frontendnetwork.py 文件源码

def get_masked(self, percent_hole, diag_off=1):
        """ Construct a random mask.
            Random training set on 20% on Data / debug5 - debug11 -- Unbalanced
        """

        data = self.data
        if type(data) is np.ndarray:
            #self.data_mat = sp.sparse.csr_matrix(data)
            pass
        else:
            raise NotImplementedError('type %s unknow as corpus' % type(data))

        n = int(data.size * percent_hole)
        mask_index = np.unravel_index(np.random.permutation(data.size)[:n], data.shape)
        mask = np.zeros(data.shape, dtype=data.dtype)
        mask[mask_index] = 1

        if self.is_symmetric():
            mask = np.tril(mask) + np.tril(mask, -1).T

        data_ma = ma.array(data, mask=mask)
        if diag_off == 1:
            np.fill_diagonal(data_ma, ma.masked)

        return data_ma