nanopyx.methods.channel_registration.corrector

  1import numpy as np
  2from skimage.io import imread
  3
  4# TODO recheck values
  5from ...core.transform.align_channels import align_channels as new_align_channels
  6
  7
  8class ChannelRegistrationCorrector(object):
  9    """
 10    Corrector class for channel registration in an image stack.
 11
 12    This class provides methods for aligning channels in an image stack using translation masks.
 13
 14    Args:
 15        None
 16
 17    Attributes:
 18        aligned_stack (numpy.ndarray): The aligned image stack after correction.
 19
 20    Methods:
 21        load_translation_masks(path=None): Load translation masks from a file.
 22
 23        align_channels(img_stack, translation_masks=None): Align channels in an image stack using translation masks.
 24
 25    Example:
 26        corrector = ChannelRegistrationCorrector()
 27        translation_masks = corrector.load_translation_masks("translation_masks.tif")
 28        aligned_stack = corrector.align_channels(img_stack, translation_masks)
 29
 30    Note:
 31        The `ChannelRegistrationCorrector` class is used for correcting channel registration in an image stack.
 32        It provides methods for loading translation masks and aligning channels using these masks.
 33    """
 34
 35    def __init__(self):
 36        """
 37        Initialize the `ChannelRegistrationCorrector` object.
 38
 39        Args:
 40            None
 41
 42        Returns:
 43            None
 44
 45        Example:
 46            corrector = ChannelRegistrationCorrector()
 47        """
 48        self.aligned_stack = None
 49
 50    def load_translation_masks(self, path=None):
 51        """
 52        Load translation masks from a file.
 53
 54        Args:
 55            path (str, optional): The file path to load translation masks from. If not provided, a user input prompt will be used to specify the path.
 56
 57        Returns:
 58            numpy.ndarray: The loaded translation masks as a NumPy array.
 59
 60        Example:
 61            translation_masks = corrector.load_translation_masks("translation_masks.tif")
 62
 63        Note:
 64            This method loads translation masks from a file and returns them as a NumPy array.
 65        """
 66        if path is not None:
 67            path = input("Please provide a filepath to the translation masks")
 68
 69        return imread(path)
 70
 71    def align_channels(self, img_stack, translation_masks=None):
 72        """
 73        Align channels in an image stack using translation masks.
 74
 75        Args:
 76            img_stack (numpy.ndarray): The input image stack with shape [n_channels, height, width].
 77            translation_masks (numpy.ndarray, optional): The translation masks to use for alignment. If not provided, they will be loaded.
 78
 79        Returns:
 80            numpy.ndarray: The aligned image stack after correction.
 81
 82        Example:
 83            aligned_stack = corrector.align_channels(img_stack, translation_masks)
 84
 85        Note:
 86            This method aligns channels in an image stack using translation masks.
 87        """
 88        translation_masks = translation_masks
 89
 90        if translation_masks is None:
 91            translation_masks = self.load_translation_masks()
 92
 93        input_d_type = img_stack.dtype
 94
 95        n_channels = img_stack.shape[0]
 96        height = img_stack.shape[1]
 97        width = img_stack.shape[2]
 98
 99        self.aligned_stack = np.empty((n_channels, height, width))
100        channels_list = list(range(n_channels))
101
102        for channel in channels_list:
103            img_slice = img_stack[channel].astype(np.float32)
104            translation_mask = translation_masks[channel].astype(np.float32)
105            if np.sum(translation_mask) == 0:
106                self.aligned_stack[channel] = img_slice
107            else:
108                self.aligned_stack[channel] = new_align_channels(np.ascontiguousarray(img_slice.reshape((1, height, width)), dtype=np.float32), translation_mask)
109
110        return self.aligned_stack.astype(input_d_type)