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fix: prune nan idxs in output when omitting nans #83

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@jvdd jvdd commented Jan 31, 2025

closes #73

This PR

  • removes NaNn idxs when non NaN downsamplers (i.e., policy = omit NaN - such as MinMaxDownsampler)
  • nothing is changed for NaN downsamplers (i.e., policy = return NaN - such as NaNMinMaxDownsampler)

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codspeed-hq bot commented Jan 31, 2025

CodSpeed Performance Report

Merging #83 will degrade performances by 55.89%

Comparing prune_nans (ffc311c) with main (7e2f14a)

Summary

⚡ 13 improvements
❌ 48 regressions
✅ 617 untouched benchmarks

⚠️ Please fix the performance issues or acknowledge them on CodSpeed.

Benchmarks breakdown

Benchmark BASE HEAD Change
test_lttb_no_x[False-float32-5,000-100,000] 1.2 ms 1.3 ms -12.9%
test_lttb_no_x[False-float64-5,000-100,000] 1.3 ms 1.5 ms -12.59%
test_lttb_no_x[False-int32-5,000-100,000] 1.3 ms 1.5 ms -11.97%
test_lttb_no_x[False-int64-5,000-100,000] 1.5 ms 1.7 ms -10.86%
test_lttb_no_x[True-float32-5,000-100,000] 1.2 ms 1.4 ms -12.57%
test_lttb_no_x[True-float64-5,000-100,000] 1.3 ms 1.5 ms -12.33%
test_lttb_no_x[True-int32-5,000-100,000] 1.3 ms 1.5 ms -11.9%
test_lttb_no_x[True-int64-5,000-100,000] 1.5 ms 1.7 ms -10.78%
test_m4_no_x[False-float32-1,000-100,000] 404.6 µs 466.6 µs -13.3%
test_m4_no_x[False-float32-5,000-100,000] 530.4 µs 705.3 µs -24.8%
test_m4_no_x[False-float64-5,000-100,000] 760 µs 941.8 µs -19.3%
test_m4_no_x[False-int32-1,000-100,000] 531.3 µs 590.8 µs -10.07%
test_m4_no_x[False-int32-5,000-100,000] 652.1 µs 820 µs -20.47%
test_m4_no_x[False-int64-5,000-100,000] 867.3 µs 1,047.1 µs -17.17%
test_m4_no_x[True-float32-5,000-100,000] 591.7 µs 737.5 µs -19.76%
test_m4_no_x[True-float64-5,000-100,000] 789 µs 986.4 µs -20.02%
test_m4_no_x[True-int32-1,000-100,000] 575.3 µs 651.6 µs -11.72%
test_m4_no_x[True-int32-5,000-100,000] 702.9 µs 867 µs -18.93%
test_m4_with_x[False-float32-5,000-100,000] 903.5 µs 1,075 µs -15.95%
test_m4_with_x[False-float64-5,000-100,000] 1.1 ms 1.3 ms -14.12%
... ... ... ... ...

ℹ️ Only the first 20 benchmarks are displayed. Go to the app to view all benchmarks.

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NaNs Are Returned by non NaN Downsamplers
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