parameters: (self, axis=None, fill_value=None, out=None)
return_statement: return d.argmin(axis, out=out)
docstring: Return array of indices to the minimum values along the given axis.
  
          Parameters
          ----------
          axis : {None, integer}
              If None, the index is into the flattened array, otherwise along
              the specified axis
          fill_value : {var}, optional
              Value used to fill in the masked values.  If None, the output of
              minimum_fill_value(self._data) is used instead.
          out : {None, array}, optional
              Array into which the result can be placed. Its type is preserved
              and it must be of the right shape to hold the output.
  
          Returns
          -------
          ndarray or scalar
              If multi-dimension input, returns a new ndarray of indices to the
              minimum values along the given axis.  Otherwise, returns a scalar
              of index to the minimum values along the given axis.
  
          Examples
          --------
          >>> x = np.ma.array(np.arange(4), mask=[1,1,0,0])
          >>> x.shape = (2,2)
          >>> x
          masked_array(
            data=[[--, --],
                  [2, 3]],
            mask=[[ True,  True],
                  [False, False]],
            fill_value=999999)
          >>> x.argmin(axis=0, fill_value=-1)
          array([0, 0])
          >>> x.argmin(axis=0, fill_value=9)
          array([1, 1])
docstring_summary: Return array of indices to the minimum values along the given axis.
docstring_tokens: Return array of indices to the minimum values along the given axis .
function: def argmin(self, axis=None, fill_value=None, out=None):
          """
          Return array of indices to the minimum values along the given axis.
  
          Parameters
          ----------
          axis : {None, integer}
              If None, the index is into the flattened array, otherwise along
              the specified axis
          fill_value : {var}, optional
              Value used to fill in the masked values.  If None, the output of
              minimum_fill_value(self._data) is used instead.
          out : {None, array}, optional
              Array into which the result can be placed. Its type is preserved
              and it must be of the right shape to hold the output.
  
          Returns
          -------
          ndarray or scalar
              If multi-dimension input, returns a new ndarray of indices to the
              minimum values along the given axis.  Otherwise, returns a scalar
              of index to the minimum values along the given axis.
  
          Examples
          --------
          >>> x = np.ma.array(np.arange(4), mask=[1,1,0,0])
          >>> x.shape = (2,2)
          >>> x
          masked_array(
            data=[[--, --],
                  [2, 3]],
            mask=[[ True,  True],
                  [False, False]],
            fill_value=999999)
          >>> x.argmin(axis=0, fill_value=-1)
          array([0, 0])
          >>> x.argmin(axis=0, fill_value=9)
          array([1, 1])
  
          """
          if fill_value is None:
              fill_value = minimum_fill_value(self)
          d = self.filled(fill_value).view(ndarray)
          return d.argmin(axis, out=out)
function_tokens: def argmin ( self , axis = None , fill_value = None , out = None ) : if fill_value is None : fill_value = minimum_fill_value ( self ) d = self . filled ( fill_value ) . view ( ndarray ) return d . argmin ( axis , out = out )