convolution.py

convolutionpy.py

from ulab import numpy as np

def meshgrid(input_rows, input_cols):
  output_shape = (input_rows.shape[0], input_cols.shape[0])
  ret_rows = np.zeros(output_shape, dtype=np.int64)
  ret_cols = np.zeros(output_shape, dtype=np.int64)

  r, c = output_shape

  for i in range(0, r):
    for j in range(0, c):
      ret_rows[i, j] = input_rows[i]
      ret_cols[i, j] = input_cols[j]

  return (ret_rows, ret_cols)


def take_with_default(arr, indices, default):
  """
  Indexes an ndarray following the indices and uses a default value for all indexes that are out of bounds
  """
  # will be broadcasted up into np.array[bool]
  mask = True
  for i, index in enumerate(indices):
      mask = mask & (index >= 0) & (index < arr.shape[i])

  # result with the shape of the mask filled with the default value
  result = default * np.ones(mask.shape, dtype=arr.dtype)

  # replacing all in bounds indices with their corresponding data
  result[mask] = arr[tuple(ind[mask] for ind in indices)]

  return result