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Created October 30, 2023 10:57
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"cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.002878416795283556, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0028727082535624504, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.002881458029150963, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0028813332319259644, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.002902541309595108, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0029092920012772083, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0029048342257738113, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0029083327390253544, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0028989999555051327, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0029077501967549324, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}, {"key": "float_array-float_array_2", "timing": 0.0029000421054661274, "eq_nan": false, "git_rev": "cdfbdf428d9df9c7119cecae323512a4cd3f57b7"}]
import numpy as np
import numpy
import seaborn as sns
import pandas as pd
import json
import matplotlib.pyplot as plt
base = np.random.randint(1, 100, (1000, 1000), dtype='int64')
a = base.copy()
a1 = base.copy()
b = base.copy().astype('float')
b[b == 50] = np.nan
b1 = b.copy()
data = {'int_array':a, 'float_array':b, 'int_array_2':a1, 'float_array_2': b1}
timings = {}
for (x, y) in [('int_array','int_array'),('int_array','int_array_2'),('float_array','float_array'),('float_array','float_array_2')]:
ax = data[x]
bx = data[y]
for en in [True, False]:
key = (x,y,en)
res = np.array_equal(ax, bx, equal_nan=en)
print(f"np.array_equal({x}, {y}, equal_nan={en}) == {res}")
timing = %timeit -n10 -r100 -o np.array_equal(ax, bx, equal_nan=en)
timings[key] = timing
data2 = []
for (x,y,en),v in timings.items():
for t in v.all_runs:
data2.append({'key':f"{x}-{y}", 'timing':t, 'eq_nan':en, 'git_rev':numpy.version.git_revision})
rev = numpy.version.git_revision
with open(f'data-numpy-{rev}.json', 'w') as f:
f.write(json.dumps(data2))
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