small cleanup

KOS-UJ · Sep 12, 2024 · 6c3d5c4 · 6c3d5c4
1 parent bf89113
commit 6c3d5c4
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Showing 8 changed files with 48 additions and 44 deletions.
diff --git a/conmech/solvers/optimization/optimization.py b/conmech/solvers/optimization/optimization.py
@@ -39,6 +39,22 @@
 from kosopt.qsmlm import make_minimizer
 
 
+QSMLM_NAMES = {
+    "quasi secant method",
+    "limited memory quasi secant method",
+    "quasi secant method limited memory",
+    "qsm",
+    "qsmlm",
+}
+GLOBAL_QSMLM_NAMES = {
+    "global quasi secant method",
+    "global limited memory quasi secant method",
+    "global quasi secant method limited memory",
+    "globqsm",
+    "globqsmlm",
+}
+
+
 class Optimization(Solver):
     def __init__(
         self,
@@ -131,34 +147,25 @@ def _solve_impl(
         sols.append(solution)
         loss.append(self.loss(solution, *args)[0])
 
-        if self.minimizer is None and method.lower() in (
-            "quasi secant method",
-            "limited memory quasi secant method",
-            "quasi secant method limited memory",
-            "qsm",
-            "qsmlm",
-            "subgradient",
-        ):
+        if self.minimizer is None and method.lower() in QSMLM_NAMES.union(GLOBAL_QSMLM_NAMES):
             self.minimizer = make_minimizer(self.loss, self.subgradient)
 
         while norm >= fixed_point_abs_tol:
-            if method.lower() in (
-                "quasi secant method",
-                "limited memory quasi secant method",
-                "quasi secant method limited memory",
-                "qsm",
-                "qsmlm",
-            ):
+            if method.lower() in QSMLM_NAMES:
                 solution = self.minimizer(solution, args, maxiter=maxiter)
                 sols.append(solution.copy())
                 loss.append(self.loss(solution, *args)[0])
-            elif method.lower() in ("subgradient",):
+            elif method.lower() in GLOBAL_QSMLM_NAMES:
                 # pylint: disable=import-outside-toplevel,import-error)
                 from kosopt import subgradient
 
                 solution = subgradient.minimize(
-                    self.minimizer, self.loss, solution, args,
-                    maxiter=maxiter, subgradient=self.subgradient
+                    self.minimizer,
+                    self.loss,
+                    solution,
+                    args,
+                    maxiter=maxiter,
+                    subgradient=self.subgradient,
                 )
                 sols.append(solution.copy())
                 loss.append(self.loss(solution, *args)[0])
@@ -195,7 +202,6 @@ def constr(x):
                 solution = result.x
                 sols.append(solution)
                 loss.append(self.loss(solution, *args)[0])
-                break
             else:
                 result = scipy.optimize.minimize(
                     self.loss,
@@ -208,12 +214,11 @@ def constr(x):
                 solution = result.x
                 sols.append(solution.copy())
                 loss.append(self.loss(solution, *args)[0])
-                break
 
             norm = np.linalg.norm(np.subtract(solution, old_solution))
             old_solution = solution.copy()
         min_index = loss.index(np.min(loss))
-        print(method, np.min(loss))   # TODO
+        print(method, np.min(loss))  # TODO
         solution = sols[min_index]
 
         return solution
diff --git a/conmech/solvers/optimization/schur_complement.py b/conmech/solvers/optimization/schur_complement.py
@@ -2,7 +2,6 @@
 Created at 22.02.2021
 """
 
-import math
 from typing import Tuple
 
 import numpy as np

diff --git a/conmech/solvers/solver_methods.py b/conmech/solvers/solver_methods.py
@@ -252,12 +252,12 @@ def contact_subgradient(
             # ASSUMING `u_vector` and `nodes` have the same order!
             vm = interpolate_node_between(edge, var, var_old, dimension=variable_dimension)
             if variable_dimension == 1:
-                raise NotImplementedError()
-                vm_normal = vm[0]
-                vm_tangential = np.empty(0)
-            else:
-                vm_normal = (vm * normal_vector).sum()
-                vm_tangential = vm - vm_normal * normal_vector
+                raise NotImplementedError()  # TODO
+                # vm_normal = vm[0]
+                # vm_tangential = np.empty(0)
+            # else:
+            vm_normal = (vm * normal_vector).sum()
+            vm_tangential = vm - vm_normal * normal_vector
 
             static_displacement_mean = interpolate_node_between(
                 edge,

diff --git a/examples/Bagirrov_Bartman_Ochal_2024.py b/examples/Bagirrov_Bartman_Ochal_2024.py
@@ -228,7 +228,7 @@ def outer_forces(x, t=None):
     # plt.legend()
     # # plt.loglog()
     # plt.show()
-    methods = ("BFGS", "CG", "qsm", "Powell", "subgradient")
+    methods = ("BFGS", "CG", "qsm", "Powell", "globqsm")
     forces = (
         23e3 * kN,
         25e3 * kN,

diff --git a/examples/Makela_et_al_1998.py b/examples/Makela_et_al_1998.py
@@ -82,10 +82,10 @@ def potential_tangential_direction(
 
     @staticmethod
     def subderivative_tangential_direction(
-            var_tau: float, static_displacement_tau: float, dt: float
+        var_tau: float, static_displacement_tau: float, dt: float
     ) -> float:
-        quadsum = np.sum(var_tau ** 2)
-        norm = quadsum ** 0.5
+        quadsum = np.sum(var_tau**2)
+        norm = quadsum**0.5
         denom = norm + quadsum
         coef = 1 / denom if denom != 0.0 else 0.0
         return var_tau * coef
@@ -273,5 +273,5 @@ def outer_forces(x, t=None):
     # plt.xlabel(r"Load [kN/m$^2$]")
     # plt.grid()
     # plt.show()
-    methods = ("BFGS", "CG", "Powell", "subgradient")[-2:]
+    methods = ("BFGS", "CG", "Powell", "globqsm")[-2:]
     main(Config(save=False, show=True, force=True).init(), methods, forces)
diff --git a/tests/test_conmech/regression/test_Makela_et_al_1998.py b/tests/test_conmech/regression/test_Makela_et_al_1998.py
@@ -120,7 +120,7 @@ def generate_test_suits():
     ]
     test_suites.append((optimization_mtd_pow, expected_displacement_vector_pow))
 
-    optimization_mtd_subg = "subgradient"
+    optimization_mtd_subg = "globqsm"
     expected_displacement_vector_subg = [
         [0.0, 0.0],
         [-0.00006594, -0.00004315],

diff --git a/tests/test_conmech/regression/test_static.py b/tests/test_conmech/regression/test_static.py
@@ -20,7 +20,7 @@ def solving_method(request):
     return request.param
 
 
-@pytest.fixture(params=["BFGS", "qsm", "subgradient"])
+@pytest.fixture(params=["BFGS", "qsm", "globqsm"])
 def opt_method(request):
     return request.param
 

diff --git a/tests/test_conmech/regression/test_static_3d.py b/tests/test_conmech/regression/test_static_3d.py
@@ -50,28 +50,28 @@ def outer_forces(x, t=None):
     setup_m02_m02 = StaticSetup(mesh_descr)
 
     expected_displacement_vector_m02_m02 = [
-        [0., 0., 0.],
-        [0., 0., 0.],
-        [0., 0., 0.],
+        [0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0],
         [0.00887781, 0.00938318, 0.01303338],
         [0.01254745, 0.0164677, 0.02173087],
         [0.00484257, 0.01694291, 0.02137632],
         [-0.00172692, 0.01755931, 0.02152949],
         [0.00322087, 0.01678243, 0.0214544],
         [0.00253174, 0.00921583, 0.01132137],
         [-0.00196061, 0.00997206, 0.01218131],
-        [0., 0., 0.],
-        [0., 0., 0.],
+        [0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0],
         [-0.0062681, 0.01092748, 0.0123151],
         [-0.00694282, 0.01796747, 0.021246],
         [-0.00016377, 0.01769789, 0.02100172],
         [-0.00086678, 0.0100699, 0.0117306],
-        [0., 0., 0.],
-        [0., 0., 0.],
+        [0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0],
         [0.00494897, 0.00864805, 0.0115685],
         [0.00615472, 0.0164003, 0.02059693],
-        [0., 0., 0.],
-        [0., 0., 0.],
+        [0.0, 0.0, 0.0],
+        [0.0, 0.0, 0.0],
         [0.01361542, 0.01025, 0.01362368],
         [0.01573552, 0.01474276, 0.02232607],
         [0.01065649, 0.01625437, 0.02177309],