diff options
Diffstat (limited to 'numpy/lib/tests/test_histograms.py')
| -rw-r--r-- | numpy/lib/tests/test_histograms.py | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py index 08f605b57..a26ed29a5 100644 --- a/numpy/lib/tests/test_histograms.py +++ b/numpy/lib/tests/test_histograms.py @@ -535,13 +535,13 @@ class TestHistogramdd(object): # Check normalization ed = [[-2, 0, 2], [0, 1, 2, 3], [0, 1, 2, 3]] - H, edges = histogramdd(x, bins=ed, normed=True) + H, edges = histogramdd(x, bins=ed, density=True) assert_(np.all(H == answer / 12.)) # Check that H has the correct shape. H, edges = histogramdd(x, (2, 3, 4), range=[[-1, 1], [0, 3], [0, 4]], - normed=True) + density=True) answer = np.array([[[0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 0]], [[0, 1, 0, 0], [0, 0, 1, 0], [0, 0, 1, 0]]]) assert_array_almost_equal(H, answer / 6., 4) @@ -587,10 +587,10 @@ class TestHistogramdd(object): def test_weights(self): v = np.random.rand(100, 2) hist, edges = histogramdd(v) - n_hist, edges = histogramdd(v, normed=True) + n_hist, edges = histogramdd(v, density=True) w_hist, edges = histogramdd(v, weights=np.ones(100)) assert_array_equal(w_hist, hist) - w_hist, edges = histogramdd(v, weights=np.ones(100) * 2, normed=True) + w_hist, edges = histogramdd(v, weights=np.ones(100) * 2, density=True) assert_array_equal(w_hist, n_hist) w_hist, edges = histogramdd(v, weights=np.ones(100, int) * 2) assert_array_equal(w_hist, 2 * hist) @@ -696,7 +696,7 @@ class TestHistogramdd(object): assert_equal(hist[0, 0], 1) - def test_normed_non_uniform_2d(self): + def test_density_non_uniform_2d(self): # Defines the following grid: # # 0 2 8 @@ -720,14 +720,14 @@ class TestHistogramdd(object): assert_equal(hist, relative_areas) # resulting histogram should be uniform, since counts and areas are propotional - hist, edges = histogramdd((y, x), bins=(y_edges, x_edges), normed=True) + hist, edges = histogramdd((y, x), bins=(y_edges, x_edges), density=True) assert_equal(hist, 1 / (8*8)) - def test_normed_non_uniform_1d(self): + def test_density_non_uniform_1d(self): # compare to histogram to show the results are the same v = np.arange(10) bins = np.array([0, 1, 3, 6, 10]) hist, edges = histogram(v, bins, density=True) - hist_dd, edges_dd = histogramdd((v,), (bins,), normed=True) + hist_dd, edges_dd = histogramdd((v,), (bins,), density=True) assert_equal(hist, hist_dd) assert_equal(edges, edges_dd[0]) |