lib5c.algorithms.express module

Module for implementation of the “Express” algorithm from Sauria et al. 2015.

lib5c.algorithms.express.express_normalize_matrix(obs_matrix, exp_matrix, max_iter=1000, eps=0.0001)[source]

Express balance a matrix given a corresponding expected matrix.

Parameters:
  • obs_matrix (np.ndarray) – The matrix to normalize.
  • exp_matrix (np.ndarray) – The expected matrix corresponding to the obs_matrix.
  • max_iter (int) – The maximum number of iterations.
  • eps (float) – When the fractional change in the residual is less than this number, the algorithm is considered to have converged and will stop iterating.
Returns:

The first element of the tuple is the normalized matrix. The second element is the multiplicative bias vector. The third element is a list containing the L1 norm of the residual at every iteration.
Return type:

Tuple[np.ndarray, np.ndarray, List[float]]
lib5c.algorithms.express.joint_express_normalize(obs_matrices, exp_matrices, max_iter=1000, eps=0.0001)[source]

Express balance a set of matrices given a set of corresponding expected matrices, using a single shared bias vector.

Parameters:
  • obs_matrices (List[np.ndarray]) – The matrix to normalize.
  • exp_matrices (List[np.ndarray]) – The expected matrix corresponding to the obs_matrix.
  • max_iter (int) – The maximum number of iterations.
  • eps (float) – When the fractional change in the residual is less than this number, the algorithm is considered to have converged and will stop iterating.
Returns:

The first element of the tuple is the list of normalized matrices. The second element is the multiplicative bias vector. The third element is a list containing the L1 norm of the residual at every iteration.
Return type:

Tuple[List[np.ndarray], np.ndarray, List[float]]