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Hendrik Möllersmann
2026-02-11 12:08:46 +01:00
parent 5a293a823a
commit 59ad560f36
38 changed files with 3419 additions and 8763 deletions
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110
GHA_triaxial/gha2_num.py
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@@ -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")
# beta1 = np.deg2rad(75)
# lamb1 = np.deg2rad(-90)
# beta2 = np.deg2rad(75)
# lamb2 = np.deg2rad(66)
# a0, a1, s = gha2_num(ell, beta1, lamb1, beta2, lamb2, n=5000)
# print(aus.gms("a0", a0, 4))
# print(aus.gms("a1", a1, 4))
# print("s: ", s)
# # 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)
ell = EllipsoidTriaxial.init_name("BursaSima1980round")
beta1 = np.deg2rad(75)
lamb1 = np.deg2rad(-90)
beta2 = np.deg2rad(75)
lamb2 = np.deg2rad(66)
a0, a1, s = gha2_num(ell, beta1, lamb1, beta2, lamb2, n=100)
print(aus.gms("a0", a0, 4))
print(aus.gms("a1", a1, 4))
print("s: ", s)
# 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)
# ell = EllipsoidTriaxial.init_name("BursaSima1980round")
# diffs_panou = []
# examples_panou = ne_panou.get_random_examples(4)
# for example in examples_panou:
# beta0, lamb0, beta1, lamb1, _, alpha0, alpha1, s = example
# P0 = ell.ell2cart(beta0, lamb0)
# try:
# alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
# diffs_panou.append(
# (wu.rad2deg(abs(alpha0 - alpha0_num)), wu.rad2deg(abs(alpha1 - alpha1_num)), abs(s - s_num)))
# except:
# print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
# diffs_panou = np.array(diffs_panou)
# print(diffs_panou)
#
# ell = EllipsoidTriaxial.init_name("KarneyTest2024")
# diffs_karney = []
# # examples_karney = ne_karney.get_examples((30500, 40500))
# examples_karney = ne_karney.get_random_examples(2)
# for example in examples_karney:
# beta0, lamb0, alpha0, beta1, lamb1, alpha1, s = example
#
# try:
# alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
# diffs_karney.append((wu.rad2deg(abs(alpha0-alpha0_num)), wu.rad2deg(abs(alpha1-alpha1_num)), abs(s-s_num)))
# except:
# print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
# diffs_karney = np.array(diffs_karney)
# print(diffs_karney)
a1, a2, s = gha2_num(ell, beta1, lamb1, beta2, lamb2, n=5000)
print(s)
ell = EllipsoidTriaxial.init_name("BursaSima1980round")
diffs_panou = []
examples_panou = ne_panou.get_random_examples(4)
for example in examples_panou:
beta0, lamb0, beta1, lamb1, _, alpha0, alpha1, s = example
P0 = ell.ell2cart(beta0, lamb0)
try:
alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
diffs_panou.append(
(wu.rad2deg(abs(alpha0 - alpha0_num)), wu.rad2deg(abs(alpha1 - alpha1_num)), abs(s - s_num)))
except:
print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
diffs_panou = np.array(diffs_panou)
print(diffs_panou)
ell = EllipsoidTriaxial.init_name("KarneyTest2024")
diffs_karney = []
# examples_karney = ne_karney.get_examples((30500, 40500))
examples_karney = ne_karney.get_random_examples(2)
for example in examples_karney:
beta0, lamb0, alpha0, beta1, lamb1, alpha1, s = example
try:
alpha0_num, alpha1_num, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=4000, iter_max=10)
diffs_karney.append((wu.rad2deg(abs(alpha0-alpha0_num)), wu.rad2deg(abs(alpha1-alpha1_num)), abs(s-s_num)))
except:
print(f"Fehler für {beta0}, {lamb0}, {beta1}, {lamb1}")
diffs_karney = np.array(diffs_karney)
print(diffs_karney)
pass