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Merge pull request #2 from better/pytest
use pytest
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import pytest, random, math, numpy, time, functools | ||
import irr | ||
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def run_many(case): | ||
@functools.wraps(case) | ||
def wrapped(): | ||
for test in range(1000): | ||
d, r = case() | ||
assert irr.irr(d) == pytest.approx(r) | ||
return wrapped | ||
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@run_many | ||
def test_simple_bond(): | ||
r = math.exp(random.gauss(0, 1)) - 1 | ||
x = random.gauss(0, 1) | ||
d = [x / (1 + r), -x] | ||
return d, r | ||
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@run_many | ||
def test_slightly_longer_bond(n=10): | ||
r = math.exp(random.gauss(0, 1)) - 1 | ||
x = random.gauss(0, 1) | ||
d = [x] + [0.0] * (n-2) + [-x * (1+r)**(n-1)] | ||
return d, r | ||
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@run_many | ||
def test_more_nonzero(n=10): | ||
r = math.exp(random.gauss(0, 1)) - 1 | ||
d = [random.random() for i in range(n-1)] | ||
d.append(-sum([x * (1+r)**(n-i-1) for i, x in enumerate(d)])) | ||
return d, r | ||
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def test_performance(): | ||
us_times = [] | ||
np_times = [] | ||
ns = [10, 20, 50, 100] | ||
for n in ns: | ||
k = 100 | ||
sums = [0.0, 0.0] | ||
for j in range(k): | ||
r = math.exp(random.gauss(0, 1.0 / n)) - 1 | ||
x = random.gauss(0, 1) | ||
d = [x] + [0.0] * (n-2) + [-x * (1+r)**(n-1)] | ||
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results = [] | ||
for i, f in enumerate([irr.irr, numpy.irr]): | ||
t0 = time.time() | ||
results.append(f(d)) | ||
sums[i] += time.time() - t0 | ||
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if not numpy.isnan(results[1]): | ||
assert results[0] == pytest.approx(results[1]) | ||
for times, sum in zip([us_times, np_times], sums): | ||
times.append(sum/k) | ||
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try: | ||
from matplotlib import pyplot | ||
import seaborn | ||
except ImportError: | ||
return | ||
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pyplot.plot(ns, us_times, label='Our library') | ||
pyplot.plot(ns, np_times, label='Numpy') | ||
pyplot.xlabel('n') | ||
pyplot.ylabel('time(s)') | ||
pyplot.yscale('log') | ||
pyplot.savefig('plot.png') | ||
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