# numpy.compress

numpy.compress(condition, a, axis=None, out=None)

  Return selected slices of an array along given axis.

  When working along a given axis, a slice along that axis is returned in output for each index where condition evaluates to True. When working on a 1-D array, `compress` is equivalent to `extract`.

  Parameters:
    condition 1-D array of bools

      Array that selects which entries to return. If len(condition) is less than the size of a along the given axis, then output is truncated to the length of the condition array.

    a array_like

      Array from which to extract a part.

    axis int, optional

      Axis along which to take slices. If None (default), work on the flattened array.

    out ndarray, optional

      Output array. Its type is preserved and it must be of the right shape to hold the output.

  Returns:
    compressed_array ndarray

      A copy of a without the slices along axis for which condition is false.

  See also

  `take`, `choose`, `diag`, `diagonal`, `select`
  `ndarray.compress`

    Equivalent method in ndarray

  `extract`

    Equivalent method when working on 1-D arrays

  Output type determination

  Examples

      >>> a = np.array([[1, 2], [3, 4], [5, 6]])
      >>> a
      array([[1, 2],
             [3, 4],
             [5, 6]])
      >>> np.compress([0, 1], a, axis=0)
      array([[3, 4]])
      >>> np.compress([False, True, True], a, axis=0)
      array([[3, 4],
             [5, 6]])
      >>> np.compress([False, True], a, axis=1)
      array([[2],
             [4],
             [6]])

  Working on the flattened array does not return slices along an axis but selects elements.

      >>> np.compress([False, True], a)
      array([2])