/* Grabs all stored historic and real time data, produce time plots and
also percentages of consistently delayed or early */
func DelayConsistencyPlot(startTime, endTime time.Time, wr io.Writer, templatePath string) {
charts := make([]DelayConsistencyChart, 0)
availableRoutes := selectdb.SelectAvailableRoutesTflPredictions()
for _, route := range availableRoutes {
// Extract fields from routes
line := route["line"]
bound := route["bound"]
fromStop := route["fromStop"]
toStop := route["toStop"]
fromStopName := selectdb.SelectStop(fromStop)
toStopName := selectdb.SelectStop(toStop)
actualJourneyTimes := performanceeval.FetchActualJourneyTimes(line, bound, fromStop, toStop, startTime, endTime)
// Extract the actual departure times for generating predictions later on (discarding those that are)
actualDepartureTimes := make([]time.Time, len(actualJourneyTimes))
actualJourneyTimeDurations := make([]time.Duration, len(actualJourneyTimes))
i := 0
for departureTime, duration := range actualJourneyTimes {
actualDepartureTimes[i] = departureTime
actualJourneyTimeDurations[i] = duration
i++
}
// Fetch Tfl predictions
// tflPredictions := performanceeval.FetchTflJourneyTimes(line, bound, fromStop, toStop, actualDepartureTimes)
/* Cache for real time estimates which can be reused for different prediction methods
map (fromStop => (toStop => (departureTime => "estimate"/"stddev" => int in seconds)))) */
realTimeEstimatesCache := make(map[string]map[string]map[time.Time]map[string]int64)
// Generate predictions using our methods (best historic and real time only)
predictions := make(map[performanceeval.Method]map[time.Time]time.Duration)
predictionsAdjacentStops := make(map[performanceeval.Method]map[time.Time]map[string]map[string]time.Duration)
methods := []performanceeval.Method{
performanceeval.DefaultHistoric(),
performanceeval.DefaultRealTime(),
}
// Highest # consistency possible - number of pairs of adjacent stops in route
maxScore := 0
for _, method := range methods {
predictions[method], predictionsAdjacentStops[method], maxScore = predictJourneyTimesWithDetails(line, bound, fromStop, toStop, actualDepartureTimes, method, realTimeEstimatesCache)
}
// Convert the above into PerformanceTestSeries2
actualJourneyTimesSeries := PerformanceTestSeries2{
SeriesName: "Actual Time",
X: actualDepartureTimes,
Y: actualJourneyTimeDurations,
Count: len(actualJourneyTimeDurations),
}
sort.Sort(actualJourneyTimesSeries)
/*tflPredictionsSeries := mapToPerformanceTestSeries2("Tfl Expected Time", tflPredictions, actualJourneyTimes)
sort.Sort(tflPredictionsSeries)*/
performanceTestSeries2 := []PerformanceTestSeries2{
actualJourneyTimesSeries,
// tflPredictionsSeries,
}
// Add all prediction series into performance test series 2
for method, predictedJouneyTimes := range predictions {
predictionSeries := mapToPerformanceTestSeries2(method.String(), predictedJouneyTimes, actualJourneyTimes)
sort.Sort(predictionSeries)
performanceTestSeries2 = append(performanceTestSeries2, predictionSeries)
}
// Form delay consistency (percentages) series
delayConsistencySeries := getDelayConsistencySeries(predictionsAdjacentStops[performanceeval.DefaultHistoric()],
predictionsAdjacentStops[performanceeval.DefaultRealTime()], maxScore)
charts = append(charts, DelayConsistencyChart{
Line: line,
Bound: bound,
Origin: fromStop,
Destination: toStop,
OriginName: fromStopName,
DestinationName: toStopName,
MultipleSeries: performanceTestSeries2,
MultiplePercentageSeries: []DelayConsistencySeries{delayConsistencySeries},
ServerDomain: credentials.GetGoServerDomain(),
})
logger.GetLogger().Info("Done for line: %v, bound: %v, fromStop: %v, toStop: %v", line, bound, fromStop, toStop)
}
summary := DelayConsistencyPlotSummary{
Methods: performanceeval.Methods(),
Charts: charts,
}
writeDelayConsistencyChart(wr, summary, templatePath)
}
/* Grabs all stored data to produce time plots */
func PerformancePlot2(startTime, endTime time.Time, wr io.Writer, templatePath string) {
charts := make([]PerformanceChart2, 0)
availableRoutes := selectdb.SelectAvailableRoutesTflPredictions()
for _, route := range availableRoutes {
// Extract fields from routes
line := route["line"]
bound := route["bound"]
fromStop := route["fromStop"]
toStop := route["toStop"]
fromStopName := selectdb.SelectStop(fromStop)
toStopName := selectdb.SelectStop(toStop)
actualJourneyTimes := performanceeval.FetchActualJourneyTimes(line, bound, fromStop, toStop, startTime, endTime)
// Extract the actual departure times for generating predictions later on (discarding those that are)
actualDepartureTimes := make([]time.Time, len(actualJourneyTimes))
actualJourneyTimeDurations := make([]time.Duration, len(actualJourneyTimes))
i := 0
for departureTime, duration := range actualJourneyTimes {
actualDepartureTimes[i] = departureTime
actualJourneyTimeDurations[i] = duration
i++
}
// Fetch Tfl predictions
tflPredictions := performanceeval.FetchTflJourneyTimes(line, bound, fromStop, toStop, actualDepartureTimes)
/* Cache for real time estimates which can be reused for different prediction methods
map (fromStop => (toStop => (departureTime => "estimate"/"stddev" => int in seconds)))) */
realTimeEstimatesCache := make(map[string]map[string]map[time.Time]map[string]int64)
// Generate predictions using our methods
predictions := make(map[performanceeval.Method]map[time.Time]time.Duration)
for _, method := range performanceeval.Methods() {
predictions[method] = performanceeval.PredictJourneyTimes(line, bound, fromStop, toStop, actualDepartureTimes, method, realTimeEstimatesCache)
}
// Convert the above into PerformanceTestSeries2
actualJourneyTimesSeries := PerformanceTestSeries2{
SeriesName: "Actual Time",
X: actualDepartureTimes,
Y: actualJourneyTimeDurations,
Count: len(actualJourneyTimeDurations),
}
sort.Sort(actualJourneyTimesSeries)
tflPredictionsSeries := mapToPerformanceTestSeries2("Tfl Expected Time", tflPredictions, actualJourneyTimes)
sort.Sort(tflPredictionsSeries)
performanceTestSeries2 := []PerformanceTestSeries2{
actualJourneyTimesSeries,
tflPredictionsSeries,
}
// Add all prediction series into performance test series 2
for method, predictedJouneyTimes := range predictions {
predictionSeries := mapToPerformanceTestSeries2(method.String(), predictedJouneyTimes, actualJourneyTimes)
sort.Sort(predictionSeries)
performanceTestSeries2 = append(performanceTestSeries2, predictionSeries)
}
charts = append(charts, PerformanceChart2{
Line: line,
Bound: bound,
Origin: fromStop,
Destination: toStop,
OriginName: fromStopName,
DestinationName: toStopName,
MultipleSeries: performanceTestSeries2,
ServerDomain: credentials.GetGoServerDomain(),
})
logger.GetLogger().Info("Done for line: %v, bound: %v, fromStop: %v, toStop: %v", line, bound, fromStop, toStop)
}
summary := PerformancePlotSummary2{
Methods: performanceeval.Methods(),
Charts: charts,
}
writePerformanceChart2(wr, summary, templatePath)
}
