cellmap_data.CellMapImage

cellmap_data.CellMapImage#

class cellmap_data.CellMapImage(path: str, target_class: str, target_scale: Sequence[float], target_voxel_shape: Sequence[int], pad: bool = False, pad_value: float | int = nan, interpolation: str = 'nearest', axis_order: str | Sequence[str] = 'zyx', value_transform: Callable | None = None, context: Context | None = None)[source]#

Initializes a CellMapImage object.

Parameters:

path (str) – The path to the image file.
target_class (str) – The label class of the image.
target_scale (Sequence[float]) – The scale of the image data to return in physical space.
target_voxel_shape (Sequence[int]) – The shape of the image data to return in voxels.
axis_order (str, optional) – The order of the axes in the image. Defaults to “zyx”.
value_transform (Optional[callable], optional) – A function to transform the image pixel data. Defaults to None.
context (Optional[tensorstore.Context], optional) – The context for the image data. Defaults to None.
pad (bool)
pad_value (float | int)
interpolation (str)

__init__(path: str, target_class: str, target_scale: Sequence[float], target_voxel_shape: Sequence[int], pad: bool = False, pad_value: float | int = nan, interpolation: str = 'nearest', axis_order: str | Sequence[str] = 'zyx', value_transform: Callable | None = None, context: Context | None = None) → None[source]#

Initializes a CellMapImage object.

Parameters:

path (str) – The path to the image file.
target_class (str) – The label class of the image.
target_scale (Sequence[float]) – The scale of the image data to return in physical space.
target_voxel_shape (Sequence[int]) – The shape of the image data to return in voxels.
axis_order (str, optional) – The order of the axes in the image. Defaults to “zyx”.
value_transform (Optional[callable], optional) – A function to transform the image pixel data. Defaults to None.
context (Optional[tensorstore.Context], optional) – The context for the image data. Defaults to None.
pad (bool)
pad_value (float | int)
interpolation (str)

Return type:

None

Methods

`__init__`(path, target_class, target_scale, ...)	Initializes a CellMapImage object.
`apply_spatial_transforms`(coords)	Applies spatial transformations to the given coordinates.
`find_level`(target_scale)	Finds the multiscale level that is closest to the target scale.
`return_data`(coords)	Pulls data from the image based on the given coordinates, applying interpolation if necessary, and returns the data as an xarray DataArray.
`rotate_coords`(coords, angles)	Rotates the given coordinates by the given angles.
`set_spatial_transforms`(transforms)	Sets spatial transformations for the image data, for setting global transforms at the 'dataset' level.
`to`(device)	Sets what device returned image data will be loaded onto.

Attributes

`array`	Returns the image data as an xarray DataArray.
`array_path`	Returns the path to the single-scale image array.
`bg_count`	Returns the number of background pixels in the ground truth data, normalized by the resolution.
`bounding_box`	Returns the bounding box of the dataset in world units.
`center`	Returns the center of the image in world units.
`class_counts`	Returns the number of pixels for the contained class in the ground truth data, normalized by the resolution.
`coordinateTransformations`	Returns the coordinate transformations of the image, based on the multiscale metadata.
`full_coords`	Returns the full coordinates of the image's axes in world units.
`group`	Returns the zarr group object for the multiscale image.
`multiscale_attrs`	Returns the multiscale metadata of the image.
`sampling_box`	Returns the sampling box of the dataset (i.e. where centers can be drawn from and still have full samples drawn from within the bounding box), in world units.
`scale_level`	Returns the multiscale level of the image.
`shape`	Returns the shape of the image.
`translation`	Returns the translation of the image.

__getitem__(center: Mapping[str, float]) → Tensor[source]#

Returns image data centered around the given point, based on the scale and shape of the target output image.

Parameters:: center (Mapping[str, float])
Return type:: Tensor

property shape: Mapping[str, int]#: Returns the shape of the image.

property center: Mapping[str, float]#: Returns the center of the image in world units.

property multiscale_attrs: MultiscaleMetadata#: Returns the multiscale metadata of the image.

property coordinateTransformations: tuple[VectorScale | PathScale] | tuple[VectorScale | PathScale, VectorTranslation | PathTranslation]#: Returns the coordinate transformations of the image, based on the multiscale metadata.

property full_coords: tuple[DataArray, ...]#: Returns the full coordinates of the image’s axes in world units.

property scale_level: str#: Returns the multiscale level of the image.

property group: Group#: Returns the zarr group object for the multiscale image.

property array_path: str#: Returns the path to the single-scale image array.

property array: DataArray#: Returns the image data as an xarray DataArray.

property translation: Mapping[str, float]#: Returns the translation of the image.

property bounding_box: Mapping[str, list[float]]#: Returns the bounding box of the dataset in world units.

property sampling_box: Mapping[str, list[float]]#: Returns the sampling box of the dataset (i.e. where centers can be drawn from and still have full samples drawn from within the bounding box), in world units.

property bg_count: float#: Returns the number of background pixels in the ground truth data, normalized by the resolution.

property class_counts: float#: Returns the number of pixels for the contained class in the ground truth data, normalized by the resolution.

to(device: str) → None[source]#

Sets what device returned image data will be loaded onto.

Parameters:: device (str)
Return type:: None

find_level(target_scale: Mapping[str, float]) → str[source]#

Finds the multiscale level that is closest to the target scale.

Parameters:: target_scale (Mapping[str, float])
Return type:: str

rotate_coords(coords: Mapping[str, Sequence[float]], angles: Mapping[str, float]) → Mapping[str, tuple[Sequence[str], ndarray]] | Mapping[str, Sequence[float]][source]#

Rotates the given coordinates by the given angles.

Parameters:

coords (Mapping[str, Sequence[float]])
angles (Mapping[str, float])

Return type:

Mapping[str, tuple[Sequence[str], ndarray]] | Mapping[str, Sequence[float]]

set_spatial_transforms(transforms: Mapping[str, Any] | None) → None[source]#

Sets spatial transformations for the image data, for setting global transforms at the ‘dataset’ level.

Parameters:: transforms (Mapping[str, Any] | None)
Return type:: None

apply_spatial_transforms(coords) → Tensor[source]#

Applies spatial transformations to the given coordinates.

Return type:: Tensor

return_data(coords: Mapping[str, Sequence[float]] | Mapping[str, tuple[Sequence[str], ndarray]]) → DataArray[source]#

Pulls data from the image based on the given coordinates, applying interpolation if necessary, and returns the data as an xarray DataArray.

Parameters:: coords (Mapping[str, Sequence[float]] | Mapping[str, tuple[Sequence[str], ndarray]])
Return type:: DataArray

cellmap_data.CellMapImage

Contents

cellmap_data.CellMapImage#