ENH: Modify intersect1d to return common indices (#10684)

* added function commonpts1d

* Update arraysetops.py

* Update arraysetops.py

* modified intersect1d to return common indices

Proposed this idea in previous pull request (https://github.com/numpy/numpy/pull/10683) and made suggested changes for implementing this idea to have relevant common indices that correspond to the values in the intersection of the two arrays.

* update intersect1d with suggested changes

* implemented return_indices options for intersect1d

I've tested out the above code and for the ~10 different test sets I've tried it's worked thus far. It's probably not the cleanest implementation but it works and is vectorized.

* cleaned up structure for intersect1d

* fixed copy-paste error, added second test, changed a conditional

* Testing return_indices in intersect1d

* formatting

* created separate test function  for intersect1d indices, added spaces after commas

* fixed up example and some style

* fixed style

* style change

* removed one example

* removed extra space

* added version number for return_indices

* added 'return_indices' keyword for np.intersect1d

* fixed formatting

* updated return_indices entry

* fixed some typos and style

* added bit about first instance of a value being used

* STY: Fix comment formats

* DOC: missing space

* DOC: correct parameter names in docstring

* made suggested changes

* fixed a mistake from previous update

also added documentation for comm1, comm2 to match doc from np.unique

* added in tests for 2d inputs

* STY: Add missing spaces around commas

* TST: Correct array to actually be unique

* STY: Spaces at beginning of comments

1 files changed, 40 insertions, 1 deletions

diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py
index 984a3b15e..dace5ade8 100644
--- a/numpy/lib/tests/test_arraysetops.py
+++ b/numpy/lib/tests/test_arraysetops.py
@@ -32,7 +32,46 @@ class TestSetOps(object):
         assert_array_equal(c, ed)
 
         assert_array_equal([], intersect1d([], []))
-
+        
+    def test_intersect1d_indices(self):
+        # unique inputs
+        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])
+        c, i1, i2 = intersect1d(a, b, return_indices=True)
+        ef = np.array([1, 2, 3, 4])
+        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]])
+        c, i1, i2 = intersect1d(a, b, assume_unique=True, return_indices=True)
+        ui1 = np.unravel_index(i1, a.shape)
+        ui2 = np.unravel_index(i2, b.shape)
+        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]])
+        c, i1, i2 = intersect1d(a, b, return_indices=True)
+        ui1 = np.unravel_index(i1, a.shape)
+        ui2 = np.unravel_index(i2, b.shape)
+        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])