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CLN: ASV stat_ops #19049
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CLN: ASV stat_ops #19049
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Hello @mroeschke! Thanks for updating the PR.
Comment last updated on January 06, 2018 at 05:37 Hours UTC |
Codecov Report
@@ Coverage Diff @@
## master #19049 +/- ##
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+ Coverage 91.51% 91.53% +0.01%
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Files 148 148
Lines 48807 48688 -119
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- Hits 44667 44566 -101
+ Misses 4140 4122 -18
Continue to review full report at Codecov.
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asv_bench/benchmarks/rolling.py
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| class DepreciatedRolling(object): | ||
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| sample_time = 0.2 | ||
| params = ['rolling_median', 'rolling_mean', 'rolling_min', 'rolling_max', |
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i would prob remove these, we go back pretty far with the newer stuff already.
asv_bench/benchmarks/stat_ops.py
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| goal_time = 0.2 | ||
| param_names = ['op', 'use_bottleneck', 'dtype', 'axis'] | ||
| params = [['mean', 'sum', 'median'], | ||
| params = [['mean', 'sum', 'median', 'std'], |
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you could make use_bottleneck a param here
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use_bottleneck is a param here, over [True, False]
jreback
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see comments
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Removed the older rolling benchmarks. |
asv_bench/benchmarks/stat_ops.py
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| class stats_rank2d_axis1_average(object): | ||
| goal_time = 0.2 | ||
| def setup(self, op, use_bottleneck, dtype): |
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you could put the bottleneck tests in a separate function / base class I think
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Created a new class for the bottleneck benchmarks: |
asv_bench/benchmarks/stat_ops.py
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| class stat_ops_series_std(object): | ||
| goal_time = 0.2 | ||
| param_names = ['op', 'dtype'] |
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what I meant about bottleneck was make it a parameter in ops, e.g. here
asv_bench/benchmarks/stat_ops.py
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| class stat_ops_level_frame_sum(object): | ||
| goal_time = 0.2 | ||
| param_names = ['op', 'dtype', 'axis'] | ||
| params = [['mean', 'sum', 'median', 'std'], |
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and use bottleneck here, also expand these to all of the stat ops (min, max, var, kurt, etc)
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Defined a list of ops at the top of the file that each benchmark |
There were some old
pd.rolling_*methods being tested instat_ops.pythat I moved torolling.py(or should they just be removed?), otherwise the usual cleanup: