def get_err_fast_sparse_svd(self, nrow, ncol, density): X = generate_sparse_matrix(shape=(nrow, ncol), density=density) # For debug np.save("/tmp/X_%d_%d.npy" % (nrow, ncol), X) # svd from parsimony fast_sparse_svd = RankOneSparseSVD(max_iter=1000) parsimony_v = fast_sparse_svd.run(X) # return self.get_err_by_np_linalg_svd(parsimony_v, X) return self.get_err_by_sp_sparse_linalg_svds(parsimony_v, X)
def get_err_fast_sparse_svd(self, nrow, ncol, density): X = generate_sparse_matrix(shape=(nrow, ncol), density=density) # For debug # np.save("/tmp/X_%d_%d.npy" % (nrow, ncol), X) fd = None try: fd, tmpfilename = tempfile.mkstemp(suffix=".npy", prefix="X_%d_%d" % (nrow, ncol)) np.save(tmpfilename, X) finally: if fd is not None: os.close(fd) # svd from parsimony fast_sparse_svd = RankOneSparseSVD(max_iter=1000) parsimony_v = fast_sparse_svd.run(X) # return self.get_err_by_np_linalg_svd(parsimony_v, X) return self.get_err_by_sp_sparse_linalg_svds(parsimony_v, X)