Revert "MRG, ENH: added edge keyword argument to digitize"revert-16248-edge

3 files changed, 3 insertions, 43 deletions

diff --git a/doc/release/upcoming_changes/16248.new_feature.rst b/doc/release/upcoming_changes/16248.new_feature.rst
deleted file mode 100644
index 823646d00..000000000
--- a/doc/release/upcoming_changes/16248.new_feature.rst
+++ /dev/null
@@ -1,13 +0,0 @@
-Digitize Keyword Egde
----------------------
-A keyword argument has been added to `np.digitize` so that the
-edge case is covered in the last bin. For example,
-
-```
-x = [1, 2, 3]
-bins = [0, 1.5, 3]
-```
-
-`np.digitize(x, bins, right=False, edge=True)` yields `[1, 2, 2]`
-whereas before the edge keyword argument existed it would yield
-`[1, 2, 3]`.
\ No newline at end of file
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py
index 41caa805e..6ea9cc4de 100644
--- a/numpy/lib/function_base.py
+++ b/numpy/lib/function_base.py
@@ -4733,12 +4733,12 @@ def append(arr, values, axis=None):
     return concatenate((arr, values), axis=axis)
 
 
-def _digitize_dispatcher(x, bins, right=None, edge=None):
+def _digitize_dispatcher(x, bins, right=None):
     return (x, bins)
 
 
 @array_function_dispatch(_digitize_dispatcher)
-def digitize(x, bins, right=False, edge=False):
+def digitize(x, bins, right=False):
     """
     Return the indices of the bins to which each value in input array belongs.
 
@@ -4767,10 +4767,6 @@ def digitize(x, bins, right=False, edge=False):
         does not include the right edge. The left bin end is open in this
         case, i.e., bins[i-1] <= x < bins[i] is the default behavior for
         monotonically increasing bins.
-    edge : bool, optional
-        Whether to include the last right edge if right==False or the first
-        left edge if right==True so that the whole interval from the least
-        to the greatest value of bins is covered.
 
     Returns
     -------
@@ -4786,7 +4782,7 @@ def digitize(x, bins, right=False, edge=False):
 
     See Also
     --------
-    bincount, histogram, unique, nextafter, searchsorted
+    bincount, histogram, unique, searchsorted
 
     Notes
     -----
@@ -4843,22 +4839,6 @@ def digitize(x, bins, right=False, edge=False):
     if mono == 0:
         raise ValueError("bins must be monotonically increasing or decreasing")
 
-    if edge:
-        # =========  =============  ============================ ===== =====
-        # `right`    order of bins  returned index `i` satisfies delta index
-        # =========  =============  ============================ ===== =====
-        # ``False``  increasing     ``bins[i-1] <= x < bins[i]``   1    -1
-        # ``True``   increasing     ``bins[i-1] < x <= bins[i]``   -1    0
-        # ``False``  decreasing     ``bins[i-1] > x >= bins[i]``   1    0
-        # ``True``   decreasing     ``bins[i-1] >= x > bins[i]``   -1    -1
-        # =========  =============  ============================ ===== =====
-        delta = -1 if right else 1
-        idx = -1 if delta == mono else 0
-        if np.issubdtype(bins.dtype, _nx.integer):
-            bins[idx] += delta
-        else:
-            bins[idx] = np.nextafter(bins[idx], bins[idx] + delta)
-
     # this is backwards because the arguments below are swapped
     side = 'left' if right else 'right'
     if mono == -1:
diff --git a/numpy/lib/tests/test_function_base.py b/numpy/lib/tests/test_function_base.py
index 32f660772..eb2fc3311 100644
--- a/numpy/lib/tests/test_function_base.py
+++ b/numpy/lib/tests/test_function_base.py
@@ -1712,12 +1712,6 @@ class TestDigitize:
         bins = [1, 1, 0]
         assert_array_equal(digitize(x, bins, False), [3, 2, 0, 0])
         assert_array_equal(digitize(x, bins, True), [3, 3, 2, 0])
-        bins = [-1, 0, 1, 2]
-        assert_array_equal(digitize(x, bins, False, True), [1, 2, 3, 3])
-        assert_array_equal(digitize(x, bins, True, True), [1, 1, 2, 3])
-        bins = [2, 1, 0, -1]
-        assert_array_equal(digitize(x, bins, False, True), [3, 2, 1, 1])
-        assert_array_equal(digitize(x, bins, True, True), [3, 3, 2, 1])
         bins = [1, 1, 1, 1]
         assert_array_equal(digitize(x, bins, False), [0, 0, 4, 4])
         assert_array_equal(digitize(x, bins, True), [0, 0, 0, 4])
@@ -1746,7 +1740,6 @@ class TestDigitize:
         # gh-11022
         x = 2**54  # loses precision in a float
         assert_equal(np.digitize(x, [x - 1, x + 1]), 1)
-        assert_equal(np.digitize(x, [x - 1, x + 1], False, True), 1)
 
     @pytest.mark.xfail(
         reason="gh-11022: np.core.multiarray._monoticity loses precision")