move maybe_upcast_numeric_to_64bit to core.dtypes.cast

Author: topper-123

pandas/core/arrays/interval.py

@@ -45,7 +45,10 @@
 from pandas.errors import IntCastingNaNError
 from pandas.util._decorators import Appender
 
-from pandas.core.dtypes.cast import LossySetitemError
+from pandas.core.dtypes.cast import (
+    LossySetitemError,
+    maybe_upcast_numeric_to_64bit,
+)
 from pandas.core.dtypes.common import (
     is_categorical_dtype,
     is_dtype_equal,
@@ -1750,5 +1753,6 @@ def _maybe_convert_platform_interval(values) -> ArrayLike:
         values = extract_array(values, extract_numpy=True)
 
     if not hasattr(values, "dtype"):
-        return np.asarray(values)
+        values = np.asarray(values)
+        values = maybe_upcast_numeric_to_64bit(values)
     return values

pandas/core/dtypes/cast.py

@@ -35,6 +35,7 @@
     ArrayLike,
     Dtype,
     DtypeObj,
+    NumpyIndexT,
     Scalar,
     npt,
 )
@@ -52,6 +53,7 @@
     ensure_int64,
     ensure_object,
     ensure_str,
+    is_array_like,
     is_bool,
     is_bool_dtype,
     is_complex,
@@ -65,6 +67,7 @@
     is_numeric_dtype,
     is_object_dtype,
     is_scalar,
+    is_signed_integer_dtype,
     is_string_dtype,
     is_timedelta64_dtype,
     is_unsigned_integer_dtype,
@@ -412,6 +415,34 @@ def trans(x):
     return result
 
 
+def maybe_upcast_numeric_to_64bit(arr: NumpyIndexT) -> NumpyIndexT:
+    """
+    If array is a int/uint/float bit size lower than 64 bit, upcast it to 64 bit.
+
+    Parameters
+    ----------
+    arr : ndarray or ExtensionArray
+
+    Returns
+    -------
+    ndarray or ExtensionArray
+    """
+
+    if not is_array_like(arr):
+        return arr
+    dtype = arr.dtype
+    if not np.issubclass_(dtype.type, np.number):
+        return arr
+    elif is_signed_integer_dtype(dtype) and dtype != np.int64:
+        return arr.astype(np.int64)
+    elif is_unsigned_integer_dtype(dtype) and dtype != np.uint64:
+        return arr.astype(np.uint64)
+    elif is_float_dtype(dtype) and dtype != np.float64:
+        return arr.astype(np.float64)
+    else:
+        return arr
+
+
 def maybe_cast_pointwise_result(
     result: ArrayLike,
     dtype: DtypeObj,

pandas/core/indexes/interval.py

@@ -31,7 +31,6 @@
     DtypeObj,
     IntervalClosedType,
     npt,
-    NumpyIndexT,
 )
 from pandas.errors import InvalidIndexError
 from pandas.util._decorators import (
@@ -45,10 +44,10 @@
     infer_dtype_from_scalar,
     maybe_box_datetimelike,
     maybe_downcast_numeric,
+    maybe_upcast_numeric_to_64bit,
 )
 from pandas.core.dtypes.common import (
     ensure_platform_int,
-    is_array_like,
     is_datetime64tz_dtype,
     is_datetime_or_timedelta_dtype,
     is_dtype_equal,
@@ -61,8 +60,6 @@
     is_number,
     is_object_dtype,
     is_scalar,
-    is_signed_integer_dtype,
-    is_unsigned_integer_dtype,
 )
 from pandas.core.dtypes.dtypes import IntervalDtype
 from pandas.core.dtypes.missing import is_valid_na_for_dtype
@@ -148,24 +145,6 @@ def _new_IntervalIndex(cls, d):
     return cls.from_arrays(**d)
 
 
-def maybe_convert_numeric_to_64bit(arr: NumpyIndexT) -> NumpyIndexT:
-    # IntervalTree only supports 64 bit numpy array
-
-    if not is_array_like(arr):
-        return arr
-    dtype = arr.dtype
-    if not np.issubclass_(dtype.type, np.number):
-        return arr
-    elif is_signed_integer_dtype(dtype) and dtype != np.int64:
-        return arr.astype(np.int64)
-    elif is_unsigned_integer_dtype(dtype) and dtype != np.uint64:
-        return arr.astype(np.uint64)
-    elif is_float_dtype(dtype) and dtype != np.float64:
-        return arr.astype(np.float64)
-    else:
-        return arr
-
-
 @Appender(
     _interval_shared_docs["class"]
     % {
@@ -362,10 +341,11 @@ def from_tuples(
     # "Union[IndexEngine, ExtensionEngine]" in supertype "Index"
     @cache_readonly
     def _engine(self) -> IntervalTree:  # type: ignore[override]
+        # IntervalTree does not supports numpy array unless they are 64 bit
         left = self._maybe_convert_i8(self.left)
-        left = maybe_convert_numeric_to_64bit(left)
+        left = maybe_upcast_numeric_to_64bit(left)
         right = self._maybe_convert_i8(self.right)
-        right = maybe_convert_numeric_to_64bit(right)
+        right = maybe_upcast_numeric_to_64bit(right)
         return IntervalTree(left, right, closed=self.closed)
 
     def __contains__(self, key: Any) -> bool:
@@ -544,7 +524,7 @@ def _maybe_convert_i8(self, key):
         """
         if is_list_like(key):
             key = ensure_index(key)
-            key = maybe_convert_numeric_to_64bit(key)
+            key = maybe_upcast_numeric_to_64bit(key)
 
         if not self._needs_i8_conversion(key):
             return key