Doc-Strings und Type-Hinting
This commit is contained in:
@@ -14,7 +14,7 @@ P_next: NDArray = None
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P_end: NDArray = None
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stepLen: float = None
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def Bogenlaenge(P1, P2):
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def Bogenlaenge(P1: NDArray, P2: NDArray) -> float:
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"""
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Berechnung der mittleren Bogenlänge zwischen zwei kartesischen Punkten
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:param P1: kartesische Koordinate Punkt 1
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@@ -23,9 +23,9 @@ def Bogenlaenge(P1, P2):
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"""
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R1 = np.linalg.norm(P1)
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R2 = np.linalg.norm(P2)
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R = 0.5*(R1 + R2)
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R = 0.5 * (R1 + R2)
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theta = arccos(P1 @ P2 / (R1 * R2))
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s = R * theta
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s = float(R * theta)
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return s
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@@ -49,7 +49,7 @@ def gha2_ES(ell: EllipsoidTriaxial, P0: NDArray, Pk: NDArray, stepLenTarget: flo
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ell_ES = ell
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P_start = P0
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P_end = Pk
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if stepLenTarget == None:
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if stepLenTarget is None:
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R0 = (ell.ax + ell.ay + ell.b) / 3
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stepLenTarget = R0 * 1 / 600
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stepLen = stepLenTarget
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@@ -99,7 +99,7 @@ def gha2_ES(ell: EllipsoidTriaxial, P0: NDArray, Pk: NDArray, stepLenTarget: flo
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# % v0 = atan2(q(2), q(1));
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# % xmean_init = [u0;
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# v0];
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xmean_init = ell.cartonell(P_prev + stepLen * (P_end - P_prev) / np.linalg.norm(P_end - P_prev))
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xmean_init = ell.point_onto_ellipsoid(P_prev + stepLen * (P_end - P_prev) / np.linalg.norm(P_end - P_prev))
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# [~, ~, aux] = geoLength(xmean_init);
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# print('Startguess: d_step=%.3f (soll %.3f), d_to_target=%.3f\n', aux(1), stepLen, aux(2));
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@@ -107,7 +107,7 @@ def gha2_ES(ell: EllipsoidTriaxial, P0: NDArray, Pk: NDArray, stepLenTarget: flo
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print(f'[Punkt {i}] Optimiere nächsten Punkt: Restdistanz = {round(d_remain, 3)} m')
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xmean_init = np.array(ell_ES.cart2para(xmean_init))
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u, v = escma(geoLength,2, xmean_init, sigmaStep, -np.inf, stopeval)
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u, v = escma(geoLength, N=2, xmean=xmean_init, sigma=sigmaStep, stopfitness=-np.inf, stopeval=stopeval)
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P_next = ell.para2cart(u, v)
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@@ -128,26 +128,30 @@ def gha2_ES(ell: EllipsoidTriaxial, P0: NDArray, Pk: NDArray, stepLenTarget: flo
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totalLen += d_step
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P_prev = P_next
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print('Maximale Schrittanzahl erreicht.')
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P_all.append(P_end)
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totalLen += Bogenlaenge(P_prev, P_end)
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p0i = ell.cartonell(P0 + 10 * (P_all[1] - P0) / np.linalg.norm(P_all[1] - P0))
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p0i = ell.point_onto_ellipsoid(P0 + 10 * (P_all[1] - P0) / np.linalg.norm(P_all[1] - P0))
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sigma0 = (p0i - P0) / np.linalg.norm(p0i - P0)
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alpha0 = sigma2alpha(ell_ES, sigma0, P0)
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p1i = ell.cartonell(Pk - 10 * (Pk - P_all[-2]) / np.linalg.norm(Pk - P_all[-2]))
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p1i = ell.point_onto_ellipsoid(Pk - 10 * (Pk - P_all[-2]) / np.linalg.norm(Pk - P_all[-2]))
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sigma1 = (Pk - p1i) / np.linalg.norm(Pk - p1i)
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alpha1 = sigma2alpha(ell_ES, sigma1, Pk)
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if all_points:
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return alpha0, alpha1, totalLen, np.array(P_all)
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else:
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return alpha0, alpha1, totalLen
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return alpha0, alpha1, totalLen
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def geoLength(P_candidate):
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def geoLength(P_candidate: Tuple) -> float:
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"""
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Berechung der Fitness eines Kandidaten anhand der Strecken
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:param P_candidate: Kandidat in parametrischen Koordinaten
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:return: Fitness-Wert
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"""
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# P_candidate = [u;v] des naechsten Punktes.
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# Ziel: Distanz zum Ziel minimieren, aber Schrittlaenge ~ stepLenTarget erzwingen.
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u, v = P_candidate
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@@ -165,7 +169,7 @@ def geoLength(P_candidate):
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pen_step = ((d_step - stepLen) / stepLen)**2
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# falls Punkt "weg" vom Ziel geht, extra bestrafen
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pen_away = max(0, (d_to_target - d_prev_to_target) / stepLen)**2
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pen_away = max(0.0, (d_to_target - d_prev_to_target) / stepLen)**2
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# Gewichtungen
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alpha = 1e2
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@@ -175,13 +179,20 @@ def geoLength(P_candidate):
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f = d_to_target * (1 + alpha * pen_step + gamma * pen_away)
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# Für Debug / Extraktion
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aux = [d_step, d_to_target]
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# aux = [d_step, d_to_target]
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return f # , P_candidate, aux
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def show_points(points: NDArray, pointsNum:NDArray, p0: NDArray, p1: NDArray):
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def show_points(points: NDArray, pointsES: NDArray, p0: NDArray, p1: NDArray):
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"""
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Anzeigen der Punkte
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:param points: wahre Punkte der Linie
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:param pointsES: Punkte der Linie aus ES
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:param p0: wahrer Startpunkt
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:param p1: wahrer Endpunkt
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"""
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fig = go.Figure()
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fig.add_scatter3d(x=pointsNum[:, 0], y=pointsNum[:, 1], z=pointsNum[:, 2],
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fig.add_scatter3d(x=pointsES[:, 0], y=pointsES[:, 1], z=pointsES[:, 2],
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mode='lines', line=dict(color="green", width=3), name="Numerisch")
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fig.add_scatter3d(x=points[:, 0], y=points[:, 1], z=points[:, 2],
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mode='lines', line=dict(color="red", width=3), name="ES")
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@@ -4,7 +4,17 @@ from panou import louville_constant, func_sigma_ell, gha1_ana
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import plotly.graph_objects as go
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import winkelumrechnungen as wu
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def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: float, all_points: bool = False) -> Tuple[NDArray, float] | Tuple[NDArray, float, NDArray]:
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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]:
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"""
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Berechung einer Näherungslösung der ersten Hauptaufgabe
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:param ell: Ellipsoid
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:param p0: Anfangspunkt
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:param alpha0: Azimut im Anfangspunkt
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:param s: Strecke bis zum Endpunkt
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:param ds: Länge einzelner Streckenelemente
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:param all_points: Ausgabe aller Punkte als Array?
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:return: Endpunkt, Azimut im Endpunkt, optional alle Punkte
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"""
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l0 = louville_constant(ell, p0, alpha0)
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points = [p0]
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alphas = [alpha0]
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@@ -17,7 +27,7 @@ def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: fl
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alpha1 = alphas[-1]
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sigma = func_sigma_ell(ell, p1, alpha1)
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p2 = p1 + ds_step * sigma
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p2 = ell.cartonell(p2)
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p2 = ell.point_onto_ellipsoid(p2)
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ds_step = np.linalg.norm(p2 - p1)
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points.append(p2)
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@@ -33,7 +43,13 @@ def gha1(ell: EllipsoidTriaxial, p0: np.ndarray, alpha0: float, s: float, ds: fl
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else:
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return points[-1], alphas[-1]
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def show_points(points, p0, p1):
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def show_points(points: NDArray, p0: NDArray, p1: NDArray):
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"""
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Anzeigen der Punkte
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:param points: Array aller approximierten Punkte
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:param p0: Startpunkt
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:param p1: wahrer Endpunkt
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"""
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fig = go.Figure()
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fig.add_scatter3d(x=points[:, 0], y=points[:, 1], z=points[:, 2],
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@@ -59,6 +75,6 @@ if __name__ == '__main__':
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alpha0 = wu.deg2rad(90)
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s = 1000000
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P1_ana, alpha1_ana = gha1_ana(ell, P0, alpha0, s, maxM=60, maxPartCircum=32)
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P1_app, alpha1_app, points = gha1(ell, P0, alpha0, s, ds=5000, all_points=True)
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P1_app, alpha1_app, points = gha1_approx(ell, P0, alpha0, s, ds=5000, all_points=True)
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show_points(points, P0, P1_ana)
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print(np.linalg.norm(P1_app - P1_ana))
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@@ -27,7 +27,7 @@ def gha2(ell: EllipsoidTriaxial, p0: NDArray, p1: NDArray, ds: float, all_points
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new_points.append(points[i])
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pi = points[i] + 1/2 * (points[i+1] - points[i])
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pi = ell.cartonell(pi)
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pi = ell.point_onto_ellipsoid(pi)
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new_points.append(pi)
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@@ -39,11 +39,11 @@ def gha2(ell: EllipsoidTriaxial, p0: NDArray, p1: NDArray, ds: float, all_points
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if np.average(elements) < ds:
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break
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p0i = ell.cartonell(p0 + ds/100 * (points[1] - p0) / np.linalg.norm(points[1] - p0))
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p0i = ell.point_onto_ellipsoid(p0 + ds / 100 * (points[1] - p0) / np.linalg.norm(points[1] - p0))
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sigma0 = (p0i - p0) / np.linalg.norm(p0i - p0)
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alpha0 = sigma2alpha(ell, sigma0, p0)
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p1i = ell.cartonell(p1 - ds/100 * (p1 - points[-2]) / np.linalg.norm(p1 - points[-2]))
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p1i = ell.point_onto_ellipsoid(p1 - ds / 100 * (p1 - points[-2]) / np.linalg.norm(p1 - points[-2]))
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sigma1 = (p1 - p1i) / np.linalg.norm(p1 - p1i)
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alpha1 = sigma2alpha(ell, sigma1, p1)
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@@ -55,6 +55,13 @@ def gha2(ell: EllipsoidTriaxial, p0: NDArray, p1: NDArray, ds: float, all_points
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return alpha0, alpha1, s
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def show_points(points: NDArray, points_app: NDArray, p0: NDArray, p1: NDArray):
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"""
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Anzeigen der Punkte
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:param points: wahre Punkte der Linie
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:param points_app: approximierte Punkte der Linie
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:param p0: wahrer Startpunkt
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:param p1: wahrer Endpunkt
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"""
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fig = go.Figure()
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fig.add_scatter3d(x=points[:, 0], y=points[:, 1], z=points[:, 2],
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@@ -1,7 +1,13 @@
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import random
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import winkelumrechnungen as wu
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from Typing import List, Tuple
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def line2example(line):
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def line2example(line: str) -> List:
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"""
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Line-String in Liste umwandeln
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:param line: Line-String
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:return: Liste mit Zahlenwerten
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"""
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split = line.split()
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example = [float(value) for value in split[:7]]
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for i, value in enumerate(example):
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@@ -10,13 +16,16 @@ def line2example(line):
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# example[i] = value
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return example
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def get_random_examples(num):
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def get_random_examples(num: int, seed: int = None) -> List:
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"""
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Rückgabe zufälliger Beispiele
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beta0, lamb0, alpha0, beta1, lamb1, alpha1, s12
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:param num:
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:return:
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:param num: Anzahl zufälliger Beispiele
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:param seed: Random-Seed
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:return: Liste mit Beispielen
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"""
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# random.seed(42)
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if seed is not None:
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random.seed(seed)
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with open("Karney_2024_Testset.txt") as datei:
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lines = datei.readlines()
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examples = []
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@@ -25,11 +34,12 @@ def get_random_examples(num):
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examples.append(example)
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return examples
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def get_examples(l_i):
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def get_examples(l_i: List) -> List:
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"""
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Rückgabe ausgewählter Beispiele
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beta0, lamb0, alpha0, beta1, lamb1, alpha1, s12
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:param num:
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:return:
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:param l_i: Liste von Indizes
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:return: Liste mit Beispielen
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"""
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with open("Karney_2024_Testset.txt") as datei:
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lines = datei.readlines()
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@@ -39,5 +49,6 @@ def get_examples(l_i):
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examples.append(example)
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return examples
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if __name__ == "__main__":
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get_random_examples(10)
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@@ -1,113 +1,134 @@
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from jedi.inference.gradual.typing import Tuple, List
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import winkelumrechnungen as wu
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import random
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table1 = [
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(wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(90), 1.00000000000,
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wu.gms2rad([90,0,0.0000]), wu.gms2rad([90,0,0.0000]), 10018754.9569),
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(wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(90), 1.00000000000,
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wu.gms2rad([90, 0, 0.0000]), wu.gms2rad([90, 0, 0.0000]), 10018754.9569),
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(wu.deg2rad(1), wu.deg2rad(0), wu.deg2rad(-80), wu.deg2rad(5), 0.05883743460,
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wu.gms2rad([179,7,12.2719]), wu.gms2rad([174,40,13.8487]), 8947130.7221),
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(wu.deg2rad(1), wu.deg2rad(0), wu.deg2rad(-80), wu.deg2rad(5), 0.05883743460,
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wu.gms2rad([179, 7, 12.2719]), wu.gms2rad([174, 40, 13.8487]), 8947130.7221),
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(wu.deg2rad(5), wu.deg2rad(0), wu.deg2rad(-60), wu.deg2rad(40), 0.34128138370,
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wu.gms2rad([160,13,24.5001]), wu.gms2rad([137,26,47.0036]), 8004762.4330),
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(wu.deg2rad(5), wu.deg2rad(0), wu.deg2rad(-60), wu.deg2rad(40), 0.34128138370,
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wu.gms2rad([160, 13, 24.5001]), wu.gms2rad([137, 26, 47.0036]), 8004762.4330),
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(wu.deg2rad(30), wu.deg2rad(0), wu.deg2rad(-30), wu.deg2rad(175), 0.86632464962,
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wu.gms2rad([91,7,30.9337]), wu.gms2rad([91,7,30.8672]), 19547128.7971),
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(wu.deg2rad(30), wu.deg2rad(0), wu.deg2rad(-30), wu.deg2rad(175), 0.86632464962,
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wu.gms2rad([91, 7, 30.9337]), wu.gms2rad([91, 7, 30.8672]), 19547128.7971),
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(wu.deg2rad(60), wu.deg2rad(0), wu.deg2rad(60), wu.deg2rad(175), 0.06207487624,
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wu.gms2rad([2,52,26.2393]), wu.gms2rad([177,4,13.6373]), 6705715.1610),
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(wu.deg2rad(60), wu.deg2rad(0), wu.deg2rad(60), wu.deg2rad(175), 0.06207487624,
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wu.gms2rad([2, 52, 26.2393]), wu.gms2rad([177, 4, 13.6373]), 6705715.1610),
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(wu.deg2rad(75), wu.deg2rad(0), wu.deg2rad(80), wu.deg2rad(120), 0.11708984898,
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wu.gms2rad([23,20,34.7823]), wu.gms2rad([140,55,32.6385]), 2482501.2608),
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(wu.deg2rad(75), wu.deg2rad(0), wu.deg2rad(80), wu.deg2rad(120), 0.11708984898,
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wu.gms2rad([23, 20, 34.7823]), wu.gms2rad([140, 55, 32.6385]), 2482501.2608),
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(wu.deg2rad(80), wu.deg2rad(0), wu.deg2rad(60), wu.deg2rad(90), 0.17478427424,
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wu.gms2rad([72,26,50.4024]), wu.gms2rad([159,38,30.3547]), 3519745.1283)
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(wu.deg2rad(80), wu.deg2rad(0), wu.deg2rad(60), wu.deg2rad(90), 0.17478427424,
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wu.gms2rad([72, 26, 50.4024]), wu.gms2rad([159, 38, 30.3547]), 3519745.1283)
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]
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table2 = [
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(wu.deg2rad(0), wu.deg2rad(-90), wu.deg2rad(0), wu.deg2rad(89.5), 1.00000000000,
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wu.gms2rad([90,0,0.0000]), wu.gms2rad([90,0,0.0000]), 19981849.8629),
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(wu.deg2rad(0), wu.deg2rad(-90), wu.deg2rad(0), wu.deg2rad(89.5), 1.00000000000,
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wu.gms2rad([90, 0, 0.0000]), wu.gms2rad([90, 0, 0.0000]), 19981849.8629),
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(wu.deg2rad(1), wu.deg2rad(-90), wu.deg2rad(1), wu.deg2rad(89.5), 0.18979826428,
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wu.gms2rad([10,56,33.6952]), wu.gms2rad([169,3,26.4359]), 19776667.0342),
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(wu.deg2rad(1), wu.deg2rad(-90), wu.deg2rad(1), wu.deg2rad(89.5), 0.18979826428,
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wu.gms2rad([10, 56, 33.6952]), wu.gms2rad([169, 3, 26.4359]), 19776667.0342),
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(wu.deg2rad(5), wu.deg2rad(-90), wu.deg2rad(5), wu.deg2rad(89), 0.09398403161,
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wu.gms2rad([5,24,48.3899]), wu.gms2rad([174,35,12.6880]), 18889165.0873),
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(wu.deg2rad(5), wu.deg2rad(-90), wu.deg2rad(5), wu.deg2rad(89), 0.09398403161,
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wu.gms2rad([5, 24, 48.3899]), wu.gms2rad([174, 35, 12.6880]), 18889165.0873),
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|
||||
(wu.deg2rad(30), wu.deg2rad(-90), wu.deg2rad(30), wu.deg2rad(86), 0.06004022935,
|
||||
wu.gms2rad([3,58,23.8038]), wu.gms2rad([176,2,7.2825]), 13331814.6078),
|
||||
(wu.deg2rad(30), wu.deg2rad(-90), wu.deg2rad(30), wu.deg2rad(86), 0.06004022935,
|
||||
wu.gms2rad([3, 58, 23.8038]), wu.gms2rad([176, 2, 7.2825]), 13331814.6078),
|
||||
|
||||
(wu.deg2rad(60), wu.deg2rad(-90), wu.deg2rad(60), wu.deg2rad(78), 0.06076096484,
|
||||
wu.gms2rad([6,56,46.4585]), wu.gms2rad([173,11,5.9592]), 6637321.6350),
|
||||
(wu.deg2rad(60), wu.deg2rad(-90), wu.deg2rad(60), wu.deg2rad(78), 0.06076096484,
|
||||
wu.gms2rad([6, 56, 46.4585]), wu.gms2rad([173, 11, 5.9592]), 6637321.6350),
|
||||
|
||||
(wu.deg2rad(75), wu.deg2rad(-90), wu.deg2rad(75), wu.deg2rad(66), 0.05805851008,
|
||||
wu.gms2rad([12,40,34.9009]), wu.gms2rad([168,20,26.7339]), 3267941.2812),
|
||||
(wu.deg2rad(75), wu.deg2rad(-90), wu.deg2rad(75), wu.deg2rad(66), 0.05805851008,
|
||||
wu.gms2rad([12, 40, 34.9009]), wu.gms2rad([168, 20, 26.7339]), 3267941.2812),
|
||||
|
||||
(wu.deg2rad(80), wu.deg2rad(-90), wu.deg2rad(80), wu.deg2rad(55), 0.05817384452,
|
||||
wu.gms2rad([18,35,40.7848]), wu.gms2rad([164,25,34.0017]), 2132316.9048)
|
||||
(wu.deg2rad(80), wu.deg2rad(-90), wu.deg2rad(80), wu.deg2rad(55), 0.05817384452,
|
||||
wu.gms2rad([18, 35, 40.7848]), wu.gms2rad([164, 25, 34.0017]), 2132316.9048)
|
||||
]
|
||||
|
||||
table3 = [
|
||||
(wu.deg2rad(0), wu.deg2rad(0.5), wu.deg2rad(80), wu.deg2rad(0.5), 0.05680316848,
|
||||
wu.gms2rad([0,-0,16.0757]), wu.gms2rad([0,1,32.5762]), 8831874.3717),
|
||||
(wu.deg2rad(0), wu.deg2rad(0.5), wu.deg2rad(80), wu.deg2rad(0.5), 0.05680316848,
|
||||
wu.gms2rad([0, 0, 16.0757]), wu.gms2rad([0, 1, 32.5762]), 8831874.3717),
|
||||
|
||||
(wu.deg2rad(-1), wu.deg2rad(5), wu.deg2rad(75), wu.deg2rad(5), 0.05659149555,
|
||||
wu.gms2rad([0,-1,47.2105]), wu.gms2rad([0,6,54.0958]), 8405370.4947),
|
||||
(wu.deg2rad(-1), wu.deg2rad(5), wu.deg2rad(75), wu.deg2rad(5), 0.05659149555,
|
||||
wu.gms2rad([0, -1, 47.2105]), wu.gms2rad([0, 6, 54.0958]), 8405370.4947),
|
||||
|
||||
(wu.deg2rad(-5), wu.deg2rad(30), wu.deg2rad(60), wu.deg2rad(30), 0.04921108945,
|
||||
wu.gms2rad([0,-4,22.3516]), wu.gms2rad([0,8,42.0756]), 7204083.8568),
|
||||
(wu.deg2rad(-5), wu.deg2rad(30), wu.deg2rad(60), wu.deg2rad(30), 0.04921108945,
|
||||
wu.gms2rad([0, -4, 22.3516]), wu.gms2rad([0, 8, 42.0756]), 7204083.8568),
|
||||
|
||||
(wu.deg2rad(-30), wu.deg2rad(45), wu.deg2rad(30), wu.deg2rad(45), 0.04017812574,
|
||||
wu.gms2rad([0,-3,41.2461]), wu.gms2rad([0,3,41.2461]), 6652788.1287),
|
||||
(wu.deg2rad(-30), wu.deg2rad(45), wu.deg2rad(30), wu.deg2rad(45), 0.04017812574,
|
||||
wu.gms2rad([0, -3, 41.2461]), wu.gms2rad([0, 3, 41.2461]), 6652788.1287),
|
||||
|
||||
(wu.deg2rad(-60), wu.deg2rad(60), wu.deg2rad(5), wu.deg2rad(60), 0.02843082609,
|
||||
wu.gms2rad([0,-8,40.4575]), wu.gms2rad([0,4,22.1675]), 7213412.4477),
|
||||
(wu.deg2rad(-60), wu.deg2rad(60), wu.deg2rad(5), wu.deg2rad(60), 0.02843082609,
|
||||
wu.gms2rad([0, -8, 40.4575]), wu.gms2rad([0, 4, 22.1675]), 7213412.4477),
|
||||
|
||||
(wu.deg2rad(-75), wu.deg2rad(85), wu.deg2rad(1), wu.deg2rad(85), 0.00497802414,
|
||||
wu.gms2rad([0,-6,44.6115]), wu.gms2rad([0,1,47.0474]), 8442938.5899),
|
||||
(wu.deg2rad(-75), wu.deg2rad(85), wu.deg2rad(1), wu.deg2rad(85), 0.00497802414,
|
||||
wu.gms2rad([0, -6, 44.6115]), wu.gms2rad([0, 1, 47.0474]), 8442938.5899),
|
||||
|
||||
(wu.deg2rad(-80), wu.deg2rad(89.5), wu.deg2rad(0), wu.deg2rad(89.5), 0.00050178253,
|
||||
wu.gms2rad([0,-1,27.9705]), wu.gms2rad([0,0,16.0490]), 8888783.7815)
|
||||
(wu.deg2rad(-80),wu.deg2rad(89.5), wu.deg2rad(0), wu.deg2rad(89.5), 0.00050178253,
|
||||
wu.gms2rad([0, -1, 27.9705]), wu.gms2rad([0, 0, 16.0490]), 8888783.7815)
|
||||
]
|
||||
|
||||
table4 = [
|
||||
(wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(90), 1.00000000000,
|
||||
wu.gms2rad([90,0,0.0000]), wu.gms2rad([90,0,0.0000]), 10018754.1714),
|
||||
(wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(90), 1.00000000000,
|
||||
wu.gms2rad([90, 0, 0.0000]), wu.gms2rad([90, 0, 0.0000]), 10018754.1714),
|
||||
|
||||
(wu.deg2rad(1), wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(179.5), 0.30320665822,
|
||||
wu.gms2rad([17,39,11.0942]), wu.gms2rad([162,20,58.9032]), 19884417.8083),
|
||||
(wu.deg2rad(1), wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(179.5), 0.30320665822,
|
||||
wu.gms2rad([17, 39, 11.0942]), wu.gms2rad([162, 20, 58.9032]), 19884417.8083),
|
||||
|
||||
(wu.deg2rad(5), wu.deg2rad(0), wu.deg2rad(-80), wu.deg2rad(170), 0.03104258442,
|
||||
wu.gms2rad([178,12,51.5083]), wu.gms2rad([10,17,52.6423]), 11652530.7514),
|
||||
(wu.deg2rad(5), wu.deg2rad(0), wu.deg2rad(-80), wu.deg2rad(170), 0.03104258442,
|
||||
wu.gms2rad([178, 12, 51.5083]), wu.gms2rad([10, 17, 52.6423]), 11652530.7514),
|
||||
|
||||
(wu.deg2rad(30), wu.deg2rad(0), wu.deg2rad(-75), wu.deg2rad(120), 0.24135347134,
|
||||
wu.gms2rad([163,49,4.4615]), wu.gms2rad([68,49,50.9617]), 14057886.8752),
|
||||
(wu.deg2rad(30), wu.deg2rad(0), wu.deg2rad(-75), wu.deg2rad(120), 0.24135347134,
|
||||
wu.gms2rad([163, 49, 4.4615]), wu.gms2rad([68, 49, 50.9617]), 14057886.8752),
|
||||
|
||||
(wu.deg2rad(60), wu.deg2rad(0), wu.deg2rad(-60), wu.deg2rad(40), 0.19408499032,
|
||||
wu.gms2rad([157,9,33.5589]), wu.gms2rad([157,9,33.5589]), 13767414.8267),
|
||||
(wu.deg2rad(60), wu.deg2rad(0), wu.deg2rad(-60), wu.deg2rad(40), 0.19408499032,
|
||||
wu.gms2rad([157, 9, 33.5589]), wu.gms2rad([157, 9, 33.5589]), 13767414.8267),
|
||||
|
||||
(wu.deg2rad(75), wu.deg2rad(0), wu.deg2rad(-30), wu.deg2rad(0.5), 0.00202789418,
|
||||
wu.gms2rad([179,33,3.8613]), wu.gms2rad([179,51,57.0077]), 11661713.4496),
|
||||
(wu.deg2rad(75), wu.deg2rad(0), wu.deg2rad(-30), wu.deg2rad(0.5), 0.00202789418,
|
||||
wu.gms2rad([179, 33, 3.8613]), wu.gms2rad([179, 51, 57.0077]), 11661713.4496),
|
||||
|
||||
(wu.deg2rad(80), wu.deg2rad(0), wu.deg2rad(-5), wu.deg2rad(120), 0.15201222384,
|
||||
wu.gms2rad([61,5,33.9600]), wu.gms2rad([171,13,22.0148]), 11105138.2902),
|
||||
(wu.deg2rad(80), wu.deg2rad(0), wu.deg2rad(-5), wu.deg2rad(120), 0.15201222384,
|
||||
wu.gms2rad([61, 5, 33.9600]), wu.gms2rad([171, 13, 22.0148]), 11105138.2902),
|
||||
|
||||
(wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(60), wu.deg2rad(0), 0.00000000000,
|
||||
wu.gms2rad([0,0,0.0000]), wu.gms2rad([0,0,0.0000]), 6663348.2060)
|
||||
(wu.deg2rad(0), wu.deg2rad(0), wu.deg2rad(60), wu.deg2rad(0), 0.00000000000,
|
||||
wu.gms2rad([0, 0, 0.0000]), wu.gms2rad([0, 0, 0.0000]), 6663348.2060)
|
||||
]
|
||||
|
||||
tables = [table1, table2, table3, table4]
|
||||
|
||||
def get_example(table, example):
|
||||
def get_example(table: int, example: int) -> Tuple:
|
||||
"""
|
||||
Rückgabe eines Beispiels
|
||||
:param table: Tabellen-Nummer
|
||||
:param example: Beispiel-Nummer
|
||||
:return: Bespiel
|
||||
"""
|
||||
table -= 1
|
||||
example -= 1
|
||||
tables = get_tables()
|
||||
return tables[table][example]
|
||||
|
||||
def get_tables():
|
||||
def get_tables() -> List:
|
||||
"""
|
||||
Rückgabe aller Tabellen
|
||||
:return: Alle Tabellen
|
||||
"""
|
||||
return tables
|
||||
|
||||
def get_random_examples(num):
|
||||
random.seed(42)
|
||||
def get_random_examples(num: int, seed: int = None) -> List:
|
||||
"""
|
||||
Rückgabe zufäliger Beispiele
|
||||
:param num: Anzahl Beispiele
|
||||
:param seed: Random-Seed
|
||||
:return:
|
||||
"""
|
||||
if seed is not None:
|
||||
random.seed(seed)
|
||||
|
||||
examples = []
|
||||
for i in range(num):
|
||||
table = random.randint(1, 4)
|
||||
@@ -120,7 +141,6 @@ def get_random_examples(num):
|
||||
return examples
|
||||
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
# test = get_example(1, 4)
|
||||
examples = get_random_examples(5)
|
||||
|
||||
@@ -10,7 +10,7 @@ from numpy.typing import NDArray
|
||||
# Panou 2013
|
||||
def gha2_num(ell: EllipsoidTriaxial, beta_1: float, lamb_1: float, beta_2: float, lamb_2: float,
|
||||
n: int = 16000, epsilon: float = 10**-12, iter_max: int = 30, all_points: bool = False
|
||||
) -> Tuple[float, float, float]| Tuple[float, float, float, NDArray, NDArray]:
|
||||
) -> Tuple[float, float, float] | Tuple[float, float, float, NDArray, NDArray]:
|
||||
"""
|
||||
|
||||
:param ell: triaxiales Ellipsoid
|
||||
@@ -252,7 +252,7 @@ def gha2_num(ell: EllipsoidTriaxial, beta_1: float, lamb_1: float, beta_2: float
|
||||
else:
|
||||
return alpha_1, alpha_2, s
|
||||
|
||||
else: # lamb_1 == lamb_2
|
||||
else: # lamb_1 == lamb_2
|
||||
|
||||
N = n
|
||||
dbeta = beta_2 - beta_1
|
||||
|
||||
@@ -154,8 +154,8 @@ class EllipsoidTriaxial:
|
||||
return cls(ax, ay, b)
|
||||
elif name == "Fiction":
|
||||
ax = 6000000
|
||||
ay = 5000000
|
||||
b = 4000000
|
||||
ay = 4000000
|
||||
b = 2000000
|
||||
return cls(ax, ay, b)
|
||||
elif name == "KarneyTest2024":
|
||||
ax = sqrt(2)
|
||||
@@ -294,9 +294,9 @@ class EllipsoidTriaxial:
|
||||
def ell2cart_bektas(self, beta: float | NDArray, omega: float | NDArray) -> NDArray:
|
||||
"""
|
||||
Bektas 2015
|
||||
:param beta:
|
||||
:param omega:
|
||||
:return:
|
||||
:param beta: elliptische Breite [rad]
|
||||
:param omega: elliptische Länge [rad]
|
||||
:return: Punkt in kartesischen Koordinaten
|
||||
"""
|
||||
x = self.ax * cos(omega) * sqrt((self.ax**2 - self.ay**2 * sin(beta)**2 - self.b**2 * cos(beta)**2) / (self.ax**2 - self.b**2))
|
||||
y = self.ay * cos(beta) * sin(omega)
|
||||
@@ -307,9 +307,9 @@ class EllipsoidTriaxial:
|
||||
def ell2cart_karney(self, beta: float | NDArray, lamb: float | NDArray) -> NDArray:
|
||||
"""
|
||||
Karney 2025 Geographic Lib
|
||||
:param beta:
|
||||
:param lamb:
|
||||
:return:
|
||||
:param beta: elliptische Breite [rad]
|
||||
:param lamb: elliptische Länge [rad]
|
||||
:return: Punkt in kartesischen Koordinaten
|
||||
"""
|
||||
k = sqrt(self.ay**2 - self.b**2) / sqrt(self.ax**2 - self.b**2)
|
||||
k_ = sqrt(self.ax**2 - self.ay**2) / sqrt(self.ax**2 - self.b**2)
|
||||
@@ -321,10 +321,10 @@ class EllipsoidTriaxial:
|
||||
def cart2ell(self, point: NDArray, eps: float = 1e-12, maxI: int = 100) -> Tuple[float, float]:
|
||||
"""
|
||||
Panou, Korakitis 2019 3f. (num)
|
||||
:param point:
|
||||
:param eps:
|
||||
:param maxI:
|
||||
:return:
|
||||
:param point: Punkt in kartesischen Koordinaten
|
||||
:param eps: zu erreichende Genauigkeit
|
||||
:param maxI: maximale Anzahl Iterationen
|
||||
:return: elliptische Breite und Länge [rad]
|
||||
"""
|
||||
x, y, z = point
|
||||
beta, lamb = self.cart2ell_panou(point)
|
||||
@@ -427,10 +427,10 @@ class EllipsoidTriaxial:
|
||||
def cart2ell_bektas(self, point: NDArray, eps: float = 1e-12, maxI: int = 100) -> Tuple[float, float]:
|
||||
"""
|
||||
Bektas 2015
|
||||
:param point:
|
||||
:param eps:
|
||||
:param maxI:
|
||||
:return:
|
||||
:param point: Punkt in kartesischen Koordinaten
|
||||
:param eps: zu erreichende Genauigkeit
|
||||
:param maxI: maximale Anzahl Iterationen
|
||||
:return: elliptische Breite und Länge [rad]
|
||||
"""
|
||||
x, y, z = point
|
||||
phi, lamb = self.cart2para(point)
|
||||
@@ -575,26 +575,70 @@ class EllipsoidTriaxial:
|
||||
return u, v
|
||||
|
||||
def ell2para(self, beta: float, lamb: float) -> Tuple[float, float]:
|
||||
"""
|
||||
Umrechung von elliptischen in parametrische Koordinaten (über kartesische Koordinaten)
|
||||
:param beta: elliptische Breite
|
||||
:param lamb: elliptische Länge
|
||||
:return: parametrische Koordinaten
|
||||
"""
|
||||
cart = self.ell2cart(beta, lamb)
|
||||
return self.cart2para(cart)
|
||||
|
||||
def para2ell(self, u: float, v: float) -> Tuple[float, float]:
|
||||
"""
|
||||
Umrechung von parametrischen in elliptische Koordinaten (über kartesische Koordinaten)
|
||||
:param u: u
|
||||
:param v: v
|
||||
:return: elliptische Koordinaten
|
||||
"""
|
||||
cart = self.para2cart(u, v)
|
||||
return self.cart2ell(cart)
|
||||
|
||||
def para2geod(self, u: float, v: float, mode: str = "ligas3", maxIter: int = 30, maxLoa: float = 0.005) -> Tuple[float, float, float]:
|
||||
"""
|
||||
Umrechung von parametrischen in geodätische Koordinaten (über kartesische Koordinaten)
|
||||
:param u: u
|
||||
:param v: v
|
||||
:param mode: ligas1, ligas2, oder ligas3
|
||||
:param maxIter: maximale Anzahl Iterationen
|
||||
:param maxLoa: Level of Accuracy, das erreicht werden soll
|
||||
:return: geodätische Koordinaten
|
||||
"""
|
||||
cart = self.para2cart(u, v)
|
||||
return self.cart2geod(cart, mode, maxIter, maxLoa)
|
||||
|
||||
def geod2para(self, phi: float, lamb: float, h: float) -> Tuple[float, float]:
|
||||
"""
|
||||
Umrechung von geodätischen in parametrische Koordinaten (über kartesische Koordinaten)
|
||||
:param phi: u
|
||||
:param lamb: v
|
||||
:param h: geodätische Höhe
|
||||
:return: parametrische Koordinaten
|
||||
"""
|
||||
cart = self.geod2cart(phi, lamb, h)
|
||||
return self.cart2para(cart)
|
||||
|
||||
def ell2geod(self, beta: float, lamb: float, mode: str = "ligas3", maxIter: int = 30, maxLoa: float = 0.005) -> Tuple[float, float, float]:
|
||||
"""
|
||||
Umrechung von elliptischen in geodätische Koordinaten (über kartesische Koordinaten)
|
||||
:param beta: elliptische Breite
|
||||
:param lamb: eliptische Länge
|
||||
:param mode: ligas1, ligas2, oder ligas3
|
||||
:param maxIter: maximale Anzahl Iterationen
|
||||
:param maxLoa: Level of Accuracy, das erreicht werden soll
|
||||
:return: geodätische Koordinaten
|
||||
"""
|
||||
cart = self.ell2cart(beta, lamb)
|
||||
return self.cart2geod(cart, mode, maxIter, maxLoa)
|
||||
|
||||
def geod2ell(self, phi: float, lamb: float, h: float) -> Tuple[float, float]:
|
||||
"""
|
||||
Umrechung von geodätischen in elliptische Koordinaten (über kartesische Koordinaten)
|
||||
:param phi: u
|
||||
:param lamb: v
|
||||
:param h: geodätische Höhe
|
||||
:return: elliptische Koordinaten
|
||||
"""
|
||||
cart = self.geod2cart(phi, lamb, h)
|
||||
return self.cart2ell(cart)
|
||||
|
||||
@@ -610,9 +654,9 @@ class EllipsoidTriaxial:
|
||||
else:
|
||||
return False
|
||||
|
||||
def cartonell(self, point: NDArray) -> NDArray:
|
||||
def point_onto_ellipsoid(self, point: NDArray) -> NDArray:
|
||||
"""
|
||||
Berechnung des Lotpunktes auf einem Ellipsoiden
|
||||
Berechnung des Lotpunktes entlang der Normalkrümmung auf einem Ellipsoiden
|
||||
:param point: Punkt in kartesischen Koordinaten, der gelotet werden soll
|
||||
:return: Lotpunkt in kartesischen Koordinaten
|
||||
"""
|
||||
@@ -620,7 +664,7 @@ class EllipsoidTriaxial:
|
||||
p = self. geod2cart(phi, lamb, 0)
|
||||
return p
|
||||
|
||||
def cartellh(self, point: NDArray, h: float) -> NDArray:
|
||||
def cart_ellh(self, point: NDArray, h: float) -> NDArray:
|
||||
"""
|
||||
Punkt auf Ellipsoid hoch loten
|
||||
:param point: Punkt auf dem Ellipsoid
|
||||
|
||||
1
utils.py
1
utils.py
@@ -13,7 +13,6 @@ def sigma2alpha(ell: EllipsoidTriaxial, sigma: NDArray, point: NDArray) -> float
|
||||
:param point: Punkt
|
||||
:return: Richtungswinkel
|
||||
"""
|
||||
""
|
||||
p, q = pq_ell(ell, point)
|
||||
P = float(p @ sigma)
|
||||
Q = float(q @ sigma)
|
||||
|
||||
@@ -10,13 +10,10 @@ def deg2gms(deg: float) -> list:
|
||||
:return: Winkel in Grad-Minuten-Sekunden
|
||||
:rtype: list
|
||||
"""
|
||||
gra = deg // 1
|
||||
minu = gra % 1
|
||||
gra = gra // 1
|
||||
minu *= 60
|
||||
sek = minu % 1
|
||||
minu = minu // 1
|
||||
sek *= 60
|
||||
gra = int(deg)
|
||||
minu_f = (deg - gra) * 60
|
||||
minu = int(minu_f)
|
||||
sek = (minu_f - minu) * 60
|
||||
return [gra, minu, sek]
|
||||
|
||||
|
||||
@@ -51,13 +48,10 @@ def gra2gms(gra: float) -> list:
|
||||
:rtype: list
|
||||
"""
|
||||
deg = gra2deg(gra)
|
||||
gra = deg // 1
|
||||
minu = gra % 1
|
||||
gra = gra // 1
|
||||
minu *= 60
|
||||
sek = minu % 1
|
||||
minu = minu // 1
|
||||
sek *= 60
|
||||
gra = int(deg)
|
||||
minu_f = (deg - gra) * 60
|
||||
minu = int(minu_f)
|
||||
sek = (minu_f - minu) * 60
|
||||
return [gra, minu, sek]
|
||||
|
||||
|
||||
@@ -114,12 +108,10 @@ def rad2gms(rad: float) -> list:
|
||||
:rtype: list
|
||||
"""
|
||||
deg = rad2deg(rad)
|
||||
minu = deg % 1
|
||||
gra = deg // 1
|
||||
minu *= 60
|
||||
sek = minu % 1
|
||||
minu = minu // 1
|
||||
sek *= 60
|
||||
gra = int(deg)
|
||||
minu_f = (deg - gra) * 60
|
||||
minu = int(minu_f)
|
||||
sek = (minu_f - minu) * 60
|
||||
return [gra, minu, sek]
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user