Documentation Index
Fetch the complete documentation index at: https://numpyts.dev/llms.txt
Use this file to discover all available pages before exploring further.
Benchmark snapshot comparing numpy-ts against native Python NumPy (OpenBLAS-backed) across small, medium, and large array sizes. Run your own via npm run bench.
All benchmarks measure computation time from JS and Python, respectively. To learn more, check out benchmark methodology. Benchmark Summary
- Average speedup: 1.11x vs NumPy
- Best case: 2422.82x
- Worst case: 0.09x
- Total benchmarks: 7159
- Machine: Apple M4 Max (16 cores, 128 GB, arm64)
- numpy-ts version: 1.4.0
| Category | Avg Speedup | Count | Faster | Slower |
|---|
| creation | 1.76x | 639 | 476 | 163 |
| arithmetic | 1.05x | 885 | 400 | 485 |
| math | 0.62x | 375 | 82 | 293 |
| trig | 0.61x | 648 | 151 | 497 |
| gradient | 4.48x | 66 | 66 | 0 |
| linalg | 1.50x | 807 | 523 | 284 |
| reductions | 0.96x | 1239 | 613 | 626 |
| manipulation | 1.16x | 693 | 329 | 364 |
| io | 2.71x | 187 | 162 | 25 |
| indexing | 0.66x | 345 | 127 | 218 |
| bitwise | 0.65x | 30 | 7 | 23 |
| sorting | 0.82x | 225 | 58 | 167 |
| logic | 1.69x | 426 | 242 | 184 |
| statistics | 1.54x | 78 | 48 | 30 |
| sets | 3.33x | 99 | 77 | 22 |
| random | 0.91x | 138 | 49 | 89 |
| polynomials | 2.06x | 81 | 63 | 18 |
| fft | 0.91x | 198 | 88 | 110 |
| DType | Avg Speedup | Median Speedup | Count |
|---|
| float64 | 1.02x | 0.95x | 863 |
| float32 | 1.05x | 0.98x | 713 |
| float16 | 1.36x | 1.36x | 632 |
| int64 | 1.03x | 0.94x | 587 |
| uint64 | 1.00x | 0.93x | 563 |
| int32 | 1.16x | 1.05x | 611 |
| uint32 | 1.19x | 1.07x | 566 |
| int16 | 1.11x | 1.01x | 554 |
| uint16 | 1.12x | 1.02x | 551 |
| int8 | 1.27x | 1.02x | 554 |
| uint8 | 1.27x | 1.05x | 557 |
| complex128 | 0.85x | 0.80x | 204 |
| complex64 | 0.80x | 0.62x | 204 |
