_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_random\\" label_accuracy_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation_fewer_frequencies\\" + sbj_id + "\\" back_project_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\back_project_fewer_frequencies\\" #Internal_save_variables best_corr_clusters=[] #Generate clusters print "Starting: Clustering" truncated_hier_cluster.hier_cluster_main(sbj_id,dates,ecog_feature_loc,ecog_cluster_loc) print "Finished: Clustering" # #Plot Clusters # # # font = {'family' : 'serif', # 'size' : 15} # # matplotlib.rc('font', **font) # # time_s = time(9,0,0) # day = date(2015,6,11) # start_time = datetime.combine(day, time_s) # for lev in [2]: # f, plots=plt.subplots(1) # f.set_size_inches(20.5, 10.5)
#Save_locations ecog_cluster_loc = "E:\\cluster_results\\" + sbj_id + "\\" extracted_label_loc = "C:\\Users\\wangnxr\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_reduced\\" extracted_random_label_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_random\\" label_accuracy_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" + sbj_id + "\\" back_project_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\back_project\\" #Internal_save_variables best_corr_clusters = [] #Generate clusters print "Starting: Clustering" truncated_hier_cluster.hier_cluster_main(sbj_id, dates, ecog_feature_loc, ecog_cluster_loc, type="high_freq") print "Finished: Clustering" # #Plot Clusters # # # font = {'family' : 'serif', # 'size' : 15} # # matplotlib.rc('font', **font) # # time_s = time(9,0,0) # day = date(2015,6,11) # start_time = datetime.combine(day, time_s) # for lev in [2]:
vid_start_end = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\vid_real_time\\" #Save_locations ecog_cluster_loc= "E:\\cluster_results\\" + sbj_id + "\\" extracted_label_loc="C:\\Users\\wangnxr\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_reduced\\" extracted_random_label_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_random\\" label_accuracy_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation\\" + sbj_id + "\\" back_project_loc="C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\back_project\\" #Internal_save_variables best_corr_clusters=[] #Generate clusters print "Starting: Clustering" truncated_hier_cluster.hier_cluster_main(sbj_id,dates,ecog_feature_loc,ecog_cluster_loc, type="high_freq") print "Finished: Clustering" # #Plot Clusters # # # font = {'family' : 'serif', # 'size' : 15} # # matplotlib.rc('font', **font) # # time_s = time(9,0,0) # day = date(2015,6,11) # start_time = datetime.combine(day, time_s) # for lev in [2]: # f, plots=plt.subplots(1) # f.set_size_inches(20.5, 10.5)
vid_start_end = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\vid_real_time\\" #Save_locations ecog_cluster_loc = "E:\\cluster_results_fewer_frequencies2\\" + sbj_id + "\\" extracted_label_loc = "C:\\Users\\wangnxr\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_reduced\\" extracted_random_label_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\manual_annotations\\extracted_labels_random\\" label_accuracy_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\validation_fewer_frequencies\\" + sbj_id + "\\" back_project_loc = "C:\\Users\\wangnxr\\Documents\\rao_lab\\video_analysis\\back_project_fewer_frequencies\\" #Internal_save_variables best_corr_clusters = [] #Generate clusters print "Starting: Clustering" truncated_hier_cluster.hier_cluster_main(sbj_id, dates, ecog_feature_loc, ecog_cluster_loc) print "Finished: Clustering" # #Plot Clusters # # # font = {'family' : 'serif', # 'size' : 15} # # matplotlib.rc('font', **font) # # time_s = time(9,0,0) # day = date(2015,6,11) # start_time = datetime.combine(day, time_s) # for lev in [2]: # f, plots=plt.subplots(1) # f.set_size_inches(20.5, 10.5)