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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 arr.

    vals 1-D sequence

      Values to put into arr. 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 arr 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]])