synthicity / activitysim
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itertools.product is slightly faster than doing lookups in a list comp

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Recent builds

Builds Branch Commit Type Ran Committer Via Coverage
312 cdap-performance itertools.product is slightly faster than doing lookups in a list comp push jiffyclub travis-ci pending completion  
307 cdap-performance allow numpy to broadcast alt in cdap.apply_final_rules push jiffyclub travis-ci pending completion  
305 cdap-performance Cache arrays in cdap.apply_final_rules Households always have the same alternative groups in the same order so it's possible to cache calculations based on household size. push jiffyclub travis-ci pending completion  
303 cdap-performance cache a couple more things in cdap.initial_household_utilities push jiffyclub travis-ci pending completion  
300 cdap-performance use numpy indexing in cdap.make_interactions Once again we get significant speedups by working with NumPy arrays instead of Pandas structures. push jiffyclub travis-ci pending completion  
296 cdap-performance move apply_final_rules work into numpy funcs push jiffyclub travis-ci pending completion  
290 cdap-performance Skip loops in cdap.apply_final_rules It's easy to check whether any of the rules even apply before starting to do all the looping, so this does a bunch of checks of that and continues if nothing applies. Big performance improvement, but probably ... push jiffyclub travis-ci pending completion  
289 cdap-performance use numpy indexing instead of pandas lookup Once again, using numpy fancy indexing is way faster than pandas indexing. push jiffyclub travis-ci pending completion  
288 cdap-performance do less indexing in cdap.apply_final_rules push jiffyclub travis-ci pending completion  
287 cdap-performance do less indexing in cdap.apply_final_rules push jiffyclub travis-ci pending completion  
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