From 03b096868e168f1b7fc93d0077f5f3a438378afd Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Wed, 28 Feb 2024 22:37:02 +0800
Subject: [PATCH 01/16] add flip transform

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/array.py      |  9 +++-
 monai/transforms/spatial/functional.py | 63 +++++++++++++++++++++++++-
 2 files changed, 69 insertions(+), 3 deletions(-)

diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py
index 094afdd3c4..56db276ff5 100644
--- a/monai/transforms/spatial/array.py
+++ b/monai/transforms/spatial/array.py
@@ -34,7 +34,8 @@
 from monai.transforms.inverse import InvertibleTransform
 from monai.transforms.spatial.functional import (
     affine_func,
-    flip,
+    flip_image,
+    flip_point,
     orientation,
     resize,
     rotate,
@@ -684,6 +685,7 @@ class Flip(InvertibleTransform, LazyTransform):
     def __init__(self, spatial_axis: Sequence[int] | int | None = None, lazy: bool = False) -> None:
         LazyTransform.__init__(self, lazy=lazy)
         self.spatial_axis = spatial_axis
+        self.operators = [flip_point, flip_image]
 
     def __call__(self, img: torch.Tensor, lazy: bool | None = None) -> torch.Tensor:
         """
@@ -695,7 +697,10 @@ def __call__(self, img: torch.Tensor, lazy: bool | None = None) -> torch.Tensor:
         """
         img = convert_to_tensor(img, track_meta=get_track_meta())
         lazy_ = self.lazy if lazy is None else lazy
-        return flip(img, self.spatial_axis, lazy=lazy_, transform_info=self.get_transform_info())  # type: ignore
+        for operator in self.operators:
+            ret = operator(img, self.spatial_axis, lazy=lazy_, transform_info=self.get_transform_info())
+            if ret is not None:
+                return ret
 
     def inverse(self, data: torch.Tensor) -> torch.Tensor:
         self.pop_transform(data)
diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index add4e7f5ea..3a65df5d80 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -16,6 +16,7 @@
 
 import math
 import warnings
+from copy import deepcopy
 from enum import Enum
 
 import numpy as np
@@ -24,6 +25,7 @@
 import monai
 from monai.config import USE_COMPILED
 from monai.config.type_definitions import NdarrayOrTensor
+from monai.data.box_utils import get_spatial_dims
 from monai.data.meta_obj import get_track_meta
 from monai.data.meta_tensor import MetaTensor
 from monai.data.utils import AFFINE_TOL, compute_shape_offset, to_affine_nd
@@ -229,7 +231,7 @@ def orientation(img, original_affine, spatial_ornt, lazy, transform_info) -> tor
     return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out  # type: ignore
 
 
-def flip(img, sp_axes, lazy, transform_info):
+def flip_image(img, sp_axes, lazy, transform_info):
     """
     Functional implementation of flip.
     This function operates eagerly or lazily according to
@@ -245,6 +247,9 @@ def flip(img, sp_axes, lazy, transform_info):
         lazy: a flag that indicates whether the operation should be performed lazily or not
         transform_info: a dictionary with the relevant information pertaining to an applied transform.
     """
+    # TODO
+    if img.meta["kind"] != "pixel":
+        return None
     sp_size = img.peek_pending_shape() if isinstance(img, MetaTensor) else img.shape[1:]
     sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist()
     extra_info = {"axes": sp_axes}  # track the spatial axes
@@ -265,6 +270,62 @@ def flip(img, sp_axes, lazy, transform_info):
     return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out
 
 
+def flip_point(points, sp_axes, lazy, transform_info):
+    """
+    Functional implementation of flip points.
+    This function operates eagerly or lazily according to
+    ``lazy`` (default ``False``).
+    Args:
+        points: point coordinates, Nx2 or Nx3 torch tensor or ndarray
+        sp_axes: spatial axes along which to flip over. Default is None.
+            The default `axis=None` will flip over all of the axes of the input array.
+            If axis is negative it counts from the last to the first axis.
+            If axis is a tuple of ints, flipping is performed on all of the axes
+            specified in the tuple.
+        lazy: a flag that indicates whether the operation should be performed lazily or not.
+        transform_info: a dictionary with the relevant information pertaining to an applied transform.
+    Returns:
+        flipped points, with same data type as ``points``, does not share memory with ``points``
+    """
+    # TODO
+    if points.meta["kind"] != "point":
+        return None
+    if points.meta.get("refer_meta", None) is not None:
+        spatial_size = points.meta["refer_meta"]["spatial_shape"]
+    else:
+        spatial_size = None
+    spatial_dims: int = get_spatial_dims(points=points[0])
+    sp_size = ensure_tuple_rep(spatial_size, spatial_dims) if spatial_size is not None else None
+    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist() if spatial_size is not None else None
+    extra_info = {"axes": sp_axes}  # track the spatial axes
+    if sp_axes is None:
+        sp_axes = tuple(range(0, spatial_dims))
+    sp_axes = ensure_tuple(sp_axes)
+    sp_axes = monai.transforms.utils.map_spatial_axes(points.ndim, sp_axes)  # use the axes with channel dim
+    # axes include the channel dim
+    xform = torch.eye(int(spatial_dims) + 1, dtype=torch.double)
+    for axis in sp_axes:
+        sp = axis - 1
+        if sp_size is not None:
+            xform[sp, sp], xform[sp, -1] = xform[sp, sp] * -1, sp_size[sp] - 1
+        else:
+            xform[sp, sp] *= -1
+    meta_info = TraceableTransform.track_transform_meta(points, affine=xform, extra_info=extra_info, lazy=lazy, transform_info=transform_info)
+
+    # flip box
+    out = deepcopy(_maybe_new_metatensor(points))
+    if lazy:
+        return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
+    if sp_size is None:
+        warnings.warn("''spatial_size'' is None, will flip in the world coordinates.")
+        for _axes in sp_axes:
+            out[..., _axes-1] = -points[..., _axes-1]
+    else:
+        for _axes in sp_axes:
+            out[..., _axes-1] = sp_size[_axes-1] - points[..., _axes-1]
+    return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out
+
+
 def resize(
     img, out_size, mode, align_corners, dtype, input_ndim, anti_aliasing, anti_aliasing_sigma, lazy, transform_info
 ):

From bb004570a707fad00d3014e43bd2a75ffd45d8d8 Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Thu, 29 Feb 2024 15:48:30 +0800
Subject: [PATCH 02/16] enable inverse

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 34 ++++++++++++--------------
 1 file changed, 16 insertions(+), 18 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 3a65df5d80..6f8ff861c5 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -287,42 +287,40 @@ def flip_point(points, sp_axes, lazy, transform_info):
     Returns:
         flipped points, with same data type as ``points``, does not share memory with ``points``
     """
-    # TODO
+    # TODO: update to use enum
     if points.meta["kind"] != "point":
         return None
     if points.meta.get("refer_meta", None) is not None:
-        spatial_size = points.meta["refer_meta"]["spatial_shape"]
+        sp_size = points.meta["refer_meta"]["spatial_shape"]
     else:
-        spatial_size = None
-    spatial_dims: int = get_spatial_dims(points=points[0])
-    sp_size = ensure_tuple_rep(spatial_size, spatial_dims) if spatial_size is not None else None
-    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist() if spatial_size is not None else None
+        sp_size = None
+    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist() if sp_size is not None else None
     extra_info = {"axes": sp_axes}  # track the spatial axes
-    if sp_axes is None:
-        sp_axes = tuple(range(0, spatial_dims))
-    sp_axes = ensure_tuple(sp_axes)
-    sp_axes = monai.transforms.utils.map_spatial_axes(points.ndim, sp_axes)  # use the axes with channel dim
+    axes = monai.transforms.utils.map_spatial_axes(points.ndim, sp_axes)  # use the axes with channel dim
+    rank = points.peek_pending_rank() if isinstance(points, MetaTensor) else torch.tensor(3.0, dtype=torch.double)
     # axes include the channel dim
-    xform = torch.eye(int(spatial_dims) + 1, dtype=torch.double)
-    for axis in sp_axes:
+    xform = torch.eye(int(rank) + 1, dtype=torch.double)
+    for axis in axes:
         sp = axis - 1
         if sp_size is not None:
             xform[sp, sp], xform[sp, -1] = xform[sp, sp] * -1, sp_size[sp] - 1
         else:
             xform[sp, sp] *= -1
-    meta_info = TraceableTransform.track_transform_meta(points, affine=xform, extra_info=extra_info, lazy=lazy, transform_info=transform_info)
+    meta_info = TraceableTransform.track_transform_meta(
+        points, affine=xform, extra_info=extra_info, lazy=lazy, transform_info=transform_info
+    )
 
     # flip box
     out = deepcopy(_maybe_new_metatensor(points))
     if lazy:
         return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
     if sp_size is None:
-        warnings.warn("''spatial_size'' is None, will flip in the world coordinates.")
-        for _axes in sp_axes:
-            out[..., _axes-1] = -points[..., _axes-1]
+        warnings.warn("''sp_size'' is None, will flip in the world coordinates.")
+        for _axes in axes:
+            out[..., _axes - 1] = - points[..., _axes - 1]
     else:
-        for _axes in sp_axes:
-            out[..., _axes-1] = sp_size[_axes-1] - points[..., _axes-1]
+        for _axes in axes:
+            out[..., _axes - 1] = sp_size[_axes - 1] - points[..., _axes - 1]
     return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out
 
 

From f5a356298a0e151e378a92890dd466d4b91c9963 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 29 Feb 2024 16:22:09 +0000
Subject: [PATCH 03/16] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 monai/transforms/spatial/functional.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 6f8ff861c5..3a65263e8e 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -25,7 +25,6 @@
 import monai
 from monai.config import USE_COMPILED
 from monai.config.type_definitions import NdarrayOrTensor
-from monai.data.box_utils import get_spatial_dims
 from monai.data.meta_obj import get_track_meta
 from monai.data.meta_tensor import MetaTensor
 from monai.data.utils import AFFINE_TOL, compute_shape_offset, to_affine_nd

From 2b114685308182f6f0221aa713cae50cc250f67a Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Fri, 1 Mar 2024 16:38:55 +0800
Subject: [PATCH 04/16] minor fix

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 18 ++++++++++++++----
 1 file changed, 14 insertions(+), 4 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 6f8ff861c5..731fe0b542 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -52,7 +52,17 @@
 cupy_ndi, _ = optional_import("cupyx.scipy.ndimage")
 np_ndi, _ = optional_import("scipy.ndimage")
 
-__all__ = ["spatial_resample", "orientation", "flip", "resize", "rotate", "zoom", "rotate90", "affine_func"]
+__all__ = [
+    "spatial_resample",
+    "orientation",
+    "flip_image",
+    "flip_point",
+    "resize",
+    "rotate",
+    "zoom",
+    "rotate90",
+    "affine_func",
+]
 
 
 def _maybe_new_metatensor(img, dtype=None, device=None):
@@ -248,7 +258,7 @@ def flip_image(img, sp_axes, lazy, transform_info):
         transform_info: a dictionary with the relevant information pertaining to an applied transform.
     """
     # TODO
-    if img.meta["kind"] != "pixel":
+    if img.meta.get("kind", "pixel") != "pixel":
         return None
     sp_size = img.peek_pending_shape() if isinstance(img, MetaTensor) else img.shape[1:]
     sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist()
@@ -288,7 +298,7 @@ def flip_point(points, sp_axes, lazy, transform_info):
         flipped points, with same data type as ``points``, does not share memory with ``points``
     """
     # TODO: update to use enum
-    if points.meta["kind"] != "point":
+    if points.meta.get("kind", "pixel") != "point":
         return None
     if points.meta.get("refer_meta", None) is not None:
         sp_size = points.meta["refer_meta"]["spatial_shape"]
@@ -317,7 +327,7 @@ def flip_point(points, sp_axes, lazy, transform_info):
     if sp_size is None:
         warnings.warn("''sp_size'' is None, will flip in the world coordinates.")
         for _axes in axes:
-            out[..., _axes - 1] = - points[..., _axes - 1]
+            out[..., _axes - 1] = -points[..., _axes - 1]
     else:
         for _axes in axes:
             out[..., _axes - 1] = sp_size[_axes - 1] - points[..., _axes - 1]

From 3b2619e23502cc75c5bf5e5c9573c7269f05e03a Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Fri, 1 Mar 2024 16:50:56 +0800
Subject: [PATCH 05/16] minor fix

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 4d961abcd0..1538821aeb 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -257,7 +257,8 @@ def flip_image(img, sp_axes, lazy, transform_info):
         transform_info: a dictionary with the relevant information pertaining to an applied transform.
     """
     # TODO
-    if img.meta.get("kind", "pixel") != "pixel":
+    kind = img.meta.get("kind", "pixel") if isinstance(img, MetaTensor) else "pixel"
+    if kind != "pixel":
         return None
     sp_size = img.peek_pending_shape() if isinstance(img, MetaTensor) else img.shape[1:]
     sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist()
@@ -297,7 +298,8 @@ def flip_point(points, sp_axes, lazy, transform_info):
         flipped points, with same data type as ``points``, does not share memory with ``points``
     """
     # TODO: update to use enum
-    if points.meta.get("kind", "pixel") != "point":
+    kind = points.meta.get("kind", "pixel") if isinstance(points, MetaTensor) else "pixel"
+    if kind != "point":
         return None
     if points.meta.get("refer_meta", None) is not None:
         sp_size = points.meta["refer_meta"]["spatial_shape"]

From ac55361ea2ac2d5ea0894e56ab77a7448160e5cf Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Wed, 6 Mar 2024 14:26:17 +0800
Subject: [PATCH 06/16] add unittest

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/array.py      |  4 ++--
 monai/transforms/spatial/functional.py |  5 +++--
 tests/test_flip.py                     | 26 ++++++++++++++++++++++++++
 tests/test_flipd.py                    | 26 ++++++++++++++++++++++++++
 4 files changed, 57 insertions(+), 4 deletions(-)

diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py
index 56db276ff5..fd624f917a 100644
--- a/monai/transforms/spatial/array.py
+++ b/monai/transforms/spatial/array.py
@@ -687,7 +687,7 @@ def __init__(self, spatial_axis: Sequence[int] | int | None = None, lazy: bool =
         self.spatial_axis = spatial_axis
         self.operators = [flip_point, flip_image]
 
-    def __call__(self, img: torch.Tensor, lazy: bool | None = None) -> torch.Tensor:
+    def __call__(self, img: torch.Tensor, lazy: bool | None = None) -> torch.Tensor:  # type: ignore[return]
         """
         Args:
             img: channel first array, must have shape: (num_channels, H[, W, ..., ])
@@ -698,7 +698,7 @@ def __call__(self, img: torch.Tensor, lazy: bool | None = None) -> torch.Tensor:
         img = convert_to_tensor(img, track_meta=get_track_meta())
         lazy_ = self.lazy if lazy is None else lazy
         for operator in self.operators:
-            ret = operator(img, self.spatial_axis, lazy=lazy_, transform_info=self.get_transform_info())
+            ret: torch.Tensor = operator(img, self.spatial_axis, lazy=lazy_, transform_info=self.get_transform_info())
             if ret is not None:
                 return ret
 
diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 1538821aeb..66a91514e7 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -286,7 +286,8 @@ def flip_point(points, sp_axes, lazy, transform_info):
     This function operates eagerly or lazily according to
     ``lazy`` (default ``False``).
     Args:
-        points: point coordinates, Nx2 or Nx3 torch tensor or ndarray
+        points: point coordinates, represented by a torch tensor or ndarray with dimensions of 1xNx2 or 1xNx3.
+            Here 1 represents the channel dimension.
         sp_axes: spatial axes along which to flip over. Default is None.
             The default `axis=None` will flip over all of the axes of the input array.
             If axis is negative it counts from the last to the first axis.
@@ -320,10 +321,10 @@ def flip_point(points, sp_axes, lazy, transform_info):
     meta_info = TraceableTransform.track_transform_meta(
         points, affine=xform, extra_info=extra_info, lazy=lazy, transform_info=transform_info
     )
-
     # flip box
     out = deepcopy(_maybe_new_metatensor(points))
     if lazy:
+        raise NotImplementedError
         return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
     if sp_size is None:
         warnings.warn("''sp_size'' is None, will flip in the world coordinates.")
diff --git a/tests/test_flip.py b/tests/test_flip.py
index 789ec86920..971da97dd2 100644
--- a/tests/test_flip.py
+++ b/tests/test_flip.py
@@ -12,6 +12,7 @@
 from __future__ import annotations
 
 import unittest
+from copy import deepcopy
 
 import numpy as np
 import torch
@@ -32,6 +33,15 @@
     for device in TEST_DEVICES:
         TORCH_CASES.append([[0, 1], torch.zeros((1, 3, 2)), track_meta, *device])
 
+POINT_2D_WITH_REFER = MetaTensor(
+    [[[3, 4], [5, 7], [6, 2], [7, 8]]], meta={"kind": "point", "refer_meta": {"spatial_shape": (10, 10)}}
+)
+POINT_3D = MetaTensor([[[3, 4, 5], [5, 7, 6], [6, 2, 7]]], meta={"kind": "point"})
+POINT_CASES = []
+for spatial_axis in [[0], [1], [0, 1]]:
+    for point in [POINT_2D_WITH_REFER, POINT_3D]:
+        POINT_CASES.append([spatial_axis, point])
+
 
 class TestFlip(NumpyImageTestCase2D):
 
@@ -73,6 +83,22 @@ def test_torch(self, spatial_axis, img: torch.Tensor, track_meta: bool, device):
             with self.assertRaisesRegex(ValueError, "MetaTensor"):
                 xform.inverse(res)
 
+    @parameterized.expand(POINT_CASES)
+    def test_points(self, spatial_axis, point):
+        init_param = {"spatial_axis": spatial_axis}
+        xform = Flip(**init_param)
+        res = xform(point)  # type: ignore[arg-type]
+        self.assertEqual(point.shape, res.shape)
+        expected = deepcopy(point)
+        if point.meta.get("refer_meta", None) is not None:
+            for _axes in spatial_axis:
+                expected[..., _axes] = (10, 10)[_axes] - point[..., _axes]
+        else:
+            for _axes in spatial_axis:
+                expected[..., _axes] = -point[..., _axes]
+        assert_allclose(res, expected, type_test="tensor")
+        test_local_inversion(xform, res, point)
+
 
 if __name__ == "__main__":
     unittest.main()
diff --git a/tests/test_flipd.py b/tests/test_flipd.py
index 277f387051..f91e896665 100644
--- a/tests/test_flipd.py
+++ b/tests/test_flipd.py
@@ -12,6 +12,7 @@
 from __future__ import annotations
 
 import unittest
+from copy import deepcopy
 
 import numpy as np
 import torch
@@ -33,6 +34,15 @@
     for device in TEST_DEVICES:
         TORCH_CASES.append([[0, 1], torch.zeros((1, 3, 2)), track_meta, *device])
 
+POINT_2D_WITH_REFER = MetaTensor(
+    [[[3, 4], [5, 7], [6, 2], [7, 8]]], meta={"kind": "point", "refer_meta": {"spatial_shape": (10, 10)}}
+)
+POINT_3D = MetaTensor([[[3, 4, 5], [5, 7, 6], [6, 2, 7]]], meta={"kind": "point"})
+POINT_CASES = []
+for spatial_axis in [[0], [1], [0, 1]]:
+    for point in [POINT_2D_WITH_REFER, POINT_3D]:
+        POINT_CASES.append([spatial_axis, point])
+
 
 class TestFlipd(NumpyImageTestCase2D):
 
@@ -80,6 +90,22 @@ def test_meta_dict(self):
         res = xform({"image": torch.zeros(1, 3, 4)})
         self.assertTrue(res["image"].applied_operations == res["image_transforms"])
 
+    @parameterized.expand(POINT_CASES)
+    def test_points(self, spatial_axis, point):
+        init_param = {"keys": "point", "spatial_axis": spatial_axis}
+        xform = Flipd(**init_param)
+        res = xform({"point": point})  # type: ignore[arg-type]
+        self.assertEqual(point.shape, res["point"].shape)
+        expected = deepcopy(point)
+        if point.meta.get("refer_meta", None) is not None:
+            for _axes in spatial_axis:
+                expected[..., _axes] = (10, 10)[_axes] - point[..., _axes]
+        else:
+            for _axes in spatial_axis:
+                expected[..., _axes] = -point[..., _axes]
+        assert_allclose(res["point"], expected, type_test="tensor")
+        test_local_inversion(xform, {"point": res["point"]}, {"point": point}, "point")
+
 
 if __name__ == "__main__":
     unittest.main()

From 7e6f134b5e60513f85f4235a2c29bb91017b204f Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Wed, 6 Mar 2024 14:39:10 +0800
Subject: [PATCH 07/16] minor fix

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 66a91514e7..fa01952914 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -285,6 +285,7 @@ def flip_point(points, sp_axes, lazy, transform_info):
     Functional implementation of flip points.
     This function operates eagerly or lazily according to
     ``lazy`` (default ``False``).
+
     Args:
         points: point coordinates, represented by a torch tensor or ndarray with dimensions of 1xNx2 or 1xNx3.
             Here 1 represents the channel dimension.
@@ -295,8 +296,6 @@ def flip_point(points, sp_axes, lazy, transform_info):
             specified in the tuple.
         lazy: a flag that indicates whether the operation should be performed lazily or not.
         transform_info: a dictionary with the relevant information pertaining to an applied transform.
-    Returns:
-        flipped points, with same data type as ``points``, does not share memory with ``points``
     """
     # TODO: update to use enum
     kind = points.meta.get("kind", "pixel") if isinstance(points, MetaTensor) else "pixel"

From c136fae055e5cf5e1d19768d1dc89a4dbf59e810 Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Thu, 30 May 2024 11:38:20 +0800
Subject: [PATCH 08/16] add flip helper

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 47 +++++++++++---------------
 1 file changed, 20 insertions(+), 27 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index fa01952914..3f40d03f5e 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -240,6 +240,24 @@ def orientation(img, original_affine, spatial_ornt, lazy, transform_info) -> tor
     return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out  # type: ignore
 
 
+def flip_helper(data, sp_size, sp_axes, lazy, transform_info):
+    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist() if sp_size is not None else None
+    extra_info = {"axes": sp_axes}  # track the spatial axes
+    axes = monai.transforms.utils.map_spatial_axes(data.ndim, sp_axes)  # use the axes with channel dim
+    rank = data.peek_pending_rank() if isinstance(data, MetaTensor) else torch.tensor(3.0, dtype=torch.double)
+    # axes include the channel dim
+    xform = torch.eye(int(rank) + 1, dtype=torch.double)
+    for axis in axes:
+        sp = axis - 1
+        if sp_size is not None:
+            xform[sp, sp], xform[sp, -1] = xform[sp, sp] * -1, sp_size[sp] - 1
+        else:
+            xform[sp, sp] *= -1
+    meta_info = TraceableTransform.track_transform_meta(
+        data, affine=xform, extra_info=extra_info, lazy=lazy, transform_info=transform_info
+    )
+    return axes, meta_info
+
 def flip_image(img, sp_axes, lazy, transform_info):
     """
     Functional implementation of flip.
@@ -261,18 +279,7 @@ def flip_image(img, sp_axes, lazy, transform_info):
     if kind != "pixel":
         return None
     sp_size = img.peek_pending_shape() if isinstance(img, MetaTensor) else img.shape[1:]
-    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist()
-    extra_info = {"axes": sp_axes}  # track the spatial axes
-    axes = monai.transforms.utils.map_spatial_axes(img.ndim, sp_axes)  # use the axes with channel dim
-    rank = img.peek_pending_rank() if isinstance(img, MetaTensor) else torch.tensor(3.0, dtype=torch.double)
-    # axes include the channel dim
-    xform = torch.eye(int(rank) + 1, dtype=torch.double)
-    for axis in axes:
-        sp = axis - 1
-        xform[sp, sp], xform[sp, -1] = xform[sp, sp] * -1, sp_size[sp] - 1
-    meta_info = TraceableTransform.track_transform_meta(
-        img, sp_size=sp_size, affine=xform, extra_info=extra_info, transform_info=transform_info, lazy=lazy
-    )
+    axes, meta_info = flip_helper(img, sp_size, sp_axes, lazy, transform_info)
     out = _maybe_new_metatensor(img)
     if lazy:
         return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
@@ -305,21 +312,7 @@ def flip_point(points, sp_axes, lazy, transform_info):
         sp_size = points.meta["refer_meta"]["spatial_shape"]
     else:
         sp_size = None
-    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist() if sp_size is not None else None
-    extra_info = {"axes": sp_axes}  # track the spatial axes
-    axes = monai.transforms.utils.map_spatial_axes(points.ndim, sp_axes)  # use the axes with channel dim
-    rank = points.peek_pending_rank() if isinstance(points, MetaTensor) else torch.tensor(3.0, dtype=torch.double)
-    # axes include the channel dim
-    xform = torch.eye(int(rank) + 1, dtype=torch.double)
-    for axis in axes:
-        sp = axis - 1
-        if sp_size is not None:
-            xform[sp, sp], xform[sp, -1] = xform[sp, sp] * -1, sp_size[sp] - 1
-        else:
-            xform[sp, sp] *= -1
-    meta_info = TraceableTransform.track_transform_meta(
-        points, affine=xform, extra_info=extra_info, lazy=lazy, transform_info=transform_info
-    )
+    axes, meta_info = flip_helper(points, sp_size, sp_axes, lazy, transform_info)
     # flip box
     out = deepcopy(_maybe_new_metatensor(points))
     if lazy:

From ac139c983f725de90448ed8912f2b7d18220e4ef Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Thu, 30 May 2024 11:43:04 +0800
Subject: [PATCH 09/16] minor fix

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 3f40d03f5e..dadb364fa8 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -258,6 +258,7 @@ def flip_helper(data, sp_size, sp_axes, lazy, transform_info):
     )
     return axes, meta_info
 
+
 def flip_image(img, sp_axes, lazy, transform_info):
     """
     Functional implementation of flip.

From 4abaa8ee41d102e9e8efeed70431ab239011112f Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Wed, 24 Apr 2024 17:15:58 +0800
Subject: [PATCH 10/16] Update pycln version (#7704)

Fixes #7703


### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 .github/workflows/pythonapp-min.yml | 2 ++
 .github/workflows/pythonapp.yml     | 2 ++
 .pre-commit-config.yaml             | 2 +-
 3 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/pythonapp-min.yml b/.github/workflows/pythonapp-min.yml
index bbe7579774..dffae10558 100644
--- a/.github/workflows/pythonapp-min.yml
+++ b/.github/workflows/pythonapp-min.yml
@@ -9,6 +9,8 @@ on:
       - main
       - releasing/*
   pull_request:
+    head_ref-ignore:
+      - dev
 
 concurrency:
   # automatically cancel the previously triggered workflows when there's a newer version
diff --git a/.github/workflows/pythonapp.yml b/.github/workflows/pythonapp.yml
index b011e65cf1..4f77389991 100644
--- a/.github/workflows/pythonapp.yml
+++ b/.github/workflows/pythonapp.yml
@@ -9,6 +9,8 @@ on:
       - main
       - releasing/*
   pull_request:
+    head_ref-ignore:
+      - dev
 
 concurrency:
   # automatically cancel the previously triggered workflows when there's a newer version
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 14b41bbeb8..0087f87578 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -69,7 +69,7 @@ repos:
           )$
 
   - repo: https://github.com/hadialqattan/pycln
-    rev: v2.1.3
+    rev: v2.4.0
     hooks:
       - id: pycln
         args: [--config=pyproject.toml]

From 9456a8b2901349e4a7f17ad2f48dff9c522475ee Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Thu, 30 May 2024 13:06:36 +0800
Subject: [PATCH 11/16] Revert "Update pycln version (#7704)"

This reverts commit 4abaa8ee41d102e9e8efeed70431ab239011112f.
---
 .github/workflows/pythonapp-min.yml | 2 --
 .github/workflows/pythonapp.yml     | 2 --
 .pre-commit-config.yaml             | 2 +-
 3 files changed, 1 insertion(+), 5 deletions(-)

diff --git a/.github/workflows/pythonapp-min.yml b/.github/workflows/pythonapp-min.yml
index dffae10558..bbe7579774 100644
--- a/.github/workflows/pythonapp-min.yml
+++ b/.github/workflows/pythonapp-min.yml
@@ -9,8 +9,6 @@ on:
       - main
       - releasing/*
   pull_request:
-    head_ref-ignore:
-      - dev
 
 concurrency:
   # automatically cancel the previously triggered workflows when there's a newer version
diff --git a/.github/workflows/pythonapp.yml b/.github/workflows/pythonapp.yml
index 4f77389991..b011e65cf1 100644
--- a/.github/workflows/pythonapp.yml
+++ b/.github/workflows/pythonapp.yml
@@ -9,8 +9,6 @@ on:
       - main
       - releasing/*
   pull_request:
-    head_ref-ignore:
-      - dev
 
 concurrency:
   # automatically cancel the previously triggered workflows when there's a newer version
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 0087f87578..14b41bbeb8 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -69,7 +69,7 @@ repos:
           )$
 
   - repo: https://github.com/hadialqattan/pycln
-    rev: v2.4.0
+    rev: v2.1.3
     hooks:
       - id: pycln
         args: [--config=pyproject.toml]

From 4a94227977f7b2d190033dee8807d9e0e4807ead Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Thu, 30 May 2024 13:11:36 +0800
Subject: [PATCH 12/16] use enum

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index dadb364fa8..0cdc890181 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -45,6 +45,7 @@
     fall_back_tuple,
     optional_import,
 )
+from monai.utils.enums import MetaKeys, KindKeys
 
 nib, has_nib = optional_import("nibabel")
 cupy, _ = optional_import("cupy")
@@ -275,9 +276,8 @@ def flip_image(img, sp_axes, lazy, transform_info):
         lazy: a flag that indicates whether the operation should be performed lazily or not
         transform_info: a dictionary with the relevant information pertaining to an applied transform.
     """
-    # TODO
-    kind = img.meta.get("kind", "pixel") if isinstance(img, MetaTensor) else "pixel"
-    if kind != "pixel":
+    kind = img.meta.get(MetaKeys.KIND, KindKeys.PIXEL) if isinstance(img, MetaTensor) else KindKeys.PIXEL
+    if kind != KindKeys.PIXEL:
         return None
     sp_size = img.peek_pending_shape() if isinstance(img, MetaTensor) else img.shape[1:]
     axes, meta_info = flip_helper(img, sp_size, sp_axes, lazy, transform_info)
@@ -305,9 +305,8 @@ def flip_point(points, sp_axes, lazy, transform_info):
         lazy: a flag that indicates whether the operation should be performed lazily or not.
         transform_info: a dictionary with the relevant information pertaining to an applied transform.
     """
-    # TODO: update to use enum
-    kind = points.meta.get("kind", "pixel") if isinstance(points, MetaTensor) else "pixel"
-    if kind != "point":
+    kind = points.meta.get(MetaKeys.KIND, KindKeys.PIXEL) if isinstance(points, MetaTensor) else KindKeys.PIXEL
+    if kind != KindKeys.POINT:
         return None
     if points.meta.get("refer_meta", None) is not None:
         sp_size = points.meta["refer_meta"]["spatial_shape"]

From 8bca179dede40c50b05fba6ca03869f046440270 Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Thu, 30 May 2024 15:56:47 +0800
Subject: [PATCH 13/16] add comments

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 0cdc890181..3d110b58ce 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -308,6 +308,7 @@ def flip_point(points, sp_axes, lazy, transform_info):
     kind = points.meta.get(MetaKeys.KIND, KindKeys.PIXEL) if isinstance(points, MetaTensor) else KindKeys.PIXEL
     if kind != KindKeys.POINT:
         return None
+    # TODO: use enum
     if points.meta.get("refer_meta", None) is not None:
         sp_size = points.meta["refer_meta"]["spatial_shape"]
     else:
@@ -316,6 +317,7 @@ def flip_point(points, sp_axes, lazy, transform_info):
     # flip box
     out = deepcopy(_maybe_new_metatensor(points))
     if lazy:
+        # TODO: add lazy support
         raise NotImplementedError
         return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
     if sp_size is None:

From 21d7fc3376c66663cbb7a126581509d907b12b09 Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Tue, 30 Jul 2024 23:03:02 +0800
Subject: [PATCH 14/16] add apply_affine_to_points

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 51 +++++++++++++-------------
 1 file changed, 26 insertions(+), 25 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index 3d110b58ce..d4b1b5762c 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -33,7 +33,7 @@
 from monai.transforms.intensity.array import GaussianSmooth
 from monai.transforms.inverse import TraceableTransform
 from monai.transforms.utils import create_rotate, create_translate, resolves_modes, scale_affine
-from monai.transforms.utils_pytorch_numpy_unification import allclose
+from monai.transforms.utils_pytorch_numpy_unification import allclose, concatenate
 from monai.utils import (
     LazyAttr,
     TraceKeys,
@@ -241,8 +241,9 @@ def orientation(img, original_affine, spatial_ornt, lazy, transform_info) -> tor
     return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out  # type: ignore
 
 
-def flip_helper(data, sp_size, sp_axes, lazy, transform_info):
-    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist() if sp_size is not None else None
+def flip_helper(data, sp_axes, lazy, transform_info):
+    sp_size = data.peek_pending_shape() if isinstance(data, MetaTensor) else data.shape[1:]
+    sp_size = convert_to_numpy(sp_size, wrap_sequence=True).tolist()
     extra_info = {"axes": sp_axes}  # track the spatial axes
     axes = monai.transforms.utils.map_spatial_axes(data.ndim, sp_axes)  # use the axes with channel dim
     rank = data.peek_pending_rank() if isinstance(data, MetaTensor) else torch.tensor(3.0, dtype=torch.double)
@@ -250,14 +251,13 @@ def flip_helper(data, sp_size, sp_axes, lazy, transform_info):
     xform = torch.eye(int(rank) + 1, dtype=torch.double)
     for axis in axes:
         sp = axis - 1
-        if sp_size is not None:
-            xform[sp, sp], xform[sp, -1] = xform[sp, sp] * -1, sp_size[sp] - 1
-        else:
-            xform[sp, sp] *= -1
+        if data.kind == KindKeys.PIXEL:
+            xform[sp, -1] = sp_size[sp] - 1
+        xform[sp, sp] = xform[sp, sp] * -1
     meta_info = TraceableTransform.track_transform_meta(
         data, affine=xform, extra_info=extra_info, lazy=lazy, transform_info=transform_info
     )
-    return axes, meta_info
+    return axes, meta_info, xform
 
 
 def flip_image(img, sp_axes, lazy, transform_info):
@@ -279,8 +279,7 @@ def flip_image(img, sp_axes, lazy, transform_info):
     kind = img.meta.get(MetaKeys.KIND, KindKeys.PIXEL) if isinstance(img, MetaTensor) else KindKeys.PIXEL
     if kind != KindKeys.PIXEL:
         return None
-    sp_size = img.peek_pending_shape() if isinstance(img, MetaTensor) else img.shape[1:]
-    axes, meta_info = flip_helper(img, sp_size, sp_axes, lazy, transform_info)
+    axes, meta_info, _ = flip_helper(img, sp_axes, lazy, transform_info)
     out = _maybe_new_metatensor(img)
     if lazy:
         return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
@@ -308,25 +307,14 @@ def flip_point(points, sp_axes, lazy, transform_info):
     kind = points.meta.get(MetaKeys.KIND, KindKeys.PIXEL) if isinstance(points, MetaTensor) else KindKeys.PIXEL
     if kind != KindKeys.POINT:
         return None
-    # TODO: use enum
-    if points.meta.get("refer_meta", None) is not None:
-        sp_size = points.meta["refer_meta"]["spatial_shape"]
-    else:
-        sp_size = None
-    axes, meta_info = flip_helper(points, sp_size, sp_axes, lazy, transform_info)
-    # flip box
-    out = deepcopy(_maybe_new_metatensor(points))
+    _, meta_info, xform = flip_helper(points, sp_axes, lazy, transform_info)
+
+    out = _maybe_new_metatensor(points)
     if lazy:
         # TODO: add lazy support
         raise NotImplementedError
         return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
-    if sp_size is None:
-        warnings.warn("''sp_size'' is None, will flip in the world coordinates.")
-        for _axes in axes:
-            out[..., _axes - 1] = -points[..., _axes - 1]
-    else:
-        for _axes in axes:
-            out[..., _axes - 1] = sp_size[_axes - 1] - points[..., _axes - 1]
+    out = apply_affine_to_points(out[0], xform, dtype=torch.float64).unsqueeze(0)
     return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out
 
 
@@ -675,3 +663,16 @@ def affine_func(
         out = _maybe_new_metatensor(img, dtype=torch.float32, device=resampler.device)
     out = out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out
     return out if image_only else (out, affine)
+
+
+def apply_affine_to_points(data, affine, dtype):
+    data = convert_to_tensor(data, track_meta=get_track_meta())
+    data_: torch.Tensor = convert_to_tensor(data, track_meta=False, dtype=dtype)
+
+    homogeneous = concatenate((data_, torch.ones((data_.shape[0], 1))), axis=1)
+    transformed_homogeneous = torch.matmul(affine, homogeneous.T)
+    transformed_coordinates = transformed_homogeneous[:-1].T
+    out, *_ = convert_to_dst_type(transformed_coordinates, data, dtype=dtype)
+
+    return out
+

From a77b8c6f4e14ec0f842758e104eb2558c7fabbc9 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 30 Jul 2024 15:03:45 +0000
Subject: [PATCH 15/16] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 monai/transforms/spatial/functional.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index d4b1b5762c..b6168a3bcb 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -16,7 +16,6 @@
 
 import math
 import warnings
-from copy import deepcopy
 from enum import Enum
 
 import numpy as np
@@ -675,4 +674,3 @@ def apply_affine_to_points(data, affine, dtype):
     out, *_ = convert_to_dst_type(transformed_coordinates, data, dtype=dtype)
 
     return out
-

From 812820a225a90fdda961c641f02003d733d305f0 Mon Sep 17 00:00:00 2001
From: YunLiu <55491388+KumoLiu@users.noreply.github.com>
Date: Thu, 1 Aug 2024 18:54:29 +0800
Subject: [PATCH 16/16] update

Signed-off-by: YunLiu <55491388+KumoLiu@users.noreply.github.com>
---
 monai/transforms/spatial/functional.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/monai/transforms/spatial/functional.py b/monai/transforms/spatial/functional.py
index b6168a3bcb..e5712ee239 100644
--- a/monai/transforms/spatial/functional.py
+++ b/monai/transforms/spatial/functional.py
@@ -313,6 +313,7 @@ def flip_point(points, sp_axes, lazy, transform_info):
         # TODO: add lazy support
         raise NotImplementedError
         return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else meta_info
+    # TODO: use CoordinateTransformd.apply_affine_to_points instead
     out = apply_affine_to_points(out[0], xform, dtype=torch.float64).unsqueeze(0)
     return out.copy_meta_from(meta_info) if isinstance(out, MetaTensor) else out