Mercurial Hosting > traffic-intelligence
changeset 1062:a2e20aba0740
bug correctiong
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Thu, 12 Jul 2018 00:22:16 -0400 |
| parents | 671426ce0f3e |
| children | 3c37d8d20e97 |
| files | scripts/process.py |
| diffstat | 1 files changed, 2 insertions(+), 2 deletions(-) [+] |
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--- a/scripts/process.py Wed Jul 11 17:31:26 2018 -0400 +++ b/scripts/process.py Thu Jul 12 00:22:16 2018 -0400 @@ -214,7 +214,7 @@ # aggregation per site data = [] # list of observation per site-user with time headers = ['site', 'date', 'time', 'user_type'] - aggFunctions, tmpheaders = utils.aggregationMethods(arg.aggMethods, args.aggCentiles) + aggFunctions, tmpheaders = utils.aggregationMethods(args.aggMethods, args.aggCentiles) headers.extend(tmpheaders) for vs in videoSequences: d = vs.startTime.date() @@ -276,7 +276,7 @@ plt.savefig(events.Interaction.indicatorNames[i]+'.png', dpi=150) plt.close() -if args.analyze == 'event': # aggregate event data by 15 min interval (arg.intervalDuration), count events with thresholds +if args.analyze == 'event': # aggregate event data by 15 min interval (args.intervalDuration), count events with thresholds data = pd.read_csv(args.eventFilename, parse_dates = [2]) #data = pd.read_csv('./speeds.csv', converters = {'time': lambda s: datetime.datetime.strptime(s, "%H:%M:%S").time()}, nrows = 5000) # create time for end of each 15 min, then group by, using the agg method for each data column