// Create the summary statistics strings.
func createStats(toEnglish bool, DispDistance []float64, TimeStamps []int64,
LapCal []float64) (totalDistance string, totalPace string,
elapsedTime string, totalCal string, avgPower string, startDateStamp string,
endDateStamp string) {
// Calculate run start and end times.
startDateStamp = time.Unix(TimeStamps[0], 0).Format(time.UnixDate)
endDateStamp = time.Unix(TimeStamps[len(TimeStamps)-1], 0).Format(time.UnixDate)
// Calculate overall distance.
totalDistance = strconv.FormatFloat(DispDistance[len(DispDistance)-1], 'f', 2, 64)
if toEnglish {
totalDistance += " mi"
} else {
totalDistance += " km"
}
// Calculate mm:ss for totalPace.
timeDiffinMinutes := (float64(TimeStamps[len(TimeStamps)-1]) - float64(TimeStamps[0])) / 60.0
decimalPace := float64(timeDiffinMinutes) / DispDistance[len(DispDistance)-1]
totalPace = strutil.DecimalTimetoMinSec(decimalPace)
if toEnglish {
totalPace += " min/mi"
} else {
totalPace += " min/km"
}
// Calculate hh:mm:ss for elapsedTime.
elapsedTime = strutil.DecimalTimetoHourMinSec(float64(timeDiffinMinutes))
// Sum up the lap calories
totcal := 0.0
for _, calorie := range LapCal {
totcal += calorie
}
totalCal = strconv.Itoa(int((math.Floor(totcal)))) + " kcal"
// Calculate power expended based on Garmin calculated calories
power := totcal * 4186.8 / (timeDiffinMinutes * 60.0)
avgPower = strconv.FormatFloat(power, 'f', 2, 64) + " Watts"
return
}
// Do a prediction based on this run.
func createAnalysis(toEnglish bool,
useSegment bool,
DispDistance []float64,
TimeStamps []int64,
splitdist float64,
splithours, splitmins, splitsecs int64,
racedist float64,
racehours, racemins, racesecs int64,
) (PredictedRaceTimes map[string]string,
VDOT float64,
VO2Max float64,
RunScore float64,
TrainingPaces map[string]string) {
// Need to assign variables based on whether the user has selected the entire
// run or just a run segment (e.g. a split time and distance) to basis the
// prediction on.
// Do the type conversions to get the inputs into forms expected by PredictRaces.
var d, dist, tStart, tEnd, elapsedTime float64
if useSegment != true {
d = DispDistance[len(DispDistance)-1]
// Need distance back in meters as PredictRaces demands metric units.
if toEnglish {
dist = d / metersToMiles
} else {
dist = d / metersToKm
}
tStart = float64(TimeStamps[0])
tEnd = float64(TimeStamps[len(TimeStamps)-1])
elapsedTime = (tEnd - tStart) / 60.0
} else {
dist = splitdist
elapsedTime = (float64(splithours) * 60.0) + float64(splitmins) + (float64(splitsecs) / 60.0)
}
// Calculate the equivalent race times for this run (segment or complete).
PredictedTimes, v, _ := predict.PredictRaces(dist, elapsedTime)
VDOT = v
// Calculate the % of VO2max for this run relative to the provided race information.
elapsedTimeRace := (float64(racehours) * 60.0) + float64(racemins) + (float64(racesecs) / 60.0)
velocityRace := racedist / elapsedTimeRace
VO2Max = predict.CalcVO2max(velocityRace, elapsedTimeRace)
RunScore = VDOT / VO2Max * 100.0
// Calculate the training paces.
easyPace, maraPace, thresholdPace, intervalPace, repPace := predict.TrainingPaces(VO2Max)
TrainingPaces = make(map[string]string)
if toEnglish {
easyPace = 1609.34 / easyPace
maraPace = 1609.34 / maraPace
thresholdPace = 1609.34 / thresholdPace
intervalPace = 1609.34 / intervalPace
repPace = 1609.34 / repPace
} else {
easyPace = 1000.0 / easyPace
maraPace = 1000.0 / maraPace
thresholdPace = 1000.0 / thresholdPace
intervalPace = 1000.0 / intervalPace
repPace = 1000.0 / repPace
}
TrainingPaces["Easy"] = strutil.DecimalTimetoMinSec(easyPace)
TrainingPaces["Marathon"] = strutil.DecimalTimetoMinSec(maraPace)
TrainingPaces["Threshold"] = strutil.DecimalTimetoMinSec(thresholdPace)
TrainingPaces["Interval"] = strutil.DecimalTimetoMinSec(intervalPace)
TrainingPaces["Repeats"] = strutil.DecimalTimetoMinSec(repPace)
// Convert the times from decimal minutes to hh:mm:ss for the user.
PredictedRaceTimes = make(map[string]string)
for key, val := range PredictedTimes {
PredictedRaceTimes[key] = strutil.DecimalTimetoHourMinSec(val)
}
return
}