Abgabe fertig

ES/Hansen_ES_CMA.py

@@ -1,7 +1,8 @@
 import numpy as np
+from numpy.typing import NDArray
 
 
-def felli(x):
+def felli(x: NDArray) -> float:
     N = x.shape[0]
     if N < 2:
         raise ValueError("dimension must be greater than one")
@@ -11,8 +12,7 @@ def felli(x):
 
 def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-14, stopeval=2000,
           func_args=(), func_kwargs=None, seed=0,
-          bestEver = np.inf, noImproveGen = 0, absTolImprove = 1e-12, maxNoImproveGen = 100, sigmaImprove = 1e-12):
+          bestEver=np.inf, noImproveGen=0, absTolImprove=1e-12, maxNoImproveGen=100, sigmaImprove=1e-12):
-
     if func_kwargs is None:
         func_kwargs = {}
 
@@ -27,7 +27,7 @@ def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-14, stopeval=2000
         N = xmean.shape[0]
 
     if stopeval is None:
-        stopeval = int(1e3 * N**2)
+        stopeval = int(1e3 * N ** 2)
 
     # Strategy parameter setting: Selection
     lambda_ = 4 + int(np.floor(3 * np.log(N)))
@@ -37,14 +37,14 @@ def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-14, stopeval=2000
     weights = np.log(mu + 0.5) - np.log(np.arange(1, int(mu) + 1))
     mu = int(np.floor(mu))
     weights = weights / np.sum(weights)
-    mueff = np.sum(weights)**2 / np.sum(weights**2)
+    mueff = np.sum(weights) ** 2 / np.sum(weights ** 2)
 
     # Strategy parameter setting: Adaptation
     cc = (4 + mueff / N) / (N + 4 + 2 * mueff / N)
     cs = (mueff + 2) / (N + mueff + 5)
-    c1 = 2 / ((N + 1.3)**2 + mueff)
+    c1 = 2 / ((N + 1.3) ** 2 + mueff)
     cmu = min(1 - c1,
-              2 * (mueff - 2 + 1 / mueff) / ((N + 2)**2 + 2 * mueff))
+              2 * (mueff - 2 + 1 / mueff) / ((N + 2) ** 2 + 2 * mueff))
     damps = 1 + 2 * max(0, np.sqrt((mueff - 1) / (N + 1)) - 1) + cs
 
     # Initialize dynamic (internal) strategy parameters and constants
@@ -54,7 +54,7 @@ def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-14, stopeval=2000
     D = np.eye(N)
     C = B @ D @ (B @ D).T
     eigeneval = 0
-    chiN = np.sqrt(N) * (1 - 1/(4*N) + 1/(21 * N**2))
+    chiN = np.sqrt(N) * (1 - 1 / (4 * N) + 1 / (21 * N ** 2))
 
     # Generation Loop
     counteval = 0
@@ -91,10 +91,9 @@ def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-14, stopeval=2000
             bestEver = fbest
             noImproveGen = 0
         else:
-            noImproveGen = noImproveGen + 1
+            noImproveGen += 1
 
-
+        if gen == 1 or gen % 50 == 0:
-        if gen == 1 or gen%50==0:
             # print(f'    [CMA-ES] Gen {gen}, best = {round(fbest, 6)}, sigma = {sigma:.3g}')
             pass
 
@@ -106,13 +105,10 @@ def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-14, stopeval=2000
             # print(f'    [CMA-ES] Abbruch: sigma zu klein {sigma:.3g}')
             break
 
-
-
         # Cumulation: Update evolution paths
         ps = (1 - cs) * ps + np.sqrt(cs * (2 - cs) * mueff) * (B @ zmean)
         norm_ps = np.linalg.norm(ps)
-        hsig = norm_ps / np.sqrt(1 - (1 - cs)**(2 * counteval / lambda_)) / chiN < \
+        hsig = norm_ps / np.sqrt(1 - (1 - cs) ** (2 * counteval / lambda_)) / chiN < (1.4 + 2 / (N + 1))
-               (1.4 + 2 / (N + 1))
         hsig = 1.0 if hsig else 0.0
 
         pc = (1 - cc) * pc + hsig * np.sqrt(cc * (2 - cc) * mueff) * (B @ D @ zmean)
@@ -142,13 +138,13 @@ def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-14, stopeval=2000
         if arfitness[0] == arfitness[int(np.ceil(0.7 * lambda_)) - 1]:
             sigma = sigma * np.exp(0.2 + cs / damps)
             # print('    [CMA-ES] stopfitness erreicht.')
-            #print("warning: flat fitness, consider reformulating the objective")
+            # print("warning: flat fitness, consider reformulating the objective")
             break
 
-        #print(f"{counteval}: {arfitness[0]}")
+        # print(f"{counteval}: {arfitness[0]}")
 
-    #Final Message
+    # Final Message
-    #print(f"{counteval}: {arfitness[0]}")
+    # print(f"{counteval}: {arfitness[0]}")
     xmin = arx[:, arindex[0]]
     bestValue = arfitness[0]
     # print(f'    [CMA-ES] Ende: Gen = {gen}, best = {round(bestValue, 6)}')

ES/gha1_ES.py

@@ -1,29 +1,17 @@
 from __future__ import annotations
 
-from codeop import PyCF_ALLOW_INCOMPLETE_INPUT
+from typing import List, Tuple
-from typing import List, Optional, Tuple
+
 import numpy as np
-from ellipsoide import EllipsoidTriaxial
+from numpy.typing import NDArray
+
+import winkelumrechnungen as wu
+from ES.Hansen_ES_CMA import escma
 from GHA_triaxial.gha1_ana import gha1_ana
 from GHA_triaxial.gha1_approx import gha1_approx
-from Hansen_ES_CMA import escma
+from GHA_triaxial.utils import jacobi_konstante
+from ellipsoid_triaxial import EllipsoidTriaxial
 from utils_angle import wrap_mpi_pi
-from numpy.typing import NDArray
-import winkelumrechnungen as wu
-
-
-def ellipsoid_formparameter(ell: EllipsoidTriaxial):
-    """
-    Berechnet die Formparameter des dreiachsigen Ellipsoiden nach Karney (2025), Gl. (2)
-    :param ell: Ellipsoid
-    :return: e, k und k'
-    """
-    nenner = np.sqrt(max(ell.ax * ell.ax - ell.b * ell.b, 0.0))
-    k = np.sqrt(max(ell.ay * ell.ay - ell.b * ell.b, 0.0)) / nenner
-    k_ = np.sqrt(max(ell.ax * ell.ax - ell.ay * ell.ay, 0.0)) / nenner
-    e = np.sqrt(max(ell.ax * ell.ax - ell.b * ell.b, 0.0)) / ell.ay
-
-    return e, k, k_
 
 
 def ENU_beta_omega(beta: float, omega: float, ell: EllipsoidTriaxial) \
@@ -74,34 +62,19 @@ def ENU_beta_omega(beta: float, omega: float, ell: EllipsoidTriaxial) \
     # U = Grad(x^2/a^2 + y^2/b^2 + z^2/c^2 - 1)
     U = np.array([X/(ell.ax*ell.ax), Y/(ell.ay*ell.ay), Z/(ell.b*ell.b)], dtype=float)
 
-    En = np.linalg.norm(E)
+    En = float(np.linalg.norm(E))
-    Nn = np.linalg.norm(N)
+    Nn = float(np.linalg.norm(N))
-    Un = np.linalg.norm(U)
+    Un = float(np.linalg.norm(U))
 
     N_hat = N / Nn
     E_hat = E / En
     U_hat = U / Un
-    E_hat = E_hat - float(np.dot(E_hat, N_hat)) * N_hat
+    E_hat -= float(np.dot(E_hat, N_hat)) * N_hat
     E_hat = E_hat / max(np.linalg.norm(E_hat), 1e-18)
 
     return E_hat, N_hat, U_hat, En, Nn, R
 
 
-def jacobi_konstante(beta: float, omega: float, alpha: float, ell: EllipsoidTriaxial) -> float:
-    """
-    Jacobi-Konstante nach Karney (2025), Gl. (14)
-    :param beta: Beta Koordinate
-    :param omega: Omega Koordinate
-    :param alpha: Azimut alpha
-    :param ell: Ellipsoid
-    :return: Jacobi-Konstante
-    """
-    e, k, k_ = ellipsoid_formparameter(ell)
-    gamma_jacobi = float((k ** 2) * (np.cos(beta) ** 2) * (np.sin(alpha) ** 2) - (k_ ** 2) * (np.sin(omega) ** 2) * (np.cos(alpha) ** 2))
-
-    return gamma_jacobi
-
-
 def azimuth_at_ESpoint(P_prev: NDArray, P_curr: NDArray, E_hat_curr: NDArray, N_hat_curr: NDArray, U_hat_curr: NDArray) -> float:
     """
     Berechnet das Azimut in der lokalen Tangentialebene am aktuellen Punkt P_curr, gemessen
@@ -117,7 +90,6 @@ def azimuth_at_ESpoint(P_prev: NDArray, P_curr: NDArray, E_hat_curr: NDArray, N_
     vT = v - float(np.dot(v, U_hat_curr)) * U_hat_curr
     vTn = max(np.linalg.norm(vT), 1e-18)
     vT_hat = vT / vTn
-    #vT_hat = vT / np.linalg.norm(vT)
     sE = float(np.dot(vT_hat, E_hat_curr))
     sN = float(np.dot(vT_hat, N_hat_curr))
 
@@ -154,9 +126,8 @@ def optimize_next_point(beta_i: float, omega_i: float, alpha_i: float, ds: float
     d_beta = float(np.clip(d_beta, -0.2, 0.2))  # rad
     d_omega = float(np.clip(d_omega, -0.2, 0.2))  # rad
 
-
+    # d_beta = ds * float(np.cos(alpha_i)) / Nn_i
-    #d_beta = ds * float(np.cos(alpha_i)) / Nn_i
+    # d_omega = ds * float(np.sin(alpha_i)) / En_i
-    #d_omega = ds * float(np.sin(alpha_i)) / En_i
     beta_pred = beta_i + d_beta
     omega_pred = wrap_mpi_pi(omega_i + d_omega)
 
@@ -197,7 +168,6 @@ def optimize_next_point(beta_i: float, omega_i: float, alpha_i: float, ds: float
 
         return f
 
-
     xb = escma(fitness, N=2, xmean=xmean, sigma=sigma0)  # Aufruf CMA-ES
 
     beta_best = xb[0]
@@ -209,7 +179,7 @@ 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, all_points: boolean = False)\
+def gha1_ES(ell: EllipsoidTriaxial, beta0: float, omega0: float, alpha0: float, s_total: float, maxSegLen: float = 1000, all_points: bool = False)\
         -> Tuple[NDArray, float, NDArray] | Tuple[NDArray, float]:
     """
     Aufruf der 1. GHA mittels CMA-ES
@@ -258,8 +228,8 @@ def gha1_ES(ell: EllipsoidTriaxial, beta0: float, omega0: float, alpha0: float,
 if __name__ == "__main__":
     ell = EllipsoidTriaxial.init_name("BursaSima1980round")
     s = 180000
-    #alpha0 = 3
+    # alpha0 = 3
-    alpha0 = wu.gms2rad([5 ,0 ,0])
+    alpha0 = wu.gms2rad([5, 0, 0])
     beta = 0
     omega = 0
     P0 = ell.ell2cart(beta, omega)
@@ -272,6 +242,6 @@ if __name__ == "__main__":
     print(res)
     print(alpha)
     print(points)
-    #print("alpha1 (am Endpunkt):", res.alpha1)
+    # print("alpha1 (am Endpunkt):", res.alpha1)
     print(res - point1)
     print(point1app - point1, "approx")

ES/gha2_ES.py

@@ -1,14 +1,13 @@
-import numpy as np
-from Hansen_ES_CMA import escma
-from ellipsoide import EllipsoidTriaxial
-from numpy.typing import NDArray
 from typing import Tuple
+
+import numpy as np
 import plotly.graph_objects as go
+from numpy.typing import NDArray
+
 from GHA_triaxial.gha2_num import gha2_num
-from GHA_triaxial.utils import sigma2alpha, pq_ell
+from GHA_triaxial.utils import sigma2alpha
-
+from Hansen_ES_CMA import escma
-
+from ellipsoid_triaxial import EllipsoidTriaxial
-
 
 
 def Sehne(P1: NDArray, P2: NDArray) -> float:
@@ -19,14 +18,11 @@ def Sehne(P1: NDArray, P2: NDArray) -> float:
     :return: Bogenlänge s
     """
     R12 = P2-P1
-    s = np.linalg.norm(R12)
+    s = float(np.linalg.norm(R12))
 
     return s
 
 
-
-
-
 def gha2_ES(ell: EllipsoidTriaxial, P0: NDArray, Pk: NDArray, maxSegLen: float = None, all_points: bool = False) -> Tuple[float, float, float, NDArray] | Tuple[float, float, float]:
     """
     Berechnen der 2. GHA mithilfe der CMA-ES.

GHA_triaxial/gha1_ana.py

@@ -3,13 +3,13 @@ from math import comb
 from typing import Tuple
 
 import numpy as np
-from numpy import sin, cos, arctan2
+from numpy import arctan2, cos, sin
 from numpy.typing import NDArray
-import winkelumrechnungen as wu
-from utils_angle import wrap_0_2pi
 
-from ellipsoide import EllipsoidTriaxial
+import winkelumrechnungen as wu
 from GHA_triaxial.utils import pq_para
+from ellipsoid_triaxial import EllipsoidTriaxial
+from utils_angle import wrap_0_2pi
 
 
 def gha1_ana_step(ell: EllipsoidTriaxial, point: NDArray, alpha0: float, s: float, maxM: int) -> Tuple[NDArray, float]:
@@ -143,4 +143,3 @@ if __name__ == "__main__":
     p0 = ell.ell2cart(wu.deg2rad(10), wu.deg2rad(20))
     p1, alpha1 = gha1_ana(ell, p0, wu.deg2rad(36), 200000, 70)
     print(p1, wu.rad2gms(alpha1))
-

GHA_triaxial/gha1_approx.py

@@ -1,14 +1,18 @@
-import numpy as np
+from typing import Tuple
-from numpy import sin, cos
-from numpy.typing import NDArray
-from ellipsoide import EllipsoidTriaxial
-from GHA_triaxial.gha1_ana import gha1_ana
-from GHA_triaxial.utils import func_sigma_ell, louville_constant, pq_ell
-import plotly.graph_objects as go
-import winkelumrechnungen as wu
-from utils_angle import wrap_0_2pi, wrap_mhalfpi_halfpi, wrap_mpi_pi
 
-def gha1_approx(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: float, all_points: bool = False) -> Tuple[NDArray, float] | Tuple[NDArray, float, NDArray]:
+import numpy as np
+import plotly.graph_objects as go
+from numpy import cos, sin
+from numpy.typing import NDArray
+
+import winkelumrechnungen as wu
+from GHA_triaxial.utils import louville_constant, pq_ell
+from ellipsoid_triaxial import EllipsoidTriaxial
+from utils_angle import wrap_0_2pi
+
+
+def gha1_approx(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: float, all_points: bool = False) \
+        -> Tuple[NDArray, float] | Tuple[NDArray, float, NDArray, NDArray]:
     """
     Berechung einer Näherungslösung der ersten Hauptaufgabe
     :param ell: Ellipsoid

GHA_triaxial/gha1_num.py

@@ -1,15 +1,15 @@
+from typing import Callable, List, Tuple
+
 import numpy as np
-from numpy import sin, cos, arctan2
+from numpy import arctan2, cos, sin
-import ellipsoide
-import runge_kutta as rk
-import winkelumrechnungen as wu
-import GHA_triaxial.numeric_examples_karney as ne_karney
-from GHA_triaxial.gha1_ana import gha1_ana
-from ellipsoide import EllipsoidTriaxial
-from typing import Callable, Tuple, List
 from numpy.typing import NDArray
 
+import GHA_triaxial.numeric_examples_karney as ne_karney
+import runge_kutta as rk
+import winkelumrechnungen as wu
+from GHA_triaxial.gha1_ana import gha1_ana
 from GHA_triaxial.utils import alpha_ell2para, pq_ell
+from ellipsoid_triaxial import EllipsoidTriaxial
 from utils_angle import wrap_0_2pi
 
 
@@ -108,7 +108,7 @@ if __name__ == "__main__":
     # diffs_panou[mask_360] = np.abs(diffs_panou[mask_360] - 360)
     # print(diffs_panou)
 
-    ell: EllipsoidTriaxial = ellipsoide.EllipsoidTriaxial.init_name("KarneyTest2024")
+    ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name("KarneyTest2024")
     diffs_karney = []
     # examples_karney = ne_karney.get_examples((30499, 30500, 40500))
     examples_karney = ne_karney.get_random_examples(20)

GHA_triaxial/gha2_approx.py

@@ -1,12 +1,13 @@
-import numpy as np
-from ellipsoide import EllipsoidTriaxial
-from GHA_triaxial.gha2_num import gha2_num
-import plotly.graph_objects as go
-import winkelumrechnungen as wu
-from numpy.typing import NDArray
 from typing import Tuple
 
+import numpy as np
+import plotly.graph_objects as go
+from numpy.typing import NDArray
+
+import winkelumrechnungen as wu
+from GHA_triaxial.gha2_num import gha2_num
 from GHA_triaxial.utils import sigma2alpha
+from ellipsoid_triaxial import EllipsoidTriaxial
 
 
 def gha2_approx(ell: EllipsoidTriaxial, p0: NDArray, p1: NDArray, ds: float, all_points: bool = False) -> Tuple[float, float, float] | Tuple[float, float, float, NDArray]:

GHA_triaxial/gha2_num.py

@@ -1,13 +1,15 @@
-import numpy as np
-from ellipsoide import EllipsoidTriaxial
-from runge_kutta import rk4, rk4_step, rk4_end, rk4_integral
-import GHA_triaxial.numeric_examples_karney as ne_karney
-import GHA_triaxial.numeric_examples_panou as ne_panou
-import winkelumrechnungen as wu
 from typing import Tuple
+
+import numpy as np
 from numpy.typing import NDArray
+
 import ausgaben as aus
-from utils_angle import cot, arccot, wrap_mpi_pi, wrap_0_2pi
+import numeric_examples_karney as ne_karney
+import numeric_examples_panou as ne_panou
+import winkelumrechnungen as wu
+from ellipsoid_triaxial import EllipsoidTriaxial
+from runge_kutta import rk4, rk4_end, rk4_integral
+from utils_angle import cot, wrap_0_2pi, wrap_mpi_pi
 
 
 def norm_a(a: float) -> float:
@@ -176,7 +178,7 @@ def gha2_num(
         )
         p_00 = 0.5 * ((E * G_beta_beta - E_beta * G_beta) / (E**2))
 
-        return (BETA, LAMBDA, E, G, p_3, p_2, p_1, p_0, p_33, p_22, p_11, p_00)
+        return BETA, LAMBDA, E, G, p_3, p_2, p_1, p_0, p_33, p_22, p_11, p_00
 
     # Berechnung der ODE Koeffizienten für Fall 2 (lambda_0 == lambda_1)
     def q_coef(beta, lamb):
@@ -589,53 +591,53 @@ def gha2_num(
 
 
 if __name__ == "__main__":
-    # ell = EllipsoidTriaxial.init_name("BursaSima1980round")
+    ell = EllipsoidTriaxial.init_name("BursaSima1980round")
-    # beta1 = np.deg2rad(75)
+    beta1 = np.deg2rad(75)
-    # lamb1 = np.deg2rad(-90)
+    lamb1 = np.deg2rad(-90)
-    # beta2 = np.deg2rad(75)
+    beta2 = np.deg2rad(75)
-    # lamb2 = np.deg2rad(66)
+    lamb2 = np.deg2rad(66)
-    # a0, a1, s = gha2_num(ell, beta1, lamb1, beta2, lamb2, n=5000)
+    a0, a1, s = gha2_num(ell, beta1, lamb1, beta2, lamb2, n=100)
-    # print(aus.gms("a0", a0, 4))
+    print(aus.gms("a0", a0, 4))
-    # print(aus.gms("a1", a1, 4))
+    print(aus.gms("a1", a1, 4))
-    # print("s: ", s)
+    print("s: ", s)
-    # # print(aus.gms("a2", a2, 4))
+    # print(aus.gms("a2", a2, 4))
-    # # print(s)
-    # cart1 = ell.para2cart(0, 0)
-    # cart2 = ell.para2cart(0.4, 1.4)
-    # beta1, lamb1 = ell.cart2ell(cart1)
-    # beta2, lamb2 = ell.cart2ell(cart2)
-    #
-    # a1, a2, s = gha2_num(ell, beta1, lamb1, beta2, lamb2, n=5000)
     # print(s)
+    cart1 = ell.para2cart(0, 0)
+    cart2 = ell.para2cart(0.4, 1.4)
+    beta1, lamb1 = ell.cart2ell(cart1)
+    beta2, lamb2 = ell.cart2ell(cart2)
 
-    # ell = EllipsoidTriaxial.init_name("BursaSima1980round")
+    a1, a2, s = gha2_num(ell, beta1, lamb1, beta2, lamb2, n=5000)
-    # diffs_panou = []
+    print(s)
-    # examples_panou = ne_panou.get_random_examples(4)
+
-    # for example in examples_panou:
+    ell = EllipsoidTriaxial.init_name("BursaSima1980round")
-    #     beta0, lamb0, beta1, lamb1, _, alpha0, alpha1, s = example
+    diffs_panou = []
-    #     P0 = ell.ell2cart(beta0, lamb0)
+    examples_panou = ne_panou.get_random_examples(4)
-    #     try:
+    for example in examples_panou:
-    #         alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
+        beta0, lamb0, beta1, lamb1, _, alpha0, alpha1, s = example
-    #         diffs_panou.append(
+        P0 = ell.ell2cart(beta0, lamb0)
-    #             (wu.rad2deg(abs(alpha0 - alpha0_num)), wu.rad2deg(abs(alpha1 - alpha1_num)), abs(s - s_num)))
+        try:
-    #     except:
+            alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
-    #         print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
+            diffs_panou.append(
-    # diffs_panou = np.array(diffs_panou)
+                (wu.rad2deg(abs(alpha0 - alpha0_num)), wu.rad2deg(abs(alpha1 - alpha1_num)), abs(s - s_num)))
-    # print(diffs_panou)
+        except:
-    #
+            print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
-    # ell = EllipsoidTriaxial.init_name("KarneyTest2024")
+    diffs_panou = np.array(diffs_panou)
-    # diffs_karney = []
+    print(diffs_panou)
-    # # examples_karney = ne_karney.get_examples((30500, 40500))
+
-    # examples_karney = ne_karney.get_random_examples(2)
+    ell = EllipsoidTriaxial.init_name("KarneyTest2024")
-    # for example in examples_karney:
+    diffs_karney = []
-    #     beta0, lamb0, alpha0, beta1, lamb1, alpha1, s = example
+    # examples_karney = ne_karney.get_examples((30500, 40500))
-    #
+    examples_karney = ne_karney.get_random_examples(2)
-    #     try:
+    for example in examples_karney:
-    #         alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
+        beta0, lamb0, alpha0, beta1, lamb1, alpha1, s = example
-    #         diffs_karney.append((wu.rad2deg(abs(alpha0-alpha0_num)), wu.rad2deg(abs(alpha1-alpha1_num)), abs(s-s_num)))
+
-    #     except:
+        try:
-    #         print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
+            alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
-    # diffs_karney = np.array(diffs_karney)
+            diffs_karney.append((wu.rad2deg(abs(alpha0-alpha0_num)), wu.rad2deg(abs(alpha1-alpha1_num)), abs(s-s_num)))
-    # print(diffs_karney)
+        except:
+            print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
+    diffs_karney = np.array(diffs_karney)
+    print(diffs_karney)
 
     pass

GHA_triaxial/numeric_examples_karney.py

@@ -1,11 +1,12 @@
 import random
+from typing import List
+
 import winkelumrechnungen as wu
-from typing import List, Tuple
+from GHA_triaxial.utils import jacobi_konstante
-import numpy as np
+from ellipsoid_triaxial import EllipsoidTriaxial
-from ellipsoide import EllipsoidTriaxial
-from GHA_triaxial.gha1_ES import jacobi_konstante
 
 ell = EllipsoidTriaxial.init_name("KarneyTest2024")
+file_path = r"Karney_2024_Testset.txt"
 
 def line2example(line: str) -> List:
     """
@@ -31,7 +32,7 @@ def get_random_examples(num: int, seed: int = None) -> List:
     """
     if seed is not None:
         random.seed(seed)
-    with open(r"C:\Users\moell\OneDrive\Desktop\Vorlesungen\Master-Projekt\Python_Masterprojekt\GHA_triaxial\Karney_2024_Testset.txt") as datei:
+    with open(file_path) as datei:
         lines = datei.readlines()
     examples = []
     for i in range(num):
@@ -46,7 +47,7 @@ def get_examples(l_i: List) -> List:
     :param l_i: Liste von Indizes
     :return: Liste mit Beispielen
     """
-    with open("Karney_2024_Testset.txt") as datei:
+    with open(file_path) as datei:
         lines = datei.readlines()
     examples = []
     for i in l_i:
@@ -54,53 +55,21 @@ def get_examples(l_i: List) -> List:
         examples.append(example)
     return examples
 
-# beta0, lamb0, alpha0_ell, beta1, lamb1, alpha1_ell, s
-
-def get_random_examples_simple_short(num: int, seed: int = None) -> List:
-    if seed is not None:
-        random.seed(seed)
-    with open(r"C:\Users\moell\OneDrive\Desktop\Vorlesungen\Master-Projekt\Python_Masterprojekt\GHA_triaxial\Karney_2024_Testset.txt") as datei:
-        lines = datei.readlines()
-    examples = []
-    while len(examples) < num:
-        example = line2example(lines[random.randint(0, len(lines) - 1)])
-        beta0, lamb0, alpha0_ell, beta1, lamb1, alpha1_ell, s = example
-        if s < 1 and abs(abs(beta0) - np.pi/2) > 1e-5 and lamb0 != 0 and abs(abs(lamb0) - np.pi) > 1e-5:
-            examples.append(example)
-    return examples
-
-def get_random_examples_umbilics_start(num: int, seed: int = None) -> List:
-    if seed is not None:
-        random.seed(seed)
-    with open(r"C:\Users\moell\OneDrive\Desktop\Vorlesungen\Master-Projekt\Python_Masterprojekt\GHA_triaxial\Karney_2024_Testset.txt") as datei:
-        lines = datei.readlines()
-    examples = []
-    while len(examples) < num:
-        example = line2example(lines[random.randint(0, len(lines) - 1)])
-        beta0, lamb0, alpha0_ell, beta1, lamb1, alpha1_ell, s = example
-        if abs(abs(beta0) - np.pi/2) < 1e-5 and (lamb0 == 0 or abs(abs(lamb0) - np.pi) < 1e-5):
-            examples.append(example)
-    return examples
-
-def get_random_examples_umbilics_end(num: int, seed: int = None) -> List:
-    if seed is not None:
-        random.seed(seed)
-    with open(r"C:\Users\moell\OneDrive\Desktop\Vorlesungen\Master-Projekt\Python_Masterprojekt\GHA_triaxial\Karney_2024_Testset.txt") as datei:
-        lines = datei.readlines()
-    examples = []
-    while len(examples) < num:
-        example = line2example(lines[random.randint(0, len(lines) - 1)])
-        beta0, lamb0, alpha0_ell, beta1, lamb1, alpha1_ell, s = example
-        if abs(abs(beta1) - np.pi/2) < 1e-5 and (lamb1 == 0 or abs(abs(lamb1) - np.pi) < 1e-5):
-            examples.append(example)
-    return examples
 
 def get_random_examples_gamma(group: str, num: int, seed: int = None, length: str = None) -> List:
+    """
+    Zufällige Beispiele aus Karney in Gruppen nach Einteilung anhand der Jacobi-Konstanten
+    :param group: Gruppe
+    :param num: Anzahl
+    :param seed: Random-Seed
+    :param length: long oder short, sond egal
+    :return: Liste mit Beispielen
+    """
     eps = 1e-20
     long_short = 2
     if seed is not None:
         random.seed(seed)
-    with open(r"C:\Users\moell\OneDrive\Desktop\Vorlesungen\Master-Projekt\Python_Masterprojekt\GHA_triaxial\Karney_2024_Testset.txt") as datei:
+    with open(file_path) as datei:
         lines = datei.readlines()
     examples = []
     i = 0

GHA_triaxial/utils.py

@@ -1,11 +1,13 @@
+from __future__ import annotations
+
 from typing import Tuple
 
 import numpy as np
-from numpy import arctan2, sin, cos, sqrt
+from numpy import arctan2, cos, sin, sqrt
 from numpy.typing import NDArray
-from utils_angle import wrap_mpi_pi, wrap_0_2pi, wrap_mhalfpi_halfpi
 
-from ellipsoide import EllipsoidTriaxial
+from ellipsoid_triaxial import EllipsoidTriaxial
+from utils_angle import wrap_0_2pi
 
 
 def sigma2alpha(ell: EllipsoidTriaxial, sigma: NDArray, point: NDArray) -> float:
@@ -178,6 +180,19 @@ def pq_para(ell: EllipsoidTriaxial, point: NDArray) -> Tuple[NDArray, NDArray]:
     return p, q
 
 
+def jacobi_konstante(beta: float, omega: float, alpha: float, ell: EllipsoidTriaxial) -> float:
+    """
+    Jacobi-Konstante nach Karney (2025), Gl. (14)
+    :param beta: Beta Koordinate
+    :param omega: Omega Koordinate
+    :param alpha: Azimut alpha
+    :param ell: Ellipsoid
+    :return: Jacobi-Konstante
+    """
+    gamma_jacobi = float((ell.k ** 2) * (np.cos(beta) ** 2) * (np.sin(alpha) ** 2) - (ell.k_ ** 2) * (np.sin(omega) ** 2) * (np.cos(alpha) ** 2))
+    return gamma_jacobi
+
+
 if __name__ == "__main__":
     ell = EllipsoidTriaxial.init_name("KarneyTest2024")
     alpha_para = 0

Tests/test_biaxial.py

@@ -1,34 +0,0 @@
-import numpy as np
-from ellipsoide import EllipsoidBiaxial
-from GHA_biaxial.bessel import gha1 as gha1_bessel
-from GHA_biaxial.gauss import gha1 as gha1_gauss
-from GHA_biaxial.rk import gha1 as gha1_rk
-from GHA_biaxial.gauss import gha2 as gha2_gauss
-
-re = EllipsoidBiaxial.init_name("Bessel")
-
-# phi0 = 0.6
-# lamb0 = 1.2
-# alpha0 = 0.45
-# s = 123456
-#
-# values_bessel = gha1_bessel(re, phi0, lamb0, alpha0, s)
-# alpha1_bessel = values_bessel[-1]
-# p1_bessel = re.bi_ell2cart(values_bessel[0], values_bessel[1], 0)
-#
-# values_gauss1 = gha1_gauss(re, phi0, lamb0, alpha0, s)
-# alpha1_gauss1 = values_gauss1[-1]
-# p1_gauss = re.bi_ell2cart(values_gauss1[0], values_gauss1[1], 0)
-#
-# values_rk = gha1_rk(re, phi0, lamb0 , alpha0, s, 10000)
-# alpha1_rk = values_rk[-1]
-# p1_rk = re.bi_ell2cart(values_rk[0], values_rk[1], 0)
-#
-# alpha0_gauss, alpha1_gauss2, s_gauss = gha2_gauss(re, phi0, lamb0, values_gauss1[0], values_gauss1[1])
-
-phi0 = 0.6
-lamb0 = 1.2
-
-cart = re.bi_ell2cart(phi0, lamb0, 0)
-ell = re.bi_cart2ell(cart)
-pass

ausgaben.py

@@ -10,7 +10,7 @@ def xyz(x: float, y: float, z: float, stellen: int) -> str:
     :param stellen: Anzahl Nachkommastellen
     :return: String zur Ausgabe der Koordinaten
     """
-    return f"""x = {(round(x,stellen))} m  y = {(round(y,stellen))} m  z = {(round(z,stellen))} m"""
+    return f"""x = {(round(x, stellen))} m  y = {(round(y, stellen))} m  z = {(round(z, stellen))} m"""
 
 
 def gms(name: str, rad: float, stellen: int) -> str:
@@ -21,5 +21,5 @@ def gms(name: str, rad: float, stellen: int) -> str:
     :param stellen: Anzahl Nachkommastellen
     :return: String zur Ausgabe des Winkels
     """
-    gms = wu.rad2gms(rad)
+    values = wu.rad2gms(rad)
-    return f"{name} = {int(gms[0])}° {int(gms[1])}' {round(gms[2],stellen):.{stellen}f}''"
+    return f"{name} = {int(values[0])}° {int(values[1])}' {round(values[2], stellen):.{stellen}f}''"

dashboard.py

@@ -1,34 +1,31 @@
-from dash import Dash, dash, html, dcc, Input, Output, State, no_update, ctx
-import plotly.graph_objects as go
-import numpy as np
-import dash_bootstrap_components as dbc
-
 import builtins
-from dash.exceptions import PreventUpdate
 import traceback
 
-import webbrowser
+import dash_bootstrap_components as dbc
-from threading import Timer
+import numpy as np
+import plotly.graph_objects as go
+from dash import Dash, Input, Output, State, dcc, html, no_update
+from dash.exceptions import PreventUpdate
+from numpy import pi
 
-from ellipsoide import EllipsoidTriaxial
-import winkelumrechnungen as wu
 import ausgaben as aus
-from GHA_triaxial.utils import alpha_ell2para, alpha_para2ell
+import winkelumrechnungen as wu
-
+from ES.gha1_ES import gha1_ES
+from ES.gha2_ES import gha2_ES
 from GHA_triaxial.gha1_ana import gha1_ana
-from GHA_triaxial.gha1_num import gha1_num
-from GHA_triaxial.gha1_ES import gha1_ES
 from GHA_triaxial.gha1_approx import gha1_approx
-
+from GHA_triaxial.gha1_num import gha1_num
-from GHA_triaxial.gha2_num import gha2_num
-from GHA_triaxial.gha2_ES import gha2_ES
 from GHA_triaxial.gha2_approx import gha2_approx
+from GHA_triaxial.gha2_num import gha2_num
+from GHA_triaxial.utils import alpha_ell2para, alpha_para2ell
+from ellipsoid_triaxial import EllipsoidTriaxial
 
 
 # Prints von importierten Funktionen unterdücken
 def _no_print(*args, **kwargs):
     pass
 
+
 builtins.print = _no_print
 
 
@@ -39,7 +36,7 @@ app.title = "Geodätische Hauptaufgaben"
 
 
 # Erzeugen der Eingabefelder
-def inputfeld(left_text, input_id, right_text="", width=200, min=None, max=None):
+def inputfeld(left_text, input_id, right_text="", width=200, mini=None, maxi=None):
     return html.Div(
         children=[
             html.Span(f"{left_text} =", style={"minWidth": 36, "textAlign": "right", "marginRight": 5}),
@@ -142,7 +139,7 @@ def method_failed(method_label: str, exc: Exception):
     return html.Div([
         html.Strong(f"{method_label}: "),
         html.Span("konnte nicht berechnet werden. ", style={"color": "red"}),
-        #html.Span(f"({type(exc).__name__}: {exc})", style={"color": "#b02a37"}),
+        # html.Span(f"({type(exc).__name__}: {exc})", style={"color": "#b02a37"}),
 
         html.Details([
             html.Summary("Details"),
@@ -177,7 +174,7 @@ def ellipsoid_figure(ell: EllipsoidTriaxial, title="Dreiachsiges Ellipsoid"):
         scene=dict(
             xaxis=dict(
                 range=[-rx, rx],
-                #title="X [m]",
+                # title="X [m]",
                 title="",
                 showgrid=False,
                 zeroline=False,
@@ -186,7 +183,7 @@ def ellipsoid_figure(ell: EllipsoidTriaxial, title="Dreiachsiges Ellipsoid"):
             ),
             yaxis=dict(
                 range=[-ry, ry],
-                #title="Y [m]",
+                # title="Y [m]",
                 title="",
                 showgrid=False,
                 zeroline=False,
@@ -195,7 +192,7 @@ def ellipsoid_figure(ell: EllipsoidTriaxial, title="Dreiachsiges Ellipsoid"):
             ),
             zaxis=dict(
                 range=[-rz, rz],
-                #title="Z [m]",
+                # title="Z [m]",
                 title="",
                 showgrid=False,
                 zeroline=False,
@@ -209,8 +206,8 @@ def ellipsoid_figure(ell: EllipsoidTriaxial, title="Dreiachsiges Ellipsoid"):
     )
 
     # Ellipsoid
-    u = np.linspace(-np.pi/2, np.pi/2, 80)
+    u = np.linspace(-pi/2, pi/2, 80)
-    v = np.linspace(-np.pi,     np.pi,   160)
+    v = np.linspace(-pi,     pi,   160)
     U, V = np.meshgrid(u, v)
     X, Y, Z = ell.para2cart(U, V)
     fig.add_trace(go.Surface(
@@ -260,7 +257,7 @@ def figure_constant_lines(fig, ell: EllipsoidTriaxial, coordsystem: str = "para"
         all_beta[-1] -= 1e-8
         constants_lamb = wu.deg2rad(np.arange(-180, 180, 15))
         for lamb in constants_lamb:
-            if lamb != 0 and abs(lamb) != np.pi:
+            if lamb != 0 and abs(lamb) != pi:
                 xyz = ell.ell2cart(all_beta, lamb)
                 fig.add_trace(go.Scatter3d(
                     x=xyz[:, 0], y=xyz[:, 1], z=xyz[:, 2], mode="lines",
@@ -335,8 +332,10 @@ def figure_lines(fig, line, name, color):
     ))
     return fig
 
+
 # HTML der beiden Tabs
 # Tab 1
+
 pane_gha1 = html.Div(
     [
         html.Div(
@@ -468,7 +467,7 @@ app.layout = html.Div(
     style={"fontFamily": "Arial", "padding": "10px", "width": "95%", "margin": "0 auto"},
     children=[
         html.H2("Geodätische Hauptaufgaben für dreiachsige Ellipsoide"),
-        #html.H2("für dreiachsige Ellipsoide"),
+        # html.H2("für dreiachsige Ellipsoide"),
 
         html.Div(
             style={
@@ -507,9 +506,9 @@ app.layout = html.Div(
 
                         html.Div(
                             [
-                                inputfeld("aₓ", "input-ax", "m", min=0, width="clamp(80px, 7vw, 200px)"),
+                                inputfeld("aₓ", "input-ax", "m", mini=0, width="clamp(80px, 7vw, 200px)"),
-                                inputfeld("aᵧ", "input-ay", "m", min=0, width="clamp(80px, 7vw, 200px)"),
+                                inputfeld("aᵧ", "input-ay", "m", mini=0, width="clamp(80px, 7vw, 200px)"),
-                                inputfeld("b", "input-b", "m", min=0, width="clamp(80px, 7vw, 200px)"),
+                                inputfeld("b", "input-b", "m", mini=0, width="clamp(80px, 7vw, 200px)"),
                             ],
                             style={
                                 "display": "grid",
@@ -520,7 +519,7 @@ app.layout = html.Div(
                             },
                         ),
 
-                        #html.Br(),
+                        # html.Br(),
 
                         dcc.Tabs(
                             id="tabs-GHA",
@@ -572,7 +571,7 @@ app.layout = html.Div(
         dcc.Store(id="calc-token-gha1", data=0),
         dcc.Store(id="calc-token-gha2", data=0),
 
-        #html.P("© 2026", style={"fontSize": "10px", "color": "gray", "textAlign": "center", "marginTop": "16px"}),
+        # html.P("© 2026", style={"fontSize": "10px", "color": "gray", "textAlign": "center", "marginTop": "16px"}),
     ],
 
 
@@ -662,10 +661,8 @@ def toggle_ds(v):
     return "on" not in (v or [])
 
 
-
 # Abfrage ob Berechnungsverfahren gewählt
-from dash.exceptions import PreventUpdate
+
-from dash import no_update, html
 
 @app.callback(
     Output("calc-token-gha1", "data"),
@@ -974,7 +971,6 @@ def compute_gha1_num(n1, cb_num, n_in, beta0, lamb0, s, a0, ax, ay, b):
         alpha_rad = wu.deg2rad(float(a0))
         s_val = float(s)
 
-
         P0 = ell.ell2cart(beta_rad, lamb_rad)
 
         P1_num, alpha1, werte = gha1_num(ell, P0, alpha_rad, s_val, n_in, all_points=True)
@@ -1402,7 +1398,7 @@ def clear_all_stores_on_ellipsoid_change(ax, ay, b):
     if None in (ax, ay, b):
         return (no_update,)*7
 
-    return (None, None, None, None, None, None, None)
+    return None, None, None, None, None, None, None
 
 # Funktionen zur Erzeugung der Überschriften
 @app.callback(
@@ -1483,6 +1479,6 @@ if __name__ == "__main__":
     # Automatisiertes Öffnen der Seite im Browser
     HOST = "127.0.0.1"
     PORT = 8050
-    #Timer(1.0, webbrowser.open_new_tab(f"http://{HOST}:{PORT}/")).start
+    # Timer(1.0, webbrowser.open_new_tab(f"http://{HOST}:{PORT}/")).start
 
     app.run(host=HOST, port=PORT, debug=False)

ellipsoid_triaxial.py

@@ -1,117 +1,20 @@
-import numpy as np
-from numpy import sin, cos, arctan, arctan2, sqrt, pi, arccos
-import winkelumrechnungen as wu
-import jacobian_Ligas
-import matplotlib.pyplot as plt
-from typing import Tuple
-from numpy.typing import NDArray
 import math
-from utils_angle import wrap_mpi_pi, wrap_0_2pi, wrap_mhalfpi_halfpi
+from typing import Tuple
 
+import numpy as np
+from numpy import arccos, arctan, arctan2, cos, pi, sin, sqrt
+from numpy.typing import NDArray
 
-class EllipsoidBiaxial:
+import jacobian_Ligas
-    def __init__(self, a: float, b: float):
+from utils_angle import wrap_mhalfpi_halfpi, wrap_mpi_pi
-        self.a = a
-        self.b = b
-        self.c = a ** 2 / b
-        self.e = sqrt(a ** 2 - b ** 2) / a
-        self.e_ = sqrt(a ** 2 - b ** 2) / b
 
-    @classmethod
-    def init_name(cls, name: str):
-        if name == "Bessel":
-            a = 6377397.15508
-            b = 6356078.96290
-            return cls(a, b)
-        elif name == "Hayford":
-            a = 6378388
-            f = 1/297
-            b = a - a * f
-            return cls(a, b)
-        elif name == "Krassowski":
-            a = 6378245
-            f = 298.3
-            b = a - a * f
-            return cls(a, b)
-        elif name == "WGS84":
-            a = 6378137
-            f = 298.257223563
-            b = a - a * f
-            return cls(a, b)
-
-    @classmethod
-    def init_af(cls, a: float, f: float):
-        b = a - a * f
-        return cls(a, b)
-
-    V = lambda self, phi: sqrt(1 + self.e_ ** 2 * cos(phi) ** 2)
-    M = lambda self, phi: self.c / self.V(phi) ** 3
-    N = lambda self, phi: self.c / self.V(phi)
-
-    beta2psi = lambda self, beta: np.arctan2(self.a * np.sin(beta), self.b * np.cos(beta))
-    beta2phi = lambda self, beta: np.arctan2(self.a ** 2 * np.sin(beta), self.b ** 2 * np.cos(beta))
-
-    psi2beta = lambda self, psi: np.arctan2(self.b * np.sin(psi), self.a * np.cos(psi))
-    psi2phi = lambda self, psi: np.arctan2(self.a * np.sin(psi), self.b * np.cos(psi))
-
-    phi2beta = lambda self, phi: np.arctan2(self.b**2 * np.sin(phi), self.a**2 * np.cos(phi))
-    phi2psi = lambda self, phi: np.arctan2(self.b * np.sin(phi), self.a * np.cos(phi))
-
-    phi2p = lambda self, phi: self.N(phi) * cos(phi)
-
-    def bi_cart2ell(self, point: NDArray, Eh: float = 0.001, Ephi: float = wu.gms2rad([0, 0, 0.001])) -> Tuple[float, float, float]:
-        """
-        Umrechnung von kartesischen in ellipsoidische Koordinaten auf einem Rotationsellipsoid
-        # TODO: Quelle
-        :param point: Punkt in kartesischen Koordinaten
-        :param Eh: Grenzwert für die Höhe
-        :param Ephi: Grenzwert für die Breite
-        :return: ellipsoidische Breite, Länge, geodätische Höhe
-        """
-        x, y, z = point
-
-        lamb = arctan2(y, x)
-
-        p = sqrt(x**2+y**2)
-
-        phi_null = arctan2(z, p*(1 - self.e**2))
-
-        hi = [0]
-        phii = [phi_null]
-
-        i = 0
-
-        while True:
-            N = self.a / sqrt(1 - self.e**2 * sin(phii[i])**2)
-            h = p / cos(phii[i]) - N
-            phi = arctan2(z,  p * (1-(self.e**2*N) / (N+h)))
-            hi.append(h)
-            phii.append(phi)
-            dh = abs(hi[i]-h)
-            dphi = abs(phii[i]-phi)
-            i = i+1
-            if dh < Eh:
-                if dphi < Ephi:
-                    break
-        return phi, lamb, h
-
-    def bi_ell2cart(self, phi: float, lamb: float, h: float) -> NDArray:
-        """
-        Umrechnung von ellipsoidischen in kartesische Koordinaten auf einem Rotationsellipsoid
-        # TODO: Quelle
-        :param phi: ellipsoidische Breite
-        :param lamb: ellipsoidische Länge
-        :param h: geodätische Höhe
-        :return: Punkt in kartesischen Koordinaten
-        """
-        W = sqrt(1 - self.e**2 * sin(phi)**2)
-        N = self.a / W
-        x = (N+h) * cos(phi) * cos(lamb)
-        y = (N+h) * cos(phi) * sin(lamb)
-        z = (N * (1-self.e**2) + h) * sin(phi)
-        return np.array([x, y, z])
 
 class EllipsoidTriaxial:
+    """
+    Klasse für dreiachsige Ellipsoide
+    Parameter: Formparameter
+    Funktionen: Koordinatenumrechnungen
+    """
     def __init__(self, ax: float, ay: float, b: float):
         self.ax = ax
         self.ay = ay
@@ -125,14 +28,19 @@ class EllipsoidTriaxial:
         self.Ex = sqrt(self.ax**2 - self.b**2)
         self.Ey = sqrt(self.ay**2 - self.b**2)
         self.Ee = sqrt(self.ax**2 - self.ay**2)
+        nenner = sqrt(max(self.ax * self.ax - self.b * self.b, 0.0))
+        self.k = sqrt(max(self.ay * self.ay - self.b * self.b, 0.0)) / nenner
+        self.k_ = sqrt(max(self.ax * self.ax - self.ay * self.ay, 0.0)) / nenner
+        self.e = sqrt(max(self.ax * self.ax - self.b * self.b, 0.0)) / self.ay
 
     @classmethod
-    def init_name(cls, name: str):
+    def init_name(cls, name: str) -> EllipsoidTriaxial:
         """
-        Mögliche Ellipsoide: BursaFialova1993, BursaSima1980, BursaSima1980round, Eitschberger1978, Bursa1972,
+        Mögliche Ellipsoide: BursaSima1980round, KarneyTest2024, Fiction, BursaFialova1993, BursaSima1980, Eitschberger1978, Bursa1972,
-        Bursa1970, BesselBiaxial, Fiction, KarneyTest2024
+        Bursa1970
         Panou et al (2020)
         :param name: Name des dreiachsigen Ellipsoids
+        :return: dreiachsiger Ellipsoid
         """
         if name == "BursaFialova1993":
             ax = 6378171.36
@@ -165,11 +73,6 @@ class EllipsoidTriaxial:
             ay = 6378105
             b = 6356754
             return cls(ax, ay, b)
-        elif name == "BesselBiaxial":
-            ax = 6377397.15509
-            ay = 6377397.15508
-            b = 6356078.96290
-            return cls(ax, ay, b)
         elif name == "Fiction":
             ax = 6000000
             ay = 4000000
@@ -180,6 +83,8 @@ class EllipsoidTriaxial:
             ay = 1
             b = 1 / sqrt(2)
             return cls(ax, ay, b)
+        else:
+            raise Exception(f"EllipsoidTriaxial.init_name: Name {name} unbekannt")
 
     def func_H(self, point: NDArray) -> float:
         """
@@ -220,7 +125,6 @@ class EllipsoidTriaxial:
               (self.ay ** 2 + self.b ** 2) * x ** 2 - (self.ax ** 2 + self.b ** 2) * y ** 2 - (
                       self.ax ** 2 + self.ay ** 2) * z ** 2)
         if c1 ** 2 - 4 * c0 < -1e-9:
-            t2 = np.nan
             raise Exception("t1, t2: Negativer Wurzelterm")
         elif c1 ** 2 - 4 * c0 < 0:
             t2 = 0
@@ -265,7 +169,6 @@ class EllipsoidTriaxial:
         s1 = 2 * sqrt(p) * cos(omega/3) - c2/3
         s2 = 2 * sqrt(p) * cos(omega/3 - 2*pi/3) - c2/3
         s3 = 2 * sqrt(p) * cos(omega/3 - 4*pi/3) - c2/3
-        # print(s1, s2, s3)
 
         beta = arctan(sqrt((-self.b**2 - s2) / (self.ay**2 + s2)))
         if abs((-self.ay**2 - s3) / (self.ax**2 + s3)) > 1e-7:
@@ -289,7 +192,7 @@ class EllipsoidTriaxial:
         beta, lamb = np.broadcast_arrays(beta, lamb)
 
         beta = np.where(
-            np.isclose(np.abs(beta), np.pi / 2, atol=1e-15),
+            np.isclose(np.abs(beta), pi / 2, atol=1e-15),
             beta * 8999999999999999 / 9000000000000000,
             beta
         )
@@ -586,6 +489,8 @@ class EllipsoidTriaxial:
                 invJ, fxE = jacobian_Ligas.case2(E, F, G, np.array([xG, yG, zG]), pE)
             elif mode == "ligas3":
                 invJ, fxE = jacobian_Ligas.case3(E, F, G, np.array([xG, yG, zG]), pE)
+            else:
+                raise Exception(f"cart2geod: Modus {mode} nicht bekannt")
             pEi = pE.reshape(-1, 1) - invJ @ fxE.reshape(-1, 1)
             pEi = pEi.reshape(1, -1).flatten()
             loa = sqrt((pEi[0]-pE[0])**2 + (pEi[1]-pE[1])**2 + (pEi[2]-pE[2])**2)
@@ -607,10 +512,10 @@ class EllipsoidTriaxial:
                 phi, lamb, h = self.cart2geod(point, f"ligas{new_mode}", maxIter, maxLoa)
             else:
                 if xG < 0 and yG < 0:
-                    lamb = -pi + lamb
+                    lamb += -pi
 
                 elif xG < 0:
-                    lamb = pi + lamb
+                    lamb += pi
 
                 if abs(zG) < eps:
                     phi = 0
@@ -759,11 +664,11 @@ class EllipsoidTriaxial:
 
 if __name__ == "__main__":
     ell = EllipsoidTriaxial.init_name("KarneyTest2024")
-    # cart = ell.ell2cart(np.pi/2, 0)
+    # cart = ell.ell2cart(pi/2, 0)
     # print(cart)
-    # cart = ell.ell2cart(np.pi/2*8999999999999999/9000000000000000, 0)
+    # cart = ell.ell2cart(pi/2*8999999999999999/9000000000000000, 0)
     # print(cart)
-    elli = ell.cart2ell([0, 0.0, 1/np.sqrt(2)])
+    elli = ell.cart2ell(np.array([0, 0.0, 1/sqrt(2)]))
     print(elli)
 
     # ell = EllipsoidTriaxial.init_name("BursaSima1980")

jacobian_Ligas.py

@@ -1,6 +1,8 @@
+from typing import Tuple
+
 import numpy as np
 from numpy.typing import NDArray
-from typing import Tuple
+
 
 def case1(E: float, F: float, G: float, pG: NDArray, pE: NDArray) -> Tuple[NDArray, NDArray]:
     """
@@ -34,7 +36,7 @@ def case1(E: float, F: float, G: float, pG: NDArray, pE: NDArray) -> Tuple[NDArr
 
     return invJ, fxE
 
-def case2(E: float, F: float, G: float, pG: np.ndarray, pE: np.ndarray) -> Tuple[NDArray, NDArray]:
+def case2(E: float, F: float, G: float, pG: NDArray, pE: NDArray) -> Tuple[NDArray, NDArray]:
     """
     Aufstellen des Gleichungssystem für den zweiten Fall
     :param E: Konstante E
@@ -68,7 +70,7 @@ def case2(E: float, F: float, G: float, pG: np.ndarray, pE: np.ndarray) -> Tuple
 
     return invJ, fxE
 
-def case3(E: float, F: float, G: float, pG: np.ndarray, pE: np.ndarray) -> Tuple[NDArray, NDArray]:
+def case3(E: float, F: float, G: float, pG: NDArray, pE: NDArray) -> Tuple[NDArray, NDArray]:
     """
     Aufstellen des Gleichungssystem für den dritten Fall
     :param E: Konstante E

nicht abgeben/GHA_biaxial/bessel.py

@@ -1,10 +1,20 @@
-from numpy import *
-import scipy as sp
-from ellipsoide import EllipsoidBiaxial
 from typing import Tuple
 
+import scipy as sp
+from ellipsoid_biaxial import EllipsoidBiaxial
+from numpy import *
+
 
 def gha1(re: EllipsoidBiaxial, phi0: float, lamb0: float, alpha0:float, s: float) -> Tuple[float, float, float]:
+    """
+    Berechnung der 1.GHA auf einem Rotationsellipsoid nach Bessel
+    :param re:
+    :param phi0:
+    :param lamb0:
+    :param alpha0:
+    :param s:
+    :return:
+    """
     psi0 = re.phi2psi(phi0)
     clairant = arcsin(cos(psi0) * sin(alpha0))
     sigma0 = arcsin(sin(psi0) / cos(clairant))

nicht abgeben/GHA_biaxial/gauss.py

@@ -1,8 +1,8 @@
-from numpy import sin, cos, pi, sqrt, tan, arcsin, arccos, arctan
-import ausgaben as aus
-from ellipsoide import EllipsoidBiaxial
 from typing import Tuple
 
+from ellipsoid_biaxial import EllipsoidBiaxial
+from numpy import arctan, cos, sin, sqrt, tan
+
 
 def gha1(re: EllipsoidBiaxial, phi0: float, lamb0: float, alpha0: float, s: float, eps: float = 1e-12) -> Tuple[float, float, float]:
     """

nicht abgeben/GHA_biaxial/rk.py

@@ -1,13 +1,26 @@
-import runge_kutta as rk
+from typing import Tuple
-from numpy import sin, cos, tan
+
-import winkelumrechnungen as wu
-from ellipsoide import EllipsoidBiaxial
 import numpy as np
+from ellipsoid_biaxial import EllipsoidBiaxial
+from numpy import cos, sin, tan
 from numpy.typing import NDArray
 
+import runge_kutta as rk
+
+
 def gha1(re: EllipsoidBiaxial, phi0: float, lamb0: float, alpha0: float, s: float, num: int) -> Tuple[float, float, float]:
+    """
+    Berechnung der 1. GHA auf einem Rotationsellipsoid mittels RK4
+    :param re:
+    :param phi0:
+    :param lamb0:
+    :param alpha0:
+    :param s:
+    :param num:
+    :return:
+    """
     def buildODE():
-        def ODE(s, v):
+        def ODE(s: float, v: NDArray):
             phi, lam, A = v
             V = re.V(phi)
             dphi = cos(A) * V ** 3 / re.c

nicht abgeben/Tests/alpha_conversion_test.ipynb

@@ -17,10 +17,11 @@
    "source": [
     "%reload_ext autoreload\n",
     "%autoreload 2\n",
+    "import numpy as np\n",
+    "\n",
     "import winkelumrechnungen as wu\n",
-    "from ellipsoide import EllipsoidTriaxial\n",
+    "from GHA_triaxial.utils import alpha_ell2para, alpha_para2ell\n",
-    "from GHA_triaxial.utils import alpha_para2ell, alpha_ell2para\n",
+    "from ellipsoid_triaxial import EllipsoidTriaxial"
-    "import numpy as np"
    ],
    "id": "46aa84a937fea491",
    "outputs": [],

nicht abgeben/Tests/conversions_test.ipynb

@@ -20,13 +20,14 @@
    "source": [
     "%reload_ext autoreload\n",
     "%autoreload 2\n",
-    "import pickle\n",
-    "import numpy as np\n",
-    "import winkelumrechnungen as wu\n",
     "from itertools import product\n",
+    "\n",
+    "import numpy as np\n",
     "import pandas as pd\n",
-    "from ellipsoide import EllipsoidTriaxial\n",
+    "import plotly.graph_objects as go\n",
-    "import plotly.graph_objects as go"
+    "\n",
+    "import winkelumrechnungen as wu\n",
+    "from ellipsoid_triaxial import EllipsoidTriaxial"
    ],
    "outputs": [],
    "execution_count": null

nicht abgeben/ellipsoid_biaxial.py

@@ -0,0 +1,126 @@
+from typing import Tuple
+
+import numpy as np
+from numpy import arctan2, cos, sin, sqrt
+from numpy.typing import NDArray
+
+import winkelumrechnungen as wu
+
+
+class EllipsoidBiaxial:
+    """
+    Klasse für Rotationsellipdoide
+    """
+    def __init__(self, a: float, b: float):
+        self.a = a
+        self.b = b
+        self.c = a ** 2 / b
+        self.e = sqrt(a ** 2 - b ** 2) / a
+        self.e_ = sqrt(a ** 2 - b ** 2) / b
+
+    @classmethod
+    def init_name(cls, name: str) -> EllipsoidBiaxial:
+        """
+        Erstellen eines Rotationsellipdoids nach Namen
+        :param name: Name des Rotationsellipsoids
+        :return: Rotationsellipsoid
+        """
+        if name == "Bessel":
+            a = 6377397.15508
+            b = 6356078.96290
+            return cls(a, b)
+        elif name == "Hayford":
+            a = 6378388
+            f = 1/297
+            b = a - a * f
+            return cls(a, b)
+        elif name == "Krassowski":
+            a = 6378245
+            f = 298.3
+            b = a - a * f
+            return cls(a, b)
+        elif name == "WGS84":
+            a = 6378137
+            f = 298.257223563
+            b = a - a * f
+            return cls(a, b)
+        else:
+            raise Exception(f"EllipsoidBiaxial.init_name: Name {name} unbekannt")
+
+    @classmethod
+    def init_af(cls, a: float, f: float) -> EllipsoidBiaxial:
+        """
+        Erstellen eines Rotationsellipdoids aus der großen Halbachse und der Abplattung
+        :param a: große Halbachse
+        :param f: großen Halbachse
+        :return: Rotationsellipsoid
+        """
+        b = a - a * f
+        return cls(a, b)
+
+    V = lambda self, phi: sqrt(1 + self.e_ ** 2 * cos(phi) ** 2)
+    M = lambda self, phi: self.c / self.V(phi) ** 3
+    N = lambda self, phi: self.c / self.V(phi)
+
+    beta2psi = lambda self, beta: arctan2(self.a * sin(beta), self.b * cos(beta))
+    beta2phi = lambda self, beta: arctan2(self.a ** 2 * sin(beta), self.b ** 2 * cos(beta))
+
+    psi2beta = lambda self, psi: arctan2(self.b * sin(psi), self.a * cos(psi))
+    psi2phi = lambda self, psi: arctan2(self.a * sin(psi), self.b * cos(psi))
+
+    phi2beta = lambda self, phi: arctan2(self.b**2 * sin(phi), self.a**2 * cos(phi))
+    phi2psi = lambda self, phi: arctan2(self.b * sin(phi), self.a * cos(phi))
+
+    phi2p = lambda self, phi: self.N(phi) * cos(phi)
+
+    def bi_cart2ell(self, point: NDArray, Eh: float = 0.001, Ephi: float = wu.gms2rad([0, 0, 0.001])) -> Tuple[float, float, float]:
+        """
+        Umrechnung von kartesischen in ellipsoidische Koordinaten auf einem Rotationsellipsoid
+        # TODO: Quelle
+        :param point: Punkt in kartesischen Koordinaten
+        :param Eh: Grenzwert für die Höhe
+        :param Ephi: Grenzwert für die Breite
+        :return: ellipsoidische Breite, Länge, geodätische Höhe
+        """
+        x, y, z = point
+
+        lamb = arctan2(y, x)
+
+        p = sqrt(x**2+y**2)
+
+        phi_null = arctan2(z, p*(1 - self.e**2))
+
+        hi = [0]
+        phii = [phi_null]
+
+        i = 0
+
+        while True:
+            N = self.a / sqrt(1 - self.e**2 * sin(phii[i])**2)
+            h = p / cos(phii[i]) - N
+            phi = arctan2(z,  p * (1-(self.e**2*N) / (N+h)))
+            hi.append(h)
+            phii.append(phi)
+            dh = abs(hi[i]-h)
+            dphi = abs(phii[i]-phi)
+            i += 1
+            if dh < Eh:
+                if dphi < Ephi:
+                    break
+        return phi, lamb, h
+
+    def bi_ell2cart(self, phi: float, lamb: float, h: float) -> NDArray:
+        """
+        Umrechnung von ellipsoidischen in kartesische Koordinaten auf einem Rotationsellipsoid
+        # TODO: Quelle
+        :param phi: ellipsoidische Breite
+        :param lamb: ellipsoidische Länge
+        :param h: geodätische Höhe
+        :return: Punkt in kartesischen Koordinaten
+        """
+        W = sqrt(1 - self.e**2 * sin(phi)**2)
+        N = self.a / W
+        x = (N+h) * cos(phi) * cos(lamb)
+        y = (N+h) * cos(phi) * sin(lamb)
+        z = (N * (1-self.e**2) + h) * sin(phi)
+        return np.array([x, y, z])

nicht abgeben/kugel.py

@@ -1,7 +1,9 @@
-import numpy as np
-from numpy import sqrt, arctan2, sin, cos, arcsin, arccos
-from numpy.typing import NDArray
 from typing import Tuple
+
+import numpy as np
+from numpy import arccos, arcsin, arctan2, cos, pi, sin, sqrt
+from numpy.typing import NDArray
+
 import winkelumrechnungen as wu
 
 
@@ -77,7 +79,7 @@ def gha2(R: float, phi0: float, lamb0: float, phi1: float, lamb1: float) -> Tupl
     alpha1 = arctan2(-cos(phi0) * sin(lamb1 - lamb0),
                      cos(phi1) * sin(phi0) - sin(phi1) * cos(phi0) * cos(lamb1 - lamb0))
     if alpha1 < 0:
-        alpha1 += 2 * np.pi
+        alpha1 += 2 * pi
 
     return alpha0, alpha1, s
 

nicht abgeben/plots.ipynb

@@ -9,10 +9,11 @@
    },
    "cell_type": "code",
    "source": [
-    "import plotly.graph_objects as go\n",
     "import numpy as np\n",
-    "from ellipsoide import EllipsoidTriaxial\n",
+    "import plotly.graph_objects as go\n",
-    "import winkelumrechnungen as wu"
+    "\n",
+    "import winkelumrechnungen as wu\n",
+    "from ellipsoid_triaxial import EllipsoidTriaxial"
    ],
    "id": "731173e4745cfe7c",
    "outputs": [],

nicht abgeben/test.py

@@ -0,0 +1,8 @@
+import numpy as np
+
+import ellipsoid_triaxial
+
+ell = ellipsoid_triaxial.EllipsoidTriaxial.init_name("KarneyTest2024")
+
+cart = ell.para2cart(0, np.pi/2)
+print(cart)

requirements.txt

@@ -0,0 +1,7 @@
+numpy~=2.3.4
+plotly~=6.4.0
+pandas~=2.3.3
+scipy~=1.16.3
+dash-bootstrap-components~=2.0.4
+dash~=4.0.0
+matplotlib~=3.10.7

runge_kutta.py

@@ -1,7 +1,10 @@
+from typing import Callable
+
 import numpy as np
+from numpy.typing import NDArray
 
 
-def rk4(ode, t0: float, v0: np.ndarray, weite: float, schritte: int, fein: bool = False) -> tuple[list, list]:
+def rk4(ode: Callable, t0: float, v0: NDArray, weite: float, schritte: int, fein: bool = False) -> tuple[list, list]:
     """
     Standard Runge-Kutta Verfahren 4. Ordnung
     :param ode: ODE-System als Funktion
@@ -9,7 +12,7 @@ def rk4(ode, t0: float, v0: np.ndarray, weite: float, schritte: int, fein: bool
     :param v0: Startwerte
     :param weite: Integrationsweite
     :param schritte: Schrittzahl
-    :param fein:
+    :param fein: Fein-Rechnung?
     :return: Variable und Funktionswerte an jedem Stützpunkt
     """
     h = weite/schritte
@@ -35,14 +38,32 @@ def rk4(ode, t0: float, v0: np.ndarray, weite: float, schritte: int, fein: bool
 
     return t_list, werte
 
-def rk4_step(ode, t: float, v: np.ndarray, h: float) -> np.ndarray:
+def rk4_step(ode: Callable, t: float, v: NDArray, h: float) -> NDArray:
+    """
+    Ein Schritt des Runge-Kutta Verfahrens 4. Ordnung
+    :param ode: ODE-System als Funktion
+    :param t: unabhängige Variable
+    :param v: abhängige Variablen
+    :param h: Schrittweite
+    :return: abhängige Variablen nach einem Schritt
+    """
     k1 = ode(t, v)
     k2 = ode(t + 0.5 * h, v + 0.5 * h * k1)
     k3 = ode(t + 0.5 * h, v + 0.5 * h * k2)
     k4 = ode(t + h, v + h * k3)
     return v + (h / 6.0) * (k1 + 2 * k2 + 2 * k3 + k4)
 
-def rk4_end(ode, t0: float, v0: np.ndarray, weite: float, schritte: int, fein: bool = False):
+def rk4_end(ode: Callable, t0: float, v0: NDArray, weite: float, schritte: int, fein: bool = False):
+    """
+    Standard Runge-Kutta Verfahren 4. Ordnung, nur Ausgabe der letzten Variablenwerte
+    :param ode: ODE-System als Funktion
+    :param t0: Startwert der unabhängigen Variable
+    :param v0: Startwerte
+    :param weite: Integrationsweite
+    :param schritte: Schrittzahl
+    :param fein: Fein-Rechnung?
+    :return: Variable und Funktionswerte am letzten Stützpunkt
+    """
     h = weite / schritte
     t = float(t0)
     v = np.array(v0, dtype=float, copy=True)
@@ -62,8 +83,19 @@ def rk4_end(ode, t0: float, v0: np.ndarray, weite: float, schritte: int, fein: b
     return t, v
 
 # RK4 mit Simpson bzw. Trapez
-def rk4_integral( ode, t0: float, v0: np.ndarray, weite: float, schritte: int, integrand_at, fein: bool = False, simpson: bool = True, ):
+def rk4_integral(ode: Callable, t0: float, v0: NDArray, weite: float, schritte: int, integrand_at: Callable, fein: bool = False, simpson: bool = True):
-
+    """
+    Runge-Kutta Verfahren 4. Ordnung mit Simpson bzw. Trapez
+    :param ode: ODE-System als Funktion
+    :param t0: Startwert der unabhängigen Variable
+    :param v0: Startwerte
+    :param weite: Integrationsweite
+    :param integrand_at: Funktion
+    :param schritte: Schrittzahl
+    :param fein: Fein-Rechnung?
+    :param simpson: Simpson? Wenn nein, dann Trapez
+    :return: Variable und Funktionswerte am letzten Stützpunkt
+    """
     h = weite / schritte
     habs = abs(h)
 

test.py

@@ -1,7 +0,0 @@
-import numpy as np
-import ellipsoide
-
-ell = ellipsoide.EllipsoidTriaxial.init_name("KarneyTest2024")
-
-cart = ell.para2cart(0, np.pi/2)
-print(cart)

utils_angle.py

@@ -1,24 +1,50 @@
 import numpy as np
+
 import winkelumrechnungen as wu
 
 
-def arccot(x):
+def arccot(x: float) -> float:
+    """
+    Berechnung von arccot eines Winkels
+    :param x: Winkel
+    :return: arccot(Winkel)
+    """
     return np.arctan2(1.0, x)
 
 
-def cot(a):
+def cot(x: float) -> float:
-    return np.cos(a) / np.sin(a)
+    """
+    Berechnung von cot eines Winkels
+    :param x: Winkel
+    :return: cot(Winkel)
+    """
+    return np.cos(x) / np.sin(x)
 
 
-def wrap_mpi_pi(x):
+def wrap_mpi_pi(x: float) -> float:
+    """
+    Wrap eines Winkels in den Wertebereich [-π, π)
+    :param x: Winkel
+    :return: Winkel in [-π, π)
+    """
     return (x + np.pi) % (2 * np.pi) - np.pi
 
 
-def wrap_mhalfpi_halfpi(x):
+def wrap_mhalfpi_halfpi(x: float) -> float:
+    """
+    Wrap eines Winkels in den Wertebereich [-π/2, π/2)
+    :param x: Winkel
+    :return: Winkel in [-π/2, π/2)
+    """
     return (x + np.pi / 2) % np.pi - np.pi / 2
 
 
-def wrap_0_2pi(x):
+def wrap_0_2pi(x: float) -> float:
+    """
+    Wrap eines Winkels in den Wertebereich [0, 2π)
+    :param x: Winkel
+    :return: Winkel in [0, 2π)
+    """
     return x % (2 * np.pi)