Näherungslösung GHA 2

This commit is contained in:
2026-01-11 16:05:15 +01:00
parent 4d5b6fcc3e
commit 6cc7245b0f
7 changed files with 260 additions and 235 deletions

View File

@@ -1,12 +1,10 @@
import numpy as np
from numpy import sin, cos, arcsin, arccos, arctan2
from ellipsoide import EllipsoidTriaxial
import matplotlib.pyplot as plt
from panou import louville_constant, func_sigma_ell, gha1_ana
import plotly.graph_objects as go
import winkelumrechnungen as wu
def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: int):
def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: float, all_points: bool = False) -> Tuple[NDArray, float] | Tuple[NDArray, float, NDArray]:
l0 = louville_constant(ell, p0, alpha0)
points = [p0]
alphas = [alpha0]
@@ -17,10 +15,9 @@ def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: in
break
p1 = points[-1]
alpha1 = alphas[-1]
x1, y1, z1 = p1
sigma = func_sigma_ell(ell, x1, y1, z1, alpha1)
sigma = func_sigma_ell(ell, p1, alpha1)
p2 = p1 + ds_step * sigma
p2, _, _, _ = ell.cartonell(p2)
p2 = ell.cartonell(p2)
ds_step = np.linalg.norm(p2 - p1)
points.append(p2)
@@ -30,7 +27,11 @@ def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: in
alpha2 = alpha1 + (l0 - l2) / dl_dalpha
alphas.append(alpha2)
s_curr += ds_step
return points[-1], alphas[-1], np.array(points)
if all_points:
return points[-1], alphas[-1], np.array(points)
else:
return points[-1], alphas[-1]
def show_points(points, p0, p1):
fig = go.Figure()
@@ -57,7 +58,7 @@ if __name__ == '__main__':
P0 = ell.para2cart(0, 0)
alpha0 = wu.deg2rad(90)
s = 1000000
P1_ana, alpha1_ana = gha1_ana(ell, P0, alpha0, s, 60, maxPartCircum=32)
P1_app, alpha1_app, points = gha1(ell, P0, alpha0, s, 5000)
P1_ana, alpha1_ana = gha1_ana(ell, P0, alpha0, s, maxM=60, maxPartCircum=32)
P1_app, alpha1_app, points = gha1(ell, P0, alpha0, s, ds=5000, all_points=True)
show_points(points, P0, P1_ana)
print(np.linalg.norm(P1_app - P1_ana))