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Doc-Strings und Type-Hinting

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Hendrik Möllersmann
2026-01-13 11:09:12 +01:00
parent 8507ca1afa
commit efd1b8c5fb
9 changed files with 235 additions and 135 deletions
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24
GHA_triaxial/approx_gha1.py
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@@ -4,7 +4,17 @@ 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: float, all_points: bool = False) -> Tuple[NDArray, float] | Tuple[NDArray, float, NDArray]:
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]:
"""
Berechung einer Näherungslösung der ersten Hauptaufgabe
:param ell: Ellipsoid
:param p0: Anfangspunkt
:param alpha0: Azimut im Anfangspunkt
:param s: Strecke bis zum Endpunkt
:param ds: Länge einzelner Streckenelemente
:param all_points: Ausgabe aller Punkte als Array?
:return: Endpunkt, Azimut im Endpunkt, optional alle Punkte
"""
l0 = louville_constant(ell, p0, alpha0)
points = [p0]
alphas = [alpha0]
@@ -17,7 +27,7 @@ def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: fl
alpha1 = alphas[-1]
sigma = func_sigma_ell(ell, p1, alpha1)
p2 = p1 + ds_step * sigma
p2 = ell.cartonell(p2)
p2 = ell.point_onto_ellipsoid(p2)
ds_step = np.linalg.norm(p2 - p1)
points.append(p2)
@@ -33,7 +43,13 @@ def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: fl
else:
return points[-1], alphas[-1]
def show_points(points, p0, p1):
def show_points(points: NDArray, p0: NDArray, p1: NDArray):
"""
Anzeigen der Punkte
:param points: Array aller approximierten Punkte
:param p0: Startpunkt
:param p1: wahrer Endpunkt
"""
fig = go.Figure()
fig.add_scatter3d(x=points[:, 0], y=points[:, 1], z=points[:, 2],
@@ -59,6 +75,6 @@ if __name__ == '__main__':
alpha0 = wu.deg2rad(90)
s = 1000000
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)
P1_app, alpha1_app, points = gha1_approx(ell, P0, alpha0, s, ds=5000, all_points=True)
show_points(points, P0, P1_ana)
print(np.linalg.norm(P1_app - P1_ana))