def dih_event_crop_select(filename1): #get list of related start times shared_times = dih_shared_groups(filename1) meta_file = open(filename1, 'r') meta_lines = meta_file.readlines() all_meta_datalist = [] for member in meta_lines: member = ast.literal_eval(member) all_meta_datalist.append(member) event_list = [] #getting full metadata for each event with time in shared_times for member in shared_times: event = [] for guy in member: for part in all_meta_datalist: if part[0] == guy: event.append(part) break event_list.append(event) uber_shared_list = [] for idx,member in enumerate(event_list): print idx #setting cut_off so program knows to ignore extra long data sets cut_off = timedelta(seconds = dih_event_range(member)) print cut_off shared_list = [] for guy in member: cut_off_time = datetime.strptime(guy[0],'%Y-%m-%dT%H:%M:%S.%f')+cut_off #find peak that corresponds to peak from original event file peak_target = dih_ev_peak_compare(guy[3]+guy[4],guy[10][0]) channel = guy[1] ivo = guy[5] if peak_target < cut_off_time: shared_list.append((datetime.strftime(peak_target,'%Y/%m/%d %H:%M:%S.%f'),channel,ivo)) channel_list = [131,171,211,304,335,193] shared_no_copy_list = [] for idx,channel in enumerate(channel_list): channel_group = [j for j, j in enumerate(shared_list) if j[1] == channel] if len(channel_group)>0: shared_no_copy_list.append(channel_group[0]) else: continue uber_shared_list.append(shared_no_copy_list) return uber_shared_list
def dih_event_select(filename1): #get list of related start times shared_times = dih_shared_groups(filename1) meta_file = open(filename1, 'r') meta_lines = meta_file.readlines() all_meta_datalist = [] for member in meta_lines: member = ast.literal_eval(member) all_meta_datalist.append(member) event_list = [] #getting full metadata for each event with time in shared_times for member in shared_times: event = [] for guy in member: for part in all_meta_datalist: if part[0] == guy: event.append(part) break event_list.append(event) uber_shared_list = [] for idx,member in enumerate(event_list): print idx primary_peaks = [] secondary_peaks = [] #setting cut_off so program knows to ignore extra long data sets cut_off = timedelta(seconds = dih_event_range(member)) print cut_off for guy in member: cut_off_time = datetime.strptime(guy[0],'%Y-%m-%dT%H:%M:%S.%f')+cut_off if guy [7] == 'flag': print 'flag' continue #getting relative peaks for tim in guy[3]: timeval = datetime.strptime(tim,'%Y/%m/%d %H:%M:%S.%f') channel = guy[1] ivo = guy[5] if timeval < cut_off_time: secondary_peaks.append((timeval,channel,ivo)) #getting primary peaks for tim in guy[4]: timeval = datetime.strptime(tim,'%Y/%m/%d %H:%M:%S.%f') channel = guy[1] ivo = guy[5] if timeval < cut_off_time: primary_peaks.append((timeval,channel,ivo)) shared_peak_list = [] #Attempt at removing extra events in every channel (needs to be refined most likely) channel_list = [171,131,211,304,335,193] primary_no_copy_peaks = [] for idx,channel in enumerate(channel_list): channel_group = [j for j, j in enumerate(primary_peaks) if j[1] == channel] if len(channel_group) > 0: primary_no_copy_peaks.append(channel_group[0]) else: continue all_peaks = primary_no_copy_peaks + secondary_peaks #comparing primary peaks to all other peaks in other channels for peak in primary_no_copy_peaks: print peak peak_time = datetime.strftime(peak[0],'%Y/%m/%d %H:%M:%S.%f') sub_peak_list = [(peak_time,peak[1],peak[2])] compare_peaks = [j for j, j in enumerate(all_peaks) if j[1] != peak[1]] compare_list = [] for channel in channel_list: compare_peaks_by_channel = list(set([j for j, j in enumerate(compare_peaks) if j[1] == channel])) compare_list.append(compare_peaks_by_channel) for group in compare_list: compare_times = [] for thing in group: time_diff = peak[0]-thing[0] num_diff = abs(time_diff.total_seconds()) compare_times.append(num_diff) compare_min = [i for i, j in enumerate(compare_times) if j == min(compare_times)] if len(compare_min) == 1: interest = list(group[compare_min[0]]) interest[0] = datetime.strftime(interest[0],'%Y/%m/%d %H:%M:%S.%f') print interest sub_peak_list.append(tuple(interest)) shared_peak_list.append(list(set(tuple(sub_peak_list)))) uber_shared_list.append(shared_peak_list) return uber_shared_list
