numba_benchmarks.ipy

# must be run in ipython

import numpy as np
import trackpy as tp


def b(command):
    get_ipython().magic(command)


dummy_noise_image = np.random.randint(0, 100, (100, 100))
real_image_raw = tp.ImageSequence('../trackpy/tests/video/image_sequence')[0]
real_image = tp.bandpass(real_image_raw, 1, 10, threshold=1)
big_image = tp.bandpass(np.tile(real_image_raw, (2, 5)), 1, 10, threshold=1)

print('Compiling Numba...')
tp.locate(dummy_noise_image, 9, engine='numba')

#print('Locate using Python Engine with Default Settings (Accurate)')
#b(u"timeit tp.locate(real_image, 9, engine='python', preprocess=False)")

print('10x: Locate using Python Engine with Default Settings (Accurate)')
b("timeit tp.locate(big_image, 9, engine='python', preprocess=False)")

print('10x: Locate using Python Engine with Fast Settings (Sloppy)')
b("timeit tp.locate(big_image, 9, engine='python', preprocess=False, filter_before=False, filter_after=False, max_iterations=0, characterize=False)")

print('1x: Locate using Numba Engine with Default Settings (Accurate)')
b("timeit tp.locate(real_image, 9, engine='numba', preprocess=False)")

print('10x: Locate using Numba Engine with Default Settings (Accurate)')
b("timeit tp.locate(big_image, 9, engine='numba', preprocess=False)")

print('10x: Locate using Numba Engine with Fast Settings (Sloppy)')
b("timeit tp.locate(big_image, 9, engine='numba', preprocess=False, filter_before=False, filter_after=False, max_iterations=0, characterize=False)")