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Find and resolve bottlenecks #53

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jGaboardi opened this issue Dec 17, 2020 · 1 comment
Open

Find and resolve bottlenecks #53

jGaboardi opened this issue Dec 17, 2020 · 1 comment
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jGaboardi commented Dec 17, 2020 •
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BY far the two largest time/memory hogs are [n2n_matrix] and [paths] within Network.cost_matrix():

# calculate shortest path length and records paths if desired
n2n_matrix, paths = utils.shortest_path(self, gp=wpaths)

An attempt to speed up should be made...

  • try numba?
  • simple multiprocessing?
@jGaboardi jGaboardi self-assigned this Dec 17, 2020
@jGaboardi jGaboardi added this to To do in pre-release build Dec 17, 2020
@jGaboardi jGaboardi removed this from To do in pre-release build Dec 20, 2020
@jGaboardi jGaboardi added this to To do in release Dec 20, 2020
@jGaboardi jGaboardi mentioned this issue Dec 21, 2020
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@jGaboardi jGaboardi removed this from the initial functional release milestone Dec 21, 2020
@jGaboardi jGaboardi moved this from To do to In progress in release Dec 21, 2020
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Try:

  • multiprocessing for observations
  • numba

@jGaboardi jGaboardi changed the title multiprocessing for cost matrices? Find and resolve bottlenecks Dec 23, 2020
@jGaboardi jGaboardi added this to To do in release +1 Jul 11, 2021
@jGaboardi jGaboardi removed this from In progress in release Jul 11, 2021
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