#About Mini project voor de statistische analyse van fnw-enquetes

#Usage

required input data

###knoopbase csv format file to the data of the knopen in the network

###linkbase csv format file to the data of the links in the network

###enquete data csv format file to the data of the obtained questionaires to be processed

example

nodejs input -t FIETS -n 247 data/enq/your-datafile.csv

This will process the data assuming the context:

• type == FIETS
• on network with id 247
• location of the data of the questionaire is in data/enq/your-datafile.csv

switches

• -b: ignore specific network id (be blind for network focus) --blind
• -t: type of network (default FIETS) --type {FIETS|WANDEL}
• -r: laat recovery toe in de positionering (default off) --enable-recovery
• -n: network id (default 126) --net {networkid}
• -o: output directory for data (default /tmp/kcfnw) --output {path-to-directory}
• -l: linkbase location (default ./data/base/linkbase.csv) --linkbase {path-to-linkbase.csv}
• -k: knoopbase location (default ./data/base/knoopbase.csv) --knoopbase {path-to-knoopbase.csv}
• argument: questionaire data location (required argument) {path-to-data-of-questionaire}

#How this works

• Base data is read from csv. This is building up the network-graph from the knoopbase and linkbase files
• Lijn-data is read from the questionaire csv file and then processed line per line. This processing takes these steps:
  • positioning: try to match the sequence of followed knopen to
  • counting:
    • for the found matching traces with unique results we actually count link by link its presence in the questionaire
    • additionally we calculate the statistics of
  • output set: csv output of the found counts and stats
    • base analysis
      • base-usage-links.csv double usage of link-nrs --> count per unique id of each
      • base-usage-knopen.csv usage of knopen-nrs, adding min-dist and location between double used knopen
    • questionaire results
      • result-overview.csv: metadata of lines processed, traces found etc etc
      • result-lines.csv: line by line - count of links and accumulated distance
      • result-traveled-links.csv: link by link - count of usage (leaving out the zero's)
  • plotting: the datasets on the map (kml for each csv described)