Micro-benchmarks for some numpy functions
- Benchmarking to compare numpy implementations
- Micro-benchmarks using
- Currently, most benchmarks are for in-place operations as I'm wanting to test algorithm time, and not conflate it with memory allocation time.
./benchmark.py [numpy library name](defaults to numpy)
- writes timings to a file of tab-separated values (TSV)
- Graph with
- just set the names of the TSV files to compare.
- See the benchmark from a 4core i7 OSX machine