Scoring Steps

Let’s now walk through the process of scoring with flare-timing. Starting from an *.fsdb competition with related *.igc or *.kml track logs, scoring proceeds in steps [1];

  1. Extract the inputs with extract-input.
  2. Trace the route of the shortest path to fly a task with task-length.
  3. Find pairs of fixes crossing over zones with cross-zone.
  4. Interpolate between crossing fixes with tag-zone.
  5. Unpack track logs to a flat list of time with latitude and longitude with unpack-track . This data supplies the pilot tracks that can be downloaded and shown on the map and is used to find the scored track indices for stopped tasks.
  6. Peg out the time range of each track log that will be scored with peg-frame.
  7. Index fixes from the time of first crossing with align-time.
  8. Discard fixes that get further from goal and note leading area with discard-further.
  9. Mask a task over its tracklogs with mask-track.
  10. Group and count land outs with land-out.
  11. Score the competition with gap-point.

If hosting the web app then the following two steps are needed too:

  1. Extract the scores and some of the workings of FS with fs-score. These values and differences are shown as extra columns in tables side-by-side with flare-timing values. This is a quick way to spot discrepancies between the two GAP scoring implementations.
[1]In this list, any step can use the inputs or outputs from a previous step. For instance *.kml and *.igc track logs are needed as inputs for the cross-zone, align-time and unpack-track steps. The app of each step logs the inputs they’re using.