parameters: (x1, x2, out=None, **kwargs)
return_statement: return _api_internal.subtract(x1, x2, out)
docstring: Subtract arguments element-wise.
  
      Parameters
      ----------
      x1, x2 : ndarrays or scalar values
          The arrays to be subtracted from each other. If x1.shape != x2.shape,
          they must be broadcastable to a common shape (which may be the shape
          of one or the other).
  
      out : ndarray
          A location into which the result is stored. If provided, it must have a shape
          that the inputs broadcast to. If not provided or None, a freshly-allocated array
          is returned.
  
      Returns
      -------
      subtract : ndarray or scalar
          The difference of x1 and x2, element-wise. This is a scalar if both x1 and x2 are scalars.
  
      Notes
      -----
      This operator now supports automatic type promotion. The resulting type will be determined
      according to the following rules:
          * If both inputs are of floating number types, the output is the more precise type.
          * If only one of the inputs is floating number type, the result is that type.
          * If both inputs are of integer types (including boolean), not supported yet.
docstring_summary: Subtract arguments element-wise.
docstring_tokens: Subtract arguments element - wise .
function: def subtract(x1, x2, out=None, **kwargs):
      """
      Subtract arguments element-wise.
  
      Parameters
      ----------
      x1, x2 : ndarrays or scalar values
          The arrays to be subtracted from each other. If x1.shape != x2.shape,
          they must be broadcastable to a common shape (which may be the shape
          of one or the other).
  
      out : ndarray
          A location into which the result is stored. If provided, it must have a shape
          that the inputs broadcast to. If not provided or None, a freshly-allocated array
          is returned.
  
      Returns
      -------
      subtract : ndarray or scalar
          The difference of x1 and x2, element-wise. This is a scalar if both x1 and x2 are scalars.
  
      Notes
      -----
      This operator now supports automatic type promotion. The resulting type will be determined
      according to the following rules:
          * If both inputs are of floating number types, the output is the more precise type.
          * If only one of the inputs is floating number type, the result is that type.
          * If both inputs are of integer types (including boolean), not supported yet.
      """
      if isinstance(x1, numeric_types) and isinstance(x2, numeric_types):
          return _np.subtract(x1, x2, out=out)
      return _api_internal.subtract(x1, x2, out)
function_tokens: def subtract ( x1 , x2 , out = None , * * kwargs ) : if isinstance ( x1 , numeric_types ) and isinstance ( x2 , numeric_types ) : return _np . subtract ( x1 , x2 , out = out ) return _api_internal . subtract ( x1 , x2 , out )