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Version: 1.0
Date: 15.04.2021
Authors: Ľuboš Buzna; Milan Straka
Address: University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia
The "tsp-fc" feature collector is a module of the Ride2Rail Offer Categorizer responsible for the computation of the following determinant factors: "cleanliness", "space_available", "ride_smoothness", "seating_quality", "internet_availability", "plugs_or_charging_points", "silence_area_presence", "privacy_level and "business_area_presence".
Computation can be executed from "tsp.py" by running the procedure extract() which is binded under the name compute with URL using FLASK (see example request below). Computation is composed of three phases:
Phase I: Extraction of data required by tsp-fc feature collector from the cache. A dedicated procedure defined for this purpose from the unit "cache_operations.py" is utilized.
Phase II: Computation of weights assigned to "tsp-fc" feature collector. For the aggregation of data at the tripleg level and for normalization of weights a dedicated procedure implemented in the unit "normalization.py" are utilized. By default "z-scores" are used to normalize data.
Phase III: Storing of the results produced by "tsp-fc" to cache. A dedicated procedure defined for this purpose in the unit "cache_operations.py" is utilized.
The following values of parameters can be defined in the configuration file "tsp.conf".
Section "running":
- "verbose" - if value "1" is used, then feature collector is run in the verbose mode,
- "scores" - if value "minmax_score" is used, the minmax approach is used for normalization of weights, otherwise, the "z-score" approach is used.
Section "cache":
- "host" - host address where the cache service that should be accessed by "tsp-fc" feature collector is available
- "port" - port number where the cache service that should be accessed used by "tsp-fc" feature collector is available
Example of the configuration file "tsp.conf":
[service]
name = tsp
type = feature collector
developed_by = Lubos Buzna <lubos(dot)buzna(at)fri(dot)uniza(dot)sk> and Milan Straka<milan(dot)straka(at)fri(dot)uniza(dot)sk>
[running]
verbose = 1
scores = z_scores
[cache]
host = cache
port = 6379
$ python3 tsp.py
* Serving Flask app "price" (lazy loading)
* Environment: development
* Debug mode: on
$ curl --header 'Content-Type: application/json' \
--request POST \
--data '{"request_id": "123x" }' \
http://localhost:5001/compute