def test_onepoint():
numpy.random.seed(1234)
data = (-numpy.arange(20)) % 10
bsfun = lambda x: x
policy = bootstrap.policy(bsfun, data)
estimator = lambda x : sum(x)
result = policy.run(estimator, data)
for i in range(10):
L, R = policy.resample(result, [i])
assert_array_equal(2 * i, R)
assert_array_equal(2, L)
def test_onepoint():
numpy.random.seed(1234)
data = (-numpy.arange(20)) % 10
bsfun = lambda x: x
policy = bootstrap.policy(bsfun, data)
estimator = lambda x : sum(x)
result = policy.run(estimator, data)
for i in range(10):
L, R = policy.resample(result, [i])
assert_array_equal(2 * i, R)
assert_array_equal(2, L)
def test_paircount():
numpy.random.seed(1234)
data = 1.0 * ((-numpy.arange(4).reshape(-1, 1)) % 2)
data = correlate.points(data)
bsfun = lambda x: numpy.int32(x.pos[:, 0])
policy = bootstrap.policy(bsfun, data)
binning=correlate.RBinning(numpy.linspace(0, 100, 2, endpoint=True))
def estimator( x, y):
r = correlate.paircount(x, y, binning, usefast=False, np=0)
return r.fullsum1
result = policy.run(estimator, data, data)
L, R = policy.resample(result, numpy.arange(2))
assert_array_equal(L, (4, 4))
assert_array_equal(R, (8, 8, 0))
def test_twopoint():
numpy.random.seed(1234)
data = (-numpy.arange(20)) % 10
bsfun = lambda x: x
policy = bootstrap.policy(bsfun, data)
estimator = lambda x, y : sum(x) * sum(y)
result = policy.run(estimator, data, data)
for i in range(10):
L, R = policy.resample(result, [i])
assert_array_equal((2 * i) ** 2, R)
assert_array_equal((2, 2), L)
for i in range(9):
L, R = policy.resample(result, [i, i + 1])
assert_array_equal((2 * i) * (2 * (i + 1)) * 2 + (2 * i) ** 2 + (2 * (i + 1)) ** 2, R)
assert_array_equal((4, 4), L)
def test_paircount():
numpy.random.seed(1234)
data = 1.0 * ((-numpy.arange(4).reshape(-1, 1)) % 2)
data = correlate.points(data)
bsfun = lambda x: numpy.int32(x.pos[:, 0])
policy = bootstrap.policy(bsfun, data)
binning=correlate.RBinning(numpy.linspace(0, 100, 2, endpoint=True))
def estimator( x, y):
r = correlate.paircount(x, y, binning, np=0)
return r.fullsum1
result = policy.run(estimator, data, data)
L, R = policy.resample(result, numpy.arange(2))
assert_array_equal(L, (4, 4))
assert_array_equal(R, (8, 8, 0))
def test_twopoint():
numpy.random.seed(1234)
data = (-numpy.arange(20)) % 10
bsfun = lambda x: x
policy = bootstrap.policy(bsfun, data)
estimator = lambda x, y : sum(x) * sum(y)
result = policy.run(estimator, data, data)
for i in range(10):
L, R = policy.resample(result, [i])
assert_array_equal((2 * i) ** 2, R)
assert_array_equal((2, 2), L)
for i in range(9):
L, R = policy.resample(result, [i, i + 1])
assert_array_equal((2 * i) * (2 * (i + 1)) * 2 + (2 * i) ** 2 + (2 * (i + 1)) ** 2, R)
assert_array_equal((4, 4), L)