bottleneck.benchmark package

Submodules

bottleneck.benchmark.autotimeit module

bottleneck.benchmark.autotimeit.autoscaler(timer: timeit.Timer, mintime: float) → Tuple[int, float]
bottleneck.benchmark.autotimeit.autotimeit(stmt: str, setup: str = 'pass', repeat: int = 3, mintime: float = 0.2) → float

bottleneck.benchmark.bench module

bottleneck.benchmark.bench.bench(shapes=[(100,), (1000, 1000), (1000, 1000), (1000, 1000), (1000, 1000), (1000, 1000)], axes=[0, None, 0, 0, 1, 1], nans=[False, True, False, True, False, True], dtype='float64', order='C', functions=None)

Bottleneck benchmark.

Parameters
shapeslist, optional

A list of tuple shapes of input arrays to use in the benchmark.

axeslist, optional

List of axes along which to perform the calculations that are being benchmarked.

nanslist, optional

A list of the bools (True or False), one for each tuple in the shapes list, that tells whether the input arrays should be randomly filled with one-fifth NaNs.

dtypestr, optional

Data type string such as ‘float64’, which is the default.

order{‘C’, ‘F’}, optional

Whether to store multidimensional data in C- or Fortran-contiguous (row- or column-wise) order in memory.

functions{list, None}, optional

A list of strings specifying which functions to include in the benchmark. By default (None) all functions are included in the benchmark.

Returns
A benchmark report is printed to stdout.

bottleneck.benchmark.bench_detailed module

bottleneck.benchmark.bench_detailed.bench_detailed(function='nansum', fraction_nan=0.0)

Benchmark a single function in detail or, optionally, all functions.

Parameters
functionstr, optional

Name of function, as a string, to benchmark. Default (‘nansum’) is to benchmark bn.nansum. If function is ‘all’ then detailed benchmarks are run on all bottleneck functions.

fraction_nanfloat, optional

Fraction of array elements that should, on average, be NaN. The default (0.0) is not to set any elements to NaN.

Returns
A benchmark report is printed to stdout.

Module contents