modernize sol.value() to -> sol()

peterdsharpe · Jan 1, 2024 · 773e253 · 773e253
1 parent e090c59
commit 773e253
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Showing 10 changed files with 75 additions and 75 deletions.
diff --git a/aerosandbox/optimization/test_optimization/test_opti_analytical_wing_aerostructures.py b/aerosandbox/optimization/test_optimization/test_opti_analytical_wing_aerostructures.py
@@ -83,7 +83,7 @@ def test_gpkit_style_solve():
 
     sol = opti.solve()
 
-    assert sol.value(D) == pytest.approx(303.1, abs=0.1)
+    assert sol(D) == pytest.approx(303.1, abs=0.1)
 
 
 def test_geometric_program_solve():
@@ -132,7 +132,7 @@ def test_geometric_program_solve():
 
     sol = opti.solve()
 
-    assert sol.value(D) == pytest.approx(303.1, abs=0.1)
+    assert sol(D) == pytest.approx(303.1, abs=0.1)
 
 
 def test_non_log_transformed_solve():
@@ -186,7 +186,7 @@ def test_non_log_transformed_solve():
 
     sol = opti.solve()
 
-    assert sol.value(D) == pytest.approx(303.1, abs=0.1)
+    assert sol(D) == pytest.approx(303.1, abs=0.1)
 
 
 if __name__ == '__main__':

diff --git a/aerosandbox/optimization/test_optimization/test_opti_analytical_wing_drag_minimization.py b/aerosandbox/optimization/test_optimization/test_opti_analytical_wing_drag_minimization.py
@@ -28,11 +28,11 @@ def test_normal_problem():
 
     sol = opti.solve()
 
-    print(f"Chord = {sol.value(chord)}")
-    print(f"Span = {sol.value(span)}")
+    print(f"Chord = {sol(chord)}")
+    print(f"Span = {sol(span)}")
 
-    assert sol.value(chord) == pytest.approx(0.2288630528244024)
-    assert sol.value(span) == pytest.approx(4.369425242121806)
+    assert sol(chord) == pytest.approx(0.2288630528244024)
+    assert sol(span) == pytest.approx(4.369425242121806)
 
 
 def test_log_transformed_problem():
@@ -51,11 +51,11 @@ def test_log_transformed_problem():
 
     sol = opti.solve()
 
-    print(f"Chord = {sol.value(chord)}")
-    print(f"Span = {sol.value(span)}")
+    print(f"Chord = {sol(chord)}")
+    print(f"Span = {sol(span)}")
 
-    assert sol.value(chord) == pytest.approx(0.2288630528244024)
-    assert sol.value(span) == pytest.approx(4.369425242121806)
+    assert sol(chord) == pytest.approx(0.2288630528244024)
+    assert sol(span) == pytest.approx(4.369425242121806)
 
 
 def test_log_transformed_negativity_error():
@@ -81,11 +81,11 @@ def test_fixed_variable():
 
     sol = opti.solve()
 
-    print(f"Chord = {sol.value(chord)}")
-    print(f"Span = {sol.value(span)}")
+    print(f"Chord = {sol(chord)}")
+    print(f"Span = {sol(span)}")
 
-    assert sol.value(chord) == pytest.approx(1)
-    assert sol.value(span) == pytest.approx(1)
+    assert sol(chord) == pytest.approx(1)
+    assert sol(span) == pytest.approx(1)
 
 
 def test_fully_fixed_problem():
@@ -104,11 +104,11 @@ def test_fully_fixed_problem():
 
     sol = opti.solve()
 
-    print(f"Chord = {sol.value(chord)}")
-    print(f"Span = {sol.value(span)}")
+    print(f"Chord = {sol(chord)}")
+    print(f"Span = {sol(span)}")
 
-    assert sol.value(chord) == pytest.approx(1)
-    assert sol.value(span) == pytest.approx(1)
+    assert sol(chord) == pytest.approx(1)
+    assert sol(span) == pytest.approx(1)
 
 
 def test_overconstrained_fully_fixed_problem():
@@ -128,11 +128,11 @@ def test_overconstrained_fully_fixed_problem():
 
     sol = opti.solve()
 
-    print(f"Chord = {sol.value(chord)}")
-    print(f"Span = {sol.value(span)}")
+    print(f"Chord = {sol(chord)}")
+    print(f"Span = {sol(span)}")
 
-    # assert sol.value(chord) == pytest.approx(1)
-    # assert sol.value(span) == pytest.approx(1)
+    # assert sol(chord) == pytest.approx(1)
+    # assert sol(span) == pytest.approx(1)
 
 
 if __name__ == '__main__':

diff --git a/aerosandbox/optimization/test_optimization/test_opti_bounds.py b/aerosandbox/optimization/test_optimization/test_opti_bounds.py
@@ -10,7 +10,7 @@ def test_bounds():
 
     sol = opti.solve()
 
-    assert sol.value(x) == pytest.approx(3)
+    assert sol(x) == pytest.approx(3)
 
 
 if __name__ == '__main__':

diff --git a/aerosandbox/optimization/test_optimization/test_opti_hanging_chain.py b/aerosandbox/optimization/test_optimization/test_opti_hanging_chain.py
@@ -83,7 +83,7 @@ def my_callback(iter: int):
         callback=my_callback
     )
 
-    assert sol.value(potential_energy) == pytest.approx(626.462, abs=1e-3)
+    assert sol(potential_energy) == pytest.approx(626.462, abs=1e-3)
 
     if plot:
         plt.show()

diff --git a/aerosandbox/optimization/test_optimization/test_opti_log_transform.py b/aerosandbox/optimization/test_optimization/test_opti_log_transform.py
@@ -9,7 +9,7 @@ def test_bounds():
     opti.minimize(x)
     sol = opti.solve()
 
-    assert sol.value(x) == pytest.approx(7)
+    assert sol(x) == pytest.approx(7)
 
 
 if __name__ == '__main__':

diff --git a/aerosandbox/optimization/test_optimization/test_opti_optimal_control_manual_integration.py b/aerosandbox/optimization/test_optimization/test_opti_optimal_control_manual_integration.py
@@ -74,7 +74,7 @@ def test_rocket_control_problem(plot=False):
 
     sol = opti.solve()  # solve
 
-    assert sol.value(a_max) == pytest.approx(0.02181991952, rel=1e-3)  # solved externally with Julia JuMP
+    assert sol(a_max) == pytest.approx(0.02181991952, rel=1e-3)  # solved externally with Julia JuMP
 
     if plot:
         import matplotlib.pyplot as plt
@@ -84,7 +84,7 @@ def test_rocket_control_problem(plot=False):
         fig, ax = plt.subplots(1, 1, figsize=(8, 6), dpi=200)
         for i, val, lab in zip(np.arange(3), [x, v, a], ["$x$", "$v$", "$a$"]):
             plt.subplot(3, 1, i + 1)
-            plt.plot(sol.value(val), label=lab)
+            plt.plot(sol(val), label=lab)
             plt.xlabel(r"Time [s]")
             plt.ylabel(lab)
             plt.legend()

diff --git a/aerosandbox/optimization/test_optimization/test_opti_parametric_sensitivites.py b/aerosandbox/optimization/test_optimization/test_opti_parametric_sensitivites.py
@@ -37,11 +37,11 @@ def test_rosenbrock_constrained(plot=False):
         for r_value in r_values
     ]
     fs = [
-        sol.value(f)
+        sol(f)
         for sol in sols
     ]
     duals = [
-        sol.value(dual)  # Ensure the dual can be evaluated
+        sol(dual)  # Ensure the dual can be evaluated
         for sol in sols
     ]
 

diff --git a/aerosandbox/optimization/test_optimization/test_opti_poorly_scaled.py b/aerosandbox/optimization/test_optimization/test_opti_poorly_scaled.py
@@ -31,8 +31,8 @@ def test_opti_poorly_scaled_constraints(constraint_jacobian_condition_number=1e1
     sol = opti.solve()
 
     # Check
-    assert sol.value(x) == pytest.approx(0.9, abs=1e-4)
-    assert sol.value(y) == pytest.approx(0.81, abs=1e-4)
+    assert sol(x) == pytest.approx(0.9, abs=1e-4)
+    assert sol(y) == pytest.approx(0.81, abs=1e-4)
 
 
 def test_opti_poorly_scaled_objective(objective_hessian_condition_number=1e10):
@@ -51,9 +51,9 @@ def test_opti_poorly_scaled_objective(objective_hessian_condition_number=1e10):
     sol = opti.solve()
 
     # Check
-    assert sol.value(x) == pytest.approx(0, abs=1e-2)
-    assert sol.value(y) == pytest.approx(0, abs=1e-2)
-    assert sol.value(f) == pytest.approx(0, abs=1e-4)
+    assert sol(x) == pytest.approx(0, abs=1e-2)
+    assert sol(y) == pytest.approx(0, abs=1e-2)
+    assert sol(f) == pytest.approx(0, abs=1e-4)
 
 
 if __name__ == '__main__':

diff --git a/aerosandbox/optimization/test_optimization/test_opti_rosenbrock.py b/aerosandbox/optimization/test_optimization/test_opti_rosenbrock.py
@@ -37,7 +37,7 @@ def test_2D_rosenbrock():  # 2-dimensional rosenbrock
     sol = opti.solve()
 
     for i in [x, y]:
-        assert sol.value(i) == pytest.approx(1, abs=1e-4)
+        assert sol(i) == pytest.approx(1, abs=1e-4)
 
 
 def test_2D_rosenbrock_circle_constrained():  # 2-dimensional rosenbrock, constrained to be within the unit circle.
@@ -58,8 +58,8 @@ def test_2D_rosenbrock_circle_constrained():  # 2-dimensional rosenbrock, constr
     sol = opti.solve()
 
     # Check
-    assert sol.value(x) == pytest.approx(0.7864, abs=1e-4)
-    assert sol.value(y) == pytest.approx(0.6177, abs=1e-4)
+    assert sol(x) == pytest.approx(0.7864, abs=1e-4)
+    assert sol(y) == pytest.approx(0.6177, abs=1e-4)
     # (Solution also given here: https://www.mathworks.com/help/optim/ug/example-nonlinear-constrained-minimization.html#brg0p3g-2 )
 
 
@@ -81,7 +81,7 @@ def test_ND_rosenbrock_constrained(N=10):  # N-dimensional rosenbrock
     sol = opti.solve()  # solve
 
     for i in range(N):
-        assert sol.value(x[i]) == pytest.approx(1, abs=1e-4)
+        assert sol(x[i]) == pytest.approx(1, abs=1e-4)
 
 
 def test_2D_rosenbrock_frozen():
@@ -98,9 +98,9 @@ def test_2D_rosenbrock_frozen():
     # Optimize
     sol = opti.solve()
 
-    assert sol.value(x) == pytest.approx(0.161, abs=1e-3)
-    assert sol.value(y) == pytest.approx(0, abs=1e-3)
-    assert sol.value(f) == pytest.approx(0.771, abs=1e-3)
+    assert sol(x) == pytest.approx(0.161, abs=1e-3)
+    assert sol(y) == pytest.approx(0, abs=1e-3)
+    assert sol(f) == pytest.approx(0.771, abs=1e-3)
 
 
 if __name__ == '__main__':

diff --git a/aerosandbox/optimization/test_optimization/test_opti_save_load.py b/aerosandbox/optimization/test_optimization/test_opti_save_load.py
@@ -28,7 +28,7 @@ def test_opti():
     sol = opti.solve()
 
     for i in [x, y]:
-        assert sol.value(i) == pytest.approx(1, abs=1e-4)
+        assert sol(i) == pytest.approx(1, abs=1e-4)
 
 
 def test_save_opti(tmp_path):
@@ -68,12 +68,12 @@ def test_save_and_load_opti(tmp_path):
     sol = opti.solve()
     opti.save_solution()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(1)
-    assert sol.value(y) == pytest.approx(1)
-    assert sol.value(f) == pytest.approx(0)
+    assert sol(x) == pytest.approx(1)
+    assert sol(y) == pytest.approx(1)
+    assert sol(f) == pytest.approx(0)
 
     ### Round 2 optimization: Cat 1 is fixed from before; slightly different objective now
     opti = asb.Opti(
@@ -90,12 +90,12 @@ def test_save_and_load_opti(tmp_path):
     # Optimize, save to cache, print
     sol = opti.solve()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(1)
-    assert sol.value(y) == pytest.approx(2)
-    assert sol.value(f) == pytest.approx(1)
+    assert sol(x) == pytest.approx(1)
+    assert sol(y) == pytest.approx(2)
+    assert sol(f) == pytest.approx(1)
 
 
 def test_save_and_load_opti_uncategorized(tmp_path):
@@ -116,12 +116,12 @@ def test_save_and_load_opti_uncategorized(tmp_path):
     sol = opti.solve()
     opti.save_solution()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(1)
-    assert sol.value(y) == pytest.approx(1)
-    assert sol.value(f) == pytest.approx(0)
+    assert sol(x) == pytest.approx(1)
+    assert sol(y) == pytest.approx(1)
+    assert sol(f) == pytest.approx(0)
 
     ### Round 2 optimization: Cat 1 is fixed from before; slightly different objective now
     opti = asb.Opti(
@@ -138,12 +138,12 @@ def test_save_and_load_opti_uncategorized(tmp_path):
     # Optimize, save to cache, print
     sol = opti.solve()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(1)
-    assert sol.value(y) == pytest.approx(1)
-    assert sol.value(f) == pytest.approx(2)
+    assert sol(x) == pytest.approx(1)
+    assert sol(y) == pytest.approx(1)
+    assert sol(f) == pytest.approx(2)
 
 
 def test_save_and_load_opti_vectorized(tmp_path):
@@ -165,12 +165,12 @@ def test_save_and_load_opti_vectorized(tmp_path):
     sol = opti.solve()
     opti.save_solution()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(1)
-    assert sol.value(y) == pytest.approx(2)
-    assert sol.value(f) == pytest.approx(0)
+    assert sol(x) == pytest.approx(1)
+    assert sol(y) == pytest.approx(2)
+    assert sol(f) == pytest.approx(0)
 
     ### Round 2 optimization: Cat 1 is fixed from before; slightly different objective now
     opti = asb.Opti(
@@ -187,12 +187,12 @@ def test_save_and_load_opti_vectorized(tmp_path):
     # Optimize, save to cache, print
     sol = opti.solve()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(1)
-    assert sol.value(y) == pytest.approx(4)
-    assert sol.value(f) == pytest.approx(12)
+    assert sol(x) == pytest.approx(1)
+    assert sol(y) == pytest.approx(4)
+    assert sol(f) == pytest.approx(12)
 
 
 def test_save_and_load_opti_freeze_override(tmp_path):
@@ -214,12 +214,12 @@ def test_save_and_load_opti_freeze_override(tmp_path):
     sol = opti.solve()
     opti.save_solution()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(1)
-    assert sol.value(y) == pytest.approx(1)
-    assert sol.value(f) == pytest.approx(0)
+    assert sol(x) == pytest.approx(1)
+    assert sol(y) == pytest.approx(1)
+    assert sol(f) == pytest.approx(0)
 
     ### Round 2 optimization: Cat 1 is fixed from before but then overridden; slightly different objective now
     opti = asb.Opti(
@@ -236,12 +236,12 @@ def test_save_and_load_opti_freeze_override(tmp_path):
     # Optimize, save to cache, print
     sol = opti.solve()
     for i in ["x", "y", "f"]:
-        print(f"{i}: {sol.value(eval(i))}")
+        print(f"{i}: {sol(eval(i))}")
 
     # Test
-    assert sol.value(x) == pytest.approx(3)
-    assert sol.value(y) == pytest.approx(2)
-    assert sol.value(f) == pytest.approx(1)
+    assert sol(x) == pytest.approx(3)
+    assert sol(y) == pytest.approx(2)
+    assert sol(f) == pytest.approx(1)
 
 
 if __name__ == '__main__':