refactor bounding box#617

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LucaMarconato merged 12 commits into from
Jul 12, 2024
Merged

refactor bounding box #617

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4ebeedb
replace concat
giovp Jul 5, 2024
0e40e1d
refactor
giovp Jul 5, 2024
95999ea
fix type
giovp Jul 5, 2024
e6bb9b0
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Jul 5, 2024
1685be3
fix typing
giovp Jul 5, 2024
7490119
cleanup
giovp Jul 5, 2024
cc85a7f
skip dataloader test
giovp Jul 5, 2024
d8beae5
address comments
giovp Jul 8, 2024
50abb20
add tests for return_request_only
giovp Jul 8, 2024
9e9fb66
add docs
giovp Jul 8, 2024
0b0edc8
removed swap variables for non-raster; fixed _adjust_bounding_box_to_…
LucaMarconato Jul 8, 2024
7627f9f
added tests
LucaMarconato Jul 12, 2024
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2 changes: 1 addition & 1 deletion CHANGELOG.md
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Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down
130 changes: 66 additions & 64 deletions src/spatialdata/_core/query/spatial_query.py
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Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
min_coordinate: list[Number] | ArrayLike,
max_coordinate: list[Number] | ArrayLike,
target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
"""Get all corners of a bounding box in the intrinsic coordinates of an element.

Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

The axes of the intrinsic coordinate system.
"""
from spatialdata.transformations import get_transformation

min_coordinate = _parse_list_into_array(min_coordinate)
max_coordinate = _parse_list_into_array(max_coordinate)
# get the transformation from the element's intrinsic coordinate system
# to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

# compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
element, target_coordinate_system
)
axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

# we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
# transformations; we focus on them
m_without_c_linear = m_without_c[:-1, :-1]
_ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

# adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
# not adjusted
axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
axes, min_coordinate, max_coordinate, output_axes_without_c
)
if set(axes_adjusted) != set(output_axes_without_c):
raise ValueError("The axes of the bounding box must match the axes of the transformation.")

# axes, input_axes_without_c = input_axes_without_c, axes

# let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
# in case 1 or 5, the transformation is invertible
spatial_transform_bb_axes = Affine(
spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
input_axes=input_axes_without_c,
output_axes=axes_adjusted,
)

# get the coordinates of the bounding box corners
bounding_box_corners = get_bounding_box_corners(
min_coordinate=min_coordinate,
max_coordinate=max_coordinate,
axes=axes,
).data

# transform the coordinates to the intrinsic coordinate system
intrinsic_axes = get_axes_names(element)
transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
input_axes=axes, output_axes=intrinsic_axes
axes=axes_adjusted,
)
rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
translation = transform_to_intrinsic[0:-1, -1]

intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
inverse = spatial_transform_bb_axes.inverse()
if not isinstance(inverse, Affine):
raise RuntimeError("This should not happen")
rotation_matrix = inverse.matrix[0:-1, 0:-1]
translation = inverse.matrix[0:-1, -1]

intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

return intrinsic_bounding_box_corners, intrinsic_axes
return (
DataArray(
intrinsic_bounding_box_corners,
coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
),
input_axes_without_c,
)


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
M = np.finfo(np.float32).max - 1
min_coordinate = np.append(min_coordinate, -M)
max_coordinate = np.append(max_coordinate, M)
else:
indices = [axes_bb.index(ax) for ax in axes_out_without_c]
min_coordinate = min_coordinate[np.array(indices)]
max_coordinate = max_coordinate[np.array(indices)]
axes_bb = axes_out_without_c
return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
min_coordinate: list[Number] | ArrayLike,
max_coordinate: list[Number] | ArrayLike,
target_coordinate_system: str,
return_request_only: bool = False,
filter_table: bool = True,
**kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
filter_table
If `True`, the table is filtered to only contain rows that are annotating regions
contained within the bounding box.
return_request_only
If `True`, the function returns the bounding box coordinates in the target coordinate system.
Only valid with `DataArray` and `DataTree` elements.

Returns
-------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
min_coordinate: list[Number] | ArrayLike,
max_coordinate: list[Number] | ArrayLike,
target_coordinate_system: str,
) -> DataArray | DataTree | None:
return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
"""Implement bounding box query for Spatialdata supported DataArray.

Notes
Expand All@@ -493,48 +526,11 @@ def _(
max_coordinate=max_coordinate,
)

# compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
image, target_coordinate_system
)
spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

# we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
# transformations; we focus on them
m_without_c_linear = m_without_c[:-1, :-1]
case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
assert case in [1, 5]

# adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
# not adjusted
axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
axes, min_coordinate, max_coordinate, output_axes_without_c
)
assert set(axes) == set(output_axes_without_c)

# since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
spatial_transform_bb_axes = Affine(
spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
input_axes=input_axes_without_c,
output_axes=axes,
)

# let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
# in case 1 or 5, the transformation is invertible
bounding_box_corners = get_bounding_box_corners(
min_coordinate=min_coordinate,
max_coordinate=max_coordinate,
axes=axes,
)
inverse = spatial_transform_bb_axes.inverse()
assert isinstance(inverse, Affine)
rotation_matrix = inverse.matrix[0:-1, 0:-1]
translation = inverse.matrix[0:-1, -1]
intrinsic_bounding_box_corners = DataArray(
bounding_box_corners.data @ rotation_matrix.T + translation,
coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
image, axes, min_coordinate, max_coordinate, target_coordinate_system
)
if TYPE_CHECKING:
assert isinstance(intrinsic_bounding_box_corners, DataArray)

# build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
# to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
else:
translation_vector.append(0)

if return_request_only:
return selection

# query the data
query_result = image.sel(selection)
if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
max_coordinate=max_coordinate,
target_coordinate_system=target_coordinate_system,
)
intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
)

# get the four corners of the bounding box
(intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
(intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
element=polygons,
axes=axes,
min_coordinate=min_coordinate,
max_coordinate=max_coordinate,
target_coordinate_system=target_coordinate_system,
)

intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
image: DataArray | DataTree,
polygon: Polygon | MultiPolygon,
target_coordinate_system: str,
return_request_only: bool = False,
**kwargs: Any,
) -> DataArray | DataTree | None:
_check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
max_coordinate=[max_x, max_y],
axes=("x", "y"),
target_coordinate_system=target_coordinate_system,
return_request_only=return_request_only,
)


Expand Down
3 changes: 2 additions & 1 deletion src/spatialdata/dataloader/datasets.py
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Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
self.dataset_index = pd.concat(index_df).reset_index(drop=True)
assert len(self.tiles_coords) == len(self.dataset_index)
if table_name:
self.dataset_table = AnnData.concatenate(*tables_l)
self.dataset_table = ad.concat(*tables_l)
assert len(self.tiles_coords) == len(self.dataset_table)

dims_ = set(chain(*dims_l))
Expand Down
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refactor bounding box#617

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to your account

 Merged

LucaMarconato
merged 12 commits into

from

Jul 12, 2024
 Merged


refactor bounding box
#617
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4ebeedb

replace concat


giovp Jul 5, 2024
0e40e1d

refactor


giovp Jul 5, 2024
95999ea

fix type


giovp Jul 5, 2024
e6bb9b0

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Jul 5, 2024
1685be3

fix typing


giovp Jul 5, 2024
7490119

cleanup


giovp Jul 5, 2024
cc85a7f

skip dataloader test


giovp Jul 5, 2024
d8beae5

address comments


giovp Jul 8, 2024
50abb20

add tests for return_request_only


giovp Jul 8, 2024
9e9fb66

add docs


giovp Jul 8, 2024
0b0edc8

removed swap variables for non-raster; fixed _adjust_bounding_box_to_…


LucaMarconato Jul 8, 2024
7627f9f

added tests


LucaMarconato Jul 12, 2024

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2 changes: 1 addition & 1 deletion
CHANGELOG.md

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down

130 changes: 66 additions & 64 deletions
src/spatialdata/_core/query/spatial_query.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
 """Get all corners of a bounding box in the intrinsic coordinates of an element.

 Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

 The axes of the intrinsic coordinate system.
 """
 from spatialdata.transformations import get_transformation

 min_coordinate = _parse_list_into_array(min_coordinate)
 max_coordinate = _parse_list_into_array(max_coordinate)
 # get the transformation from the element's intrinsic coordinate system
 # to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 element, target_coordinate_system
 )
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 _ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 if set(axes_adjusted) != set(output_axes_without_c):
 raise ValueError("The axes of the bounding box must match the axes of the transformation.")

 # axes, input_axes_without_c = input_axes_without_c, axes

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
 input_axes=input_axes_without_c,
 output_axes=axes_adjusted,
 )

 # get the coordinates of the bounding box corners
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 ).data

 # transform the coordinates to the intrinsic coordinate system
 intrinsic_axes = get_axes_names(element)
 transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
 input_axes=axes, output_axes=intrinsic_axes
 axes=axes_adjusted,
 )
 rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
 translation = transform_to_intrinsic[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
 inverse = spatial_transform_bb_axes.inverse()
 if not isinstance(inverse, Affine):
 raise RuntimeError("This should not happen")
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

 return intrinsic_bounding_box_corners, intrinsic_axes
 return (
 DataArray(
 intrinsic_bounding_box_corners,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 ),
 input_axes_without_c,
 )


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
 M = np.finfo(np.float32).max - 1
 min_coordinate = np.append(min_coordinate, -M)
 max_coordinate = np.append(max_coordinate, M)
 else:
 indices = [axes_bb.index(ax) for ax in axes_out_without_c]
 min_coordinate = min_coordinate[np.array(indices)]
 max_coordinate = max_coordinate[np.array(indices)]
 axes_bb = axes_out_without_c
 return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
 return_request_only: bool = False,
 filter_table: bool = True,
 **kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
 filter_table
 If `True`, the table is filtered to only contain rows that are annotating regions
 contained within the bounding box.
 return_request_only
 If `True`, the function returns the bounding box coordinates in the target coordinate system.
 Only valid with `DataArray` and `DataTree` elements.

 Returns
 -------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> DataArray | DataTree | None:
 return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
 """Implement bounding box query for Spatialdata supported DataArray.

 Notes
Expand All@@ -493,48 +526,11 @@ def _(
 max_coordinate=max_coordinate,
 )

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
 # and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 image, target_coordinate_system
 )
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
 assert case in [1, 5]

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 assert set(axes) == set(output_axes_without_c)

 # since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
 input_axes=input_axes_without_c,
 output_axes=axes,
 )

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 )
 inverse = spatial_transform_bb_axes.inverse()
 assert isinstance(inverse, Affine)
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]
 intrinsic_bounding_box_corners = DataArray(
 bounding_box_corners.data @ rotation_matrix.T + translation,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
 image, axes, min_coordinate, max_coordinate, target_coordinate_system
 )
 if TYPE_CHECKING:
 assert isinstance(intrinsic_bounding_box_corners, DataArray)

 # build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
 # to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
 else:
 translation_vector.append(0)

 if return_request_only:
 return selection

 # query the data
 query_result = image.sel(selection)
 if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )
 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
 max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
 )

 # get the four corners of the bounding box
 (intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
 (intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
 element=polygons,
 axes=axes,
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )

 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
 indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
 queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
 image: DataArray | DataTree,
 polygon: Polygon | MultiPolygon,
 target_coordinate_system: str,
 return_request_only: bool = False,
 **kwargs: Any,
) -> DataArray | DataTree | None:
 _check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
 max_coordinate=[max_x, max_y],
 axes=("x", "y"),
 target_coordinate_system=target_coordinate_system,
 return_request_only=return_request_only,
 )


Expand Down

3 changes: 2 additions & 1 deletion
src/spatialdata/dataloader/datasets.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
 self.dataset_index = pd.concat(index_df).reset_index(drop=True)
 assert len(self.tiles_coords) == len(self.dataset_index)
 if table_name:
 self.dataset_table = AnnData.concatenate(*tables_l)
 self.dataset_table = ad.concat(*tables_l)
 assert len(self.tiles_coords) == len(self.dataset_table)

 dims_ = set(chain(*dims_l))
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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refactor bounding box#617

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LucaMarconato
merged 12 commits into

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Jul 12, 2024
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refactor bounding box
#617
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4ebeedb

replace concat


giovp Jul 5, 2024
0e40e1d

refactor


giovp Jul 5, 2024
95999ea

fix type


giovp Jul 5, 2024
e6bb9b0

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Jul 5, 2024
1685be3

fix typing


giovp Jul 5, 2024
7490119

cleanup


giovp Jul 5, 2024
cc85a7f

skip dataloader test


giovp Jul 5, 2024
d8beae5

address comments


giovp Jul 8, 2024
50abb20

add tests for return_request_only


giovp Jul 8, 2024
9e9fb66

add docs


giovp Jul 8, 2024
0b0edc8

removed swap variables for non-raster; fixed _adjust_bounding_box_to_…


LucaMarconato Jul 8, 2024
7627f9f

added tests


LucaMarconato Jul 12, 2024

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2 changes: 1 addition & 1 deletion
CHANGELOG.md

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Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down

130 changes: 66 additions & 64 deletions
src/spatialdata/_core/query/spatial_query.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
 """Get all corners of a bounding box in the intrinsic coordinates of an element.

 Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

 The axes of the intrinsic coordinate system.
 """
 from spatialdata.transformations import get_transformation

 min_coordinate = _parse_list_into_array(min_coordinate)
 max_coordinate = _parse_list_into_array(max_coordinate)
 # get the transformation from the element's intrinsic coordinate system
 # to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 element, target_coordinate_system
 )
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 _ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 if set(axes_adjusted) != set(output_axes_without_c):
 raise ValueError("The axes of the bounding box must match the axes of the transformation.")

 # axes, input_axes_without_c = input_axes_without_c, axes

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
 input_axes=input_axes_without_c,
 output_axes=axes_adjusted,
 )

 # get the coordinates of the bounding box corners
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 ).data

 # transform the coordinates to the intrinsic coordinate system
 intrinsic_axes = get_axes_names(element)
 transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
 input_axes=axes, output_axes=intrinsic_axes
 axes=axes_adjusted,
 )
 rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
 translation = transform_to_intrinsic[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
 inverse = spatial_transform_bb_axes.inverse()
 if not isinstance(inverse, Affine):
 raise RuntimeError("This should not happen")
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

 return intrinsic_bounding_box_corners, intrinsic_axes
 return (
 DataArray(
 intrinsic_bounding_box_corners,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 ),
 input_axes_without_c,
 )


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
 M = np.finfo(np.float32).max - 1
 min_coordinate = np.append(min_coordinate, -M)
 max_coordinate = np.append(max_coordinate, M)
 else:
 indices = [axes_bb.index(ax) for ax in axes_out_without_c]
 min_coordinate = min_coordinate[np.array(indices)]
 max_coordinate = max_coordinate[np.array(indices)]
 axes_bb = axes_out_without_c
 return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
 return_request_only: bool = False,
 filter_table: bool = True,
 **kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
 filter_table
 If `True`, the table is filtered to only contain rows that are annotating regions
 contained within the bounding box.
 return_request_only
 If `True`, the function returns the bounding box coordinates in the target coordinate system.
 Only valid with `DataArray` and `DataTree` elements.

 Returns
 -------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> DataArray | DataTree | None:
 return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
 """Implement bounding box query for Spatialdata supported DataArray.

 Notes
Expand All@@ -493,48 +526,11 @@ def _(
 max_coordinate=max_coordinate,
 )

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
 # and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 image, target_coordinate_system
 )
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
 assert case in [1, 5]

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 assert set(axes) == set(output_axes_without_c)

 # since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
 input_axes=input_axes_without_c,
 output_axes=axes,
 )

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 )
 inverse = spatial_transform_bb_axes.inverse()
 assert isinstance(inverse, Affine)
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]
 intrinsic_bounding_box_corners = DataArray(
 bounding_box_corners.data @ rotation_matrix.T + translation,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
 image, axes, min_coordinate, max_coordinate, target_coordinate_system
 )
 if TYPE_CHECKING:
 assert isinstance(intrinsic_bounding_box_corners, DataArray)

 # build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
 # to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
 else:
 translation_vector.append(0)

 if return_request_only:
 return selection

 # query the data
 query_result = image.sel(selection)
 if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )
 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
 max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
 )

 # get the four corners of the bounding box
 (intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
 (intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
 element=polygons,
 axes=axes,
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )

 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
 indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
 queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
 image: DataArray | DataTree,
 polygon: Polygon | MultiPolygon,
 target_coordinate_system: str,
 return_request_only: bool = False,
 **kwargs: Any,
) -> DataArray | DataTree | None:
 _check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
 max_coordinate=[max_x, max_y],
 axes=("x", "y"),
 target_coordinate_system=target_coordinate_system,
 return_request_only=return_request_only,
 )


Expand Down

3 changes: 2 additions & 1 deletion
src/spatialdata/dataloader/datasets.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
 self.dataset_index = pd.concat(index_df).reset_index(drop=True)
 assert len(self.tiles_coords) == len(self.dataset_index)
 if table_name:
 self.dataset_table = AnnData.concatenate(*tables_l)
 self.dataset_table = ad.concat(*tables_l)
 assert len(self.tiles_coords) == len(self.dataset_table)

 dims_ = set(chain(*dims_l))
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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refactor bounding box#617

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 Merged

LucaMarconato
merged 12 commits into

from

Jul 12, 2024
 Merged


refactor bounding box
#617
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4ebeedb

replace concat


giovp Jul 5, 2024
0e40e1d

refactor


giovp Jul 5, 2024
95999ea

fix type


giovp Jul 5, 2024
e6bb9b0

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Jul 5, 2024
1685be3

fix typing


giovp Jul 5, 2024
7490119

cleanup


giovp Jul 5, 2024
cc85a7f

skip dataloader test


giovp Jul 5, 2024
d8beae5

address comments


giovp Jul 8, 2024
50abb20

add tests for return_request_only


giovp Jul 8, 2024
9e9fb66

add docs


giovp Jul 8, 2024
0b0edc8

removed swap variables for non-raster; fixed _adjust_bounding_box_to_…


LucaMarconato Jul 8, 2024
7627f9f

added tests


LucaMarconato Jul 12, 2024

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2 changes: 1 addition & 1 deletion
CHANGELOG.md

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down

130 changes: 66 additions & 64 deletions
src/spatialdata/_core/query/spatial_query.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
 """Get all corners of a bounding box in the intrinsic coordinates of an element.

 Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

 The axes of the intrinsic coordinate system.
 """
 from spatialdata.transformations import get_transformation

 min_coordinate = _parse_list_into_array(min_coordinate)
 max_coordinate = _parse_list_into_array(max_coordinate)
 # get the transformation from the element's intrinsic coordinate system
 # to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 element, target_coordinate_system
 )
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 _ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 if set(axes_adjusted) != set(output_axes_without_c):
 raise ValueError("The axes of the bounding box must match the axes of the transformation.")

 # axes, input_axes_without_c = input_axes_without_c, axes

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
 input_axes=input_axes_without_c,
 output_axes=axes_adjusted,
 )

 # get the coordinates of the bounding box corners
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 ).data

 # transform the coordinates to the intrinsic coordinate system
 intrinsic_axes = get_axes_names(element)
 transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
 input_axes=axes, output_axes=intrinsic_axes
 axes=axes_adjusted,
 )
 rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
 translation = transform_to_intrinsic[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
 inverse = spatial_transform_bb_axes.inverse()
 if not isinstance(inverse, Affine):
 raise RuntimeError("This should not happen")
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

 return intrinsic_bounding_box_corners, intrinsic_axes
 return (
 DataArray(
 intrinsic_bounding_box_corners,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 ),
 input_axes_without_c,
 )


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
 M = np.finfo(np.float32).max - 1
 min_coordinate = np.append(min_coordinate, -M)
 max_coordinate = np.append(max_coordinate, M)
 else:
 indices = [axes_bb.index(ax) for ax in axes_out_without_c]
 min_coordinate = min_coordinate[np.array(indices)]
 max_coordinate = max_coordinate[np.array(indices)]
 axes_bb = axes_out_without_c
 return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
 return_request_only: bool = False,
 filter_table: bool = True,
 **kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
 filter_table
 If `True`, the table is filtered to only contain rows that are annotating regions
 contained within the bounding box.
 return_request_only
 If `True`, the function returns the bounding box coordinates in the target coordinate system.
 Only valid with `DataArray` and `DataTree` elements.

 Returns
 -------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> DataArray | DataTree | None:
 return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
 """Implement bounding box query for Spatialdata supported DataArray.

 Notes
Expand All@@ -493,48 +526,11 @@ def _(
 max_coordinate=max_coordinate,
 )

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
 # and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 image, target_coordinate_system
 )
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
 assert case in [1, 5]

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 assert set(axes) == set(output_axes_without_c)

 # since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
 input_axes=input_axes_without_c,
 output_axes=axes,
 )

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 )
 inverse = spatial_transform_bb_axes.inverse()
 assert isinstance(inverse, Affine)
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]
 intrinsic_bounding_box_corners = DataArray(
 bounding_box_corners.data @ rotation_matrix.T + translation,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
 image, axes, min_coordinate, max_coordinate, target_coordinate_system
 )
 if TYPE_CHECKING:
 assert isinstance(intrinsic_bounding_box_corners, DataArray)

 # build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
 # to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
 else:
 translation_vector.append(0)

 if return_request_only:
 return selection

 # query the data
 query_result = image.sel(selection)
 if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )
 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
 max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
 )

 # get the four corners of the bounding box
 (intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
 (intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
 element=polygons,
 axes=axes,
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )

 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
 indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
 queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
 image: DataArray | DataTree,
 polygon: Polygon | MultiPolygon,
 target_coordinate_system: str,
 return_request_only: bool = False,
 **kwargs: Any,
) -> DataArray | DataTree | None:
 _check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
 max_coordinate=[max_x, max_y],
 axes=("x", "y"),
 target_coordinate_system=target_coordinate_system,
 return_request_only=return_request_only,
 )


Expand Down

3 changes: 2 additions & 1 deletion
src/spatialdata/dataloader/datasets.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
 self.dataset_index = pd.concat(index_df).reset_index(drop=True)
 assert len(self.tiles_coords) == len(self.dataset_index)
 if table_name:
 self.dataset_table = AnnData.concatenate(*tables_l)
 self.dataset_table = ad.concat(*tables_l)
 assert len(self.tiles_coords) == len(self.dataset_table)

 dims_ = set(chain(*dims_l))
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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refactor bounding box#617

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LucaMarconato
merged 12 commits into

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Jul 12, 2024
 Merged


refactor bounding box
#617
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4ebeedb

replace concat


giovp Jul 5, 2024
0e40e1d

refactor


giovp Jul 5, 2024
95999ea

fix type


giovp Jul 5, 2024
e6bb9b0

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Jul 5, 2024
1685be3

fix typing


giovp Jul 5, 2024
7490119

cleanup


giovp Jul 5, 2024
cc85a7f

skip dataloader test


giovp Jul 5, 2024
d8beae5

address comments


giovp Jul 8, 2024
50abb20

add tests for return_request_only


giovp Jul 8, 2024
9e9fb66

add docs


giovp Jul 8, 2024
0b0edc8

removed swap variables for non-raster; fixed _adjust_bounding_box_to_…


LucaMarconato Jul 8, 2024
7627f9f

added tests


LucaMarconato Jul 12, 2024

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2 changes: 1 addition & 1 deletion
CHANGELOG.md

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down

130 changes: 66 additions & 64 deletions
src/spatialdata/_core/query/spatial_query.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
 """Get all corners of a bounding box in the intrinsic coordinates of an element.

 Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

 The axes of the intrinsic coordinate system.
 """
 from spatialdata.transformations import get_transformation

 min_coordinate = _parse_list_into_array(min_coordinate)
 max_coordinate = _parse_list_into_array(max_coordinate)
 # get the transformation from the element's intrinsic coordinate system
 # to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 element, target_coordinate_system
 )
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 _ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 if set(axes_adjusted) != set(output_axes_without_c):
 raise ValueError("The axes of the bounding box must match the axes of the transformation.")

 # axes, input_axes_without_c = input_axes_without_c, axes

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
 input_axes=input_axes_without_c,
 output_axes=axes_adjusted,
 )

 # get the coordinates of the bounding box corners
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 ).data

 # transform the coordinates to the intrinsic coordinate system
 intrinsic_axes = get_axes_names(element)
 transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
 input_axes=axes, output_axes=intrinsic_axes
 axes=axes_adjusted,
 )
 rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
 translation = transform_to_intrinsic[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
 inverse = spatial_transform_bb_axes.inverse()
 if not isinstance(inverse, Affine):
 raise RuntimeError("This should not happen")
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

 return intrinsic_bounding_box_corners, intrinsic_axes
 return (
 DataArray(
 intrinsic_bounding_box_corners,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 ),
 input_axes_without_c,
 )


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
 M = np.finfo(np.float32).max - 1
 min_coordinate = np.append(min_coordinate, -M)
 max_coordinate = np.append(max_coordinate, M)
 else:
 indices = [axes_bb.index(ax) for ax in axes_out_without_c]
 min_coordinate = min_coordinate[np.array(indices)]
 max_coordinate = max_coordinate[np.array(indices)]
 axes_bb = axes_out_without_c
 return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
 return_request_only: bool = False,
 filter_table: bool = True,
 **kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
 filter_table
 If `True`, the table is filtered to only contain rows that are annotating regions
 contained within the bounding box.
 return_request_only
 If `True`, the function returns the bounding box coordinates in the target coordinate system.
 Only valid with `DataArray` and `DataTree` elements.

 Returns
 -------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> DataArray | DataTree | None:
 return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
 """Implement bounding box query for Spatialdata supported DataArray.

 Notes
Expand All@@ -493,48 +526,11 @@ def _(
 max_coordinate=max_coordinate,
 )

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
 # and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 image, target_coordinate_system
 )
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
 assert case in [1, 5]

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 assert set(axes) == set(output_axes_without_c)

 # since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
 input_axes=input_axes_without_c,
 output_axes=axes,
 )

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 )
 inverse = spatial_transform_bb_axes.inverse()
 assert isinstance(inverse, Affine)
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]
 intrinsic_bounding_box_corners = DataArray(
 bounding_box_corners.data @ rotation_matrix.T + translation,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
 image, axes, min_coordinate, max_coordinate, target_coordinate_system
 )
 if TYPE_CHECKING:
 assert isinstance(intrinsic_bounding_box_corners, DataArray)

 # build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
 # to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
 else:
 translation_vector.append(0)

 if return_request_only:
 return selection

 # query the data
 query_result = image.sel(selection)
 if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )
 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
 max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
 )

 # get the four corners of the bounding box
 (intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
 (intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
 element=polygons,
 axes=axes,
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )

 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
 indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
 queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
 image: DataArray | DataTree,
 polygon: Polygon | MultiPolygon,
 target_coordinate_system: str,
 return_request_only: bool = False,
 **kwargs: Any,
) -> DataArray | DataTree | None:
 _check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
 max_coordinate=[max_x, max_y],
 axes=("x", "y"),
 target_coordinate_system=target_coordinate_system,
 return_request_only=return_request_only,
 )


Expand Down

3 changes: 2 additions & 1 deletion
src/spatialdata/dataloader/datasets.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
 self.dataset_index = pd.concat(index_df).reset_index(drop=True)
 assert len(self.tiles_coords) == len(self.dataset_index)
 if table_name:
 self.dataset_table = AnnData.concatenate(*tables_l)
 self.dataset_table = ad.concat(*tables_l)
 assert len(self.tiles_coords) == len(self.dataset_table)

 dims_ = set(chain(*dims_l))
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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refactor bounding box#617

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to your account

 Merged

LucaMarconato
merged 12 commits into

from

Jul 12, 2024
 Merged


refactor bounding box
#617
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4ebeedb

replace concat


giovp Jul 5, 2024
0e40e1d

refactor


giovp Jul 5, 2024
95999ea

fix type


giovp Jul 5, 2024
e6bb9b0

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Jul 5, 2024
1685be3

fix typing


giovp Jul 5, 2024
7490119

cleanup


giovp Jul 5, 2024
cc85a7f

skip dataloader test


giovp Jul 5, 2024
d8beae5

address comments


giovp Jul 8, 2024
50abb20

add tests for return_request_only


giovp Jul 8, 2024
9e9fb66

add docs


giovp Jul 8, 2024
0b0edc8

removed swap variables for non-raster; fixed _adjust_bounding_box_to_…


LucaMarconato Jul 8, 2024
7627f9f

added tests


LucaMarconato Jul 12, 2024

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2 changes: 1 addition & 1 deletion
CHANGELOG.md

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down

130 changes: 66 additions & 64 deletions
src/spatialdata/_core/query/spatial_query.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
 """Get all corners of a bounding box in the intrinsic coordinates of an element.

 Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

 The axes of the intrinsic coordinate system.
 """
 from spatialdata.transformations import get_transformation

 min_coordinate = _parse_list_into_array(min_coordinate)
 max_coordinate = _parse_list_into_array(max_coordinate)
 # get the transformation from the element's intrinsic coordinate system
 # to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 element, target_coordinate_system
 )
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 _ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 if set(axes_adjusted) != set(output_axes_without_c):
 raise ValueError("The axes of the bounding box must match the axes of the transformation.")

 # axes, input_axes_without_c = input_axes_without_c, axes

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
 input_axes=input_axes_without_c,
 output_axes=axes_adjusted,
 )

 # get the coordinates of the bounding box corners
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 ).data

 # transform the coordinates to the intrinsic coordinate system
 intrinsic_axes = get_axes_names(element)
 transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
 input_axes=axes, output_axes=intrinsic_axes
 axes=axes_adjusted,
 )
 rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
 translation = transform_to_intrinsic[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
 inverse = spatial_transform_bb_axes.inverse()
 if not isinstance(inverse, Affine):
 raise RuntimeError("This should not happen")
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

 return intrinsic_bounding_box_corners, intrinsic_axes
 return (
 DataArray(
 intrinsic_bounding_box_corners,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 ),
 input_axes_without_c,
 )


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
 M = np.finfo(np.float32).max - 1
 min_coordinate = np.append(min_coordinate, -M)
 max_coordinate = np.append(max_coordinate, M)
 else:
 indices = [axes_bb.index(ax) for ax in axes_out_without_c]
 min_coordinate = min_coordinate[np.array(indices)]
 max_coordinate = max_coordinate[np.array(indices)]
 axes_bb = axes_out_without_c
 return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
 return_request_only: bool = False,
 filter_table: bool = True,
 **kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
 filter_table
 If `True`, the table is filtered to only contain rows that are annotating regions
 contained within the bounding box.
 return_request_only
 If `True`, the function returns the bounding box coordinates in the target coordinate system.
 Only valid with `DataArray` and `DataTree` elements.

 Returns
 -------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> DataArray | DataTree | None:
 return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
 """Implement bounding box query for Spatialdata supported DataArray.

 Notes
Expand All@@ -493,48 +526,11 @@ def _(
 max_coordinate=max_coordinate,
 )

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
 # and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 image, target_coordinate_system
 )
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
 assert case in [1, 5]

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 assert set(axes) == set(output_axes_without_c)

 # since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
 input_axes=input_axes_without_c,
 output_axes=axes,
 )

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 )
 inverse = spatial_transform_bb_axes.inverse()
 assert isinstance(inverse, Affine)
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]
 intrinsic_bounding_box_corners = DataArray(
 bounding_box_corners.data @ rotation_matrix.T + translation,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
 image, axes, min_coordinate, max_coordinate, target_coordinate_system
 )
 if TYPE_CHECKING:
 assert isinstance(intrinsic_bounding_box_corners, DataArray)

 # build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
 # to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
 else:
 translation_vector.append(0)

 if return_request_only:
 return selection

 # query the data
 query_result = image.sel(selection)
 if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )
 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
 max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
 )

 # get the four corners of the bounding box
 (intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
 (intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
 element=polygons,
 axes=axes,
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )

 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
 indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
 queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
 image: DataArray | DataTree,
 polygon: Polygon | MultiPolygon,
 target_coordinate_system: str,
 return_request_only: bool = False,
 **kwargs: Any,
) -> DataArray | DataTree | None:
 _check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
 max_coordinate=[max_x, max_y],
 axes=("x", "y"),
 target_coordinate_system=target_coordinate_system,
 return_request_only=return_request_only,
 )


Expand Down

3 changes: 2 additions & 1 deletion
src/spatialdata/dataloader/datasets.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
 self.dataset_index = pd.concat(index_df).reset_index(drop=True)
 assert len(self.tiles_coords) == len(self.dataset_index)
 if table_name:
 self.dataset_table = AnnData.concatenate(*tables_l)
 self.dataset_table = ad.concat(*tables_l)
 assert len(self.tiles_coords) == len(self.dataset_table)

 dims_ = set(chain(*dims_l))
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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refactor bounding box#617

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 Merged

LucaMarconato
merged 12 commits into

from

Jul 12, 2024
 Merged


refactor bounding box
#617
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4ebeedb

replace concat


giovp Jul 5, 2024
0e40e1d

refactor


giovp Jul 5, 2024
95999ea

fix type


giovp Jul 5, 2024
e6bb9b0

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Jul 5, 2024
1685be3

fix typing


giovp Jul 5, 2024
7490119

cleanup


giovp Jul 5, 2024
cc85a7f

skip dataloader test


giovp Jul 5, 2024
d8beae5

address comments


giovp Jul 8, 2024
50abb20

add tests for return_request_only


giovp Jul 8, 2024
9e9fb66

add docs


giovp Jul 8, 2024
0b0edc8

removed swap variables for non-raster; fixed _adjust_bounding_box_to_…


LucaMarconato Jul 8, 2024
7627f9f

added tests


LucaMarconato Jul 12, 2024

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2 changes: 1 addition & 1 deletion
CHANGELOG.md

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Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down

130 changes: 66 additions & 64 deletions
src/spatialdata/_core/query/spatial_query.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
 """Get all corners of a bounding box in the intrinsic coordinates of an element.

 Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

 The axes of the intrinsic coordinate system.
 """
 from spatialdata.transformations import get_transformation

 min_coordinate = _parse_list_into_array(min_coordinate)
 max_coordinate = _parse_list_into_array(max_coordinate)
 # get the transformation from the element's intrinsic coordinate system
 # to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 element, target_coordinate_system
 )
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 _ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 if set(axes_adjusted) != set(output_axes_without_c):
 raise ValueError("The axes of the bounding box must match the axes of the transformation.")

 # axes, input_axes_without_c = input_axes_without_c, axes

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
 input_axes=input_axes_without_c,
 output_axes=axes_adjusted,
 )

 # get the coordinates of the bounding box corners
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 ).data

 # transform the coordinates to the intrinsic coordinate system
 intrinsic_axes = get_axes_names(element)
 transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
 input_axes=axes, output_axes=intrinsic_axes
 axes=axes_adjusted,
 )
 rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
 translation = transform_to_intrinsic[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
 inverse = spatial_transform_bb_axes.inverse()
 if not isinstance(inverse, Affine):
 raise RuntimeError("This should not happen")
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

 return intrinsic_bounding_box_corners, intrinsic_axes
 return (
 DataArray(
 intrinsic_bounding_box_corners,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 ),
 input_axes_without_c,
 )


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
 M = np.finfo(np.float32).max - 1
 min_coordinate = np.append(min_coordinate, -M)
 max_coordinate = np.append(max_coordinate, M)
 else:
 indices = [axes_bb.index(ax) for ax in axes_out_without_c]
 min_coordinate = min_coordinate[np.array(indices)]
 max_coordinate = max_coordinate[np.array(indices)]
 axes_bb = axes_out_without_c
 return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
 return_request_only: bool = False,
 filter_table: bool = True,
 **kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
 filter_table
 If `True`, the table is filtered to only contain rows that are annotating regions
 contained within the bounding box.
 return_request_only
 If `True`, the function returns the bounding box coordinates in the target coordinate system.
 Only valid with `DataArray` and `DataTree` elements.

 Returns
 -------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> DataArray | DataTree | None:
 return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
 """Implement bounding box query for Spatialdata supported DataArray.

 Notes
Expand All@@ -493,48 +526,11 @@ def _(
 max_coordinate=max_coordinate,
 )

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
 # and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 image, target_coordinate_system
 )
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
 assert case in [1, 5]

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 assert set(axes) == set(output_axes_without_c)

 # since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
 input_axes=input_axes_without_c,
 output_axes=axes,
 )

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 )
 inverse = spatial_transform_bb_axes.inverse()
 assert isinstance(inverse, Affine)
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]
 intrinsic_bounding_box_corners = DataArray(
 bounding_box_corners.data @ rotation_matrix.T + translation,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
 image, axes, min_coordinate, max_coordinate, target_coordinate_system
 )
 if TYPE_CHECKING:
 assert isinstance(intrinsic_bounding_box_corners, DataArray)

 # build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
 # to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
 else:
 translation_vector.append(0)

 if return_request_only:
 return selection

 # query the data
 query_result = image.sel(selection)
 if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )
 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
 max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
 )

 # get the four corners of the bounding box
 (intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
 (intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
 element=polygons,
 axes=axes,
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )

 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
 indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
 queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
 image: DataArray | DataTree,
 polygon: Polygon | MultiPolygon,
 target_coordinate_system: str,
 return_request_only: bool = False,
 **kwargs: Any,
) -> DataArray | DataTree | None:
 _check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
 max_coordinate=[max_x, max_y],
 axes=("x", "y"),
 target_coordinate_system=target_coordinate_system,
 return_request_only=return_request_only,
 )


Expand Down

3 changes: 2 additions & 1 deletion
src/spatialdata/dataloader/datasets.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
 self.dataset_index = pd.concat(index_df).reset_index(drop=True)
 assert len(self.tiles_coords) == len(self.dataset_index)
 if table_name:
 self.dataset_table = AnnData.concatenate(*tables_l)
 self.dataset_table = ad.concat(*tables_l)
 assert len(self.tiles_coords) == len(self.dataset_table)

 dims_ = set(chain(*dims_l))
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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refactor bounding box#617

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 Merged

LucaMarconato
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Jul 12, 2024
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refactor bounding box
#617
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4ebeedb

replace concat


giovp Jul 5, 2024
0e40e1d

refactor


giovp Jul 5, 2024
95999ea

fix type


giovp Jul 5, 2024
e6bb9b0

[pre-commit.ci] auto fixes from pre-commit.com hooks


pre-commit-ci[bot] Jul 5, 2024
1685be3

fix typing


giovp Jul 5, 2024
7490119

cleanup


giovp Jul 5, 2024
cc85a7f

skip dataloader test


giovp Jul 5, 2024
d8beae5

address comments


giovp Jul 8, 2024
50abb20

add tests for return_request_only


giovp Jul 8, 2024
9e9fb66

add docs


giovp Jul 8, 2024
0b0edc8

removed swap variables for non-raster; fixed _adjust_bounding_box_to_…


LucaMarconato Jul 8, 2024
7627f9f

added tests


LucaMarconato Jul 12, 2024

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2 changes: 1 addition & 1 deletion
CHANGELOG.md

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Original file line numberDiff line numberDiff line change
Expand Up@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning][].

### Minor

- Relaxing `spatial-image` package requirement #616
- Relaxing `spatial-image` package requirement #616

## [0.2.0] - 2024-07-03

Expand Down

130 changes: 66 additions & 64 deletions
src/spatialdata/_core/query/spatial_query.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,9 +2,10 @@

import warnings
from abc import abstractmethod
from collections.abc import Mapping
from dataclasses import dataclass
from functools import singledispatch
from typing import Any, Callable
from typing import TYPE_CHECKING, Any, Callable

import dask.array as da
import dask.dataframe as dd
Expand DownExpand Up@@ -49,7 +50,7 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> tuple[ArrayLike, tuple[str, ...]]:
) -> tuple[DataArray, tuple[str, ...]]:
 """Get all corners of a bounding box in the intrinsic coordinates of an element.

 Parameters
Expand All@@ -74,38 +75,60 @@ def _get_bounding_box_corners_in_intrinsic_coordinates(

 The axes of the intrinsic coordinate system.
 """
 from spatialdata.transformations import get_transformation

 min_coordinate = _parse_list_into_array(min_coordinate)
 max_coordinate = _parse_list_into_array(max_coordinate)
 # get the transformation from the element's intrinsic coordinate system
 # to the query coordinate space
transform_to_query_space = get_transformation(element, to_coordinate_system=target_coordinate_system)

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
# and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 element, target_coordinate_system
 )
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 _ = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes_adjusted, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 if set(axes_adjusted) != set(output_axes_without_c):
 raise ValueError("The axes of the bounding box must match the axes of the transformation.")

 # axes, input_axes_without_c = input_axes_without_c, axes

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes_adjusted),
 input_axes=input_axes_without_c,
 output_axes=axes_adjusted,
 )

 # get the coordinates of the bounding box corners
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 ).data

 # transform the coordinates to the intrinsic coordinate system
 intrinsic_axes = get_axes_names(element)
 transform_to_intrinsic = transform_to_query_space.inverse().to_affine_matrix( # type: ignore[union-attr]
 input_axes=axes, output_axes=intrinsic_axes
 axes=axes_adjusted,
 )
 rotation_matrix = transform_to_intrinsic[0:-1, 0:-1]
 translation = transform_to_intrinsic[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners @ rotation_matrix.T + translation
 inverse = spatial_transform_bb_axes.inverse()
 if not isinstance(inverse, Affine):
 raise RuntimeError("This should not happen")
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]

 intrinsic_bounding_box_corners = bounding_box_corners.data @ rotation_matrix.T + translation

 return intrinsic_bounding_box_corners, intrinsic_axes
 return (
 DataArray(
 intrinsic_bounding_box_corners,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 ),
 input_axes_without_c,
 )


def _get_polygon_in_intrinsic_coordinates(
Expand DownExpand Up@@ -227,6 +250,11 @@ def _adjust_bounding_box_to_real_axes(
 M = np.finfo(np.float32).max - 1
 min_coordinate = np.append(min_coordinate, -M)
 max_coordinate = np.append(max_coordinate, M)
 else:
 indices = [axes_bb.index(ax) for ax in axes_out_without_c]
 min_coordinate = min_coordinate[np.array(indices)]
 max_coordinate = max_coordinate[np.array(indices)]
 axes_bb = axes_out_without_c
 return axes_bb, min_coordinate, max_coordinate


Expand DownExpand Up@@ -407,6 +435,7 @@ def bounding_box_query(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
 return_request_only: bool = False,
 filter_table: bool = True,
 **kwargs: Any,
) -> SpatialElement | SpatialData | None:
Expand All@@ -426,6 +455,9 @@ def bounding_box_query(
 filter_table
 If `True`, the table is filtered to only contain rows that are annotating regions
 contained within the bounding box.
 return_request_only
 If `True`, the function returns the bounding box coordinates in the target coordinate system.
 Only valid with `DataArray` and `DataTree` elements.

 Returns
 -------
Expand DownExpand Up@@ -472,7 +504,8 @@ def _(
 min_coordinate: list[Number] | ArrayLike,
 max_coordinate: list[Number] | ArrayLike,
 target_coordinate_system: str,
) -> DataArray | DataTree | None:
 return_request_only: bool = False,
) -> DataArray | DataTree | Mapping[str, slice] | None:
 """Implement bounding box query for Spatialdata supported DataArray.

 Notes
Expand All@@ -493,48 +526,11 @@ def _(
 max_coordinate=max_coordinate,
 )

 # compute the output axes of the transformation, remove c from input and output axes, return the matrix without c
 # and then build an affine transformation from that
 m_without_c, input_axes_without_c, output_axes_without_c = _get_axes_of_tranformation(
 image, target_coordinate_system
 )
 spatial_transform = Affine(m_without_c, input_axes=input_axes_without_c, output_axes=output_axes_without_c)

 # we identified 5 cases (see the responsible function for details), cases 1 and 5 correspond to invertible
 # transformations; we focus on them
 m_without_c_linear = m_without_c[:-1, :-1]
 case = _get_case_of_bounding_box_query(m_without_c_linear, input_axes_without_c, output_axes_without_c)
 assert case in [1, 5]

 # adjust the bounding box to the real axes, dropping or adding eventually mismatching axes; the order of the axes is
 # not adjusted
 axes, min_coordinate, max_coordinate = _adjust_bounding_box_to_real_axes(
 axes, min_coordinate, max_coordinate, output_axes_without_c
 )
 assert set(axes) == set(output_axes_without_c)

 # since the order of the axes is arbitrary, let's adjust the affine transformation without c to match those axes
 spatial_transform_bb_axes = Affine(
 spatial_transform.to_affine_matrix(input_axes=input_axes_without_c, output_axes=axes),
 input_axes=input_axes_without_c,
 output_axes=axes,
 )

 # let's get the bounding box corners and inverse transform then to the intrinsic coordinate system; since we are
 # in case 1 or 5, the transformation is invertible
 bounding_box_corners = get_bounding_box_corners(
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 axes=axes,
 )
 inverse = spatial_transform_bb_axes.inverse()
 assert isinstance(inverse, Affine)
 rotation_matrix = inverse.matrix[0:-1, 0:-1]
 translation = inverse.matrix[0:-1, -1]
 intrinsic_bounding_box_corners = DataArray(
 bounding_box_corners.data @ rotation_matrix.T + translation,
 coords={"corner": range(len(bounding_box_corners)), "axis": list(inverse.output_axes)},
 intrinsic_bounding_box_corners, axes = _get_bounding_box_corners_in_intrinsic_coordinates(
 image, axes, min_coordinate, max_coordinate, target_coordinate_system
 )
 if TYPE_CHECKING:
 assert isinstance(intrinsic_bounding_box_corners, DataArray)

 # build the request: now that we have the bounding box corners in the intrinsic coordinate system, we can use them
 # to build the request to query the raster data using the xarray APIs
Expand All@@ -555,6 +551,9 @@ def _(
 else:
 translation_vector.append(0)

 if return_request_only:
 return selection

 # query the data
 query_result = image.sel(selection)
 if isinstance(image, DataArray):
Expand DownExpand Up@@ -652,6 +651,7 @@ def _(
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )
 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 min_coordinate_intrinsic = intrinsic_bounding_box_corners.min(axis=0)
 max_coordinate_intrinsic = intrinsic_bounding_box_corners.max(axis=0)

Expand DownExpand Up@@ -722,14 +722,14 @@ def _(
 )

 # get the four corners of the bounding box
 (intrinsic_bounding_box_corners, intrinsic_axes) = _get_bounding_box_corners_in_intrinsic_coordinates(
 (intrinsic_bounding_box_corners, _) = _get_bounding_box_corners_in_intrinsic_coordinates(
 element=polygons,
 axes=axes,
 min_coordinate=min_coordinate,
 max_coordinate=max_coordinate,
 target_coordinate_system=target_coordinate_system,
 )

 intrinsic_bounding_box_corners = intrinsic_bounding_box_corners.data
 bounding_box_non_axes_aligned = Polygon(intrinsic_bounding_box_corners)
 indices = polygons.geometry.intersects(bounding_box_non_axes_aligned)
 queried = polygons[indices]
Expand DownExpand Up@@ -841,6 +841,7 @@ def _(
 image: DataArray | DataTree,
 polygon: Polygon | MultiPolygon,
 target_coordinate_system: str,
 return_request_only: bool = False,
 **kwargs: Any,
) -> DataArray | DataTree | None:
 _check_deprecated_kwargs(kwargs)
Expand All@@ -852,6 +853,7 @@ def _(
 max_coordinate=[max_x, max_y],
 axes=("x", "y"),
 target_coordinate_system=target_coordinate_system,
 return_request_only=return_request_only,
 )


Expand Down

3 changes: 2 additions & 1 deletion
src/spatialdata/dataloader/datasets.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -7,6 +7,7 @@
from types import MappingProxyType
from typing import Any, Callable

import anndata as ad
import numpy as np
import pandas as pd
from anndata import AnnData
Expand DownExpand Up@@ -276,7 +277,7 @@ def _preprocess(
 self.dataset_index = pd.concat(index_df).reset_index(drop=True)
 assert len(self.tiles_coords) == len(self.dataset_index)
 if table_name:
 self.dataset_table = AnnData.concatenate(*tables_l)
 self.dataset_table = ad.concat(*tables_l)
 assert len(self.tiles_coords) == len(self.dataset_table)

 dims_ = set(chain(*dims_l))
Expand Down
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