legendre_decomp.module_cond_mba

Functions

decomp_given_tensor(X_, I[, n_iter, lr, eps, ...])
build_condition(theta_dict, I, shape)
conditional_decomp_tensor(X_, I, I_c, theta, mask, ...)
CLD_MBA(X, I, Y, I_c[, n_iter, lr, eps, error_tol, ...])

Module Contents

legendre_decomp.module_cond_mba.decomp_given_tensor(X_, I, n_iter=100, lr=1.0, eps=1e-05, error_tol=1e-05, ngd=True, ngd_lstsq=True, gpu=True, verbose=True)

Parameters:

• X_ (numpy.typing.NDArray[numpy.float64])

• I (List[Tuple[int, Ellipsis]])

• n_iter (int)

• lr (float)

• eps (float)

• error_tol (float)

• ngd (bool)

• ngd_lstsq (bool)

• gpu (bool)

• verbose (bool)

legendre_decomp.module_cond_mba.build_condition(theta_dict, I, shape)

Parameters:

• theta_dict (Dict[Tuple[int, Ellipsis], numpy.typing.NDArray[numpy.float64]])

• I (List[Tuple[int, Ellipsis]])

• shape (Tuple[int, Ellipsis])

legendre_decomp.module_cond_mba.conditional_decomp_tensor(X_, I, I_c, theta, mask, X_out_given_, theta_given, n_iter=100, lr=1.0, eps=1e-05, error_tol=1e-05, ngd=True, ngd_lstsq=True, verbose=True, verbose_ld=True, gpu=True)

Parameters:

• X_ (numpy.typing.NDArray[numpy.float64])

• I (List[Tuple[int, Ellipsis]])

• I_c (Tuple[int, Ellipsis])

• theta (numpy.typing.NDArray[numpy.float64])

• mask (numpy.typing.NDArray[numpy.float64])

• X_out_given_ (Dict[Any, Any])

• theta_given (numpy.typing.NDArray[numpy.float64])

• n_iter (int)

• lr (float)

• eps (float)

• error_tol (float)

• ngd (bool)

• ngd_lstsq (bool)

• verbose (bool)

• verbose_ld (bool)

• gpu (bool)

legendre_decomp.module_cond_mba.CLD_MBA(X, I, Y, I_c, n_iter=100, lr=1.0, eps=1e-05, error_tol=1e-05, ngd=True, ngd_lstsq=True, verbose=False, gpu=True)

Parameters:

• X (numpy.typing.NDArray[numpy.float64])

• I (List[Tuple[int, Ellipsis]])

• Y (numpy.typing.NDArray[numpy.float64])

• I_c (Tuple[int, Ellipsis])

• n_iter (int)

• lr (float)

• eps (float)

• error_tol (float)

• ngd (bool)

• ngd_lstsq (bool)

• verbose (bool)

• gpu (bool)