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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: 1.13x vs NumPy
  • Best case: 2336.20x
  • Worst case: 0.10x
  • Total benchmarks: 7159
  • Machine: Apple M4 Max (16 cores, 128 GB, arm64)
  • numpy-ts version: 1.3.0

Performance by Category

CategoryAvg SpeedupCountFasterSlower
creation1.79x639480159
arithmetic1.10x885414471
math0.60x37580295
trig0.59x648148500
gradient4.20x66660
linalg1.45x807504303
reductions1.00x1239639600
manipulation1.20x693331362
io2.73x18716225
indexing0.65x345118227
bitwise0.63x30723
sorting0.80x22560165
logic1.87x426250176
statistics1.57x784830
sets3.01x997029
random0.89x1384890
polynomials2.01x816318
fft0.92x19886112

Performance by DType

DTypeAvg SpeedupMedian SpeedupCount
float641.01x0.93x863
float321.07x0.99x713
float161.40x1.36x632
int641.05x0.98x587
uint640.99x0.93x563
int321.19x1.07x611
uint321.21x1.11x566
int161.15x1.02x554
uint161.16x1.01x551
int81.30x1.04x554
uint81.28x1.02x557
complex1280.83x0.81x204
complex640.77x0.61x204