parameters: (x, v1, v2, copy=True)
return_statement: return masked_where(condition, x, copy=copy)
docstring: 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)
docstring_summary: Mask an array inside a given interval.
docstring_tokens: Mask an array inside a given interval .
function: def 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)
  
      """
      if v2 < v1:
          (v1, v2) = (v2, v1)
      xf = filled(x)
      condition = (xf >= v1) & (xf <= v2)
      return masked_where(condition, x, copy=copy)
function_tokens: def masked_inside ( x , v1 , v2 , copy = True ) : if v2 < v1 : ( v1 , v2 ) = ( v2 , v1 ) xf = filled ( x ) condition = ( xf >= v1 ) & ( xf <= v2 ) return masked_where ( condition , x , copy = copy )