change default sampling points and example folder

fabian-sp · Apr 30, 2024 · 6f8b5d0 · 6f8b5d0
1 parent d90120c
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Showing 3 changed files with 11 additions and 14 deletions.
diff --git a/scripts/example_residual.py → examples/example_residual.py b/scripts/example_residual.py → examples/example_residual.py
@@ -1,6 +1,4 @@
 """
-@author: Fabian Schaipp
-
 Implements Example 5.3 in
 
     Frank E. Curtis and Michael L. Overton, A sequential quadratic programming

diff --git a/example_rosenbrock.py → examples/example_rosenbrock.py b/example_rosenbrock.py → examples/example_rosenbrock.py
@@ -1,5 +1,10 @@
 """
-@author: Fabian Schaipp
+Implements Example 5.1 in
+
+    Frank E. Curtis and Michael L. Overton, A sequential quadratic programming
+    algorithm for nonconvex, nonsmooth constrained optimization,
+    SIAM Journal on Optimization 2012 22:2, 474-500, https://doi.org/10.1137/090780201.
+
 """
 
 import matplotlib.pyplot as plt
@@ -12,8 +17,6 @@
 from ncopt.functions.rosenbrock import NonsmoothRosenbrock
 from ncopt.sqpgs import SQPGS
 
-np.random.seed(1234)
-
 # %% Setup
 
 f = ObjectiveOrConstraint(NonsmoothRosenbrock(a=8.0), dim=2)
@@ -37,7 +40,7 @@
 
 # %% How to use the solver
 
-problem = SQPGS(f, gI, gE, x0=None, tol=1e-6, max_iter=100, verbose=True)
+problem = SQPGS(f, gI, gE, x0=None, tol=1e-10, max_iter=100, verbose=True)
 x = problem.solve()
 
 print("Distance to solution:", f"{np.linalg.norm(x - xstar):.9f}")
@@ -60,15 +63,11 @@
 
 # Plot contour and solution
 ax.contourf(X, Y, Z, cmap="gist_heat", levels=20, alpha=0.7, antialiased=True, lw=0, zorder=0)
-# ax.contourf(X, Y, Z, colors='lightgrey', levels=20, alpha=0.7,
-#             antialiased=True, lw=0, zorder=0)
-# ax.contour(X, Y, Z, cmap='gist_heat', levels=8, alpha=0.7,
-#             antialiased=True, linewidths=4, zorder=0)
 ax.scatter(xstar[0], xstar[1], marker="*", s=200, c="gold", zorder=1)
 
 for i in range(7):
     x0 = np.random.randn(2)
-    problem = SQPGS(f, gI, gE, x0, tol=1e-6, max_iter=100, verbose=False, store_history=True)
+    problem = SQPGS(f, gI, gE, x0, tol=1e-10, max_iter=100, verbose=False, store_history=True)
     x_k = problem.solve()
     print(x_k)
 
@@ -90,4 +89,4 @@
 ax.legend(handles=legend_elements, ncol=3, fontsize=8)
 
 fig.tight_layout()
-fig.savefig("data/img/rosenbrock.png")
+fig.savefig("../data/img/rosenbrock.png")
diff --git a/src/ncopt/sqpgs/defaults.py b/src/ncopt/sqpgs/defaults.py
@@ -29,8 +29,8 @@ class Dotdict(dict):
     "xi_y": 1e3,
     "xi_sy": 1e-6,
     "iter_H": 10,
-    "num_points_obj": 2,
-    "num_points_gI": 3,
+    "num_points_obj": 4,
+    "num_points_gI": 4,
     "num_points_gE": 4,
     "qp_solver": "osqp",
     "reg_H": 1e-03,