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# numpy.place

numpy.place(arr, mask, vals)

  Change elements of an array based on conditional and input values.

  Similar to `np.copyto(arr, vals, where=mask)`, the difference is that `place` uses the first N elements of vals, where N is the number of True values in mask, while `copyto` uses the elements where mask is True.

  Note that `extract` does the exact opposite of `place`.

  Parameters:
    arr ndarray

      Array to put data into.

    mask array_like

      Boolean mask array. Must have the same size as a.

    vals 1-D sequence

      Values to put into a. Only the first N elements are used, where N is the number of True values in mask. If vals is smaller than N, it will be repeated, and if elements of a are to be masked, this sequence must be non-empty.

  See also

  `copyto`, `put`, `take`, `extract`

  Examples

      >>> import numpy as np
      >>> arr = np.arange(6).reshape(2, 3)
      >>> np.place(arr, arr>2, [44, 55])
      >>> arr
      array([[ 0,  1,  2],
             [44, 55, 44]])