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# numpy.ma.masked_inside

`numpy.ma.``masked_inside`(x, v1, v2, copy=True)

  Mask an array inside a given interval.

  Shortcut to `masked_where`, where condition is True for x inside the interval [v1,v2] (v1 <= x <= v2). The boundaries v1 and v2 can be given in either order.

  See also

  `masked_where`
    Mask where a condition is met.

  Notes

  The array x is prefilled with its filling value.

  Examples

      >>> import numpy.ma as ma
      >>> x = [0.31, 1.2, 0.01, 0.2, -0.4, -1.1]
      >>> ma.masked_inside(x, -0.3, 0.3)
      masked_array(data = [0.31 1.2 -- -- -0.4 -1.1],
            mask = [False False  True  True False False],
            fill_value=1e+20)

  The order of v1 and v2 doesn’t matter.

      >>> ma.masked_inside(x, 0.3, -0.3)
      masked_array(data = [0.31 1.2 -- -- -0.4 -1.1],
            mask = [False False  True  True False False],
            fill_value=1e+20)