Refactoring

scripts/optimize.py

@@ -5,7 +5,6 @@ from scipy.optimize import least_squares
 K1_REFERENCE = 0.577
 K2_REFERENCE = 0.422
 
-# Диапазоны из задания
 K1_BOUNDS = (1e-5, 1e2)
 K2_BOUNDS = (1e-2, 1.0)
 
@@ -79,15 +78,11 @@ def rk4_solution(t, k1, k2):
 
     return solution
 
-
-# Моменты времени из задания:
-# tj = 0.1j, j = 0, ..., 100
 time = np.linspace(T_BEGIN, T_END, 101)
 
 # Эталонные данные
 reference_solution = analytical_solution(time, K1_REFERENCE, K2_REFERENCE)
 
-
 def residuals(parameters):
     """
     Вектор невязок между моделью и эталонными данными.
@@ -120,17 +115,16 @@ absolute_error_k2 = abs(found_k2 - K2_REFERENCE)
 
 relative_error_k1 = absolute_error_k1 / K1_REFERENCE * 100.0
 relative_error_k2 = absolute_error_k2 / K2_REFERENCE * 100.0
-criterion_value = np.sum(result.fun ** 2)
 
 print("Results")
 print(f"Found k1:{found_k1:.4f}")
 print(f"Theoretical k1:{K1_REFERENCE:.4f}")
-print(f"Absolute error of k1:{absolute_error_k1:.4e}")
-print(f"Relative error of k1:{relative_error_k1:.4e} %")
+print(f"Absolute error of k1:{absolute_error_k1:.5e}")
+print(f"Relative error of k1:{relative_error_k1:.5e} %")
 print()
 
-print(f"Found k2:{found_k2:.4f}")
-print(f"Theoretical k2:{K2_REFERENCE:.4f}")
-print(f"Absolute error of k2:{absolute_error_k2:.4e}")
-print(f"Relative error of k2:{relative_error_k2:.4e} %")
+print(f"Found k2:{found_k2:.5f}")
+print(f"Theoretical k2:{K2_REFERENCE:.5f}")
+print(f"Absolute error of k2:{absolute_error_k2:.5e}")
+print(f"Relative error of k2:{relative_error_k2:.5e} %")
 print()