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# Script to compare the speedup provided by fast-histogram
from timeit import repeat, timeit
import numpy as np
SETUP_1D = """
import numpy as np
from numpy import histogram as np_histogram1d
from fast_histogram import histogram1d
x = np.random.random({size})
"""
NUMPY_1D_STMT = "np_histogram1d(x, range=[-1, 2], bins=30)"
FAST_1D_STMT = "histogram1d(x, range=[-1, 2], bins=30)"
SETUP_2D = """
import numpy as np
from numpy import histogram2d as np_histogram2d
from fast_histogram import histogram2d
x = np.random.random({size})
y = np.random.random({size})
"""
NUMPY_2D_STMT = "np_histogram2d(x, y, range=[[-1, 2], [-2, 4]], bins=30)"
FAST_2D_STMT = "histogram2d(x, y, range=[[-1, 2], [-2, 4]], bins=30)"
# How long each benchmark should aim to take
TARGET_TIME = 1.0
def time_stats(stmt=None, setup=None):
# Call once to check how long it takes
time_single = timeit(stmt=stmt, setup=setup, number=1)
# Find out how many times we can call it. We always call it at least three
# times for accuracy
number = max(3, int(TARGET_TIME / time_single))
print(f" -> estimated time to complete test: {time_single * 10 * number:.1f}s")
times = repeat(stmt=stmt, setup=setup, repeat=10, number=number)
return np.min(times) / number, np.mean(times) / number, np.median(times) / number
FMT_HEADER = "# {:7s}" + " {:10s}" * 12 + "\n"
FMT = "{:9d}" + " {:10.7e}" * 12 + "\n"
with open("benchmark_times.txt", "w") as f:
f.write(
FMT_HEADER.format(
"size",
"np_1d_min",
"np_1d_mean",
"np_1d_median",
"fa_1d_min",
"fa_1d_mean",
"fa_1d_median",
"np_2d_min",
"np_2d_mean",
"np_2d_median",
"fa_2d_min",
"fa_2d_mean",
"fa_2d_median",
)
)
for log10_size in range(0, 9):
size = int(10**log10_size)
print(f"Running benchmarks for size={size}")
np_1d_min, np_1d_mean, np_1d_median = time_stats(
stmt=NUMPY_1D_STMT, setup=SETUP_1D.format(size=size)
)
fa_1d_min, fa_1d_mean, fa_1d_median = time_stats(
stmt=FAST_1D_STMT, setup=SETUP_1D.format(size=size)
)
np_2d_min, np_2d_mean, np_2d_median = time_stats(
stmt=NUMPY_2D_STMT, setup=SETUP_2D.format(size=size)
)
fa_2d_min, fa_2d_mean, fa_2d_median = time_stats(
stmt=FAST_2D_STMT, setup=SETUP_2D.format(size=size)
)
f.write(
FMT.format(
size,
np_1d_min,
np_1d_mean,
np_1d_median,
fa_1d_min,
fa_1d_mean,
fa_1d_median,
np_2d_min,
np_2d_mean,
np_2d_median,
fa_2d_min,
fa_2d_mean,
fa_2d_median,
)
)
f.flush()
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