diff options
Diffstat (limited to 'numpy/lib/tests/test_function_base.py')
| -rw-r--r-- | numpy/lib/tests/test_function_base.py | 112 |
1 files changed, 56 insertions, 56 deletions
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py index 65519d0bc..28f094653 100644 --- a/numpy/lib/tests/test_function_base.py +++ b/numpy/lib/tests/test_function_base.py @@ -174,10 +174,10 @@ class TestInsert(TestCase): assert_equal(insert(a, 0, 1), [1, 1, 2, 3]) assert_equal(insert(a, 3, 1), [1, 2, 3, 1]) assert_equal(insert(a, [1, 1, 1], [1, 2, 3]), [1, 1, 2, 3, 2, 3]) - assert_equal(insert(a, 1,[1,2,3]), [1, 1, 2, 3, 2, 3]) - assert_equal(insert(a,[1,-1,3],9),[1,9,2,9,3,9]) - assert_equal(insert(a,slice(-1,None,-1), 9),[9,1,9,2,9,3]) - assert_equal(insert(a,[-1,1,3], [7,8,9]),[1,8,2,7,3,9]) + assert_equal(insert(a, 1, [1, 2, 3]), [1, 1, 2, 3, 2, 3]) + assert_equal(insert(a, [1, -1, 3], 9), [1, 9, 2, 9, 3, 9]) + assert_equal(insert(a, slice(-1, None, -1), 9), [9, 1, 9, 2, 9, 3]) + assert_equal(insert(a, [-1, 1, 3], [7, 8, 9]), [1, 8, 2, 7, 3, 9]) b = np.array([0, 1], dtype=np.float64) assert_equal(insert(b, 0, b[0]), [0., 0., 1.]) assert_equal(insert(b, [], []), b) @@ -185,42 +185,42 @@ class TestInsert(TestCase): #assert_equal(insert(a, np.array([True]*4), 9), [9,1,9,2,9,3,9]) with warnings.catch_warnings(record=True) as w: warnings.filterwarnings('always', '', FutureWarning) - assert_equal(insert(a, np.array([True]*4), 9), [1,9,9,9,9,2,3]) + assert_equal(insert(a, np.array([True]*4), 9), [1, 9, 9, 9, 9, 2, 3]) assert_(w[0].category is FutureWarning) def test_multidim(self): a = [[1, 1, 1]] r = [[2, 2, 2], [1, 1, 1]] - assert_equal(insert(a, 0, [1]), [1,1,1,1]) + assert_equal(insert(a, 0, [1]), [1, 1, 1, 1]) assert_equal(insert(a, 0, [2, 2, 2], axis=0), r) assert_equal(insert(a, 0, 2, axis=0), r) assert_equal(insert(a, 2, 2, axis=1), [[1, 1, 2, 1]]) a = np.array([[1, 1], [2, 2], [3, 3]]) - b = np.arange(1,4).repeat(3).reshape(3,3) - c = np.concatenate((a[:,0:1], np.arange(1,4).repeat(3).reshape(3,3).T, - a[:,1:2]), axis=1) - assert_equal(insert(a, [1], [[1],[2],[3]], axis=1), b) + b = np.arange(1, 4).repeat(3).reshape(3, 3) + c = np.concatenate((a[:, 0:1], np.arange(1, 4).repeat(3).reshape(3, 3).T, + a[:, 1:2]), axis=1) + assert_equal(insert(a, [1], [[1], [2], [3]], axis=1), b) assert_equal(insert(a, [1], [1, 2, 3], axis=1), c) # scalars behave differently, in this case exactly opposite: assert_equal(insert(a, 1, [1, 2, 3], axis=1), b) - assert_equal(insert(a, 1, [[1],[2],[3]], axis=1), c) + assert_equal(insert(a, 1, [[1], [2], [3]], axis=1), c) - a = np.arange(4).reshape(2,2) - assert_equal(insert(a[:,:1], 1, a[:,1], axis=1), a) + a = np.arange(4).reshape(2, 2) + assert_equal(insert(a[:, :1], 1, a[:, 1], axis=1), a) assert_equal(insert(a[:1,:], 1, a[1,:], axis=0), a) # negative axis value - a = np.arange(24).reshape((2,3,4)) - assert_equal(insert(a, 1, a[:,:,3], axis=-1), - insert(a, 1, a[:,:,3], axis=2)) - assert_equal(insert(a, 1, a[:,2,:], axis=-2), - insert(a, 1, a[:,2,:], axis=1)) + a = np.arange(24).reshape((2, 3, 4)) + assert_equal(insert(a, 1, a[:,:, 3], axis=-1), + insert(a, 1, a[:,:, 3], axis=2)) + assert_equal(insert(a, 1, a[:, 2,:], axis=-2), + insert(a, 1, a[:, 2,:], axis=1)) # invalid axis value - assert_raises(IndexError, insert, a, 1, a[:,2,:], axis=3) - assert_raises(IndexError, insert, a, 1, a[:,2,:], axis=-4) + assert_raises(IndexError, insert, a, 1, a[:, 2,:], axis=3) + assert_raises(IndexError, insert, a, 1, a[:, 2,:], axis=-4) def test_0d(self): # This is an error in the future @@ -236,9 +236,9 @@ class TestInsert(TestCase): a = np.arange(10).view(SubClass) assert_(isinstance(np.insert(a, 0, [0]), SubClass)) assert_(isinstance(np.insert(a, [], []), SubClass)) - assert_(isinstance(np.insert(a, [0,1], [1,2]), SubClass)) - assert_(isinstance(np.insert(a, slice(1,2), [1,2]), SubClass)) - assert_(isinstance(np.insert(a, slice(1,-2), []), SubClass)) + assert_(isinstance(np.insert(a, [0, 1], [1, 2]), SubClass)) + assert_(isinstance(np.insert(a, slice(1, 2), [1, 2]), SubClass)) + assert_(isinstance(np.insert(a, slice(1, -2), []), SubClass)) # This is an error in the future: a = np.array(1).view(SubClass) assert_(isinstance(np.insert(a, 0, [0]), SubClass)) @@ -355,10 +355,10 @@ class TestDiff(TestCase): def test_nd(self): x = 20 * rand(10, 20, 30) - out1 = x[:, :, 1:] - x[:, :, :-1] - out2 = out1[:, :, 1:] - out1[:, :, :-1] - out3 = x[1:, :, :] - x[:-1, :, :] - out4 = out3[1:, :, :] - out3[:-1, :, :] + out1 = x[:,:, 1:] - x[:,:, :-1] + out2 = out1[:,:, 1:] - out1[:,:, :-1] + out3 = x[1:,:,:] - x[:-1,:,:] + out4 = out3[1:,:,:] - out3[:-1,:,:] assert_array_equal(diff(x), out1) assert_array_equal(diff(x, n=2), out2) assert_array_equal(diff(x, axis=0), out3) @@ -368,7 +368,7 @@ class TestDiff(TestCase): class TestDelete(TestCase): def setUp(self): self.a = np.arange(5) - self.nd_a = np.arange(5).repeat(2).reshape(1,5,2) + self.nd_a = np.arange(5).repeat(2).reshape(1, 5, 2) def _check_inverse_of_slicing(self, indices): a_del = delete(self.a, indices) @@ -380,8 +380,8 @@ class TestDelete(TestCase): indices = indices[(indices >= 0) & (indices < 5)] assert_array_equal(setxor1d(a_del, self.a[indices,]), self.a, err_msg=msg) - xor = setxor1d(nd_a_del[0,:,0], self.nd_a[0,indices,0]) - assert_array_equal(xor, self.nd_a[0,:,0], err_msg=msg) + xor = setxor1d(nd_a_del[0,:, 0], self.nd_a[0, indices, 0]) + assert_array_equal(xor, self.nd_a[0,:, 0], err_msg=msg) def test_slices(self): lims = [-6, -2, 0, 1, 2, 4, 5] @@ -394,7 +394,7 @@ class TestDelete(TestCase): def test_fancy(self): # Deprecation/FutureWarning tests should be kept after change. - self._check_inverse_of_slicing(np.array([[0,1],[2,1]])) + self._check_inverse_of_slicing(np.array([[0, 1], [2, 1]])) assert_raises(DeprecationWarning, delete, self.a, [100]) assert_raises(DeprecationWarning, delete, self.a, [-100]) with warnings.catch_warnings(record=True) as w: @@ -422,9 +422,9 @@ class TestDelete(TestCase): a = self.a.view(SubClass) assert_(isinstance(delete(a, 0), SubClass)) assert_(isinstance(delete(a, []), SubClass)) - assert_(isinstance(delete(a, [0,1]), SubClass)) - assert_(isinstance(delete(a, slice(1,2)), SubClass)) - assert_(isinstance(delete(a, slice(1,-2)), SubClass)) + assert_(isinstance(delete(a, [0, 1]), SubClass)) + assert_(isinstance(delete(a, slice(1, 2)), SubClass)) + assert_(isinstance(delete(a, slice(1, -2)), SubClass)) class TestGradient(TestCase): def test_basic(self): @@ -598,7 +598,7 @@ class TestVectorize(TestCase): while _p: res = res*x + _p.pop(0) return res - vpolyval = np.vectorize(mypolyval, excluded=['p',1]) + vpolyval = np.vectorize(mypolyval, excluded=['p', 1]) ans = [3, 6] assert_array_equal(ans, vpolyval(x=[0, 1], p=[1, 2, 3])) assert_array_equal(ans, vpolyval([0, 1], p=[1, 2, 3])) @@ -776,18 +776,18 @@ class TestTrapz(TestCase): wz[0] /= 2 wz[-1] /= 2 - q = x[:, None, None] + y[None, :, None] + z[None, None, :] + q = x[:, None, None] + y[None,:, None] + z[None, None,:] qx = (q * wx[:, None, None]).sum(axis=0) - qy = (q * wy[None, :, None]).sum(axis=1) - qz = (q * wz[None, None, :]).sum(axis=2) + qy = (q * wy[None,:, None]).sum(axis=1) + qz = (q * wz[None, None,:]).sum(axis=2) # n-d `x` r = trapz(q, x=x[:, None, None], axis=0) assert_almost_equal(r, qx) - r = trapz(q, x=y[None, :, None], axis=1) + r = trapz(q, x=y[None,:, None], axis=1) assert_almost_equal(r, qy) - r = trapz(q, x=z[None, None, :], axis=2) + r = trapz(q, x=z[None, None,:], axis=2) assert_almost_equal(r, qz) # 1-d `x` @@ -1052,7 +1052,7 @@ class TestHistogramdd(TestCase): def test_identical_samples(self): x = np.zeros((10, 2), int) hist, edges = histogramdd(x, bins=2) - assert_array_equal(edges[0], np.array([-0.5, 0. , 0.5])) + assert_array_equal(edges[0], np.array([-0.5, 0., 0.5])) def test_empty(self): a, b = histogramdd([[], []], bins=([0, 1], [0, 1])) @@ -1114,23 +1114,23 @@ class TestCheckFinite(TestCase): class TestCorrCoef(TestCase): A = np.array([[ 0.15391142, 0.18045767, 0.14197213], [ 0.70461506, 0.96474128, 0.27906989], - [ 0.9297531 , 0.32296769, 0.19267156]]) - B = np.array([[ 0.10377691, 0.5417086 , 0.49807457], + [ 0.9297531, 0.32296769, 0.19267156]]) + B = np.array([[ 0.10377691, 0.5417086, 0.49807457], [ 0.82872117, 0.77801674, 0.39226705], - [ 0.9314666 , 0.66800209, 0.03538394]]) - res1 = np.array([[ 1. , 0.9379533 , -0.04931983], - [ 0.9379533 , 1. , 0.30007991], + [ 0.9314666, 0.66800209, 0.03538394]]) + res1 = np.array([[ 1., 0.9379533, -0.04931983], + [ 0.9379533, 1., 0.30007991], [-0.04931983, 0.30007991, 1. ]]) - res2 = np.array([[ 1. , 0.9379533 , -0.04931983, + res2 = np.array([[ 1., 0.9379533, -0.04931983, 0.30151751, 0.66318558, 0.51532523], - [ 0.9379533 , 1. , 0.30007991, + [ 0.9379533, 1., 0.30007991, - 0.04781421, 0.88157256, 0.78052386], - [-0.04931983, 0.30007991, 1. , + [-0.04931983, 0.30007991, 1., - 0.96717111, 0.71483595, 0.83053601], [ 0.30151751, -0.04781421, -0.96717111, - 1. , -0.51366032, -0.66173113], + 1., -0.51366032, -0.66173113], [ 0.66318558, 0.88157256, 0.71483595, - - 0.51366032, 1. , 0.98317823], + - 0.51366032, 1., 0.98317823], [ 0.51532523, 0.78052386, 0.83053601, - 0.66173113, 0.98317823, 1. ]]) @@ -1160,10 +1160,10 @@ class TestCov(TestCase): class Test_I0(TestCase): def test_simple(self): assert_almost_equal(i0(0.5), np.array(1.0634833707413234)) - A = np.array([ 0.49842636, 0.6969809 , 0.22011976, 0.0155549]) + A = np.array([ 0.49842636, 0.6969809, 0.22011976, 0.0155549]) assert_almost_equal(i0(A), np.array([ 1.06307822, 1.12518299, 1.01214991, 1.00006049])) - B = np.array([[ 0.827002 , 0.99959078], + B = np.array([[ 0.827002, 0.99959078], [ 0.89694769, 0.39298162], [ 0.37954418, 0.05206293], [ 0.36465447, 0.72446427], @@ -1173,7 +1173,7 @@ class Test_I0(TestCase): [ 1.21147086, 1.0389829 ], [ 1.03633899, 1.00067775], [ 1.03352052, 1.13557954], - [ 1.0588429 , 1.06432317]])) + [ 1.0588429, 1.06432317]])) class TestKaiser(TestCase): @@ -1182,10 +1182,10 @@ class TestKaiser(TestCase): assert_(np.isfinite(kaiser(1, 1.0))) assert_almost_equal(kaiser(2, 1.0), np.array([ 0.78984831, 0.78984831])) assert_almost_equal(kaiser(5, 1.0), - np.array([ 0.78984831, 0.94503323, 1. , + np.array([ 0.78984831, 0.94503323, 1., 0.94503323, 0.78984831])) assert_almost_equal(kaiser(5, 1.56789), - np.array([ 0.58285404, 0.88409679, 1. , + np.array([ 0.58285404, 0.88409679, 1., 0.88409679, 0.58285404])) def test_int_beta(self): |