Source code for ddd_pylib.morphology._base_morphological_operator

from ddd_pylib._base import ImageOperator
from ddd_pylib.morphology import Kernel
from ddd_pylib import ImageUtils
import numpy as np




class BaseMorphologicalOperator(ImageOperator):
    """
    Provides more precise functions for morphology operation, mainly for kernel, with a kernel_radius attribute
    and a shape attribute for the kernel shape, Circle, Square or Diamond for a 2D kernel, and Sphere, Cube or
    Diamond for a 3D one.

    Args:
        kernel_radius: The radius of the wanted kernel
        shape: The shape of the kernel
    """
    def __init__(self):
        super().__init__()
        self._kernelRadius = self.defaultKernelRadius()
        self._kernelShape = self.defaultKernelShape()
        self._kernel = None



    @staticmethod
    def defaultKernelRadius() -> int:
        return 1




    @staticmethod
    def defaultKernelShape() -> str:
        return "Square"




    def setKernelRadius(self, radius: int):
        """
        Set the kernel radius

        Args:
            radius: the radius of the kernel that will be created
        """
        if radius <= 0:
            raise ValueError("Kernel radius can't be 0 or under")
        self._kernelRadius = radius




    def setKernelShape(self, shape: str):
        """
        Set the shape of the kernel, depending of the number of dimensions

        Args:
            shape: The shape of the kernel, picked in shape_2d or shape_3d depending of the need
        """
        if shape not in Kernel.validShapes:
            raise ValueError("Shape unknown or not supported")
        self._kernelShape = shape




    def getKernel(self) -> np.ndarray:
        if self._kernel is None:
            im = self.getMainImage()
            self._kernel = Kernel.makeKernel(
                self._kernelShape, 
                self._kernelRadius, 
                im.dims, 
                ImageUtils.scaleToTuple(im)
            )
        return self._kernel