refactor: Move is_close to CompliantColumn

Now that #2962 has merged, this part of the plan is possible (#2962 (comment))

Author: dangotbanned

narwhals/_compliant/column.py

@@ -103,6 +103,66 @@ def is_between(
             return (self > lower_bound) & (self < upper_bound)
         return (self >= lower_bound) & (self <= upper_bound)
 
+    def is_close(
+        self,
+        other: Self | NumericLiteral,
+        *,
+        abs_tol: float,
+        rel_tol: float,
+        nans_equal: bool,
+    ) -> Self:
+        from decimal import Decimal
+
+        other_abs: Self | NumericLiteral
+        other_is_nan: Self | bool
+        other_is_inf: Self | bool
+        other_is_not_inf: Self | bool
+
+        if isinstance(other, (float, int, Decimal)):
+            from math import isinf, isnan
+
+            # NOTE: See https://discuss.python.org/t/inferred-type-of-function-that-calls-dunder-abs-abs/101447
+            other_abs = other.__abs__()
+            other_is_nan = isnan(other)
+            other_is_inf = isinf(other)
+
+            # Define the other_is_not_inf variable to prevent triggering the following warning:
+            # > DeprecationWarning: Bitwise inversion '~' on bool is deprecated and will be
+            # >     removed in Python 3.16.
+            other_is_not_inf = not other_is_inf
+
+        else:
+            other_abs, other_is_nan = other.abs(), other.is_nan()
+            other_is_not_inf = other.is_finite() | other_is_nan
+            other_is_inf = ~other_is_not_inf
+
+        rel_threshold = self.abs().clip(lower_bound=other_abs, upper_bound=None) * rel_tol
+        tolerance = rel_threshold.clip(lower_bound=abs_tol, upper_bound=None)
+
+        self_is_nan = self.is_nan()
+        self_is_not_inf = self.is_finite() | self_is_nan
+
+        # Values are close if abs_diff <= tolerance, and both finite
+        is_close = (
+            ((self - other).abs() <= tolerance) & self_is_not_inf & other_is_not_inf
+        )
+
+        # Handle infinity cases: infinities are close/equal if they have the same sign
+        self_sign, other_sign = self > 0, other > 0
+        is_same_inf = (~self_is_not_inf) & other_is_inf & (self_sign == other_sign)
+
+        # Handle nan cases:
+        #   * If any value is NaN, then False (via `& ~either_nan`)
+        #   * However, if `nans_equals = True` and if _both_ values are NaN, then True
+        either_nan = self_is_nan | other_is_nan
+        result = (is_close | is_same_inf) & ~either_nan
+
+        if nans_equal:
+            both_nan = self_is_nan & other_is_nan
+            result = result | both_nan
+
+        return result
+
     def is_duplicated(self) -> Self:
         return ~self.is_unique()
 

narwhals/_compliant/series.py

@@ -17,7 +17,6 @@
     NativeSeriesT,
     NativeSeriesT_co,
 )
-from narwhals._compliant.utils import IsClose
 from narwhals._translate import FromIterable, FromNative, NumpyConvertible, ToNarwhals
 from narwhals._typing_compat import TypeVar, assert_never
 from narwhals._utils import (
@@ -74,7 +73,6 @@ class HistData(TypedDict, Generic[NativeSeriesT, "_CountsT_co"]):
 
 
 class CompliantSeries(
-    IsClose,
     NumpyConvertible["_1DArray", "Into1DArray"],
     FromIterable,
     FromNative[NativeSeriesT],