nickodell · May 6, 2024 01:02
diff --git a/bench.csv b/bench.csv
diff --git a/bench_approx_derivative.py b/bench_approx_derivative.py
 from scipy.optimize._numdiff import approx_derivative
 from scipy.optimize import rosen
 import numpy as np
 import timeit
 import functools
 import subprocess
 import sys


 def bench(xk, method):
    approx_derivative(np.linalg.norm, xk, method)


 def auto_timeit(stmt, number):
    # Warmup, throw result away
    timeit.timeit(stmt, number=1)
    t = timeit.timeit(stmt, number=number)

    #while t < 0.5:
    #    n *= 10
    #    t = timeit.timeit(stmt, setup, number=n)

    return t / number, number # normalise to time-per-run



 branch = subprocess.check_output("git rev-parse --abbrev-ref HEAD", shell=True).decode('ascii').strip()
 print(branch)
 total_iter = 50000
 for N in [1, 10, 100, 1000, 10000]:
    for method in ['2-point', '3-point', 'cs']:
        xk = np.ones(N)
        duration, trials = auto_timeit(functools.partial(bench, xk, method), number=total_iter // N)
        print(f"branch={branch} N={N}\tmethod={method}\ttime={duration:.8f}s\tloops={trials}")
        with open('foo/bench.csv', 'at') as f:
            f.write(','.join(map(str, (branch, method, N, duration))) + '\n')
diff --git a/bench_branch.sh b/bench_branch.sh
 #!/usr/bin/env bash
 set -euo pipefail
 bench() {
 	git checkout $1
 	git rev-parse --abbrev-ref HEAD
 	python3 dev.py python foo/bench_approx_derivative.py | sed -ne '/Installation OK/,$ p'
 	sleep 1
 }
 echo 'branch,method,dim,time' > foo/bench.csv
 for i in $(seq 1 20); do
 	branches=( 'main' 'njo-numdiff-mem-usage' 'njo-numdiff-loop-exchange' 'njo-numdiff-sep-vars' )
 	branches=( $(shuf -e "${branches[@]}") )
 	for i in "${branches[@]}"
 	do
 		bench "$i"
 	done
 done
diff --git a/benchmark_analysis.ipynb b/benchmark_analysis.ipynb
	from scipy.optimize._numdiff import approx_derivative
	from scipy.optimize import rosen
	import numpy as np
	import timeit
	import functools
	import subprocess
	import sys


	def bench(xk, method):
	approx_derivative(np.linalg.norm, xk, method)


	def auto_timeit(stmt, number):
	# Warmup, throw result away
	timeit.timeit(stmt, number=1)
	t = timeit.timeit(stmt, number=number)

	#while t < 0.5:
	# n *= 10
	# t = timeit.timeit(stmt, setup, number=n)

	return t / number, number # normalise to time-per-run



	branch = subprocess.check_output("git rev-parse --abbrev-ref HEAD", shell=True).decode('ascii').strip()
	print(branch)
	total_iter = 50000
	for N in [1, 10, 100, 1000, 10000]:
	for method in ['2-point', '3-point', 'cs']:
	xk = np.ones(N)
	duration, trials = auto_timeit(functools.partial(bench, xk, method), number=total_iter // N)
	print(f"branch={branch} N={N}\tmethod={method}\ttime={duration:.8f}s\tloops={trials}")
	with open('foo/bench.csv', 'at') as f:
	f.write(','.join(map(str, (branch, method, N, duration))) + '\n')
	#!/usr/bin/env bash
	set -euo pipefail
	bench() {
	git checkout $1
	git rev-parse --abbrev-ref HEAD
	python3 dev.py python foo/bench_approx_derivative.py \| sed -ne '/Installation OK/,$ p'
	sleep 1
	}
	echo 'branch,method,dim,time' > foo/bench.csv
	for i in $(seq 1 20); do
	branches=( 'main' 'njo-numdiff-mem-usage' 'njo-numdiff-loop-exchange' 'njo-numdiff-sep-vars' )
	branches=( $(shuf -e "${branches[@]}") )
	for i in "${branches[@]}"
	do
	bench "$i"
	done
	done