TST: use np.intp pandas-dev#36579

Author: fangchenli

pandas/tests/indexes/period/test_indexing.py

@@ -5,7 +5,6 @@
 import pytest
 
 from pandas._libs.tslibs import period as libperiod
-from pandas.compat import IS64
 from pandas.errors import InvalidIndexError
 
 import pandas as pd
@@ -451,8 +450,7 @@ def test_get_indexer_non_unique(self):
 
         result = idx1.get_indexer_non_unique(idx2)
         expected_indexer = np.array([1, 0, 2, -1, -1], dtype=np.intp)
-        expected_dtype = np.int64 if IS64 else np.int32
-        expected_missing = np.array([2, 3], dtype=expected_dtype)
+        expected_missing = np.array([2, 3], dtype=np.intp)
 
         tm.assert_numpy_array_equal(result[0], expected_indexer)
         tm.assert_numpy_array_equal(result[1], expected_missing)

pandas/tests/indexes/test_base.py

@@ -11,7 +11,6 @@
 import pandas._config.config as cf
 
 from pandas._libs.tslib import Timestamp
-from pandas.compat import IS64
 from pandas.compat.numpy import np_datetime64_compat
 from pandas.util._test_decorators import async_mark
 
@@ -2608,8 +2607,7 @@ def construct(dtype):
         ex1 = np.array([0, 3, 1, 4, 2, 5] * 2, dtype=np.intp)
         ex2 = np.array([], dtype=np.intp)
         tm.assert_numpy_array_equal(result[0], ex1)
-        expected_dtype = np.int64 if IS64 else np.int32
-        tm.assert_numpy_array_equal(result[1], ex2.astype(expected_dtype))
+        tm.assert_numpy_array_equal(result[1], ex2)
 
     else:
         no_matches = np.array([-1] * 6, dtype=np.intp)

pandas/tests/test_algos.py

@@ -1545,10 +1545,7 @@ def test_lookup_nan(self, writable):
         xs.setflags(write=writable)
         m = ht.Float64HashTable()
         m.map_locations(xs)
-        expected_dtype = np.int64 if IS64 else np.int32
-        tm.assert_numpy_array_equal(
-            m.lookup(xs), np.arange(len(xs), dtype=expected_dtype)
-        )
+        tm.assert_numpy_array_equal(m.lookup(xs), np.arange(len(xs), dtype=np.intp))
 
     def test_add_signed_zeros(self):
         # GH 21866 inconsistent hash-function for float64
@@ -1581,10 +1578,7 @@ def test_lookup_overflow(self, writable):
         xs.setflags(write=writable)
         m = ht.UInt64HashTable()
         m.map_locations(xs)
-        expected_dtype = np.int64 if IS64 else np.int32
-        tm.assert_numpy_array_equal(
-            m.lookup(xs), np.arange(len(xs), dtype=expected_dtype)
-        )
+        tm.assert_numpy_array_equal(m.lookup(xs), np.arange(len(xs), dtype=np.intp))
 
     def test_get_unique(self):
         s = Series([1, 2, 2 ** 63, 2 ** 63], dtype=np.uint64)