Nice

GHA_triaxial/gha1_ES.py

@@ -209,8 +209,8 @@ def optimize_next_point(beta_i: float, omega_i: float, alpha_i: float, ds: float
     return beta_best, omega_best, P_best, alpha_end
 
 
-def gha1_ES(ell: EllipsoidTriaxial, beta0: float, omega0: float, alpha0: float, s_total: float, maxSegLen: float = 1000)\
-        -> Tuple[NDArray, float, NDArray]:
+def gha1_ES(ell: EllipsoidTriaxial, beta0: float, omega0: float, alpha0: float, s_total: float, maxSegLen: float = 1000, all_points: boolean = False)\
+        -> Tuple[NDArray, float, NDArray] | Tuple[NDArray, float]:
     """
     Aufruf der 1. GHA mittels CMA-ES
     :param ell: Ellipsoid
@@ -219,6 +219,7 @@ def gha1_ES(ell: EllipsoidTriaxial, beta0: float, omega0: float, alpha0: float,
     :param alpha0: Azimut Startkoordinate
     :param s_total: Gesamtstrecke
     :param maxSegLen: maximale Segmentlänge
+    :param all_points: Alle Punkte ausgeben?
     :return: Zielpunkt Pk, Azimut am Zielpunkt und Punktliste
     """
     beta = float(beta0)
@@ -236,7 +237,7 @@ def gha1_ES(ell: EllipsoidTriaxial, beta0: float, omega0: float, alpha0: float,
     while s_acc < s_total - 1e-9:
         step += 1
         ds = min(maxSegLen, s_total - s_acc)
-        print(f"[GHA1-ES] Step {step}/{nsteps_est}  ds={ds:.3f} m  s_acc={s_acc:.3f} m  beta={beta:.6f}  omega={omega:.6f}  alpha={alpha:.6f}")
+        # print(f"[GHA1-ES] Step {step}/{nsteps_est}  ds={ds:.3f} m  s_acc={s_acc:.3f} m  beta={beta:.6f}  omega={omega:.6f}  alpha={alpha:.6f}")
 
         beta, omega, P, alpha = optimize_next_point(beta_i=beta, omega_i=omega, alpha_i=alpha, ds=ds, gamma0=gamma0,
                                                     ell=ell, maxSegLen=maxSegLen)
@@ -248,7 +249,10 @@ def gha1_ES(ell: EllipsoidTriaxial, beta0: float, omega0: float, alpha0: float,
     Pk = P_all[-1]
     alpha1 = float(alpha_end[-1])
 
-    return Pk, alpha1, np.array(P_all)
+    if all_points:
+        return Pk, alpha1, np.array(P_all)
+    else:
+        return Pk, alpha1
 
 
 if __name__ == "__main__":