Summarising
Operator to aggregate analytical features and create raster and render image
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tracklib.algo.Summarising.getMeasureName(af_algo, aggregate=None)[source]
Return the identifier of the measure defined by: af + aggregate operator
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tracklib.algo.Summarising.summarize(collection, af_algos, aggregates, resolution=None, margin=0.05, verbose=True)[source]
- Example:
af_algos = [algo.speed, algo.speed]
cell_operators = [celloperator.co_avg, celloperator.co_max]
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tracklib.algo.Summarising.co_sum(tarray)[source]
TODO
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tracklib.algo.Summarising.co_min(tarray)[source]
TODO
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tracklib.algo.Summarising.co_max(tarray)[source]
TODO
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tracklib.algo.Summarising.co_count(tarray)[source]
TODO
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tracklib.algo.Summarising.co_avg(tarray)[source]
TODO
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tracklib.algo.Summarising.co_dominant(tarray)[source]
TODO
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tracklib.algo.Summarising.co_median(tarray)[source]
TODO