]> git.madduck.net Git - etc/vim.git/blobdiff - tests/data/simple_cases/power_op_spacing.py

madduck's git repository

Every one of the projects in this repository is available at the canonical URL git://git.madduck.net/madduck/pub/<projectpath> — see each project's metadata for the exact URL.

All patches and comments are welcome. Please squash your changes to logical commits before using git-format-patch and git-send-email to patches@git.madduck.net. If you'd read over the Git project's submission guidelines and adhered to them, I'd be especially grateful.

SSH access, as well as push access can be individually arranged.

If you use my repositories frequently, consider adding the following snippet to ~/.gitconfig and using the third clone URL listed for each project:

[url "git://git.madduck.net/madduck/"]
  insteadOf = madduck:

Copy over comments when hugging power ops (#2874)
[etc/vim.git] / tests / data / simple_cases / power_op_spacing.py
index 87dde7f39dcd34d9a67eba52f18a4eda0a352dde..c95fa788fc3eba93de835ab39c37138c9e7dbbe6 100644 (file)
@@ -49,6 +49,20 @@ p = {(k, k**2): v**2.0 for k, v in pairs}
 q = [10.5**i for i in range(6)]
 
 
+# WE SHOULD DEFINITELY NOT EAT THESE COMMENTS (https://github.com/psf/black/issues/2873)
+if hasattr(view, "sum_of_weights"):
+    return np.divide(  # type: ignore[no-any-return]
+        view.variance,  # type: ignore[union-attr]
+        view.sum_of_weights,  # type: ignore[union-attr]
+        out=np.full(view.sum_of_weights.shape, np.nan),  # type: ignore[union-attr]
+        where=view.sum_of_weights**2 > view.sum_of_weights_squared,  # type: ignore[union-attr]
+    )
+
+return np.divide(
+    where=view.sum_of_weights_of_weight_long**2 > view.sum_of_weights_squared,  # type: ignore
+)
+
+
 # output
 
 
@@ -101,3 +115,17 @@ n = count <= 10**5.0
 o = settings(max_examples=10**6.0)
 p = {(k, k**2): v**2.0 for k, v in pairs}
 q = [10.5**i for i in range(6)]
+
+
+# WE SHOULD DEFINITELY NOT EAT THESE COMMENTS (https://github.com/psf/black/issues/2873)
+if hasattr(view, "sum_of_weights"):
+    return np.divide(  # type: ignore[no-any-return]
+        view.variance,  # type: ignore[union-attr]
+        view.sum_of_weights,  # type: ignore[union-attr]
+        out=np.full(view.sum_of_weights.shape, np.nan),  # type: ignore[union-attr]
+        where=view.sum_of_weights**2 > view.sum_of_weights_squared,  # type: ignore[union-attr]
+    )
+
+return np.divide(
+    where=view.sum_of_weights_of_weight_long**2 > view.sum_of_weights_squared,  # type: ignore
+)