Skip to main content
`Ctrl`+`K`

# Summarising

Operator to aggregate analytical features and create raster and render image

tracklib.algo.Summarising.getMeasureName(af_algo, aggregate=None)

  Return the identifier of the measure defined by: af + aggregate operator

tracklib.algo.Summarising.summarize(collection, af_algos, aggregates, resolution=None, margin=0.05, verbose=True)
  Example:

    af_algos = [algo.speed, algo.speed] cell_operators = [celloperator.co_avg, celloperator.co_max]

tracklib.algo.Summarising.co_sum(tarray)

  TODO

tracklib.algo.Summarising.co_min(tarray)

  TODO

tracklib.algo.Summarising.co_max(tarray)

  TODO

tracklib.algo.Summarising.co_count(tarray)

  TODO

tracklib.algo.Summarising.co_avg(tarray)

  TODO

tracklib.algo.Summarising.co_dominant(tarray)

  TODO

tracklib.algo.Summarising.co_median(tarray)

  TODO