'project x onto the principle axes, dropping any axes where fraction
of variance<minfrac'

def project(self, x, minfrac=0.0):

    x = np.asarray(x)
    if (x.shape[(-1)] != self.numcols):
        raise ValueError((u'Expected    an    array    with    dims[-1]==%d' % self.numcols))
    Y = np.dot(self.Wt, self.center(x).T).T
    mask = (self.fracs >= minfrac)
    if (x.ndim == 2):
        Yreduced = Y[:, mask]
    else:
        Yreduced = Y[mask]
    return Yreduced
