Example #1
0
    n = len(ids)
    m = len(freq_pat)
    count = np.zeros((n, m))
     
 
    for i in range(n):
        for seq in seqs_by_subject[i]:
            # print subject i daily sequences
            if i == 1:
                print ','.join(seq)
                
            for j, (pat,f) in enumerate(freq_pat):
                if pat in ','.join(seq):
                    count[i, j] += 1
          
    print count  
    
    print n, m
    print count[1]  
    print count[:, 0:7]

    ## write the first 7 frequent patterns to csv
    for j, (pat,f) in enumerate(freq_pat[:2]):
        id_feature = {}
        feature = count[:, j]
        #print feature
        for i, id in enumerate(ids):
            id_feature[id] = feature[i]
        feature_name = "fp_test_" + pat.replace(',',';')
        write_feature_to_csv(feature_name, id_feature)
        
Example #2
0
        if len(complete) < 30:
            continue
        
        print 
        print 'subject id: ' + id
        

        sample_days = complete[:30]
        
#         seqs = per_subject_by_weekdays(fp, sample_days)
#         result = get_weekday_sum_avg_edit_dist(seqs)
        
        seqs = per_subject(fp, sample_days, by_complete_dates)
        #pprint(seqs)
        result = get_avg_edit_dist(seqs)

        id_feature[id] = result
    return id_feature


    
    
if __name__ == '__main__':
#     fp = os.path.join(cur_dir, 'data', 'gps_osm', 'wifigps_addr_04.csv')
#     per_subject_by_weekdays(fp)
    
    #all_subjects_plot()
    id_edit_dist = get_feature()
    write_feature_to_csv('gps_edit_dist', id_edit_dist)

    
Example #3
0
        id_feature[id] = result
        
    return id_feature
        
    


if __name__ == '__main__':  


#     fp = r'data\by subjects\wifigps_subject08.csv'
#     get_avg_edit_dist(fp)
    

    id_edit_dist = get_feature()
    write_feature_to_csv('len_diff', id_edit_dist)
    #write_raw_feature_to_csv('len_diff', id_edit_dist)

    
    
    
    
    
    
    
    
    
    
    
    
    
        id_feature[id] = result
        
    return id_feature
        
    


if __name__ == '__main__':  


#     fp = r'data\by subjects\wifigps_subject08.csv'
#     get_avg_edit_dist(fp)
    

    feature = get_feature()
    write_feature_to_csv('num_pattern', feature)