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#!/usr/bin/env python
#
# @license Apache-2.0
#
# Copyright (c) 2018 The Stdlib Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Benchmark scipy.stats.beta."""
from __future__ import print_function
import timeit
REPEATS = 3
COUNT = [0] # use a list to allow modification within nested scopes
def print_version():
"""Print the TAP version."""
print("TAP version 13")
def print_summary(total, passing):
"""Print the benchmark summary.
# Arguments
* `total`: total number of tests
* `passing`: number of passing tests
"""
print("#")
print("1.." + str(total)) # TAP plan
print("# total " + str(total))
print("# pass " + str(passing))
print("#")
print("# ok")
def print_results(iterations, elapsed):
"""Print benchmark results.
# Arguments
* `iterations`: number of iterations
* `elapsed`: elapsed time (in seconds)
# Examples
``` python
python> print_results(1000000, 0.131009101868)
```
"""
rate = iterations / elapsed
print(" ---")
print(" iterations: " + str(iterations))
print(" elapsed: " + str(elapsed))
print(" rate: " + str(rate))
print(" ...")
def benchmark(name, setup, stmt, iterations):
"""Run the benchmark and print benchmark results.
# Arguments
* `name`: benchmark name
* `setup`: benchmark setup
* `stmt`: statement to benchmark
* `iterations`: number of iterations
# Examples
``` python
python> benchmark("random", "from random import random;", "y = random()", 1000000)
```
"""
t = timeit.Timer(stmt, setup=setup)
print_version()
i = 0
while i < REPEATS:
print("# python::" + name)
COUNT[0] += 1
elapsed = t.timeit(number=iterations)
print_results(iterations, elapsed)
print("ok " + str(COUNT[0]) + " benchmark finished")
i += 1
def main():
"""Run the benchmarks."""
name = "beta:entropy"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.entropy()"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:kurtosis"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.stats(moments='k')"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:mean"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.mean()"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:median"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.median()"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:skewness"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.stats(moments='s')"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:stdev"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.std()"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:variance"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.var()"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:cdf"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.cdf(random())"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:logpdf"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.logpdf(random())"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:pdf"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.pdf(random())"
iterations = 1000
benchmark(name, setup, stmt, iterations)
name = "beta:quantile"
setup = "from scipy.stats import beta; from random import random; rv = beta(100.56789, 55.54321);"
stmt = "y = rv.ppf(random())"
iterations = 1000
benchmark(name, setup, stmt, iterations)
print_summary(COUNT[0], COUNT[0])
if __name__ == "__main__":
main()
|
