Function meshgrid

tensorflow/python/ops/array_ops.py:2874–2946

Broadcasts parameters for evaluation on an N-D grid. Given N one-dimensional coordinate arrays `*args`, returns a list `outputs` of N-D coordinate arrays for evaluating expressions on an N-D grid. Notes: `meshgrid` supports cartesian ('xy') and matrix ('ij') indexing conventions. When t

(*args, **kwargs)

@tf_export("meshgrid")
def meshgrid(*args, **kwargs):
  """Broadcasts parameters for evaluation on an N-D grid.

  Given N one-dimensional coordinate arrays `*args`, returns a list `outputs`
  of N-D coordinate arrays for evaluating expressions on an N-D grid.

  Notes:

  `meshgrid` supports cartesian ('xy') and matrix ('ij') indexing conventions.
  When the `indexing` argument is set to 'xy' (the default), the broadcasting
  instructions for the first two dimensions are swapped.

  Examples:

  Calling `X, Y = meshgrid(x, y)` with the tensors

  ```python
  x = [1, 2, 3]
  y = [4, 5, 6]
  X, Y = tf.meshgrid(x, y)
  # X = [[1, 2, 3],
  #      [1, 2, 3],
  #      [1, 2, 3]]
  # Y = [[4, 4, 4],
  #      [5, 5, 5],
  #      [6, 6, 6]]
  ```

  Args:
    *args: `Tensor`s with rank 1.
    **kwargs:
      - indexing: Either 'xy' or 'ij' (optional, default: 'xy').
      - name: A name for the operation (optional).

  Returns:
    outputs: A list of N `Tensor`s with rank N.

  Raises:
    TypeError: When no keyword arguments (kwargs) are passed.
    ValueError: When indexing keyword argument is not one of `xy` or `ij`.
  """

  indexing = kwargs.pop("indexing", "xy")
  name = kwargs.pop("name", "meshgrid")
  if kwargs:
    key = list(kwargs.keys())[0]
    raise TypeError("'{}' is an invalid keyword argument "
                    "for this function".format(key))

  if indexing not in ("xy", "ij"):
    raise ValueError("indexing parameter must be either 'xy' or 'ij'")

  with ops.name_scope(name, "meshgrid", args) as name:
    ndim = len(args)
    s0 = (1,) * ndim

    # Prepare reshape by inserting dimensions with size 1 where needed
    output = []