Source code for starfish.core.morphology.label_image.label_image

from pathlib import Path
from typing import Any, Hashable, Mapping, MutableMapping, Optional, Tuple, Union

import numpy as np
import xarray as xr
from semantic_version import Version

from starfish.core.morphology.util import (
from starfish.core.types import ArrayLike, Axes, Coordinates, LOG, Number, STARFISH_EXTRAS_KEY
from starfish.core.util.logging import Log

class AttrKeys:

DOCTYPE_STRING = "starfish/LabelImage"
CURRENT_VERSION = Version("0.0.0")
MIN_SUPPORTED_VERSION = Version("0.0.0")
MAX_SUPPORTED_VERSION = Version("0.0.0")

[docs]class LabelImage: """Wraps an xarray that contains a 2D or 3D labeled image. Each axis is labeled with physical coordinate data.""" def __init__(self, label_image: xr.DataArray): # verify that the data array has the required elements. if label_image.dtype.kind not in ("i", "u"): raise TypeError("label image should be an integer type") for axis in (Axes.X, Axes.Y): if axis.value not in label_image.coords: raise ValueError(f"label image should have an {axis.value} axis") expected_physical_coordinates: Tuple[Coordinates, ...] if label_image.ndim == 5: expected_physical_coordinates = (Coordinates.X, Coordinates.Y, Coordinates.Z) else: expected_physical_coordinates = (Coordinates.X, Coordinates.Y) for coord in expected_physical_coordinates: if coord.value not in label_image.coords: raise ValueError(f"label image should have a {coord.value} coordinates") self.label_image = label_image.copy(deep=False) if AttrKeys.DOCTYPE not in self.label_image.attrs: self.label_image.attrs[AttrKeys.DOCTYPE] = DOCTYPE_STRING if AttrKeys.LOG not in self.label_image.attrs: self.label_image.attrs[AttrKeys.LOG] = Log().encode()
[docs] @classmethod def from_label_array_and_ticks( cls, array: np.ndarray, pixel_ticks: Optional[Union[ Mapping[Axes, ArrayLike[int]], Mapping[str, ArrayLike[int]]]], physical_ticks: Union[ Mapping[Coordinates, ArrayLike[Number]], Mapping[str, ArrayLike[Number]]], log: Optional[Log], ) -> "LabelImage": """Constructs a LabelImage from an array containing the labels, a set of physical coordinates, and an optional log of how this label image came to be. Parameters ---------- array : np.ndarray A 2D or 3D array containing the labels. The ordering of the axes must be Y, X for 2D images and ZPLANE, Y, X for 3D images. pixel_ticks : Optional[Union[Mapping[Axes, ArrayLike[int]], Mapping[str, ArrayLike[int]]]] A map from the axis to the values for that axis. For any axis that exist in the array but not in pixel_coordinates, the pixel coordinates are assigned from 0..N-1, where N is the size along that axis. physical_ticks : Union[Mapping[Coordinates, ArrayLike[Number]], Mapping[str, ArrayLike[Number]]] A map from the physical coordinate type to the values for axis. For 2D label images, X and Y physical coordinates must be provided. For 3D label images, Z physical coordinates must also be provided. log : Optional[Log] A log of how this label image came to be. """ # normalize the pixel coordinates to Mapping[Axes, ArrayLike[int]] pixel_ticks = _normalize_pixel_ticks(pixel_ticks) # normalize the physical coordinates to Mapping[Coordinates, ArrayLike[Number]] physical_ticks = _normalize_physical_ticks(physical_ticks) img_axes, img_coords = _get_axes_names(array.ndim) xr_axes = [axis.value for axis in img_axes] try: xr_coords: MutableMapping[Hashable, Any] = { coord.value: (axis.value, physical_ticks[coord]) for axis, coord in zip(img_axes, img_coords) } except KeyError as ex: raise KeyError(f"missing physical coordinates {ex.args[0]}") from ex for ix, axis in enumerate(img_axes): xr_coords[axis.value] = pixel_ticks.get(axis, np.arange(0, array.shape[ix])) dataarray = xr.DataArray( array, dims=xr_axes, coords=xr_coords, ) dataarray.attrs.update({ AttrKeys.LOG: (log or Log()).encode(), AttrKeys.DOCTYPE: DOCTYPE_STRING, AttrKeys.VERSION: str(CURRENT_VERSION), }) return LabelImage(dataarray)
@property def xarray(self): """Returns the xarray that contains the label image and the physical coordinates.""" return self.label_image @property def log(self) -> Log: """Returns a copy of the provenance data. Modifications to this copy will not affect the log stored on this label image.""" return Log.decode(self.label_image.attrs[AttrKeys.LOG])
[docs] @classmethod def open_netcdf(cls, path: Union[str, Path]) -> "LabelImage": """Load a label image saved as a netcdf file from disk. Parameters ---------- path : Union[str, Path] Path of the label image to instantiate from. Returns ------- label_image : LabelImage Label image from the path. """ label_image = xr.open_dataarray(path) if ( AttrKeys.DOCTYPE not in label_image.attrs or label_image.attrs[AttrKeys.DOCTYPE] != DOCTYPE_STRING or AttrKeys.VERSION not in label_image.attrs ): raise ValueError(f"{path} does not appear to be a starfish label image") if not ( MIN_SUPPORTED_VERSION <= Version(label_image.attrs[AttrKeys.VERSION]) <= MAX_SUPPORTED_VERSION): raise ValueError( f"{path} contains a label image, but the version " f"{label_image.attrs[AttrKeys.VERSION]} is not supported") return cls(label_image)
[docs] def to_netcdf(self, path: Union[str, Path]): """Save the label image as a netcdf file. Parameters ---------- path : Union[str, Path] Path of the netcdf file to write to. """ self.label_image.to_netcdf(path)