diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/lib/arraysetops.py | 24 | ||||
| -rw-r--r-- | numpy/lib/tests/test_arraysetops.py | 25 |
2 files changed, 32 insertions, 17 deletions
diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py index 5880ea154..d84455a8f 100644 --- a/numpy/lib/arraysetops.py +++ b/numpy/lib/arraysetops.py @@ -312,12 +312,12 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False. return_indices : bool - If True, the indices which correspond to the intersection of the - two arrays are returned. The first instance of a value is used - if there are multiple. Default is False. - - .. versionadded:: 1.15.0 - + If True, the indices which correspond to the intersection of the two + arrays are returned. The first instance of a value is used if there are + multiple. Default is False. + + .. versionadded:: 1.15.0 + Returns ------- intersect1d : ndarray @@ -326,7 +326,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): The indices of the first occurrences of the common values in `ar1`. Only provided if `return_indices` is True. comm2 : ndarray - The indices of the first occurrences of the common values in `ar2`. + The indices of the first occurrences of the common values in `ar2`. Only provided if `return_indices` is True. @@ -345,7 +345,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): >>> from functools import reduce >>> reduce(np.intersect1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2])) array([3]) - + To return the indices of the values common to the input arrays along with the intersected values: >>> x = np.array([1, 1, 2, 3, 4]) @@ -355,8 +355,11 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): (array([0, 2, 4]), array([1, 0, 2])) >>> xy, x[x_ind], y[y_ind] (array([1, 2, 4]), array([1, 2, 4]), array([1, 2, 4])) - + """ + ar1 = np.asanyarray(ar1) + ar2 = np.asanyarray(ar2) + if not assume_unique: if return_indices: ar1, ind1 = unique(ar1, return_index=True) @@ -367,7 +370,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): else: ar1 = ar1.ravel() ar2 = ar2.ravel() - + aux = np.concatenate((ar1, ar2)) if return_indices: aux_sort_indices = np.argsort(aux, kind='mergesort') @@ -389,6 +392,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): else: return int1d + def setxor1d(ar1, ar2, assume_unique=False): """ Find the set exclusive-or of two arrays. diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py index dace5ade8..c76afb8e5 100644 --- a/numpy/lib/tests/test_arraysetops.py +++ b/numpy/lib/tests/test_arraysetops.py @@ -30,19 +30,30 @@ class TestSetOps(object): ed = np.array([1, 2, 5]) c = intersect1d(a, b) assert_array_equal(c, ed) - assert_array_equal([], intersect1d([], [])) - + + def test_intersect1d_array_like(self): + # See gh-11772 + class Test(object): + def __array__(self): + return np.arange(3) + + a = Test() + res = intersect1d(a, a) + assert_array_equal(res, a) + res = intersect1d([1, 2, 3], [1, 2, 3]) + assert_array_equal(res, [1, 2, 3]) + def test_intersect1d_indices(self): # unique inputs - a = np.array([1, 2, 3, 4]) + a = np.array([1, 2, 3, 4]) b = np.array([2, 1, 4, 6]) c, i1, i2 = intersect1d(a, b, assume_unique=True, return_indices=True) ee = np.array([1, 2, 4]) assert_array_equal(c, ee) assert_array_equal(a[i1], ee) assert_array_equal(b[i2], ee) - + # non-unique inputs a = np.array([1, 2, 2, 3, 4, 3, 2]) b = np.array([1, 8, 4, 2, 2, 3, 2, 3]) @@ -51,7 +62,7 @@ class TestSetOps(object): assert_array_equal(c, ef) assert_array_equal(a[i1], ef) assert_array_equal(b[i2], ef) - + # non1d, unique inputs a = np.array([[2, 4, 5, 6], [7, 8, 1, 15]]) b = np.array([[3, 2, 7, 6], [10, 12, 8, 9]]) @@ -61,7 +72,7 @@ class TestSetOps(object): ea = np.array([2, 6, 7, 8]) assert_array_equal(ea, a[ui1]) assert_array_equal(ea, b[ui2]) - + # non1d, not assumed to be uniqueinputs a = np.array([[2, 4, 5, 6, 6], [4, 7, 8, 7, 2]]) b = np.array([[3, 2, 7, 7], [10, 12, 8, 7]]) @@ -71,7 +82,7 @@ class TestSetOps(object): ea = np.array([2, 7, 8]) assert_array_equal(ea, a[ui1]) assert_array_equal(ea, b[ui2]) - + def test_setxor1d(self): a = np.array([5, 7, 1, 2]) b = np.array([2, 4, 3, 1, 5]) |