parameters: (self, axis=None, out=None, fill_value=None, keepdims=np._NoValue)
return_statement: return out
docstring: Return the minimum along a given axis.
  
          Parameters
          ----------
          axis : {None, int}, optional
              Axis along which to operate.  By default, ``axis`` is None and the
              flattened input is used.
          out : array_like, optional
              Alternative output array in which to place the result.  Must be of
              the same shape and buffer length as the expected output.
          fill_value : {var}, optional
              Value used to fill in the masked values.
              If None, use the output of `minimum_fill_value`.
          keepdims : bool, optional
              If this is set to True, the axes which are reduced are left
              in the result as dimensions with size one. With this option,
              the result will broadcast correctly against the array.
  
          Returns
          -------
          amin : array_like
              New array holding the result.
              If ``out`` was specified, ``out`` is returned.
  
          See Also
          --------
          minimum_fill_value
              Returns the minimum filling value for a given datatype.
docstring_summary: Return the minimum along a given axis.
docstring_tokens: Return the minimum along a given axis .
function: def min(self, axis=None, out=None, fill_value=None, keepdims=np._NoValue):
          """
          Return the minimum along a given axis.
  
          Parameters
          ----------
          axis : {None, int}, optional
              Axis along which to operate.  By default, ``axis`` is None and the
              flattened input is used.
          out : array_like, optional
              Alternative output array in which to place the result.  Must be of
              the same shape and buffer length as the expected output.
          fill_value : {var}, optional
              Value used to fill in the masked values.
              If None, use the output of `minimum_fill_value`.
          keepdims : bool, optional
              If this is set to True, the axes which are reduced are left
              in the result as dimensions with size one. With this option,
              the result will broadcast correctly against the array.
  
          Returns
          -------
          amin : array_like
              New array holding the result.
              If ``out`` was specified, ``out`` is returned.
  
          See Also
          --------
          minimum_fill_value
              Returns the minimum filling value for a given datatype.
  
          """
          kwargs = {} if keepdims is np._NoValue else {'keepdims': keepdims}
  
          _mask = self._mask
          newmask = _check_mask_axis(_mask, axis, **kwargs)
          if fill_value is None:
              fill_value = minimum_fill_value(self)
          # No explicit output
          if out is None:
              result = self.filled(fill_value).min(
                  axis=axis, out=out, **kwargs).view(type(self))
              if result.ndim:
                  # Set the mask
                  result.__setmask__(newmask)
                  # Get rid of Infs
                  if newmask.ndim:
                      np.copyto(result, result.fill_value, where=newmask)
              elif newmask:
                  result = masked
              return result
          # Explicit output
          result = self.filled(fill_value).min(axis=axis, out=out, **kwargs)
          if isinstance(out, MaskedArray):
              outmask = getmask(out)
              if outmask is nomask:
                  outmask = out._mask = make_mask_none(out.shape)
              outmask.flat = newmask
          else:
              if out.dtype.kind in 'biu':
                  errmsg = "Masked data information would be lost in one or more"\
                           " location."
                  raise MaskError(errmsg)
              np.copyto(out, np.nan, where=newmask)
          return out
function_tokens: def min ( self , axis = None , out = None , fill_value = None , keepdims = np . _NoValue ) : kwargs = { } if keepdims is np . _NoValue else { 'keepdims' : keepdims } _mask = self . _mask newmask = _check_mask_axis ( _mask , axis , * * kwargs ) if fill_value is None : fill_value = minimum_fill_value ( self ) # No explicit output if out is None : result = self . filled ( fill_value ) . min ( axis = axis , out = out , * * kwargs ) . view ( type ( self ) ) if result . ndim : # Set the mask result . __setmask__ ( newmask ) # Get rid of Infs if newmask . ndim : np . copyto ( result , result . fill_value , where = newmask ) elif newmask : result = masked return result # Explicit output result = self . filled ( fill_value ) . min ( axis = axis , out = out , * * kwargs ) if isinstance ( out , MaskedArray ) : outmask = getmask ( out ) if outmask is nomask : outmask = out . _mask = make_mask_none ( out . shape ) outmask . flat = newmask else : if out . dtype . kind in 'biu' : errmsg = "Masked data information would be lost in one or more" " location." raise MaskError ( errmsg ) np . copyto ( out , np . nan , where = newmask ) return out