benchmarks_16.7.0x86_64Darwin_2017-11-06 17h15m49s.csv

system information: Intel(R) Core(TM) i7-5557U CPU @ 3.10GHz16.7.0x86_64Darwin2.7.13
n, basex, basex_bs, direct_C, direct_C_f, direct_Python, direct_Python_f, hansenlaw, hansenlaw_f, linbasex, linbasex_bs, onion_bordas, onion_peeling, onion_peeling_bs, two_point, two_point_bs, three_point, three_point_bs, 
101,        0.355,      307.988,        1.073,        0.889,        8.973,        8.731,        2.977,        2.035,        7.562,        0.989,       46.556,        0.075,        0.624,        0.082,        0.829,        0.074,        1.667, 
145,        0.853,      806.014,        2.352,        4.204,       18.338,       19.016,        5.344,        4.279,       11.060,        1.706,      121.463,        0.144,        0.845,        0.217,        0.912,        0.540,        3.066, 
213,        2.293,     2126.145,        7.182,        5.839,       44.457,       40.238,       11.123,        4.818,       25.126,        3.690,      227.825,        0.344,        2.059,        0.473,        2.236,        0.320,        6.775, 
311,        5.762,     5313.606,       35.206,       18.407,      168.899,      121.702,       25.027,        9.351,       91.040,        8.513,      752.732,        1.408,        3.905,        2.547,        5.386,        1.028,       12.482, 
453,       29.575,    12562.603,       56.263,       52.017,      500.339,      565.410,       52.389,       16.747,      140.989,       24.919,     1285.347,        2.921,       12.818,        3.203,       11.437,        3.281,       30.384, 
661,       83.989,    29769.498,      179.122,      167.475,     1723.701,     2355.122,       88.457,       32.452,      258.163,       39.478,     3013.935,       12.558,       25.534,        8.811,       30.522,        8.137,       88.847, 

plot_benchmarks_txt.py

import numpy as np
import matplotlib.pyplot as plt

filename = 'benchmarks_16.7.0x86_64Darwin_2017-11-06 17h15m49s.csv'

with open(filename,'r') as f:
    system = f.readline()[12:]
    methods = f.readline().split(', ')[1:-1]

data = np.loadtxt(filename, delimiter=',', skiprows=2, usecols=range(0,len(methods)+1))
n = data[:,0]

fig, ax = plt.subplots()

cnum = 0 # for the colors
for i, meth  in enumerate(methods):
    times = data[:,i+1]

    if '_bs' in meth:
        ls = 'dotted'
    elif '_f' in meth:
        ls = 'dashed'
    else:
        ls = 'solid'
        cnum = cnum+1
  
    ax.plot(n, times, 'o-', color='C%i'%cnum, label=meth, ls=ls)


ax.set_xlabel("Image size")
ax.set_ylabel("Time (ms)")
ax.set_xscale('log')
ax.set_yscale('log')
ax.legend(fontsize='small', frameon=True, loc=4, numpoints=1, labelspacing=0.1)
ax.set_title(system, fontsize='smaller')
ax.axis(xmax=1.0e4, ymin=1.0e-2)

plt.savefig('benchmarks.png', dpi=100)
plt.show()

run_benchmarks_txt.py

from __future__ import print_function
import numpy as np
import abel
import sys
import time
import platform
import cpuinfo 

maxtime = 100000 # maximum execution time period before method is excluded from timing (milliseconds)

sizes = np.logspace(np.log10(100), np.log10(3000), 10)
n_max_bs   = 10000
n_max_slow = 10000
transform_repeat = 2 # for less than 10000

methods = ['basex', 'direct_C', 'direct_Python', 'hansenlaw', 'linbasex','onion_bordas', 'onion_peeling', 'two_point', 'three_point']
select = methods[:] # make a copy

# system information --------------
cpu = cpuinfo.get_cpu_info().get('brand')
os =  platform.release() + platform.machine() + platform.system()
pyv = platform.python_version()
system = cpu + os + pyv
print('\n'+system+'\n')

time_string = time.strftime("%Y-%m-%d %Hh%Mm%Ss", time.gmtime())

outfilename = 'benchmarks_' + os + '_' + time_string + '.csv'
print('Saving to:  %s\n\n'%outfilename)

outfile = open(outfilename, 'w')
outfile.write('system information: ' + system + '\n')

all_methods = ['basex','basex_bs', 'direct_C', 'direct_C_f', 'direct_Python', 'direct_Python_f', 'hansenlaw', 'hansenlaw_f', 'linbasex', 'linbasex_bs', 'onion_bordas','onion_peeling', 'onion_peeling_bs', 'two_point', 'two_point_bs', 'three_point', 'three_point_bs']

def print_and_write(s): # conveience function to print and write to output file at the same time
    print(s, end='')
    outfile.write(s)

# write the outputfile header:
print_and_write('n, ')
for method in all_methods:
    print_and_write(method+', ')
print_and_write('\n')

for i, n in enumerate(sizes):
    n = int( (n//2)*2 + 1 )  # force odd size
    
    if n > 10000: 
        transform_repeat = 1
        
    try:
        res = abel.benchmark.AbelTiming([n], select=select, n_max_bs=n_max_bs,
                   n_max_slow=n_max_slow, transform_repeat=transform_repeat)
    except KeyboardInterrupt:
        outfile.close()
        sys.exit()
    
    print_and_write('%i, '%n)
    
    for method in select:
        iabel = res.iabel[method][0]
        print_and_write('% 12.3f, '%iabel)
        
        if method + '_f' in all_methods:
            try:
                fabel = res.fabel[method][0]
                print_and_write('% 12.3f, '%fabel)
            except:
                fabel = None
                print_and_write('% 12.3f, '%0)
        else:
            fabel = None

        if method + '_bs' in all_methods:
            try:
                bs = res.bs[method+'_bs'][0]
                print_and_write('% 12.3f, '%bs)
            
            except:
                bs = None
                print_and_write('%12.3f, '%0)
        else:
            bs = None
            
        # drop methods that are taking too long
        if iabel > maxtime:
            select.remove(method)
        elif bs is not None and bs > maxtime:
            select.remove(method)
    
    print_and_write('\n')
    outfile.flush()

outfile.close()
print('complete!!')