parameters: (a)
return_statement: return result
docstring: Find contiguous unmasked data in a masked array along the given axis.
  
      Parameters
      ----------
      a : narray
          The input array.
  
      Returns
      -------
      slice_list : list
          A sorted sequence of `slice` objects (start index, end index).
  
          ..versionchanged:: 1.15.0
              Now returns an empty list instead of None for a fully masked array
  
      See Also
      --------
      flatnotmasked_edges, notmasked_contiguous, notmasked_edges
      clump_masked, clump_unmasked
  
      Notes
      -----
      Only accepts 2-D arrays at most.
  
      Examples
      --------
      >>> a = np.ma.arange(10)
      >>> np.ma.flatnotmasked_contiguous(a)
      [slice(0, 10, None)]
  
      >>> mask = (a < 3) | (a > 8) | (a == 5)
      >>> a[mask] = np.ma.masked
      >>> np.array(a[~a.mask])
      array([3, 4, 6, 7, 8])
  
      >>> np.ma.flatnotmasked_contiguous(a)
      [slice(3, 5, None), slice(6, 9, None)]
      >>> a[:] = np.ma.masked
      >>> np.ma.flatnotmasked_contiguous(a)
      []
docstring_summary: Find contiguous unmasked data in a masked array along the given axis.
docstring_tokens: Find contiguous unmasked data in a masked array along the given axis .
function: def flatnotmasked_contiguous(a):
      """
      Find contiguous unmasked data in a masked array along the given axis.
  
      Parameters
      ----------
      a : narray
          The input array.
  
      Returns
      -------
      slice_list : list
          A sorted sequence of `slice` objects (start index, end index).
  
          ..versionchanged:: 1.15.0
              Now returns an empty list instead of None for a fully masked array
  
      See Also
      --------
      flatnotmasked_edges, notmasked_contiguous, notmasked_edges
      clump_masked, clump_unmasked
  
      Notes
      -----
      Only accepts 2-D arrays at most.
  
      Examples
      --------
      >>> a = np.ma.arange(10)
      >>> np.ma.flatnotmasked_contiguous(a)
      [slice(0, 10, None)]
  
      >>> mask = (a < 3) | (a > 8) | (a == 5)
      >>> a[mask] = np.ma.masked
      >>> np.array(a[~a.mask])
      array([3, 4, 6, 7, 8])
  
      >>> np.ma.flatnotmasked_contiguous(a)
      [slice(3, 5, None), slice(6, 9, None)]
      >>> a[:] = np.ma.masked
      >>> np.ma.flatnotmasked_contiguous(a)
      []
  
      """
      m = getmask(a)
      if m is nomask:
          return [slice(0, a.size)]
      i = 0
      result = []
      for (k, g) in itertools.groupby(m.ravel()):
          n = len(list(g))
          if not k:
              result.append(slice(i, i + n))
          i += n
      return result
function_tokens: def flatnotmasked_contiguous ( a ) : m = getmask ( a ) if m is nomask : return [ slice ( 0 , a . size ) ] i = 0 result = [ ] for ( k , g ) in itertools . groupby ( m . ravel ( ) ) : n = len ( list ( g ) ) if not k : result . append ( slice ( i , i + n ) ) i += n return result