Add nightly feature

[leviska]

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-hq]

CodSpeed Performance Report

Merging #79 will degrade performances by 27.55%

_{Comparing leviska:main (04599e4) with main (05334d5)}

🎉 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 🥳!
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

⚠️ 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%
...	...	...	...	...

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

[codecov-commenter]

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