Bugfix in passing extra arguments

Author: lindonroberts

dfols/solver.py

@@ -1036,12 +1036,12 @@ def solve(objfun, x0, h=None, lh=None, prox_uh=None, argsf=(), argsh=(), argspro
             x0 = xp.copy()
 
     # Enforce lower & upper bounds on x0
-    idx = (x0 <= xl)
+    idx = (x0 < xl)
     if np.any(idx):
         warnings.warn("x0 below lower bound, adjusting", RuntimeWarning)
     x0[idx] = xl[idx]
 
-    idx = (x0 >= xu)
+    idx = (x0 > xu)
     if np.any(idx):
         warnings.warn("x0 above upper bound, adjusting", RuntimeWarning)
     x0[idx] = xu[idx]

dfols/trust_region.py

@@ -79,7 +79,7 @@
     # Fall back to Python implementation
     USE_FORTRAN = False
 
-from .util import dykstra, pball, pbox, sumsq, model_value
+from .util import dykstra, pball, pbox, sumsq, model_value, remove_scaling
 
 __all__ = ['ctrsbox_sfista', 'ctrsbox_pgd', 'ctrsbox_geometry', 'trsbox', 'trsbox_geometry']
 
@@ -135,7 +135,7 @@ def proj(d0):
         return p - xopt
 
     # general step
-    model_value_best = model_value(g, H, d, xopt, h, *argsh, scaling_changes)
+    model_value_best = model_value(g, H, d, xopt, h, argsh, scaling_changes)
     d_best = d.copy()
     for k in range(MAX_LOOP_ITERS):
         prev_d = d.copy()
@@ -148,7 +148,7 @@ def proj(d0):
         # SOLVED: (previously) make sfista decrease in each iteration (might have d = 0, criticality measure=0)
         # if model_value(g, H, d, xopt, h, *argsh) > model_value(g, H, prev_d, xopt, h, *argsh):
         #     d = prev_d
-        new_model_value = model_value(g, H, d, xopt, h, *argsh, scaling_changes)
+        new_model_value = model_value(g, H, d, xopt, h, argsh, scaling_changes)
         if new_model_value < model_value_best:
             d_best = d.copy()
             model_value_best = new_model_value

dfols/util.py

@@ -64,7 +64,7 @@ def eval_least_squares_with_regularisation(objfun, x, h=None, argsf=(), argsh=()
 
     # objective = least-squares + regularisation
     obj = f
-    if h != None:
+    if h is not None:
         # Evaluate regularisation term
         hvalue = h(x, *argsh)
         obj = f + hvalue
@@ -83,7 +83,7 @@ def model_value(g, H, s, xopt=(), h=None,argsh=(), scaling_changes=None):
     assert g.shape == s.shape, "g and s have incompatible sizes"
     Hs = H.dot(s)
     rtn = np.dot(s, g + 0.5*Hs)
-    if h != None:
+    if h is not None:
         hvalue = h(remove_scaling(xopt+s, scaling_changes), *argsh)
         rtn += hvalue
     return rtn