diff options
Diffstat (limited to 'numpy/lib/tests/test_histograms.py')
| -rw-r--r-- | numpy/lib/tests/test_histograms.py | 47 |
1 files changed, 37 insertions, 10 deletions
diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py index a2c684a20..06daacbdc 100644 --- a/numpy/lib/tests/test_histograms.py +++ b/numpy/lib/tests/test_histograms.py @@ -2,13 +2,12 @@ from __future__ import division, absolute_import, print_function import numpy as np -from numpy.lib.histograms import histogram, histogramdd +from numpy.lib.histograms import histogram, histogramdd, histogram_bin_edges from numpy.testing import ( - run_module_suite, assert_, assert_equal, assert_array_equal, - assert_almost_equal, assert_array_almost_equal, assert_raises, - assert_allclose, assert_array_max_ulp, assert_warns, assert_raises_regex, - dec, suppress_warnings, HAS_REFCOUNT, -) + assert_, assert_equal, assert_array_equal, assert_almost_equal, + assert_array_almost_equal, assert_raises, assert_allclose, + assert_array_max_ulp, assert_warns, assert_raises_regex, suppress_warnings, + ) class TestHistogram(object): @@ -346,6 +345,20 @@ class TestHistogram(object): self.do_precision(np.single, np.longdouble) self.do_precision(np.double, np.longdouble) + def test_histogram_bin_edges(self): + hist, e = histogram([1, 2, 3, 4], [1, 2]) + edges = histogram_bin_edges([1, 2, 3, 4], [1, 2]) + assert_array_equal(edges, e) + + arr = np.array([0., 0., 0., 1., 2., 3., 3., 4., 5.]) + hist, e = histogram(arr, bins=30, range=(-0.5, 5)) + edges = histogram_bin_edges(arr, bins=30, range=(-0.5, 5)) + assert_array_equal(edges, e) + + hist, e = histogram(arr, bins='auto', range=(0, 1)) + edges = histogram_bin_edges(arr, bins='auto', range=(0, 1)) + assert_array_equal(edges, e) + class TestHistogramOptimBinNums(object): """ @@ -430,6 +443,24 @@ class TestHistogramOptimBinNums(object): assert_equal(len(a), numbins, err_msg="{0} estimator, " "No Variance test".format(estimator)) + def test_limited_variance(self): + """ + Check when IQR is 0, but variance exists, we return the sturges value + and not the fd value. + """ + lim_var_data = np.ones(1000) + lim_var_data[:3] = 0 + lim_var_data[-4:] = 100 + + edges_auto = histogram_bin_edges(lim_var_data, 'auto') + assert_equal(edges_auto, np.linspace(0, 100, 12)) + + edges_fd = histogram_bin_edges(lim_var_data, 'fd') + assert_equal(edges_fd, np.array([0, 100])) + + edges_sturges = histogram_bin_edges(lim_var_data, 'sturges') + assert_equal(edges_sturges, np.linspace(0, 100, 12)) + def test_outlier(self): """ Check the FD, Scott and Doane with outliers. @@ -629,7 +660,3 @@ class TestHistogramdd(object): range=[[0.0, 1.0], [0.25, 0.75], [0.25, np.inf]]) assert_raises(ValueError, histogramdd, vals, range=[[0.0, 1.0], [np.nan, 0.75], [0.25, 0.5]]) - - -if __name__ == "__main__": - run_module_suite() |