def test_bootstrap():
bootarr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])
# test general bootstrapping
answer = np.array([[7, 4, 8, 5, 7, 0, 3, 7, 8, 5],
[4, 8, 8, 3, 6, 5, 2, 8, 6, 2]])
with NumpyRNGContext(42):
assert_equal(answer, funcs.bootstrap(bootarr, 2))
# test with a bootfunction
with NumpyRNGContext(42):
bootresult = np.mean(funcs.bootstrap(bootarr, 10000, bootfunc=np.mean))
assert_allclose(np.mean(bootarr), bootresult, atol=0.01)
def test_bootstrap():
bootarr = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 0])
# test general bootstrapping
answer = np.array([[7, 4, 8, 5, 7, 0, 3, 7, 8, 5],
[4, 8, 8, 3, 6, 5, 2, 8, 6, 2]])
with NumpyRNGContext(42):
assert_equal(answer, funcs.bootstrap(bootarr, 2))
# test with a bootfunction
with NumpyRNGContext(42):
bootresult = np.mean(funcs.bootstrap(bootarr, 10000, bootfunc=np.mean))
assert_allclose(np.mean(bootarr), bootresult, atol=0.01)
def test_bootstrap_multiple_outputs():
from scipy.stats import spearmanr
# test a bootfunc with several output values
# return just bootstrapping with one output from bootfunc
with NumpyRNGContext(42):
bootarr = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 0],
[4, 8, 8, 3, 6, 5, 2, 8, 6, 2]]).T
answer = np.array((0.19425, 0.02094))
def bootfunc(x): return spearmanr(x)[0]
bootresult = funcs.bootstrap(bootarr, 2,
bootfunc=bootfunc)
assert_allclose(answer, bootresult, atol=1e-3)
# test a bootfunc with several output values
# return just bootstrapping with the second output from bootfunc
with NumpyRNGContext(42):
bootarr = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 0],
[4, 8, 8, 3, 6, 5, 2, 8, 6, 2]]).T
answer = np.array((0.5907,
0.9541))
def bootfunc(x): return spearmanr(x)[1]
bootresult = funcs.bootstrap(bootarr, 2,
bootfunc=bootfunc)
assert_allclose(answer, bootresult, atol=1e-3)
# return just bootstrapping with two outputs from bootfunc
with NumpyRNGContext(42):
answer = np.array(((0.1942, 0.5907),
(0.0209, 0.9541),
(0.4286, 0.2165)))
def bootfunc(x): return spearmanr(x)
bootresult = funcs.bootstrap(bootarr, 3,
bootfunc=bootfunc)
assert bootresult.shape == (3, 2)
assert_allclose(answer, bootresult, atol=1e-3)
def test_bootstrap_multiple_outputs():
from scipy.stats import spearmanr
# test a bootfunc with several output values
# return just bootstrapping with one output from bootfunc
with NumpyRNGContext(42):
bootarr = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 0],
[4, 8, 8, 3, 6, 5, 2, 8, 6, 2]]).T
answer = np.array((0.19425, 0.02094))
def bootfunc(x): return spearmanr(x)[0]
bootresult = funcs.bootstrap(bootarr, 2,
bootfunc=bootfunc)
assert_allclose(answer, bootresult, atol=1e-3)
# test a bootfunc with several output values
# return just bootstrapping with the second output from bootfunc
with NumpyRNGContext(42):
bootarr = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 0],
[4, 8, 8, 3, 6, 5, 2, 8, 6, 2]]).T
answer = np.array((0.5907,
0.9541))
def bootfunc(x): return spearmanr(x)[1]
bootresult = funcs.bootstrap(bootarr, 2,
bootfunc=bootfunc)
assert_allclose(answer, bootresult, atol=1e-3)
# return just bootstrapping with two outputs from bootfunc
with NumpyRNGContext(42):
answer = np.array(((0.1942, 0.5907),
(0.0209, 0.9541),
(0.4286, 0.2165)))
def bootfunc(x): return spearmanr(x)
bootresult = funcs.bootstrap(bootarr, 3,
bootfunc=bootfunc)
assert bootresult.shape == (3, 2)
assert_allclose(answer, bootresult, atol=1e-3)
