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Co-authored-by: Elliott Sales de Andrade <[email protected]>
Co-authored-by: Kyle Sunden <[email protected]>

Author: 3 people

lib/matplotlib/cbook.py

@@ -1113,14 +1113,13 @@ def _broadcast_with_masks(*args, compress=False):
     masks = bcast[len(args):]
     if masks:
         # combine the masks into one
-        mask = functools.reduce(np.logical_or, masks)
+        mask = np.logical_or.reduce(masks)
         # put mask on and compress
         if compress:
             inputs = [np.ma.array(k, mask=mask).compressed()
                       for k in inputs]
         else:
-            inputs = [np.ravel(np.ma.array(k, mask=mask,
-                                           dtype=float).filled(np.nan))
+            inputs = [np.ma.array(k, mask=mask, dtype=float).filled(np.nan).ravel()
                       for k in inputs]
     else:
         inputs = [np.ravel(k) for k in inputs]

lib/matplotlib/cbook.pyi

@@ -130,7 +130,7 @@ class GrouperView(Generic[_T]):
 
 def simple_linear_interpolation(a: ArrayLike, steps: int) -> np.ndarray: ...
 def delete_masked_points(*args): ...
-def _broadcast_with_masks(*args, compress: bool=False) -> list[ArrayLike]: ...
+def _broadcast_with_masks(*args: ArrayLike, compress: bool = ...) -> list[ArrayLike]: ...
 def boxplot_stats(
     X: ArrayLike,
     whis: float | tuple[float, float] = ...,