BUG: masked array proper deepcopies

Fixes #22556
Fixes #21022

* add regression test and fix for gh-22556, where
we were relying on the array `copy` arg to deepcopy
a compound object type; I thought about performance issues
here, but if you are already in the land of `object` and
you are explicitly opting in to `deepcopy`, it seems like
performance might be wishful thinking anyway

* add regression test and fix for gh-21022--this one was
weirder but seems possible to sidestep by not trying
to assign a shape of `()` to something that already has
shape `()` and a non-writeable `shape` attribute

1 files changed, 14 insertions, 1 deletions

diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index b76ff8ea9..795e79e00 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -2870,7 +2870,13 @@ class MaskedArray(ndarray):
                     _data._mask = _data._mask.copy()
                     # Reset the shape of the original mask
                     if getmask(data) is not nomask:
-                        data._mask.shape = data.shape
+                        # gh-21022 encounters an issue here
+                        # because data._mask.shape is not writeable, but
+                        # the op was also pointless in that case, because
+                        # the shapes were the same, so we can at least
+                        # avoid that path
+                        if data._mask.shape != data.shape:
+                            data._mask.shape = data.shape
         else:
             # Case 2. : With a mask in input.
             # If mask is boolean, create an array of True or False
@@ -6300,6 +6306,13 @@ class MaskedArray(ndarray):
         memo[id(self)] = copied
         for (k, v) in self.__dict__.items():
             copied.__dict__[k] = deepcopy(v, memo)
+        # as clearly documented for np.copy(), you need to use
+        # deepcopy() directly for arrays of object type that may
+        # contain compound types--you cannot depend on normal
+        # copy semantics to do the right thing here
+        if self.dtype.type is np.object_:
+            for idx, _ in enumerate(copied):
+                copied[idx] = deepcopy(copied[idx])
         return copied