R Export Activities

# using the function to export several CSV files
exportCSV('Sport = "Bike"','2018/07/14','2019/12/31',"/home/majikstone/GoldenCheetah/export_mid2018_2019_Bike.csv");

exportCSV('Sport = "Bike"','2018/01/01','2019/12/31',"/home/majikstone/GoldenCheetah/export_2018_2019_Bike.csv");

exportCSV('Sport CONTAINS "Trainer"','2018/01/01','2019/12/31',"/home/majikstone/GoldenCheetah/export_2018_2019_Trainer.csv");


# CSV export function
# Parameters:
#   filtText    - the text used to filter the activities, same format as for GC graphs
#   startDate   - string in POSIX compatible format corresponding to the start date of the interval
#   endDate     - string in POSIX compatible format corresponding to the end date of the interval
#   outFileName - the destination (absolute or relative) and the filename of the exported CSV file
exportCSV<-function(filtText,startDate,endDate,outFileName)
{
    # convert the dates to POSIXct variables, initialize other variables
    sDate = as.POSIXct(startDate);
    eDate = as.POSIXct(endDate);
    noDatasets = 3;
    init = 0;

    # get the full list of activities filtered by the filtered text
    # the list is a list of POSIXct dates, that can be used to extract one single activity later
    actDates <- GC.activities(filter=filtText);
    # for each date in the list
    for (date in actDates)
    {
        # if the date is valid
        if (date >= sDate && date <= eDate)
        {
            # extract the activity with the given date
            # remark: the date is actually the entire starting time of the activity
            activity = GC.activity(date)[[1]];

            # the metrics are not processed here, we extract and concatenate raw data
            # either initialize or concatenate the data vectors
            # for now, only speed, cadence and HR are being extracted
            if (init == 0)
            {
                cadence = c(activity$cadence);
                hr = c(activity$heart.rate);
                speed = c(activity$speed);
                init = 1;
            }
            else
            {
                cadence = c(cadence,activity$cadence);
                hr = c(hr,activity$heart.rate);
                speed = c(speed,activity$speed);
            }
        }
    }

    # filter out all NA values (bad readings)
    # if a value is filtered out from one array, the corresponding values from the other arrays have to be filtered out as well
    # we do that to make sure the datasets are still coherent one with the other
    cadence = cadence[!is.na(cadence)];
    speed = speed[!is.na(cadence)];
    hr = hr[!is.na(cadence)];

    cadence = cadence[!is.na(speed)];
    speed = speed[!is.na(speed)];
    hr = hr[!is.na(speed)];

    cadence = cadence[!is.na(hr)];
    speed = speed[!is.na(hr)];
    hr = hr[!is.na(hr)];

    # we create and initialize a matrix to merge together all the datasets
    len = length(speed);
    csvMat = matrix(nrow=len, ncol=noDatasets);

    # we put each dataset on a column of the matrix
    csvMat[,1] = speed;
    csvMat[,2] = cadence;
    csvMat[,3] = hr;

    # export the CSV file, with no headers and ; as a separator
    write.table(csvMat, file=outFileName, col.names=FALSE, row.names=FALSE, sep=";");

    # display a success message
    message("Exporting complete to: ",outFileName);
}