<gh_stars>1-10
import Dynamic_Network_Graph_Exploration_py3 as dynamic
import Data_Cleaning as dc
#import heatmap_functions as heatmap
#import Member_Distribution as dist


'''
So far the main method only includes dynamic network graph functions

Heatmap_functions and Member_Distribution functions to be added 
'''

def main():
    SELECTED_BEACON = 12,
    time_zone = 'US/Eastern'
    log_version = '2.0'
    time_bins_size = '1min'
    members_metadata_filename = "Member-2019-05-28.csv"
    beacons_metadata_filename = "location table.xlsx"
    attendees_metadata_filename = "Badge assignments_Attendees_2019.xlsx"
    data_dir = "../proximity_2019-06-01/"
    
    tmp_m2ms,tmp_m2bs,attendees_metadata,members_metadata= dc.DataCleaning(SELECTED_BEACON,
                                        time_zone,log_version,time_bins_size,
                                        members_metadata_filename,
                                        beacons_metadata_filename,
                                        attendees_metadata_filename,
                                        data_dir)  
    
    
    
    dynamic.NetworkGraphBasicExample('2019-06-01 10:00','2019-06-01 11:20',tmp_m2ms)
    '''
    This function is the code given in the Open Badge Analysis Library 
    '''
    
    dynamic.LunchTimeAnalysis(tmp_m2ms)
    '''
    Find interactive groups during lunch time
    All the parameters in this function are preset 
    '''
    
    dynamic.BreakoutSessionAnalysis(tmp_m2ms)
    '''
    Find interactive groups during breakout session
    All the parameters in this function are preset 
    '''
    
    dynamic.InteractionNetworkGraph(time_interval_start_h=9,time_interval_start_m=50,
                            time_interval_end_h=11,time_interval_end_m=20,
                            interval=2,t_count_threshold = 2,tmp_m2ms=tmp_m2ms)
    '''
    Find interactive groups during any given time with any given parameters 
    The values of the parameters are manually determined by the activities 
    engaged in the time frame given
    '''

if __name__ == "__main__":
    main()
import Dynamic_Network_Graph_Exploration_py3 as dynamic
import Data_Cleaning as dc
#import heatmap_functions as heatmap
#import Member_Distribution as dist


'''
So far the main method only includes dynamic network graph functions

Heatmap_functions and Member_Distribution functions to be added 
'''

def main():
    SELECTED_BEACON = 12,
    time_zone = 'US/Eastern'
    log_version = '2.0'
    time_bins_size = '1min'
    members_metadata_filename = "Member-2019-05-28.csv"
    beacons_metadata_filename = "location table.xlsx"
    attendees_metadata_filename = "Badge assignments_Attendees_2019.xlsx"
    data_dir = "../proximity_2019-06-01/"
    
    tmp_m2ms,tmp_m2bs,attendees_metadata,members_metadata= dc.DataCleaning(SELECTED_BEACON,
                                        time_zone,log_version,time_bins_size,
                                        members_metadata_filename,
                                        beacons_metadata_filename,
                                        attendees_metadata_filename,
                                        data_dir)  
    
    
    
    dynamic.NetworkGraphBasicExample('2019-06-01 10:00','2019-06-01 11:20',tmp_m2ms)
    '''
    This function is the code given in the Open Badge Analysis Library 
    '''
    
    dynamic.LunchTimeAnalysis(tmp_m2ms)
    '''
    Find interactive groups during lunch time
    All the parameters in this function are preset 
    '''
    
    dynamic.BreakoutSessionAnalysis(tmp_m2ms)
    '''
    Find interactive groups during breakout session
    All the parameters in this function are preset 
    '''
    
    dynamic.InteractionNetworkGraph(time_interval_start_h=9,time_interval_start_m=50,
                            time_interval_end_h=11,time_interval_end_m=20,
                            interval=2,t_count_threshold = 2,tmp_m2ms=tmp_m2ms)
    '''
    Find interactive groups during any given time with any given parameters 
    The values of the parameters are manually determined by the activities 
    engaged in the time frame given
    '''

if __name__ == "__main__":
    main()
#import heatmap_functions as heatmap #import Member_Distribution as dist So far the main method only includes dynamic network graph functions
 
 Heatmap_functions and Member_Distribution functions to be added This function is the code given in the Open Badge Analysis Library Find interactive groups during lunch time
     All the parameters in this function are preset Find interactive groups during breakout session
     All the parameters in this function are preset Find interactive groups during any given time with any given parameters 
     The values of the parameters are manually determined by the activities 
     engaged in the time frame given