/**
 * This file defines a line chart used in the full replay page, showing Ublox horizontal accuracy,
 * smartphone horizontal accuracy and distance between the positions of the Ublox
 * and the Smartphone at a same time in meters, over time.
 *
 * @authors Timo Volkmann, Frank Herkommer.
 */

//list of all horizontal accuracies sent in by the Ublox
let allAccSerial = []
//list of all coordinates sent in by the Ublox
let allSerialCoords = []

//Defines the chart and its properties
let ctx1 = document.getElementById('accChart').getContext('2d');
let accChart = new Chart(ctx1, {
    type: 'line',
    data: {
        labels: [],
        datasets: [{
            label: 'Ublox Horizontal acc. (m)',
            backgroundColor: 'rgba(255, 255, 255, 1)',
            borderColor: 'rgba(255, 255, 255, 1)',
            borderWidth: 1,
            fill: false,
            pointRadius: 0.5,
            lineTension: 0.5,
            data: []
        },
        {
            label: 'Smartphone Horizontal acc. (m)',
            backgroundColor: 'rgb(185,190,45)',
            borderColor: 'rgb(185,190,45)',
            borderWidth: 1,
            fill: false,
            pointRadius: 0.5,
            lineTension: 0.5,
            data: []
        },
        {
            label: 'Distance Ublox - Smartphone (m)',
            backgroundColor: 'rgba(30, 130, 76, 1)',
            borderColor: 'rgba(30, 130, 76, 1)',
            borderWidth: 1,
            fill: false,
            pointRadius: 0.5,
            lineTension: 0.5,
            data: []
        }]
    },
    options: {
        scales: {
            yAxes: [{
                ticks: {
                    min: 0,
                    max: 20,
                }
            }],
            xAxes: [{
                type: 'time',
                time: {
                    unit: 'second'
                }
            }]
        },
        animation: {
            duration: 0
        }
    }
});

/**
 * Function to calculate the distance between to coordinates at a same time using the vincenty algorithm.
 *
 * @param data    all collected data.
 */
function addDistances(data){
    //collect all horizontal accuracies from serial source and tcp source.
    let serialHAccs = data.filter(el => el.ser != null).map(el => {
        return el.ser.HAcc
    })
    let tcpHAccs = data.filter(el => el.tcp != null).map(el => {
        return el.tcp.HAcc
    })
    //apply vincenty algorithm on coordinates from serial and tcp source.
    let distances = data.filter(el => el.ser != null && el.tcp != null).map((el, i, arr) => {
        // return distVincenty(el.ser.Position, el.tcp.Position)
        const plaindist = distVincenty(el.ser.Position, el.tcp.Position)
        arr[i]['distance'] = plaindist

        // if closest measurements not happening in the exact same millisecond,
        // calculate traveled distance for the time difference and substract it from result
        // bear in mind that this is not exact because the two measurements are not always exactly aligned with
        // the direction of motion. that's okay because we only need to estimate the accuracy
        arr[i]['distanceCleanAbs'] = plaindist - Math.abs(el.ser.Speed / 1000 * el.differenceMs)
        return arr[i].distanceCleanAbs // plaindist - Math.abs(el.ser.Speed / 1000 * el.differenceMs)
    })

    let timelabels = data.filter(el => el.tcp != null).map(el => {
        return el.tcp.Timestamp
    })
    if (timelabels.length === 0) {
        timelabels = data.filter(el => el.ser != null).map(el => {
            return el.ser.Timestamp
        })
    }

    //add the data to the chart and update the hart
    accChart.data.labels = timelabels
    accChart.data.datasets[0].data = serialHAccs
    accChart.data.datasets[1].data = tcpHAccs
    accChart.data.datasets[2].data = distances
    accChart.update()
}