diff options
Diffstat (limited to 'numpy/lib/tests/test_function_base.py')
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 41 |
1 files changed, 32 insertions, 9 deletions
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index f1b64c8d5..82aa5efb1 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -382,7 +382,8 @@ class TestHistogram(NumpyTestCase): (a,b)=histogram(v) #check if the sum of the bins equals the number of samples assert(sum(a,axis=0)==n) - #check that the bin counts are evenly spaced when the data is from a linear function + #check that the bin counts are evenly spaced when the data is from a + # linear function (a,b)=histogram(linspace(0,10,100)) assert(all(a==10)) @@ -391,17 +392,21 @@ class TestHistogramdd(NumpyTestCase): x = array([[-.5, .5, 1.5], [-.5, 1.5, 2.5], [-.5, 2.5, .5], \ [.5, .5, 1.5], [.5, 1.5, 2.5], [.5, 2.5, 2.5]]) H, edges = histogramdd(x, (2,3,3), range = [[-1,1], [0,3], [0,3]]) - answer = asarray([[[0,1,0], [0,0,1], [1,0,0]], [[0,1,0], [0,0,1], [0,0,1]]]) + answer = asarray([[[0,1,0], [0,0,1], [1,0,0]], [[0,1,0], [0,0,1], + [0,0,1]]]) assert_array_equal(H,answer) # Check normalization ed = [[-2,0,2], [0,1,2,3], [0,1,2,3]] H, edges = histogramdd(x, bins = ed, normed = True) assert(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) - answer = asarray([[[0,1,0,0], [0,0,1,0], [1,0,0,0]], [[0,1,0,0], [0,0,1,0], [0,0,1,0]]]) + H, edges = histogramdd(x, (2,3,4), range = [[-1,1], [0,3], [0,4]], + normed=True) + answer = asarray([[[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) - # Check that a sequence of arrays is accepted and H has the correct shape. + # Check that a sequence of arrays is accepted and H has the correct + # shape. z = [squeeze(y) for y in split(x,3,axis=1)] H, edges = histogramdd(z, bins=(4,3,2),range=[[-2,2], [0,3], [0,2]]) answer = asarray([[[0,0],[0,0],[0,0]], @@ -415,10 +420,28 @@ class TestHistogramdd(NumpyTestCase): H,edges = histogramdd([arange(5), arange(5), arange(5)], 5) assert_array_equal(H, Z) - def check_shape(self): - x = rand(100,3) - hist3d, edges = histogramdd(x, bins = (5, 7, 6)) - assert_array_equal(hist3d.shape, (5,7,6)) + def check_shape_3d(self): + # All possible permutations for bins of different lengths in 3D. + bins = ((5, 4, 6), (6, 4, 5), (5, 6, 4), (4, 6, 5), (6, 5, 4), + (4, 5, 6)) + r = rand(10,3) + for b in bins: + H, edges = histogramdd(r, b) + assert(H.shape == b) + + def check_shape_4d(self): + # All possible permutations for bins of different lengths in 4D. + bins = ((7, 4, 5, 6), (4, 5, 7, 6), (5, 6, 4, 7), (7, 6, 5, 4), + (5, 7, 6, 4), (4, 6, 7, 5), (6, 5, 7, 4), (7, 5, 4, 6), + (7, 4, 6, 5), (6, 4, 7, 5), (6, 7, 5, 4), (4, 6, 5, 7), + (4, 7, 5, 6), (5, 4, 6, 7), (5, 7, 4, 6), (6, 7, 4, 5), + (6, 5, 4, 7), (4, 7, 6, 5), (4, 5, 6, 7), (7, 6, 4, 5), + (5, 4, 7, 6), (5, 6, 7, 4), (6, 4, 5, 7), (7, 5, 6, 4)) + + r = rand(10,4) + for b in bins: + H, edges = histogramdd(r, b) + assert(H.shape == b) def check_weights(self): v = rand(100,2) |