add docs

skglm/experimental/pdcd_ws.py

@@ -9,6 +9,48 @@
 
 
 class PDCD_WS:
+ """Primal-Dual Coordinate Descent solver with working sets.
+
+ Solver inspired by [1] that uses working sets.
+
+ Parameters
+ ----------
+ max_iter : int, optional
+ The maximum number of iterations or equivalently the
+ the maximum number solved subproblems.
+
+ max_epochs : int, optional
+ Maximum number of CD epochs on each subproblem.
+
+ p0 : int, optional
+ First working set size.
+
+ tol : float, optional
+ The tolerance for the optimization.
+
+ dual_init : array, shape (n_samples,) default None
+ The initialization of dual variables.
+ If None, they are initialized as the 0 vector ``np.zeros(n_samples)``.
+
+ return_p_objs : bool, default False
+ If True, returns the values of the objective in each iteration.
+ Otherwise returns an empty array.
+
+ verbose : bool or int, default False
+ Amount of verbosity. 0/False is silent.
+
+ References
+ ----------
+ .. [1] Olivier Fercoq and Pascal Bianchi,
+ "A Coordinate-Descent Primal-Dual Algorithm with Large Step Size and Possibly
+ Nonseparable Functions", SIAM Journal on Optimization, 2020,
+ https://epubs.siam.org/doi/10.1137/18M1168480,
+ code: https://github.com/Badr-MOUFAD/Fercoq-Bianchi-solver
+
+ .. [2] Mathurin Massias, Alexandre Gramfort, Joseph Salmon,
+ "From safe screening rules to working sets for faster Lasso-type solvers",
+ OPTML workshop at NIPS 2017, https://arxiv.org/abs/1703.07285v2
+ """
 
  def __init__(self, max_iter=1000, max_epochs=1000, p0=100, tol=1e-6,
  dual_init=None, return_p_objs=False, verbose=False):
@@ -131,11 +173,11 @@ def _solve_subproblem(y, X, w, Xw, z, z_bar, datafit, penalty,
  break
 
  @staticmethod
- def _validate_init(datafit, penalty):
+ def _validate_init(datafit_, penalty_):
  # validate datafit
  missing_attrs = []
  for attr in ('prox_conjugate', 'subdiff_distance'):
- if not hasattr(datafit, attr):
+ if not hasattr(datafit_, attr):
  missing_attrs.append(f"`{attr}`")
 
  if len(missing_attrs):
@@ -146,7 +188,7 @@ def _validate_init(datafit, penalty):
  )
 
  # jit compile classes
- compiled_datafit = compiled_clone(datafit)
- compiled_penalty = compiled_clone(penalty)
+ compiled_datafit = compiled_clone(datafit_)
+ compiled_penalty = compiled_clone(penalty_)
 
  return compiled_datafit, compiled_penalty