🍵 use slice internally + implement for various types

[jvdd]

• use slice (&[T]) under the hood instead of ArrayView1
• ndarray -> optional dependency
• extend trait implementation, resolves ✨ implement ArgMinMax trait for other types #9
  • slice
  • Vec
    • test this
  • ndarray
    • test this
  • arrow
    • test this
• update Readme

---

• final rerun of benchmarks
  • no regressions (i.e., same performance or even better 🚀) for scalar implementation
  • no regressions (i.e., same performance or even better 🚀) for SIMD implementation
    => I notices very few (minor) regressions for certain dtype / SIMD combinations & highlighted those in the benches/results file.. But, since the codspeed continuous monitoring only shows 2% regressions for the AVX2 u8 & i8 - (which is most likely not the most common datatypes for end users) - I am pro for merging this into main, given the significant enhanced flexibility that this PR adds :)

[jvdd]

LGTM 🙃

[codspeed-hq]

CodSpeed Performance Report

Merging #13 other_types (bad1543) will improve performances by 5.5%.

Summary

🔥 21 improvements
❌ 2 regressions
✅ 21 untouched benchmarks

🆕 0 new benchmarks
⁉️ 0 dropped benchmarks

Benchmarks breakdown

	Benchmark	main	other_types	Change
🔥	scalar_random_long_f32	1.9 ms	1.7 ms	9.08%
🔥	sse_random_long_f32	883.6 µs	712.1 µs	19.41%
🔥	scalar_random_long_i16	2.1 ms	1.6 ms	23.97%
🔥	sse_random_long_i16	411.3 µs	389.3 µs	5.35%
🔥	scalar_random_long_i32	2.1 ms	1.7 ms	16.62%
🔥	sse_random_long_i32	819.4 µs	797.3 µs	2.70%
🔥	scalar_random_long_f64	2.1 ms	1.9 ms	8.30%
🔥	sse_random_long_f64	1.8 ms	1.4 ms	19.38%
🔥	scalar_random_long_i64	2.2 ms	1.9 ms	15.30%
🔥	sse_random_long_i64	2 ms	1.8 ms	12.71%
🔥	scalar_random_long_u32	2.1 ms	1.7 ms	16.62%
🔥	scalar_random_long_u64	2.2 ms	1.9 ms	15.30%
🔥	sse_random_long_u64	2.1 ms	1.8 ms	12.19%
🔥	scalar_random_long_f16	2.6 ms	2.3 ms	12.89%
🔥	sse_random_long_f16	497.6 µs	475.6 µs	4.42%
🔥	scalar_random_long_u16	2.1 ms	1.6 ms	23.97%
🔥	sse_random_long_u16	433.1 µs	421.3 µs	2.73%
🔥	scalar_random_long_i8	2 ms	1.9 ms	4.28%
❌	avx2_random_long_i8	200.8 µs	205.3 µs	-2.26%
🔥	scalar_random_long_u8	2 ms	1.9 ms	4.28%
🔥	sse_random_long_u8	287 µs	275.6 µs	3.98%
❌	avx2_random_long_u8	197.3 µs	201.8 µs	-2.28%
🔥	impl_random_long_u8	287.2 µs	275.8 µs	3.97%