(cls, X, axis=None, out=None)
Normalize `X` array so it sums to 1.0 over the `axis`.

        Parameters
        ----------
        X : array
            Array to normalize.
        axis : optional int
            Axis over which the resulting array sums to 1.
        out : optional array
            Output array of the same shape as X.
Normalize `X` array so it sums to 1.0 over the `axis`.
Normalize X array so it sums to 1 . 0 over the axis .
def _normalize(cls, X, axis=None, out=None):
        """
        Normalize `X` array so it sums to 1.0 over the `axis`.

        Parameters
        ----------
        X : array
            Array to normalize.
        axis : optional int
            Axis over which the resulting array sums to 1.
        out : optional array
            Output array of the same shape as X.
        """
        X = np.asarray(X, dtype=float)
        scale = np.sum(X, axis=axis, keepdims=True)
        if out is None:
            return X / scale
        else:
            if out is not X:
                assert out.shape == X.shape
                out[:] = X
            out /= scale
            return out
def _normalize ( cls , X , axis = None , out = None ) : X = np . asarray ( X , dtype = float ) scale = np . sum ( X , axis = axis , keepdims = True ) if out is None : return X / scale else : if out is not X : assert out . shape == X . shape out [ : ] = X out /= scale return out