tsdownsample
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Add nightly feature
Currently downsample_rs cannot be built with stable compiler, because nightly_simd is enabled by default for argminmax.
I've added nightly feature (which is enabled by default) which activates nightly_simd, so this crate can be compiled with stable with default-features=false
(yes, I really need that :) )
CodSpeed Performance Report
Merging #79 will degrade performances by 27.55%
Comparing leviska:main (04599e4) with main (05334d5)
:tada: Hooray! pytest-codspeed just leveled up to 3.0.0!
A heads-up, this is a breaking change and it might affect your current performance baseline a bit. But here's the exciting part - it's packed with new, cool features and promises improved result stability :partying_face:! Curious about what's new? Visit our releases page to delve into all the awesome details about this new version.
Summary
⚡ 11 improvements
❌ 12 regressions
✅ 655 untouched benchmarks
:warning: Please fix the performance issues or acknowledge them on CodSpeed.
Benchmarks breakdown
| Benchmark | main |
leviska:main |
Change | |
|---|---|---|---|---|
| ❌ | test_m4_no_x[True-int64-1,000-100,000] |
816.6 µs | 946.4 µs | -13.72% |
| ❌ | test_m4_with_x[True-float64-1,000-100,000] |
1.6 ms | 2 ms | -22.41% |
| ❌ | test_m4_with_x[True-int32-100-100,000] |
871.1 µs | 1,005.1 µs | -13.33% |
| ⚡ | test_minmax_no_x[True-float64-100-100,000] |
749.8 µs | 661.5 µs | +13.34% |
| ⚡ | test_minmax_no_x[True-int32-100-100,000] |
637.3 µs | 566.9 µs | +12.42% |
| ⚡ | test_minmax_with_x[True-float64-1,000-100,000] |
2.2 ms | 1.8 ms | +21.87% |
| ❌ | test_minmax_with_x[True-int32-1,000-100,000] |
1.6 ms | 2.1 ms | -23.06% |
| ❌ | test_minmaxlttb_no_x[True-int32-100-100,000] |
603.2 µs | 687.3 µs | -12.24% |
| ❌ | test_nanm4_no_x[True-float32-1,000-100,000] |
466.7 µs | 542.4 µs | -13.94% |
| ❌ | test_nanm4_with_x[True-float32-1,000-1,000,000] |
3.4 ms | 3.8 ms | -10.46% |
| ⚡ | test_nanm4_with_x[True-float32-1,000-100,000] |
1.8 ms | 1.4 ms | +26.73% |
| ⚡ | test_nanm4_with_x[True-int32-1,000-1,000,000] |
4.2 ms | 3.5 ms | +19.3% |
| ❌ | test_nanminmax_with_x[True-float32-1,000-1,000,000] |
3.6 ms | 4.1 ms | -12.22% |
| ⚡ | test_nanminmax_with_x[True-float32-1,000-100,000] |
2 ms | 1.6 ms | +26.53% |
| ❌ | test_nanminmax_with_x[True-float32-5,000-1,000,000] |
7.1 ms | 7.9 ms | -10.22% |
| ⚡ | test_nanminmax_with_x[True-float64-1,000-100,000] |
2.2 ms | 2 ms | +12.46% |
| ❌ | test_nanminmax_with_x[True-int32-1,000-100,000] |
2.1 ms | 2.4 ms | -12.87% |
| ⚡ | test_nanminmax_with_x[True-int64-1,000-100,000] |
2.3 ms | 1.9 ms | +23.06% |
| ❌ | test_nanminmaxlttb_no_x[True-int32-1,000-100,000] |
916 µs | 1,088.8 µs | -15.87% |
| ⚡ | test_nanminmaxlttb_with_x[True-float32-100-1,000,000] |
4.1 ms | 3.1 ms | +31% |
| ... | ... | ... | ... | ... |
:information_source: Only the first 20 benchmarks are displayed. Go to the app to view all benchmarks.
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