Merge pull request #114 from chrhansk/feature-active-set-display

Fix several errors in display

docs/conf.py

@@ -14,7 +14,7 @@
 project = "pygradflow"
 copyright = "2023, Christoph Hansknecht"
 author = "Christoph Hansknecht"
-release = "0.5.19"
+release = "0.5.20"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

pygradflow/display.py

@@ -11,7 +11,9 @@
 
 
 class StateData:
-    def __init__(self):
+    def __init__(self, iterate, step_result):
+        self.iterate = iterate
+        self.step_result = step_result
         self._entries = dict()
 
     def __setitem__(self, key, value):
@@ -21,7 +23,7 @@ def __getitem__(self, key):
         try:
             entry = self._entries[key]
             if callable(entry):
-                return entry()
+                return entry(self.iterate, self.step_result)
             return entry
         except Exception:
             return None
@@ -219,7 +221,12 @@ def solver_display(problem: Problem, params: Params):
     cols.append(
         AttrColumn("Primal step", 16, "{:16.8e}", StateAttr("primal_step_norm"))
     )
-    cols.append(AttrColumn("Dual step", 16, "{:16.8e}", StateAttr("dual_step_norm")))
+
+    if problem.num_cons > 0:
+        cols.append(
+            AttrColumn("Dual step", 16, "{:16.8e}", StateAttr("dual_step_norm"))
+        )
+
     cols.append(AttrColumn("Lambda", 16, "{:16.8e}", StateAttr("lamb")))
 
     if problem.var_bounded:

pygradflow/integration/integration_solver.py

@@ -432,7 +432,7 @@ def solve(self, x0: Optional[np.ndarray] = None, y0: Optional[np.ndarray] = None
             path_dist += result.dist
 
             if display.should_display():
-                state = StateData()
+                state = StateData(curr_it, step_result=None)
                 curr_x, curr_y = self.flow.split_states(curr_z)
                 iterate = curr_it
                 state["iterate"] = iterate

pygradflow/solver.py

@@ -305,24 +305,26 @@ def solve(
             self.callbacks(CallbackType.ComputedStep, iterate, next_iterate, accept)
 
             if display_iterate:
-                state = StateData()
+                state = StateData(iterate, step_result)
                 state["iterate"] = iterate
-                state["active_set"] = lambda: step_result.active_set
-                state["obj_nonlin"] = lambda: iterate.obj_nonlin(next_iterate)
+                state["active_set"] = lambda _, step_result: step_result.active_set
+                state["obj_nonlin"] = lambda iterate, _: iterate.obj_nonlin(
+                    step_result.iterate
+                )
 
                 if problem.num_cons > 0:
-                    state["cons_nonlin"] = lambda: np.linalg.norm(
-                        iterate.cons_nonlin(next_iterate), ord=np.inf
+                    state["cons_nonlin"] = lambda iterate, _: np.linalg.norm(
+                        iterate.cons_nonlin(step_result.iterate), ord=np.inf
                     )
 
-                state["aug_lag"] = lambda: iterate.aug_lag(self.rho)
-                state["obj"] = lambda: iterate.obj()
+                state["aug_lag"] = lambda iterate, _: iterate.aug_lag(self.rho)
+                state["obj"] = lambda iterate, _: iterate.obj()
                 state["iter"] = iteration + 1
-                state["primal_step_norm"] = lambda: primal_step_norm
-                state["dual_step_norm"] = lambda: dual_step_norm
-                state["lamb"] = lambda: lamb
-                state["step_accept"] = lambda: accept
-                state["rcond"] = lambda: step_result.rcond
+                state["primal_step_norm"] = primal_step_norm
+                state["dual_step_norm"] = dual_step_norm
+                state["lamb"] = lamb
+                state["step_accept"] = accept
+                state["rcond"] = lambda _, step_result: step_result.rcond
 
                 logger.info(display.row(state))
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pygradflow"
-version = "0.5.19"
+version = "0.5.20"
 description = "PyGradFlow is a simple implementation of the sequential homotopy method to be used to solve general nonlinear programs."
 authors = ["Christoph Hansknecht <[email protected]>"]
 readme = "README.md"