processing.py

module src.processing

Created By: Andrew Player
File Name: processing.py
Date Created: 01-25-2021
Description: Functions for the pre and post-processing of interferogram arrays

---

function tile

tile(
    arr: ndarray,
    tile_shape: Tuple[int, int],
    crop_size: int = 0,
    x_offset: int = 0,
    y_offset: int = 0,
    even_pad: bool = False,
    pad_value: float = 0.0
) → Tuple[ndarray, int, int]

Tile a 2-dimensional array into an array of tiles of shape tile_shape.

Parameters:

• arr : np.ndarray
  The 2-dimensional array that should be tiled.
• tile_shape : tuple(int, int)
  The desired shape of the tiles: (row length, column length). This should match the input shape of the model.
• crop_size : int, Optional
  An extra amount of padding to maintain full array coverage when the model will crop the tiles later. This amount should be equal to the shape of the output tiles from the model.
• x_offset : int, Optional
  Offset the tiling process by this amount in the columns direction.
• y_offset : int, Optional
  Offset the tiling process by this amount in the row direction.
• even_pad : bool, Optional
  If True, the array will be padded symmetrically; else, it will be padded on the end of each dimension.
• pad_value : float, Optional
  The value to fill the padded areas of the array with.

Returns:

• tiles : np.ndarray
  The array of tiles.
• num_rows : int
  The number of rows of tiles.
• num_cols : int
  The number of columns of tiles.

---

function pad

pad(
    arr: ndarray,
    tile_shape: Tuple[int, int],
    value: float = 0.0,
    extra_padding: int = 0,
    even_pad: bool = False
) → ndarray

Pad an array with a given value so that it can be tiled.

Parameters:

• arr : np.ndarray
  The array that should be padded.
• tile_shape : tuple(int, int)
  A tuple representing the shape of the tiles (rows, columns) to pad for.
• value : float, Optional
  The value that should fill the padded area.
• extra_pad : int, Optional
  An extra amount of padding to add to each dimension.
• even_padding : bool, Optional
  If True, the array will be padded symmetrically; else, it will be padded on the end of each dimension.

Returns:

• arr_padded : np.ndarray
  The padded array.

---

function simulate_unet_cropping

simulate_unet_cropping(arr: ndarray, crop_shape: tuple) → ndarray

Symmetrically crop the inputed array.

Parameters:

• arr : np.ndarray
  The 2-dimensional interferogram array to be cropped.
• crop_shape : tuple
  The length of the rows and columns after being cropped, respectively. If the crop_shape in a direction does not divide 2, the extra value will be placed on the 0 side. This should match the models output shape.

Returns:

• cropped_arr : np.ndarray
  The cropped interferogram array.

---

function tiles_to_image

tiles_to_image(
    arr: ndarray,
    rows: int,
    cols: int,
    original_shape: Tuple[int, int]
) → ndarray

Stich an array of 2-dimensional tiles into a single 2-dimensional array.

Parameters:

• arr : np.ndarray(shape=(rows*cols, tile_size, tile_size))
  The array of tiles to be stiched together.
• rows : int
  The number of tiles that should go in the row direction.
• cols : int
  The number of tiles that should go in the column direction.
• original_shape : Tuple[int, int]
  The shape of the interferogram before any processing.
• cropped : bool
  Set to True if the model has cropping, else leave it as False.
• tiling_size : int
  If the model was cropped, set this to the original tile size, else leave this false.

Returns:

• rebuilt_arr : np.ndarray(shape=(rows*tile_size, cols*tile_size))
  The stiched 2-dimensional array.

---

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