Set phenotype matrix
        
        Args:
            Y:              phenotype matrix [N, P]
            standardize:	if True, phenotype is standardized (zero mean, unit variance)

def setY(self,Y,standardize=False):
        """
        Set phenotype matrix
        
        Args:
            Y:              phenotype matrix [N, P]
            standardize:	if True, phenotype is standardized (zero mean, unit variance)
        """
        assert Y.shape[0]==self.N, 'CVarianceDecomposition:: Incompatible shape'
        assert Y.shape[1]==self.P, 'CVarianceDecomposition:: Incompatible shape'

        
        if standardize:
            Y=preprocess.standardize(Y)

        #check that missing values match the current structure
        assert (~(SP.isnan(Y).any(axis=1))==self.Iok).all(), 'CVarianceDecomposition:: pattern of missing values needs to match Y given at initialization'

        self.Y = Y
        self.vd.setPheno(Y)

        self.optimum = None
    
        self.cache['Sigma']   = None
        self.cache['Hessian'] = None
        self.cache['Lparams'] = None
        self.cache['paramsST']= None