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# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from numpy.testing import assert_allclose
from ...tests.helper import pytest
from .. import histogram, scott_bin_width, freedman_bin_width, knuth_bin_width
try:
import scipy # pylint: disable=W0611
except ImportError:
HAS_SCIPY = False
else:
HAS_SCIPY = True
def test_scott_bin_width(N=10000, rseed=0):
rng = np.random.RandomState(rseed)
X = rng.randn(N)
delta = scott_bin_width(X)
assert_allclose(delta, 3.5 * np.std(X) / N ** (1 / 3))
delta, bins = scott_bin_width(X, return_bins=True)
assert_allclose(delta, 3.5 * np.std(X) / N ** (1 / 3))
with pytest.raises(ValueError):
scott_bin_width(rng.rand(2, 10))
def test_freedman_bin_width(N=10000, rseed=0):
rng = np.random.RandomState(rseed)
X = rng.randn(N)
v25, v75 = np.percentile(X, [25, 75])
delta = freedman_bin_width(X)
assert_allclose(delta, 2 * (v75 - v25) / N ** (1 / 3))
delta, bins = freedman_bin_width(X, return_bins=True)
assert_allclose(delta, 2 * (v75 - v25) / N ** (1 / 3))
with pytest.raises(ValueError):
freedman_bin_width(rng.rand(2, 10))
@pytest.mark.skipif('not HAS_SCIPY')
def test_knuth_bin_width(N=10000, rseed=0):
rng = np.random.RandomState(rseed)
X = rng.randn(N)
dx, bins = knuth_bin_width(X, return_bins=True)
assert_allclose(len(bins), 59)
dx2 = knuth_bin_width(X)
assert dx == dx2
with pytest.raises(ValueError):
knuth_bin_width(rng.rand(2, 10))
@pytest.mark.skipif('not HAS_SCIPY')
def test_knuth_histogram(N=1000, rseed=0):
rng = np.random.RandomState(rseed)
x = rng.randn(N)
counts, bins = histogram(x, 'knuth')
assert (counts.sum() == len(x))
assert (len(counts) == len(bins) - 1)
def test_histogram(N=1000, rseed=0):
rng = np.random.RandomState(rseed)
x = rng.randn(N)
for bins in [30, np.linspace(-5, 5, 31),
'scott', 'freedman', 'blocks']:
counts, bins = histogram(x, bins)
assert (counts.sum() == len(x))
assert (len(counts) == len(bins) - 1)
def test_histogram_range(N=1000, rseed=0):
rng = np.random.RandomState(rseed)
x = rng.randn(N)
range = (0.1, 0.8)
for bins in ['scott', 'freedman', 'blocks']:
counts, bins = histogram(x, bins, range=range)
@pytest.mark.skipif('not HAS_SCIPY')
def test_histogram_output_knuth():
rng = np.random.RandomState(0)
X = rng.randn(100)
counts, bins = histogram(X, bins='knuth')
assert_allclose(counts, [1, 6, 9, 14, 21, 22, 12, 8, 7])
assert_allclose(bins, [-2.55298982, -2.01712932, -1.48126883, -0.94540834,
-0.40954784, 0.12631265, 0.66217314, 1.19803364,
1.73389413, 2.26975462])
def test_histogram_output():
rng = np.random.RandomState(0)
X = rng.randn(100)
counts, bins = histogram(X, bins=10)
assert_allclose(counts, [1, 5, 7, 13, 17, 18, 16, 11, 7, 5])
assert_allclose(bins, [-2.55298982, -2.07071537, -1.58844093, -1.10616648,
-0.62389204, -0.1416176, 0.34065685, 0.82293129,
1.30520574, 1.78748018, 2.26975462])
counts, bins = histogram(X, bins='scott')
assert_allclose(counts, [2, 13, 23, 34, 16, 10, 2])
assert_allclose(bins, [-2.55298982, -1.79299405, -1.03299829, -0.27300252,
0.48699324, 1.24698901, 2.00698477, 2.76698054])
counts, bins = histogram(X, bins='freedman')
assert_allclose(counts, [2, 7, 13, 20, 26, 14, 11, 5, 2])
assert_allclose(bins, [-2.55298982, -1.95796338, -1.36293694, -0.7679105,
-0.17288406, 0.42214237, 1.01716881, 1.61219525,
2.20722169, 2.80224813])
counts, bins = histogram(X, bins='blocks')
assert_allclose(counts, [10, 61, 29])
assert_allclose(bins, [-2.55298982, -1.24381059, 0.46422235, 2.26975462])
def test_histogram_badargs(N=1000, rseed=0):
rng = np.random.RandomState(rseed)
x = rng.randn(N)
# weights is not supported
for bins in ['scott', 'freedman', 'blocks']:
with pytest.raises(NotImplementedError):
histogram(x, bins, weights=x)
# bad bins arg gives ValueError
with pytest.raises(ValueError):
histogram(x, bins='bad_argument')
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