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BUG: IntervalIndex.get_indexer raising for read only array #53703

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Jun 19, 2023
Merged

BUG: IntervalIndex.get_indexer raising for read only array #53703

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3cc9846
BUG: IntervalIndex.get_indexer raising for read only array
phofl Jun 16, 2023
6d050d8
Fix windows failure
phofl Jun 16, 2023
85f0075
Update
phofl Jun 18, 2023
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v2.1.0.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -400,7 +400,7 @@ Strings

Interval
^^^^^^^^
-
- :meth:`pd.IntervalIndex.get_indexer` and :meth:`pd.IntervalIndex.get_indexer_nonunique` raising if ``target`` is read-only array (:issue:`53703`)
-

Indexing
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4 changes: 2 additions & 2 deletions pandas/_libs/intervaltree.pxi.in
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Expand Up @@ -125,7 +125,7 @@ cdef class IntervalTree(IntervalMixin):
sort_order = self.left_sorter
return is_monotonic(sort_order, False)[0]

def get_indexer(self, scalar_t[:] target) -> np.ndarray:
def get_indexer(self, ndarray[scalar_t, ndim=1] target) -> np.ndarray:
"""Return the positions corresponding to unique intervals that overlap
with the given array of scalar targets.
"""
Expand Down Expand Up @@ -153,7 +153,7 @@ cdef class IntervalTree(IntervalMixin):
old_len = result.data.n
return result.to_array().astype('intp')

def get_indexer_non_unique(self, scalar_t[:] target):
def get_indexer_non_unique(self, ndarray[scalar_t, ndim=1] target):
"""Return the positions corresponding to intervals that overlap with
the given array of scalar targets. Non-unique positions are repeated.
"""
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11 changes: 11 additions & 0 deletions pandas/tests/indexes/interval/test_indexing.py
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Expand Up @@ -424,6 +424,17 @@ def test_get_indexer_interval_index(self, box):
expected = np.array([-1, -1, -1], dtype=np.intp)
tm.assert_numpy_array_equal(actual, expected)

def test_get_indexer_read_only(self):
idx = interval_range(start=0, end=5)
arr = np.array([1, 2])
arr.flags.writeable = False
result = idx.get_indexer(arr)
expected = np.array([0, 1])
tm.assert_numpy_array_equal(result, expected, check_dtype=False)

result = idx.get_indexer_non_unique(arr)[0]
tm.assert_numpy_array_equal(result, expected, check_dtype=False)
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Hmm what's going on with the dtype? Wouldn't expect that issue

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Windows/non windows stuff and since the dtype really doesnt matter here, I just ignored it

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Maybe you can explicitly specify the type of the np.array call instead?

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This would kill the 32 bit build... Open for suggestions but dtype really doesn't matter



class TestSliceLocs:
def test_slice_locs_with_interval(self):
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