Source code for simplebench.stats.operation_timings

# -*- coding: utf-8 -*-
"""Containers for benchmark statistics"""
from __future__ import annotations

from typing import Optional, Sequence

from ..defaults import DEFAULT_INTERVAL_SCALE, DEFAULT_INTERVAL_UNIT
from ..exceptions import SimpleBenchTypeError
from ..iteration import Iteration
from ..validators import validate_sequence_of_numbers
from . import Stats, StatsSummary
from .exceptions.operation_timings import _OperationTimingsErrorTag


[docs] class OperationTimings(Stats): """Container for the operation timing statistics of a benchmark. :ivar unit: The unit of measurement for the timings (e.g., "ns"). :vartype unit: str :ivar scale: The scale factor for the timings (e.g., "1e-9" for nanoseconds). :vartype scale: float :ivar rounds: The number of data points in the benchmark. :vartype rounds: int :ivar data: Tuple of timing data points. :vartype data: tuple[int | float, ...] :ivar mean: The mean time per operation. :vartype mean: float :ivar median: The median time per operation. :vartype median: float :ivar minimum: The minimum time per operation. :vartype minimum: float :ivar maximum: The maximum time per operation. :vartype maximum: float :ivar standard_deviation: The standard deviation of the time per operation. :vartype standard_deviation: float :ivar relative_standard_deviation: The relative standard deviation of the time per operation. :vartype relative_standard_deviation: float :ivar percentiles: Percentiles of time per operation. :vartype percentiles: dict[int, float] """ def __init__(self, *, iterations: Sequence[Iteration] | None = None, unit: str = DEFAULT_INTERVAL_UNIT, scale: float = DEFAULT_INTERVAL_SCALE, rounds: int = 1, data: Optional[Sequence[int | float]] = None): """Construct OperationTimings stats from Iteration or raw timing data. :param iterations: Sequence of :class:`~simplebench.iteration.Iteration` objects to extract timing data from. :param unit: The unit of measurement for the timings (e.g., "ns"). :param scale: The scale factor for the timings (e.g., "1e-9" for nanoseconds). :param rounds: The number of data points in the benchmark. :param data: Optional sequence of timing data points. If not provided, timing data will be extracted from the iterations if available. :raises ~simplebench.exceptions.SimpleBenchTypeError: If any of the arguments are of the wrong type. :raises ~simplebench.exceptions.SimpleBenchValueError: If any of the arguments have invalid values. """ if iterations is None and data is None: raise SimpleBenchTypeError( "either iterations or data must be provided", tag=_OperationTimingsErrorTag.NO_DATA_OR_ITERATIONS_PROVIDED) if data is None: data = [] imported_data: list[int | float] = list(validate_sequence_of_numbers( data, 'data', type_tag=_OperationTimingsErrorTag.INVALID_DATA_ARG_TYPE, value_tag=_OperationTimingsErrorTag.INVALID_DATA_ARG_VALUE)) if iterations is not None: if not isinstance(iterations, Sequence): raise SimpleBenchTypeError( "passed iterations arg is not a Sequence", tag=_OperationTimingsErrorTag.INVALID_ITERATIONS_ARG_TYPE) if not all(isinstance(iteration, Iteration) for iteration in iterations): raise SimpleBenchTypeError( "There are items in the iterations arg sequence that are not Iteration objects", tag=_OperationTimingsErrorTag.INVALID_ITERATIONS_ITEM_ARG_TYPE) imported_data.extend(iteration.per_round_elapsed for iteration in iterations) super().__init__(unit=unit, scale=scale, rounds=rounds, data=imported_data)
[docs] class OperationTimingsSummary(StatsSummary): """Container for summary of operation timing statistics of a benchmark. :ivar unit: The unit of measurement for the benchmark (e.g., "ops/s"). :vartype unit: str :ivar scale: The scale factor for the interval (e.g. 1 for seconds). :vartype scale: float :ivar rounds: The number of data points in the benchmark. :vartype rounds: int :ivar mean: The mean operations per time interval. :vartype mean: float :ivar median: The median operations per time interval. :vartype median: float :ivar minimum: The minimum operations per time interval. :vartype minimum: float :ivar maximum: The maximum operations per time interval. :vartype maximum: float :ivar standard_deviation: The standard deviation of operations per time interval. :vartype standard_deviation: float :ivar relative_standard_deviation: The relative standard deviation of ops per time interval. :vartype relative_standard_deviation: float :ivar percentiles: Percentiles of operations per time interval. :vartype percentiles: dict[int, float] """