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from __future__ import division
import numpy as np
from numpy.testing import assert_allclose, assert_
from astropy.tests.helper import catch_warnings
from astroML.density_estimation import \
scotts_bin_width, freedman_bin_width, knuth_bin_width, histogram
from astroML.utils.exceptions import AstroMLDeprecationWarning
def test_scotts_bin_width(N=10000, rseed=0):
np.random.seed(rseed)
X = np.random.normal(size=N)
with catch_warnings(AstroMLDeprecationWarning):
delta = scotts_bin_width(X)
assert_allclose(delta, 3.5 * np.std(X) / N ** (1. / 3))
def test_freedman_bin_width(N=10000, rseed=0):
np.random.seed(rseed)
X = np.random.normal(size=N)
with catch_warnings(AstroMLDeprecationWarning):
delta = freedman_bin_width(X)
v25, v75 = np.percentile(X, [25, 75])
assert_allclose(delta, 2 * (v75 - v25) / N ** (1. / 3))
def test_knuth_bin_width(N=10000, rseed=0):
np.random.seed(0)
X = np.random.normal(size=N)
with catch_warnings(AstroMLDeprecationWarning):
dx, bins = knuth_bin_width(X, return_bins=True)
assert_allclose(len(bins), 59)
def test_histogram(N=1000, rseed=0):
np.random.seed(0)
x = np.random.normal(0, 1, N)
for bins in [30, np.linspace(-5, 5, 31),
'knuth', 'scotts', 'freedman']:
with catch_warnings(AstroMLDeprecationWarning):
counts, bins = histogram(x, bins)
assert_(counts.sum() == len(x))
assert_(len(counts) == len(bins) - 1)
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