from pathlib import Path
from typing import Any, Dict, List, Optional, Sequence, Union
from urllib.parse import urlparse
from warnings import warn
import numpy as np
from PIL import Image
from biocframe import BiocFrame
import biocutils as ut
from summarizedexperiment._combineutils import (
check_assays_are_equal,
merge_assays,
merge_se_colnames,
relaxed_merge_assays
)
from summarizedexperiment._frameutils import _sanitize_frame
from summarizedexperiment.RangedSummarizedExperiment import GRangesOrGRangesList
from singlecellexperiment import SingleCellExperiment
from singlecellexperiment._combineutils import (
merge_generic,
relaxed_merge_generic,
relaxed_merge_numpy_generic
)
from ._imgutils import retrieve_rows_by_id
from ._validators import (
_validate_column_data,
_validate_id,
_validate_img_data,
_validate_sample_ids,
_validate_sample_image_ids,
_validate_spatial_coords,
_validate_spatial_coords_names,
)
from ._combineutils import merge_spatial_frames, merge_spatial_coordinates
from .SpatialImage import construct_spatial_image_class, VirtualSpatialImage
__author__ = "keviny2"
__copyright__ = "keviny2"
__license__ = "MIT"
[docs]
class SpatialExperiment(SingleCellExperiment):
"""Container class for storing data from spatial -omics experiments, extending
:py:class:`~singlecellexperiment.SingleCellExperiment` to provide slots for
image data and spatial coordinates.
In contrast to R, :py:class:`~numpy.ndarray` or scipy matrices are unnamed and do
not contain rownames and colnames. Hence, these matrices cannot be directly used as
values in assays or alternative experiments. We strictly enforce type checks in these cases.
"""
[docs]
def __init__(
self,
assays: Dict[str, Any] = None,
row_ranges: Optional[GRangesOrGRangesList] = None,
row_data: Optional[BiocFrame] = None,
column_data: Optional[BiocFrame] = None,
row_names: Optional[List[str]] = None,
column_names: Optional[List[str]] = None,
metadata: Optional[dict] = None,
reduced_dims: Optional[Dict[str, Any]] = None,
main_experiment_name: Optional[str] = None,
alternative_experiments: Optional[Dict[str, Any]] = None,
alternative_experiment_check_dim_names: bool = True,
row_pairs: Optional[Any] = None,
column_pairs: Optional[Any] = None,
spatial_coords: Optional[Union[BiocFrame, np.ndarray]] = None,
img_data: Optional[BiocFrame] = None,
validate: bool = True,
**kwargs,
) -> None:
"""Initialize a spatial experiment.
Args:
assays:
A dictionary containing matrices, with assay names as keys
and 2-dimensional matrices represented as either
:py:class:`~numpy.ndarray` or :py:class:`~scipy.sparse.spmatrix`.
Alternatively, you may use any 2-dimensional matrix that has
the ``shape`` property and implements the slice operation
using the ``__getitem__`` dunder method.
All matrices in assays must be 2-dimensional and have the
same shape (number of rows, number of columns).
row_ranges:
Genomic features, must be the same length as the number of rows of
the matrices in assays.
row_data:
Features, must be the same length as the number of rows of
the matrices in assays.
Feature information is coerced to a
:py:class:`~biocframe.BiocFrame.BiocFrame`. Defaults to None.
column_data:
Sample data, must be the same length as the number of
columns of the matrices in assays. For instances of the
``SpatialExperiment`` class, the sample data must include
a column named `sample_id`. If any 'sample_id' in the sample data is not present in the 'sample_id's of 'img_data', a warning will be issued.
If `sample_id` is not present, a column with this name
will be created and filled with the default value `sample01`.
Sample information is coerced to a
:py:class:`~biocframe.BiocFrame.BiocFrame`. Defaults to None.
row_names:
A list of strings, same as the number of rows.Defaults to None.
column_names:
A list of strings, same as the number of columns. Defaults to None.
metadata:
Additional experimental metadata describing the methods.
Defaults to None.
reduced_dims:
Slot for low-dimensionality embeddings.
Usually a dictionary with the embedding method as keys (e.g., t-SNE, UMAP)
and the dimensions as values.
Embeddings may be represented as a matrix or a data frame, must contain a shape.
main_experiment_name:
A string, specifying the main experiment name.
alternative_experiments:
Used to manage multi-modal experiments performed on the same sample/cells.
Alternative experiments must contain the same cells (rows) as the primary experiment.
It's a dictionary with keys as the names of the alternative experiments
(e.g., sc-atac, crispr) and values as subclasses of
:py:class:`~summarizedexperiment.SummarizedExperiment.SummarizedExperiment`.
alternative_experiment_check_dim_names:
Whether to check if the column names of the alternative experiment match the column names
of the main experiment. This is the equivalent to the ``withDimnames``
parameter in the R implementation.
Defaults to True.
row_pairs:
Row pairings/relationships between features.
Defaults to None.
column_pairs:
Column pairings/relationships between cells.
Defaults to None.
spatial_coords:
Optional :py:class:`~np.ndarray` or :py:class:`~biocframe.BiocFrame.BiocFrame` containing columns of spatial coordinates. Must be the same length as `column_data`.
If `spatial_coords` is a :py:class:`~biocframe.BiocFrame.BiocFrame`, typical column names might include:
- **['x', 'y']**: For simple 2D coordinates.
- **['pxl_col_in_fullres', 'pxl_row_in_fullres']**: For pixel-based coordinates in full-resolution images.
If spatial coordinates is a :py:class:`~pd.DataFrame` or `None`, it is coerced to a
:py:class:`~biocframe.BiocFrame.BiocFrame`. Defaults to `None`.
img_data:
Optional :py:class:`~biocframe.BiocFrame.BiocFrame` containing the image data, structured with the following columns:
- **sample_id** (str): A string identifier for the sample to which an image corresponds.
- **image_id** (str): A unique string identifier for each image within each sample.
- **data** (VirtualSpatialImage): The image itself, represented as a `VirtualSpatialImage` object or one of its subclasses.
- **scale_factor** (float): A numerical value that indicates the scaling factor applied to the image.
All 'sample_id's in 'img_data' must be present in the 'sample_id's of 'column_data'.
Image data are coerced to a
:py:class:`~biocframe.BiocFrame.BiocFrame`. Defaults to None.
validate:
Internal use only.
"""
super().__init__(
assays=assays,
row_ranges=row_ranges,
row_data=row_data,
column_data=column_data,
row_names=row_names,
column_names=column_names,
metadata=metadata,
reduced_dims=reduced_dims,
main_experiment_name=main_experiment_name,
alternative_experiments=alternative_experiments,
row_pairs=row_pairs,
column_pairs=column_pairs,
alternative_experiment_check_dim_names=alternative_experiment_check_dim_names,
validate=validate,
**kwargs,
)
column_data = _sanitize_frame(column_data, num_rows=self.shape[1])
if not column_data.has_column("sample_id"):
column_data["sample_id"] = ["sample01"] * self.shape[
1
] # hard code default sample_id as "sample01"
spatial_coords = _sanitize_frame(spatial_coords, num_rows=self.shape[1])
img_data = _sanitize_frame(img_data, num_rows=0)
self._img_data = img_data
self._cols = column_data
self._spatial_coords = spatial_coords
if validate:
_validate_column_data(column_data=column_data)
_validate_img_data(img_data=img_data)
_validate_sample_ids(column_data=column_data, img_data=img_data)
_validate_spatial_coords(
spatial_coords=spatial_coords, column_data=column_data
)
#########################
######>> Copying <<######
#########################
[docs]
def __deepcopy__(self, memo=None, _nil=[]):
"""
Returns:
A deep copy of the current ``SpatialExperiment``.
"""
from copy import deepcopy
_assays_copy = deepcopy(self._assays)
_rows_copy = deepcopy(self._rows)
_rowranges_copy = deepcopy(self._row_ranges)
_cols_copy = deepcopy(self._cols)
_row_names_copy = deepcopy(self._row_names)
_col_names_copy = deepcopy(self._column_names)
_metadata_copy = deepcopy(self.metadata)
_main_expt_name_copy = deepcopy(self._main_experiment_name)
_red_dim_copy = deepcopy(self._reduced_dims)
_alt_expt_copy = deepcopy(self._alternative_experiments)
_row_pair_copy = deepcopy(self._row_pairs)
_col_pair_copy = deepcopy(self._column_pairs)
_spatial_coords_copy = deepcopy(self._spatial_coords)
_img_data_copy = deepcopy(self._img_data)
current_class_const = type(self)
return current_class_const(
assays=_assays_copy,
row_ranges=_rowranges_copy,
row_data=_rows_copy,
column_data=_cols_copy,
row_names=_row_names_copy,
column_names=_col_names_copy,
metadata=_metadata_copy,
reduced_dims=_red_dim_copy,
main_experiment_name=_main_expt_name_copy,
alternative_experiments=_alt_expt_copy,
row_pairs=_row_pair_copy,
column_pairs=_col_pair_copy,
spatial_coords=_spatial_coords_copy,
img_data=_img_data_copy,
)
[docs]
def __copy__(self):
"""
Returns:
A shallow copy of the current ``SpatialExperiment``.
"""
current_class_const = type(self)
return current_class_const(
assays=self._assays,
row_ranges=self._row_ranges,
row_data=self._rows,
column_data=self._cols,
row_names=self._row_names,
column_names=self._column_names,
metadata=self._metadata,
reduced_dims=self._reduced_dims,
main_experiment_name=self._main_experiment_name,
alternative_experiments=self._alternative_experiments,
row_pairs=self._row_pairs,
column_pairs=self._column_pairs,
spatial_coords=self._spatial_coords,
img_data=self._img_data,
)
[docs]
def copy(self):
"""Alias for :py:meth:`~__copy__`."""
return self.__copy__()
##########################
######>> Printing <<######
##########################
[docs]
def __repr__(self) -> str:
"""
Returns:
A string representation.
"""
output = f"{type(self).__name__}(number_of_rows={self.shape[0]}"
output += f", number_of_columns={self.shape[1]}"
output += ", assays=" + ut.print_truncated_list(self.assay_names)
output += ", row_data=" + self._rows.__repr__()
if self._row_names is not None:
output += ", row_names=" + ut.print_truncated_list(self._row_names)
output += ", column_data=" + self._cols.__repr__()
if self._column_names is not None:
output += ", column_names=" + ut.print_truncated_list(self._column_names)
if self._spatial_coords is not None:
output += ", spatial_coords=" + self._spatial_coords.__repr__()
if self._img_data is not None:
output += ", img_data=" + self._img_data.__repr__()
if self._row_ranges is not None:
output += ", row_ranges=" + self._row_ranges.__repr__()
if self._alternative_experiments is not None:
output += ", alternative_experiments=" + ut.print_truncated_list(
self.alternative_experiment_names
)
if self._reduced_dims is not None:
output += ", reduced_dims=" + ut.print_truncated_list(
self.reduced_dim_names
)
if self._main_experiment_name is not None:
output += ", main_experiment_name=" + self._main_experiment_name
if len(self._row_pairs) > 0:
output += ", row_pairs=" + ut.print_truncated_dict(self._row_pairs)
if len(self._column_pairs) > 0:
output += ", column_pairs=" + ut.print_truncated_dict(self._column_pairs)
if len(self._metadata) > 0:
output += ", metadata=" + ut.print_truncated_dict(self._metadata)
output += ")"
return output
def __str__(self) -> str:
"""
Returns:
A pretty-printed string containing the contents of this object.
"""
output = f"class: {type(self).__name__}\n"
output += f"dimensions: ({self.shape[0]}, {self.shape[1]})\n"
output += f"assays({len(self.assay_names)}): {ut.print_truncated_list(self.assay_names)}\n"
output += f"row_data columns({len(self._rows.column_names)}): {ut.print_truncated_list(self._rows.column_names)}\n"
output += f"row_names({0 if self._row_names is None else len(self._row_names)}): {' ' if self._row_names is None else ut.print_truncated_list(self._row_names)}\n"
output += f"column_data columns({len(self._cols.column_names)}): {ut.print_truncated_list(self._cols.column_names)}\n"
output += f"column_names({0 if self._column_names is None else len(self._column_names)}): {' ' if self._column_names is None else ut.print_truncated_list(self._column_names)}\n"
output += f"main_experiment_name: {' ' if self._main_experiment_name is None else self._main_experiment_name}\n"
output += f"reduced_dims({len(self.reduced_dim_names)}): {ut.print_truncated_list(self.reduced_dim_names)}\n"
output += f"alternative_experiments({len(self.alternative_experiment_names)}): {ut.print_truncated_list(self.alternative_experiment_names)}\n"
output += f"row_pairs({len(self.row_pair_names)}): {ut.print_truncated_list(self.row_pair_names)}\n"
output += f"column_pairs({len(self.column_pair_names)}): {ut.print_truncated_list(self.column_pair_names)}\n"
output += f"metadata({str(len(self.metadata))}): {ut.print_truncated_list(list(self.metadata.keys()), sep=' ', include_brackets=False, transform=lambda y: y)}\n"
output += f"spatial_coords columns({len(self.spatial_coords_names)}): {ut.print_truncated_list(self.spatial_coords_names)}\n"
output += f"img_data columns({len(self._img_data.column_names)}): {ut.print_truncated_list(self._img_data.column_names)}"
return output
##############################
#####>> spatial_coords <<#####
##############################
[docs]
def get_spatial_coordinates(self) -> Union[BiocFrame, np.ndarray]:
"""Access spatial coordinates.
Returns:
A ``BiocFrame`` containing columns of spatial coordinates.
"""
return self._spatial_coords
[docs]
def get_spatial_coords(self) -> BiocFrame:
"""Alias for :py:meth:`~get_spatial_coordinates`."""
return self.get_spatial_coordinates()
[docs]
def set_spatial_coordinates(
self,
spatial_coords: Optional[Union[BiocFrame, np.ndarray]],
in_place: bool = False,
) -> "SpatialExperiment":
"""Set new spatial coordinates.
Args:
spatial_coords:
Optional :py:class:`~np.ndarray` or :py:class:`~biocframe.BiocFrame.BiocFrame` containing columns of spatial coordinates. Must be the same length as `column_data`.
If `spatial_coords` is a :py:class:`~biocframe.BiocFrame.BiocFrame`, typical column names might include:
- **['x', 'y']**: For simple 2D coordinates.
- **['pxl_col_in_fullres', 'pxl_row_in_fullres']**: For pixel-based coordinates in full-resolution images.
To remove coordinate information, set `spatial_coords=None`.
If spatial coordinates is a :py:class:`~pd.DataFrame` or `None`, it is coerced to a
:py:class:`~biocframe.BiocFrame.BiocFrame`. Defaults to `None`.
in_place:
Whether to modify the ``SpatialExperiment`` in place. Defaults to False.
Returns:
A modified ``SpatialExperiment`` object, either as a copy of the original or as a reference to the (in-place-modified) original.
"""
spatial_coords = _sanitize_frame(spatial_coords, self.shape[1])
_validate_spatial_coords(spatial_coords, self.column_data)
output = self._define_output(in_place)
output._spatial_coords = spatial_coords
return output
[docs]
def set_spatial_coords(
self,
spatial_coords: Optional[Union[BiocFrame, np.ndarray]],
in_place: bool = False,
) -> "SpatialExperiment":
"""Alias for :py:meth:`~set_spatial_coordinates`."""
return self.set_spatial_coordinates(
spatial_coords=spatial_coords, in_place=in_place
)
@property
def spatial_coords(self) -> BiocFrame:
"""Alias for :py:meth:`~get_spatial_coordinates`."""
return self.get_spatial_coordinates()
@spatial_coords.setter
def spatial_coords(self, spatial_coords: Optional[Union[BiocFrame, np.ndarray]]):
"""Alias for :py:meth:`~set_spatial_coordinates`."""
warn(
"Setting property 'spatial_coords' is an in-place operation, use 'set_spatial_coordinates' instead.",
UserWarning,
)
self.set_spatial_coordinates(spatial_coords=spatial_coords, in_place=True)
@property
def spatial_coordinates(self) -> BiocFrame:
"""Alias for :py:meth:`~get_spatial_coordinates`."""
return self.get_spatial_coordinates()
@spatial_coordinates.setter
def spatial_coordinates(
self, spatial_coords: Optional[Union[BiocFrame, np.ndarray]]
):
"""Alias for :py:meth:`~set_spatial_coordinates`."""
warn(
"Setting property 'spatial_coords' is an in-place operation, use 'set_spatial_coordinates' instead.",
UserWarning,
)
self.set_spatial_coordinates(spatial_coords=spatial_coords, in_place=True)
##############################
##>> spatial_coords_names <<##
##############################
[docs]
def get_spatial_coordinates_names(self) -> List[str]:
"""Access spatial coordinates names.
Returns:
The defined names of the spatial coordinates.
"""
if not hasattr(self._spatial_coords, "columns"):
return []
return self._spatial_coords.columns.as_list()
[docs]
def get_spatial_coords_names(self) -> List[str]:
"""Alias for :py:meth:`~get_spatial_coordinate_names`."""
return self.get_spatial_coordinate_names()
[docs]
def set_spatial_coordinates_names(
self, spatial_coords_names: List[str], in_place: bool = False
) -> "SpatialExperiment":
"""Set new spatial coordinates names.
Args:
spatial_coords_names:
New spatial coordinates names.
in_place:
Whether to modify the ``SpatialExperiment`` in place. Defaults to False.
Returns:
A modified ``SpatialExperiment`` object, either as a copy of the original or as a reference to the (in-place-modified) original.
"""
if not hasattr(self._spatial_coords, "set_column_names"):
warn(
f"The spatial coordinates object is of type {type(self._spatial_coords).__name__} which does not support setting column names.",
UserWarning,
)
new_spatial_coords = self._spatial_coords
else:
_validate_spatial_coords_names(spatial_coords_names, self._spatial_coords)
new_spatial_coords = self._spatial_coords.set_column_names(
spatial_coords_names
)
output = self._define_output(in_place)
output._spatial_coords = new_spatial_coords
return output
[docs]
def set_spatial_coords_names(
self, spatial_coords_names: List[str], in_place: bool = False
) -> "SpatialExperiment":
"""Alias for :py:meth:`~set_spatial_coordinates_names`."""
return self.set_spatial_coordinates_names(
spatial_coords_names=spatial_coords_names, in_place=in_place
)
@property
def spatial_coords_names(self) -> List[str]:
"""Alias for :py:meth:`~get_spatial_coordinates_names`."""
return self.get_spatial_coordinates_names()
@spatial_coords_names.setter
def spatial_coords_names(self, spatial_coords_names: List[str]):
"""Alias for :py:meth:`~set_spatial_coordinates_names`."""
warn(
"Setting property 'spatial_coords_names' is an in-place operation, use 'set_spatial_coordinates_names' instead.",
UserWarning,
)
self.set_spatial_coordinates_names(
spatial_coords_names=spatial_coords_names, in_place=True
)
@property
def spatial_coordinates_names(self) -> List[str]:
"""Alias for :py:meth:`~get_spatial_coordinates_names`."""
return self.get_spatial_coordinates_names()
@spatial_coordinates_names.setter
def spatial_coordinates_names(self, spatial_coords_names: List[str]):
"""Alias for :py:meth:`~set_spatial_coordinates_names`."""
warn(
"Setting property 'spatial_coords_names' is an in-place operation, use 'set_spatial_coordinates_names' instead.",
UserWarning,
)
self.set_spatial_coordinates_names(
spatial_coords_names=spatial_coords_names, in_place=True
)
##############################
########>> img_data <<########
##############################
[docs]
def get_image_data(self) -> BiocFrame:
"""Access image data.
Returns:
A BiocFrame object containing the image data.
"""
return self._img_data
[docs]
def get_img_data(self) -> BiocFrame:
"""Alias for :py:meth:`~get_image_data`."""
return self.get_image_data()
[docs]
def set_image_data(
self, img_data: Optional[BiocFrame], in_place: bool = False
) -> "SpatialExperiment":
"""Set new image data.
Args:
img_data:
:py:class:`~biocframe.BiocFrame.BiocFrame` containing the image data, structured with the following columns:
- **sample_id** (str): A string identifier for the sample to which an image corresponds.
- **image_id** (str): A unique string identifier for each image within each sample.
- **data** (VirtualSpatialImage): The image itself, represented as a `VirtualSpatialImage` object or one of its subclasses.
- **scale_factor** (float): A numerical value that indicates the scaling factor applied to the image.
Image data are coerced to a
:py:class:`~biocframe.BiocFrame.BiocFrame`.
in_place:
Whether to modify the ``SpatialExperiment`` in place. Defaults to False.
Returns:
A modified ``SpatialExperiment`` object, either as a copy of the original or as a reference to the (in-place-modified) original.
"""
img_data = _sanitize_frame(img_data, num_rows=0)
_validate_img_data(img_data)
_validate_sample_ids(self.column_data, img_data)
output = self._define_output(in_place)
output._img_data = img_data
return output
[docs]
def set_img_data(
self, img_data: BiocFrame, in_place: bool = False
) -> "SpatialExperiment":
"""Alias for :py:meth:`~set_image_data`."""
return self.set_image_data(img_data=img_data, in_place=in_place)
@property
def img_data(self) -> BiocFrame:
"""Alias for :py:meth:`~get_image_data`."""
return self.get_image_data()
@img_data.setter
def img_data(self, img_data: BiocFrame):
"""Alias for :py:meth:`~set_image_data`."""
warn(
"Setting property 'img_data' is an in-place operation, use 'set_image_data' instead.",
UserWarning,
)
self.set_image_data(img_data=img_data, in_place=True)
@property
def image_data(self) -> BiocFrame:
"""Alias for :py:meth:`~get_image_data`."""
return self.get_image_data()
@image_data.setter
def image_data(self, img_data: BiocFrame):
"""Alias for :py:meth:`~set_image_data`."""
warn(
"Setting property 'img_data' is an in-place operation, use 'set_image_data' instead.",
UserWarning,
)
self.set_image_data(img_data=img_data, in_place=True)
##############################
#####>> scale_factors <<######
##############################
[docs]
def get_scale_factors(
self,
sample_id: Union[str, bool, None] = None,
image_id: Union[str, bool, None] = None,
) -> List[float]:
"""Return scale factor(s) of image(s) based on the provided sample and image ids.
See :py:meth:`~get_img` for more details on the behavior for various
combinations of `sample_id` and `image_id` values.
Args:
sample_id:
- `sample_id=True`: Matches all samples.
- `sample_id=None`: Matches the first sample.
- `sample_id="<str>"`: Matches a sample by its id.
image_id:
- `image_id=True`: Matches all images for the specified sample(s).
- `image_id=None`: Matches the first image for the sample(s).
- `image_id="<str>"`: Matches image(s) by its(their) id.
Returns:
The scale factor(s) of the specified image(s).
"""
_validate_id(sample_id)
_validate_id(image_id)
img_data_subset = retrieve_rows_by_id(
img_data=self.img_data, sample_id=sample_id, image_id=image_id
)
if img_data_subset.shape[0] == 1:
return img_data_subset["scale_factor"][0]
return img_data_subset["scale_factor"]
################################
###>> OVERRIDE column_data <<###
################################
[docs]
def set_column_data(
self,
cols: Optional[BiocFrame],
replace_column_names: bool = False,
in_place: bool = False,
) -> "SpatialExperiment":
"""Override: Set sample data.
Args:
cols:
New sample data. If 'cols' contains a column
named 'sample_id's, a check is performed to ensure
that all 'sample_id's in the 'img_data' are present. If any 'sample_id' in the 'cols' is not present in the 'sample_id's of 'img_data', a warning will be issued.
If 'sample_id' is not present or 'cols' is None, the original 'sample_id's are retained.
replace_column_names:
Whether to replace experiment's column_names with the names from the
new object. Defaults to False.
in_place:
Whether to modify the ``SpatialExperiment`` in place. Defaults to False.
Returns:
A modified ``SpatialExperiment`` object, either as a copy of the original or as a reference to the (in-place-modified) original.
"""
cols = _sanitize_frame(cols, num_rows=self.shape[1])
if "sample_id" not in cols.columns:
cols["sample_id"] = self.column_data["sample_id"]
_validate_column_data(column_data=cols)
_validate_sample_ids(column_data=cols, img_data=self.img_data)
output = self._define_output(in_place)
output._cols = cols
if replace_column_names:
return output.set_column_names(cols.row_names, in_place=in_place)
return output
################################
#########>> slicers <<##########
################################
[docs]
def get_slice(
self,
rows: Optional[Union[str, int, bool, Sequence]],
columns: Optional[Union[str, int, bool, Sequence]],
) -> "SpatialExperiment":
"""Alias for :py:attr:`~__getitem__`."""
spe = super().get_slice(rows=rows, columns=columns)
slicer = self._generic_slice(rows=rows, columns=columns)
do_slice_cols = not (
isinstance(slicer.col_indices, slice) and slicer.col_indices == slice(None)
)
new_spatial_coords = None
if do_slice_cols:
new_spatial_coords = self.spatial_coords[slicer.col_indices, :]
column_sample_ids = set(spe.column_data["sample_id"])
mask = [
sample_id in column_sample_ids for sample_id in self.img_data["sample_id"]
]
new_img_data = self.img_data[mask,]
current_class_const = type(self)
return current_class_const(
assays=spe.assays,
row_ranges=spe.row_ranges,
row_data=spe.row_data,
column_data=spe.column_data,
row_names=spe.row_names,
column_names=spe.column_names,
metadata=spe.metadata,
main_experiment_name=spe.main_experiment_name,
reduced_dims=spe.reduced_dims,
alternative_experiments=spe.alternative_experiments,
row_pairs=spe.row_pairs,
column_pairs=spe.column_pairs,
spatial_coords=new_spatial_coords,
img_data=new_img_data,
)
################################
######>> img_data funcs <<######
################################
[docs]
def get_img(
self,
sample_id: Union[str, bool, None] = None,
image_id: Union[str, bool, None] = None,
) -> Union[VirtualSpatialImage, List[VirtualSpatialImage]]:
"""
Retrieve spatial images based on the provided sample and image ids.
Args:
sample_id:
- `sample_id=True`: Matches all samples.
- `sample_id=None`: Matches the first sample.
- `sample_id="<str>"`: Matches a sample by its id.
image_id:
- `image_id=True`: Matches all images for the specified sample(s).
- `image_id=None`: Matches the first image for the sample(s).
- `image_id="<str>"`: Matches image(s) by its(their) id.
Returns:
Zero, one, or more `VirtualSpatialImage` objects.
Behavior:
- sample_id = True, image_id = True:
Returns all images from all samples.
- sample_id = None, image_id = None:
Returns the first image entry in the dataset.
- sample_id = True, image_id = None:
Returns the first image for each sample.
- sample_id = None, image_id = True:
Returns all images for the first sample.
- sample_id = <str>, image_id = True:
Returns all images for the specified sample.
- sample_id = <str>, image_id = None:
Returns the first image for the specified sample.
- sample_id = <str>, image_id = <str>:
Returns the image matching the specified sample and image identifiers.
"""
_validate_id(sample_id)
_validate_id(image_id)
img_data_subset = retrieve_rows_by_id(
img_data=self.img_data, sample_id=sample_id, image_id=image_id
)
if img_data_subset is None:
return []
if img_data_subset.shape[0] == 1:
return img_data_subset["data"][0]
return img_data_subset["data"]
[docs]
def add_img(
self,
image_source: Union[Image.Image, np.ndarray, str, Path],
scale_factor: float,
sample_id: Union[str, bool, None],
image_id: Union[str, bool, None],
load: bool = True,
in_place: bool = False,
) -> "SpatialExperiment":
"""Add a new image entry.
Args:
image_source:
The file path to the image.
scale_factor:
The scaling factor associated with the image.
sample_id:
The sample id of the image.
image_id:
The image id of the image.
load:
Whether to load the image into memory. If `True`,
the method reads the image file from
`image_source`.
Defaults to `True`.
in_place:
Whether to modify the ``SpatialExperiment`` in place.
Defaults to False.
Returns:
A modified ``SpatialExperiment`` object, either as a copy of the original or as a reference to the (in-place-modified) original.
Raises:
ValueError: If the sample_id and image_id pair already exists.
"""
_validate_sample_image_ids(
img_data=self._img_data, new_sample_id=sample_id, new_image_id=image_id
)
if isinstance(image_source, (str, Path)):
is_url = urlparse(str(image_source)).scheme in ("http", "https", "ftp")
spi = construct_spatial_image_class(image_source, is_url=is_url)
if load:
img = spi.img_raster()
spi = construct_spatial_image_class(img, is_url=False)
else:
spi = construct_spatial_image_class(image_source, is_url=False)
new_row = BiocFrame(
{
"sample_id": [sample_id],
"image_id": [image_id],
"data": [spi],
"scale_factor": [scale_factor],
}
)
new_img_data = self._img_data.combine_rows(new_row)
output = self._define_output(in_place)
output._img_data = new_img_data
return output
# TODO: implement rmv_img()
[docs]
def rmv_img(
self,
sample_id: Union[str, bool, None] = None,
image_id: Union[str, bool, None] = None,
) -> "SpatialExperiment":
raise NotImplementedError()
[docs]
def img_source(
self,
sample_id: Union[str, bool, None] = None,
image_id: Union[str, bool, None] = None,
path=False,
):
raise NotImplementedError(
"This function is irrelevant because it is for `RemoteSpatialImages`"
)
[docs]
def img_raster(self, sample_id=None, image_id=None):
# NOTE: this function seems redundant, might be an artifact of the different subclasses of SpatialImage in the R implementation? just call `get_img()` for now
self.get_img(sample_id=sample_id, image_id=image_id)
[docs]
def rotate_img(self, sample_id=None, image_id=None, degrees=90):
raise NotImplementedError()
[docs]
def mirror_img(self, sample_id=None, image_id=None, axis=("h", "v")):
raise NotImplementedError()
[docs]
@staticmethod
def to_spatial_experiment():
raise NotImplementedError()
################################
#######>> combine ops <<########
################################
[docs]
def relaxed_combine_columns(self, *other) -> "SpatialExperiment":
"""Wrapper around :py:func:`~relaxed_combine_columns`."""
return relaxed_combine_columns(self, *other)
[docs]
def combine_columns(self, *other) -> "SpatialExperiment":
"""Wrapper around :py:func:`~combine_columns`."""
return combine_columns(self, *other)
################################
#######>> combine ops <<########
################################
[docs]
@ut.combine_columns.register(SpatialExperiment)
def combine_columns(*x: SpatialExperiment) -> SpatialExperiment:
"""Combine multiple ``SpatialExperiment`` objects by column.
All assays must contain the same assay names. If you need a
flexible combine operation, checkout :py:func:`~relaxed_combine_columns`.
Returns:
A combined ``SpatialExperiment``.
"""
warn(
"'row_pairs' and 'column_pairs' are currently ignored during this operation.",
UserWarning,
)
first = x[0]
_all_assays = [y.assays for y in x]
check_assays_are_equal(_all_assays)
_new_assays = merge_assays(_all_assays, by="column")
_new_col_names = merge_se_colnames(x)
_new_rdim = None
try:
_new_rdim = merge_generic(x, by="row", attr="reduced_dims")
except Exception as e:
warn(
f"Cannot combine 'reduced_dimensions' across experiments, {str(e)}",
UserWarning,
)
_new_alt_expt = None
try:
_new_alt_expt = merge_generic(x, by="column", attr="alternative_experiments")
except Exception as e:
warn(
f"Cannot combine 'alternative_experiments' across experiments, {str(e)}",
UserWarning,
)
_all_spatial_coords = [y._spatial_coords for y in x]
_new_spatial_coords = merge_spatial_coordinates(_all_spatial_coords)
_new_cols, _new_img_data = merge_spatial_frames(x)
current_class_const = type(first)
return current_class_const(
assays=_new_assays,
row_ranges=first._row_ranges,
row_data=first._rows,
column_data=_new_cols,
row_names=first._row_names,
column_names=_new_col_names,
metadata=first._metadata,
reduced_dims=_new_rdim,
main_experiment_name=first._main_experiment_name,
alternative_experiments=_new_alt_expt,
spatial_coords=_new_spatial_coords,
img_data=_new_img_data,
)
[docs]
@ut.relaxed_combine_columns.register(SpatialExperiment)
def relaxed_combine_columns(
*x: SpatialExperiment,
) -> SpatialExperiment:
"""A relaxed version of the :py:func:`~biocutils.combine_rows.combine_columns` method for
:py:class:`~SpatialExperiment` objects. Whereas ``combine_columns`` expects that all objects have the same rows,
``relaxed_combine_columns`` allows for different rows. Absent columns in any object are filled in with appropriate
placeholder values before combining.
Args:
x:
One or more ``SpatialExperiment`` objects, possibly with differences in the
number and identity of their rows.
Returns:
A ``SpatialExperiment`` that combines all ``experiments`` along their columns and contains
the union of all rows. Rows absent in any ``x`` are filled in
with placeholders consisting of Nones or masked NumPy values.
"""
warn(
"'row_pairs' and 'column_pairs' are currently ignored during this operation.",
UserWarning,
)
first = x[0]
_new_assays = relaxed_merge_assays(x, by="column")
_new_col_names = merge_se_colnames(x)
_new_rdim = None
try:
_new_rdim = relaxed_merge_numpy_generic(x, by="row", attr="reduced_dims")
except Exception as e:
warn(
f"Cannot combine 'reduced_dimensions' across experiments, {str(e)}",
UserWarning,
)
_new_alt_expt = None
try:
_new_alt_expt = relaxed_merge_generic(x, by="column", attr="alternative_experiments")
except Exception as e:
warn(
f"Cannot combine 'alternative_experiments' across experiments, {str(e)}",
UserWarning,
)
_all_spatial_coords = [y._spatial_coords for y in x]
_new_spatial_coords = merge_spatial_coordinates(_all_spatial_coords)
_new_cols, _new_img_data = merge_spatial_frames(x)
current_class_const = type(first)
return current_class_const(
assays=_new_assays,
row_ranges=first._row_ranges,
row_data=first._rows,
column_data=_new_cols,
row_names=first._row_names,
column_names=_new_col_names,
metadata=first._metadata,
reduced_dims=_new_rdim,
main_experiment_name=first._main_experiment_name,
alternative_experiments=_new_alt_expt,
spatial_coords=_new_spatial_coords,
img_data=_new_img_data,
)