class_docstr: Base class for IntegerArray and FloatingArray.
class_docstr_tok: ["Base","class","for","IntegerArray","and","FloatingArray","."]
code: def __init__(
      self,
      values: np.ndarray,
      mask: npt.NDArray[np.bool_],
      copy: bool = False,
  ) -> None:
      checker = self._dtype_cls._checker
      if not (isinstance(values, np.ndarray) and checker(values.dtype)):
          descr = (
              "floating"
              if self._dtype_cls.kind == "f"  # type: ignore[comparison-overlap]
              else "integer"
          )
          raise TypeError(
              f"values should be {descr} numpy array. Use "
              "the 'pd.array' function instead"
          )
      if values.dtype == np.float16:
          # If we don't raise here, then accessing self.dtype would raise
          raise TypeError(
              "FloatingArray does not support np.float16 dtype."
          )
  
      super().__init__(values, mask, copy=copy)
  
imports: from __future__ import annotations
  import numbers
  from typing import TYPE_CHECKING, Any, Callable, Mapping, TypeVar
  import numpy
  from pandas._libs import lib, missing
  from pandas._typing import Dtype, DtypeObj, npt
  from pandas.errors import AbstractMethodError
  from pandas.util._decorators import cache_readonly
  from pandas.core.dtypes.common import is_bool_dtype, is_float_dtype, is_integer_dtype, is_object_dtype, is_string_dtype, pandas_dtype
  from pandas.core.arrays.masked import BaseMaskedArray, BaseMaskedDtype
label_desc: Use image node_id 1 to create a new NumericArray object from inherited base classes: BaseMaskedArray with example: obj = NumericArray(values, mask, copy)