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)