Merge remote-tracking branch 'origin/main'

# Conflicts:
#	Hansen_ES_CMA.py
#	dashboard.py

Hansen_ES_CMA.py

@@ -1,5 +1,5 @@
 import numpy as np
-from typing import Callable
+
 
 def felli(x):
     N = x.shape[0]
@@ -9,16 +9,24 @@ def felli(x):
     return float(np.sum((1e6 ** exponents) * (x ** 2)))
 
 
-def escma(fitnessfct: Callable, N, xmean, sigma, stopfitness, stopeval,
+def escma(func, *, N=10, xmean=None, sigma=0.5, stopfitness=1e-10, stopeval=None,
-          bestEver = np.inf, noImproveGen = 0, absTolImprove = 1e-10, maxNoImproveGen = 100, sigmaImprove = 1e-12):
+          func_args=(), func_kwargs=None, seed=None):
-    #Initialization
 
-    # User defined input parameters
+    if func_kwargs is None:
-    # N = 10
+        func_kwargs = {}
-    # xmean = np.random.rand(N)
+
-    # sigma = 0.5
+    if seed is not None:
-    # stopfitness = 1e-10
+        np.random.seed(seed)
-    # stopeval = int(1e3 * N**2)
+
+    # Initialization (aus Parametern statt hart verdrahtet)
+    if xmean is None:
+        xmean = np.random.rand(N)
+    else:
+        xmean = np.asarray(xmean, dtype=float)
+        N = xmean.shape[0]
+
+    if stopeval is None:
+        stopeval = int(1e3 * N**2)
 
     # Strategy parameter setting: Selection
     lambda_ = 4 + int(np.floor(3 * np.log(N)))
@@ -47,7 +55,7 @@ def escma(fitnessfct: Callable, N, xmean, sigma, stopfitness, stopeval,
     eigeneval = 0
     chiN = np.sqrt(N) * (1 - 1/(4*N) + 1/(21 * N**2))
 
-    #Generation Loop
+    # Generation Loop
     counteval = 0
     arx = np.zeros((N, lambda_))
     arz = np.zeros((N, lambda_))
@@ -64,7 +72,7 @@ def escma(fitnessfct: Callable, N, xmean, sigma, stopfitness, stopeval,
         for k in range(lambda_):
             arz[:, k] = np.random.randn(N)
             arx[:, k] = xmean + sigma * (B @ D @ arz[:, k])
-            arfitness[k] = fitnessfct(arx[:, k])
+            arfitness[k] = float(func(arx[:, k], *func_args, **func_kwargs))  # <-- allgemein
             counteval += 1
 
         # Sort by fitness and compute weighted mean into xmean
@@ -145,6 +153,6 @@ def escma(fitnessfct: Callable, N, xmean, sigma, stopfitness, stopeval,
 
 
 if __name__ == "__main__":
-    xmin = escma()
+    xmin = escma(felli, N=10)  # <-- Zielfunktion wird übergeben
     print("Bestes gefundenes x:", xmin)
     print("f(xmin) =", felli(xmin))

dashboard.py

@@ -3,14 +3,16 @@ import dash
 import plotly.graph_objects as go
 import numpy as np
 
-from GHA_triaxial.panou import gha1_ana
-from GHA_triaxial.panou import gha1_num
-from GHA_triaxial.panou_2013_2GHA_num import gha2_num
-from GHA_triaxial.ES_gha2 import gha2_ES
 from ellipsoide import EllipsoidTriaxial
 import winkelumrechnungen as wu
 import ausgaben as aus
 
+from GHA_triaxial.panou import gha1_ana
+from GHA_triaxial.panou import gha1_num
+from es_cma_gha1 import gha1_es
+
+from GHA_triaxial.panou_2013_2GHA_num import gha2_num
+
 
 app = Dash(__name__, suppress_callback_exceptions=True)
 app.title = "Geodätische Hauptaufgaben"
@@ -115,6 +117,7 @@ def figure_constant_lines(fig, ell: EllipsoidTriaxial, coordsystem: str = "para"
 
     return fig
 
+
 def figure_points(fig, points):
     """
 
@@ -151,12 +154,15 @@ def figure_lines(fig, line, color):
     return fig
 
 
+# HTML-Elemente
 app.layout = html.Div(
     style={"fontFamily": "Arial", "padding": "5px", "width": "70%", "margin-left": "auto"},
     children=[
         html.H1("Geodätische Hauptaufgaben"),
         html.H2("für dreiachsige Ellipsoide"),
 
+
+        # Dropdown und Eingabefelder Ellipsoid
         html.Label("Ellipsoid wählen:"),
         dcc.Dropdown(
             id="dropdown-ellipsoid",
@@ -169,8 +175,7 @@ app.layout = html.Div(
                 {"label": "Bursa1970", "value": "Bursa1970"},
                 {"label": "BesselBiaxial", "value": "BesselBiaxial"},
                 {"label": "Fiction", "value": "Fiction"},
-                {"label": "KarneyTest2024", "value": "KarneyTest2024"},
+                #{"label": "Ei", "value": "Ei"},
-                # {"label": "Ei", "value": "Ei"},
             ],
             value="",
             style={"width": "300px", "marginBottom": "20px"},
@@ -206,8 +211,10 @@ app.layout = html.Div(
             style={"marginRight": "10px", "marginBottom": "20px"},
         ),
 
+        # Ausgabebereich für Ellipsoid-Berechnung
         html.Div(id="output-area", style={"marginBottom": "20px"}),
 
+        # Tabs für beide Hauptaufgaben - Inhalt wird per Funktion generiert s.u.
         dcc.Tabs(
             id="tabs-GHA",
             value="tab-GHA1",
@@ -223,15 +230,28 @@ app.layout = html.Div(
             style={"marginRight": "10px", "marginBottom": "20px", "width": "50%"},
         ),
 
-        html.Div(id="output-gha1", style={"marginBottom": "20px"}),
+        dcc.Loading(html.Div(id="output-gha1-ana")),
+        dcc.Loading(html.Div(id="output-gha1-num")),
+        dcc.Loading(html.Div(id="output-gha1-stoch")),
 
-        html.Div(id="output-gha2", style={"marginBottom": "20px"}),
+        dcc.Store(id="store-gha1-ana"),
+        dcc.Store(id="store-gha1-num"),
+        dcc.Store(id="store-gha1-stoch"),
 
+        dcc.Loading(html.Div(id="output-gha2-num")),
+        dcc.Loading(html.Div(id="output-gha2-stoch")),
+
+        dcc.Store(id="store-gha2-num"),
+        dcc.Store(id="store-gha2-stoch"),
+
+
+        # Ausgabebereich für den Plot
         dcc.Graph(
             id="ellipsoid-plot",
             style={"height": "500px", "width": "700px"},
         ),
 
+        # Fussleiste
         html.P(
             "© 2025",
             style={
@@ -243,7 +263,7 @@ app.layout = html.Div(
     ],
 )
 
-
+# Funktion zur Wahl der Halbachsen
 @app.callback(
     Output("input-ax", "value"),
     Output("input-ay", "value"),
@@ -254,13 +274,14 @@ def fill_inputs_from_dropdown(selected_ell):
     if not selected_ell:
         return None, None, None
 
+
     ell = EllipsoidTriaxial.init_name(selected_ell)
     ax = ell.ax
     ay = ell.ay
     b = ell.b
     return ax, ay, b
 
-
+# Funktion zur Berechnung der Ellipsoid-Parameter
 @app.callback(
     Output("output-area", "children"),
     Input("calc-ell", "n_clicks"),
@@ -276,8 +297,16 @@ def update_output(n_clicks, ax, ay, b):
     if ay >= ax or b >= ay or ax <= 0 or ay <= 0 or b <= 0:
         return html.Span("Eingabe inkorrekt.", style={"color": "red"})
     ell = EllipsoidTriaxial(ax, ay, b)
-    return f"eₓ = {round(ell.ex, 6)}, ", f"eᵧ = {round(ell.ey, 6)}, ", f"eₑ = {round(ell.ee, 6)}"
+    out_ell = []
+    out_ell.append(
+        html.Div([
+            html.P(f"eₓ = {round(ell.ex, 6)}, eᵧ = {round(ell.ey, 6)}, eₑ = {round(ell.ee, 6)}"),
+            #html.Br(),
+            html.P(f"Eₓ = {round(ell.Ex, 3)}, Eᵧ = {round(ell.Ey, 3)}, Eₑ = {round(ell.Ee, 3)}"),
+        ]))
+    return out_ell
 
+# Funktion zur Generierung der Tab-Inhalte
 @app.callback(
     Output("tabs-GHA-out", "children"),
     Input("tabs-GHA", "value"),
@@ -318,6 +347,7 @@ def render_content(tab):
                 ],
                 style={"marginBottom": "20px"},
             ),
+            html.H4("Erste Hauptaufgabe"),
         ],
         id="pane-gha1",
         style=show1,
@@ -354,6 +384,7 @@ def render_content(tab):
                 ],
                 style={"marginBottom": "20px"},
             ),
+            html.H4("Zweite Hauptaufgabe"),
         ],
         id="pane-gha2",
         style=show2,
@@ -361,17 +392,341 @@ def render_content(tab):
 
     return html.Div([pane_gha1, pane_gha2])
 
+# Funktion zur Berechnung der Hauptaufgaben
+# @app.callback(
+#     Output("output-gha1", "children"),
+#     Output("output-gha2", "children"),
+#     Output("ellipsoid-plot", "figure"),
+#     Input("button-calc-gha1", "n_clicks"),
+#     Input("button-calc-gha2", "n_clicks"),
+#     State("input-GHA1-beta1", "value"),
+#     State("input-GHA1-lamb1", "value"),
+#     State("input-GHA1-s", "value"),
+#     State("input-GHA1-a", "value"),
+#     State("input-GHA2-beta1", "value"),
+#     State("input-GHA2-lamb1", "value"),
+#     State("input-GHA2-beta2", "value"),
+#     State("input-GHA2-lamb2", "value"),
+#     State("input-ax", "value"),
+#     State("input-ay", "value"),
+#     State("input-b", "value"),
+#     State("method-checklist-1", "value"),
+#     State("method-checklist-2", "value"),
+#
+#     prevent_initial_call=True,
+# )
+#
+# def calc_and_plot(n1, n2,
+#                   beta11, lamb11, s, a_deg,
+#                   beta21, lamb21, beta22, lamb22,
+#                   ax, ay, b, method1, method2):
+#
+#     if not (n1 or n2):
+#         return no_update, no_update, no_update
+#
+#     if not ax or not ay or not b:
+#         return html.Span("Bitte Ellipsoid auswählen!", style={"color": "red"}), "", go.Figure()
+#
+#     ell = EllipsoidTriaxial(ax, ay, b)
+#
+#     if dash.ctx.triggered_id == "button-calc-gha1":
+#         if None in (beta11, lamb11, s, a_deg):
+#
+#             return html.Span("Bitte β₁, λ₁, s und α eingeben.", style={"color": "red"}), "",  go.Figure()
+#
+#         beta_rad = wu.deg2rad(float(beta11))
+#         lamb_rad = wu.deg2rad(float(lamb11))
+#         alpha_rad = wu.deg2rad(float(a_deg))
+#         s_val = float(s)
+#
+#         p1 = tuple(map(float, ell.ell2cart(beta_rad, lamb_rad)))
+#         out1 = []
+#
+#         if "analytisch" in method1:
+#             # ana
+#             x2, y2, z2 = gha1_ana(ell, p1, alpha_rad, s_val, 70)
+#             p2_ana = (float(x2), float(y2), float(z2))
+#             beta2, lamb2 = ell.cart2ell([x2, y2, z2])
+#
+#             #out1 += f"kartesisch: x₂={p2[0]:.5f} m, y₂={p2[1]:.5f} m, z₂={p2[2]:.5f} m; ellipsoidisch: {aus.gms("β₂", beta2, 5)}, {aus.gms("λ₂", lamb2, 5)},"
+#             out1.append(
+#                 html.Div([
+#                     html.Strong("Analytisch: "),
+#                     html.Br(),
+#                     html.Span(f"kartesisch: x₂={x2:.4f} m, y₂={y2:.4f} m, z₂={z2:.4f} m"),
+#                     html.Br(),
+#                     html.Span(f"ellipsoidisch: {aus.gms('β₂', beta2, 4)}, {aus.gms('λ₂', lamb2, 4)}")
+#                 ])
+#             )
+#
+#         if "numerisch" in method1:
+#             # num
+#             x1, y1, z1, werte = gha1_num(ell, p1, alpha_rad, s_val, 10000)
+#             p2_num = x1, y1, z1
+#             beta2_num, lamb2_num = ell.cart2ell(p2_num)
+#
+#             out1.append(
+#                 html.Div([
+#                     html.Strong("Numerisch: "),
+#                     html.Br(),
+#                     html.Span(f"kartesisch: x₂={p2_num[0]:.4f} m, y₂={p2_num[1]:.4f} m, z₂={p2_num[2]:.4f} m"),
+#                     html.Br(),
+#                     html.Span(f"ellipsoidisch: {aus.gms('β₂', beta2_num, 4)}, {aus.gms('λ₂', lamb2_num, 4)}")
+#                 ])
+#             )
+#
+#             geo_line_num1 = []
+#             for x1, _, y1, _, z1, _ in werte:
+#                 geo_line_num1.append([x1, y1, z1])
+#
+#
+#         if "stochastisch" in method1:
+#             # stoch
+#             p2_stoch = "noch nicht implementiert.."
+#
+#             out1.append(
+#                 html.Div([
+#                     html.Strong("Stochastisch (ES): "),
+#                     html.Span(f"{p2_stoch}")
+#                 ])
+#             )
+#
+#         if not method1:
+#             return html.Span("Bitte Berechnungsverfahren auswählen!", style={"color": "red"}), "", go.Figure()
+#
+#         fig = ellipsoid_figure(ell, title="Erste Hauptaufgabe - analytisch")
+#         #fig = figure_constant_lines(fig, ell, "geod")
+#         fig = figure_constant_lines(fig, ell, "ell")
+#         #fig = figure_constant_lines(fig, ell, "para")
+#         if "analytisch" in method1:
+#             fig = figure_points(fig, [("P1", p1, "black"), ("P2", p2_ana, "red")])
+#         if "numerisch" in method1:
+#             fig = figure_lines(fig, geo_line_num1, "#ff8c00")
+#
+#         #out1 = f"kartesisch: x₂={p2[0]:.5f} m, y₂={p2[1]:.5f} m, z₂={p2[2]:.5f} m; ellipsoidisch: {aus.gms("β₂", beta2, 5)}, {aus.gms("λ₂", lamb2, 5)}, {p2_num}"
+#         return out1, "", fig
+#
+#     if dash.ctx.triggered_id == "button-calc-gha2":
+#         if None in (beta21, lamb21, beta22, lamb22):
+#             return html.Span("Bitte β₁, λ₁, β₂, λ₂ eingeben.", style={"color": "red"}), "", go.Figure()
+#
+#         p1 = tuple(ell.ell2cart(np.deg2rad(float(beta21)), np.deg2rad(float(lamb21))))
+#         p2 = tuple(ell.ell2cart(np.deg2rad(float(beta22)), np.deg2rad(float(lamb22))))
+#
+#         out2 = []
+#
+#         if "numerisch" in method2:
+#             alpha_1, alpha_2, s12, beta_arr, lamb_arr = gha2_num(
+#                 ell,
+#                 np.deg2rad(float(beta21)), np.deg2rad(float(lamb21)),
+#                 np.deg2rad(float(beta22)), np.deg2rad(float(lamb22))
+#             )
+#             geo_line_num = []
+#             for beta, lamb in zip(beta_arr, lamb_arr):
+#                 point = ell.ell2cart(beta, lamb)
+#                 geo_line_num.append(point)
+#
+#             out2.append(
+#                 html.Div([
+#                     html.Strong("Numerisch: "),
+#                     html.Span(f"{aus.gms('α₁₂', alpha_1, 4)}, {aus.gms('α₂₁', alpha_2, 4)}, s = {s12:.4f} m"),
+#                 ])
+#             )
+#
+#
+#         if "stochastisch" in method2:
+#             # stoch
+#             a_stoch = "noch nicht implementiert.."
+#
+#             out2.append(
+#                 html.Div([
+#                     html.Strong("Stochastisch (ES): "),
+#                     html.Span(f"{a_stoch}")
+#                 ])
+#             )
+#
+#         if not method2:
+#             return html.Span("Bitte Berechnungsverfahren auswählen!", style={"color": "red"}), "", go.Figure()
+#
+#         fig = ellipsoid_figure(ell, title="Zweite Hauptaufgabe")
+#         fig = figure_constant_lines(fig, ell, "ell")
+#         if "numerisch" in method2:
+#             fig = figure_lines(fig, geo_line_num, "#ff8c00")
+#         fig = figure_points(fig, [("P1", p1, "black"), ("P2", p2, "red")])
+#
+#
+#
+#         return "", out2, fig
+#
+#     return no_update, no_update, no_update
 
+# -- GHA 1 ---
 @app.callback(
-    Output("output-gha1", "children"),
+    Output("output-gha1-ana", "children"),
-    Output("output-gha2", "children"),
+    Output("store-gha1-ana", "data"),
-    Output("ellipsoid-plot", "figure"),
     Input("button-calc-gha1", "n_clicks"),
-    Input("button-calc-gha2", "n_clicks"),
     State("input-GHA1-beta1", "value"),
     State("input-GHA1-lamb1", "value"),
     State("input-GHA1-s", "value"),
     State("input-GHA1-a", "value"),
+    State("input-ax", "value"),
+    State("input-ay", "value"),
+    State("input-b", "value"),
+    State("method-checklist-1", "value"),
+    prevent_initial_call=True,
+)
+def compute_gha1_ana(n1, beta11, lamb11, s, a_deg, ax, ay, b, method1):
+    if not n1:
+        return no_update, no_update
+    if None in (ax, ay, b):
+        return html.Span("Bitte Ellipsoid wählen.", style={"color": "red"}), None
+    if None in (beta11, lamb11, s, a_deg):
+        return html.Span("Bitte β₁, λ₁, s und α eingeben.", style={"color": "red"}), None
+    if not method1:
+        return html.Span("Bitte Berechnungsverfahren wählen.", style={"color": "red"}), None
+    if "analytisch" not in (method1 or []):
+        return no_update, no_update
+
+
+    ell = EllipsoidTriaxial(ax, ay, b)
+    beta_rad = wu.deg2rad(float(beta11))
+    lamb_rad = wu.deg2rad(float(lamb11))
+    alpha_rad = wu.deg2rad(float(a_deg))
+    s_val = float(s)
+
+    p1 = tuple(map(float, ell.ell2cart(beta_rad, lamb_rad)))
+    x2, y2, z2 = gha1_ana(ell, p1, alpha_rad, s_val, 70)
+    p2 = (float(x2), float(y2), float(z2))
+    beta2, lamb2 = ell.cart2ell([x2, y2, z2])
+
+    out = html.Div([
+        html.Strong("Analytisch: "),
+        html.Br(),
+        html.Span(f"kartesisch: x₂={x2:.4f} m, y₂={y2:.4f} m, z₂={z2:.4f} m"),
+        html.Br(),
+        html.Span(f"ellipsoidisch: {aus.gms('β₂', beta2, 4)}, {aus.gms('λ₂', lamb2, 4)}"),
+        html.Br(),
+    ])
+
+    store = {
+        "points": [("P1", p1, "black"), ("P2", p2, "red")],
+        "polyline": None,
+        "color": "#d62728"
+    }
+    return out, store
+
+@app.callback(
+    Output("output-gha1-num", "children"),
+    Output("store-gha1-num", "data"),
+    Input("button-calc-gha1", "n_clicks"),
+    State("input-GHA1-beta1", "value"),
+    State("input-GHA1-lamb1", "value"),
+    State("input-GHA1-s", "value"),
+    State("input-GHA1-a", "value"),
+    State("input-ax", "value"),
+    State("input-ay", "value"),
+    State("input-b", "value"),
+    State("method-checklist-1", "value"),
+    prevent_initial_call=True,
+)
+def compute_gha1_num(n1, beta11, lamb11, s, a_deg, ax, ay, b, method1):
+    if not n1:
+        return no_update, no_update
+    if "numerisch" not in (method1 or []):
+        return no_update, no_update
+
+    ell = EllipsoidTriaxial(ax, ay, b)
+    beta_rad = wu.deg2rad(float(beta11))
+    lamb_rad = wu.deg2rad(float(lamb11))
+    alpha_rad = wu.deg2rad(float(a_deg))
+    s_val = float(s)
+
+    p1 = tuple(map(float, ell.ell2cart(beta_rad, lamb_rad)))
+
+    xN, yN, zN, werte = gha1_num(ell, p1, alpha_rad, s_val, 10000)
+    p2 = (xN, yN, zN)
+    beta2_num, lamb2_num = ell.cart2ell(p2)
+
+    out = html.Div([
+        html.Strong("Numerisch: "),
+        html.Br(),
+        html.Span(f"kartesisch: x₂={p2[0]:.4f} m, y₂={p2[1]:.4f} m, z₂={p2[2]:.4f} m"),
+        html.Br(),
+        html.Span(f"ellipsoidisch: {aus.gms('β₂', beta2_num, 4)}, {aus.gms('λ₂', lamb2_num, 4)}"),
+        html.Br(),
+    ])
+
+    polyline = [[x1, y1, z1] for x1, _, y1, _, z1, _ in werte]
+
+    store = {
+        "points": [("P1", p1, "black"), ("P2", p2, "#ff8c00")],
+        "polyline": polyline,
+        "color": "#ff8c00"
+    }
+    return out, store
+
+@app.callback(
+    Output("output-gha1-stoch", "children"),
+    Output("store-gha1-stoch", "data"),
+    Input("button-calc-gha1", "n_clicks"),
+    State("input-GHA1-beta1", "value"),
+    State("input-GHA1-lamb1", "value"),
+    State("input-GHA1-s", "value"),
+    State("input-GHA1-a", "value"),
+    State("input-ax", "value"),
+    State("input-ay", "value"),
+    State("input-b", "value"),
+    State("method-checklist-1", "value"),
+    prevent_initial_call=True,
+)
+def compute_gha1_stoch(n1, beta11, lamb11, s, a_deg, ax, ay, b, method1):
+    if not n1:
+        return no_update, no_update
+    if "stochastisch" not in (method1 or []):
+        return no_update, no_update
+
+    ell = EllipsoidTriaxial(ax, ay, b)
+    beta_rad = wu.deg2rad(float(beta11))
+    lamb_rad = wu.deg2rad(float(lamb11))
+    alpha_rad = wu.deg2rad(float(a_deg))
+    s_val = float(s)
+
+    betas, lambs, alphas, S_real = gha1_es(
+        beta_rad, lamb_rad, alpha_rad,
+        s_val,
+        10000,
+        ell,
+        sigma0=1e-10
+    )
+    beta2 = betas[-1]
+    lamb2 = lambs[-1]
+    alpha2 = alphas[-1]
+
+    p1 = ell.ell2cart(beta_rad, lamb_rad)
+    p2 = ell.ell2cart(beta2, lamb2)
+    x2, y2, z2 = p2[0], p2[1], p2[2]
+
+    out = html.Div([
+        html.Strong("Stochastisch: "),
+        html.Br(),
+        html.Span(f"kartesisch: x₂={x2:.4f} m, y₂={y2:.4f} m, z₂={z2:.4f} m"),
+        html.Br(),
+        html.Span(f"ellipsoidisch: {aus.gms('β₂', beta2, 4)}, {aus.gms('λ₂', lamb2, 4)}"),
+    ])
+
+    store = {
+        "points": [("P1", p1, "black"), ("P2", p2, "red")],
+        "polyline": None,
+        "color": "#d62728"
+    }
+    return out, store
+
+
+# --- GHA 2 ---
+@app.callback(
+    Output("output-gha2-num", "children"),
+    Output("store-gha2-num", "data"),
+    Input("button-calc-gha2", "n_clicks"),
     State("input-GHA2-beta1", "value"),
     State("input-GHA2-lamb1", "value"),
     State("input-GHA2-beta2", "value"),
@@ -379,163 +734,112 @@ def render_content(tab):
     State("input-ax", "value"),
     State("input-ay", "value"),
     State("input-b", "value"),
-    State("method-checklist-1", "value"),
     State("method-checklist-2", "value"),
-
     prevent_initial_call=True,
 )
-def calc_and_plot(n1, n2,
+def compute_gha2_num(n2, beta1, lamb1, beta2, lamb2, ax, ay, b, method2):
-                  beta11, lamb11, s, a_deg,
+    if not n2:
-                  beta21, lamb21, beta22, lamb22,
+        return no_update, no_update
-                  ax, ay, b, method1, method2):
+    if None in (ax, ay, b):
-
+        return html.Span("Bitte Ellipsoid wählen.", style={"color": "red"}), None
-    if not (n1 or n2):
+    if None in (beta1, lamb1, beta2, lamb2):
-        return no_update, no_update, no_update
+        return html.Span("Bitte β₁, λ₁, β₂ und λ₂ eingeben.", style={"color": "red"}), None
-
+    if not method2:
-    if not ax or not ay or not b:
+        return html.Span("Bitte Berechnungsverfahren wählen.", style={"color": "red"}), None
-        return html.Span("Bitte Ellipsoid auswählen!", style={"color": "red"}), "", go.Figure()
+    if "numerisch" not in (method2 or []):
+        return no_update, no_update
 
     ell = EllipsoidTriaxial(ax, ay, b)
 
-    if dash.ctx.triggered_id == "button-calc-gha1":
+    b1 = wu.deg2rad(float(beta1)); l1 = wu.deg2rad(float(lamb1))
-        if None in (beta11, lamb11, s, a_deg):
+    b2 = wu.deg2rad(float(beta2)); l2 = wu.deg2rad(float(lamb2))
 
-            return html.Span("Bitte β₁, λ₁, s und α eingeben.", style={"color": "red"}), "",  go.Figure()
+    p1 = tuple(map(float, ell.ell2cart(b1, l1)))
+    p2 = tuple(map(float, ell.ell2cart(b2, l2)))
 
-        beta_rad = wu.deg2rad(float(beta11))
+    alpha_1, alpha_2, s12, beta_arr, lamb_arr = gha2_num(ell, b1, l1, b2, l2)
-        lamb_rad = wu.deg2rad(float(lamb11))
-        alpha_rad = wu.deg2rad(float(a_deg))
-        s_val = float(s)
 
-        p1 = ell.ell2cart(beta_rad, lamb_rad)
+    # Polyline der Geodäte: [[x,y,z], ...]
-        out1 = []
+    polyline = []
+    for b_rad, l_rad in zip(beta_arr, lamb_arr):
+        x, y, z = ell.ell2cart(b_rad, l_rad)
+        polyline.append([float(x), float(y), float(z)])
 
-        if "analytisch" in method1:
+    out = html.Div([
-            # ana
+        html.Strong("Zweite Hauptaufgabe – Numerisch: "),
-            p2_ana, alpha2 = gha1_ana(ell, p1, alpha_rad, s_val, 70)
-            x2, y2, z2 = p2_ana
-            beta2, lamb2 = ell.cart2ell(p2_ana)
-
-            # out1 += f"kartesisch: x₂={p2[0]:.5f} m, y₂={p2[1]:.5f} m, z₂={p2[2]:.5f} m; ellipsoidisch: {aus.gms("β₂", beta2, 5)}, {aus.gms("λ₂", lamb2, 5)},"
-            out1.append(
-                html.Div([
-                    html.Strong("Analytisch: "),
-                    html.Br(),
-                    html.Span(f"kartesisch: x₂={x2:.4f} m, y₂={y2:.4f} m, z₂={z2:.4f} m"),
-                    html.Br(),
-                    html.Span(f"ellipsoidisch: {aus.gms('β₂', beta2, 4)}, {aus.gms('λ₂', lamb2, 4)}")
-                ])
-            )
-
-        if "numerisch" in method1:
-            # num
-            p2_num, alpha1, werte = gha1_num(ell, p1, alpha_rad, s_val, 10000, all_points=True)
-            beta2_num, lamb2_num = ell.cart2ell(p2_num)
-
-            out1.append(
-                html.Div([
-                    html.Strong("Numerisch: "),
-                    html.Br(),
-                    html.Span(f"kartesisch: x₂={p2_num[0]:.4f} m, y₂={p2_num[1]:.4f} m, z₂={p2_num[2]:.4f} m"),
-                    html.Br(),
-                    html.Span(f"ellipsoidisch: {aus.gms('β₂', beta2_num, 4)}, {aus.gms('λ₂', lamb2_num, 4)}")
-                ])
-            )
-
-            geo_line_num1 = []
-            for x1, _, y1, _, z1, _ in werte:
-                geo_line_num1.append([x1, y1, z1])
-
-        if "stochastisch" in method1:
-            # stoch
-            p2_stoch = "noch nicht implementiert.."
-
-            out1.append(
-                html.Div([
-                    html.Strong("Stochastisch (ES): "),
-                    html.Span(f"{p2_stoch}")
-                ])
-            )
-
-        if not method1:
-            return html.Span("Bitte Berechnungsverfahren auswählen!", style={"color": "red"}), "", go.Figure()
-
-        fig = ellipsoid_figure(ell, title="Erste Hauptaufgabe - analystisch")
-        # fig = figure_constant_lines(fig, ell, "geod")
-        fig = figure_constant_lines(fig, ell, "ell")
-        # fig = figure_constant_lines(fig, ell, "para")
-        if "analytisch" in method1:
-            fig = figure_points(fig, [("P1", p1, "black"), ("P2", p2_ana, "red")])
-        if "numerisch" in method1:
-            fig = figure_lines(fig, geo_line_num1, "#ff8c00")
-
-        # out1 = f"kartesisch: x₂={p2[0]:.5f} m, y₂={p2[1]:.5f} m, z₂={p2[2]:.5f} m; ellipsoidisch: {aus.gms("β₂", beta2, 5)}, {aus.gms("λ₂", lamb2, 5)}, {p2_num}"
-        return out1, "", fig
-
-    if dash.ctx.triggered_id == "button-calc-gha2":
-        if None in (beta21, lamb21, beta22, lamb22):
-            return html.Span("Bitte β₁, λ₁, β₂, λ₂ eingeben.", style={"color": "red"}), "", go.Figure()
-
-        p1 = tuple(ell.ell2cart(np.deg2rad(float(beta21)), np.deg2rad(float(lamb21))))
-        p2 = tuple(ell.ell2cart(np.deg2rad(float(beta22)), np.deg2rad(float(lamb22))))
-
-        out2 = []
-
-        if "numerisch" in method2:
-            alpha_1, alpha_2, s12, beta_arr, lamb_arr = gha2_num(
-                ell,
-                np.deg2rad(float(beta21)), np.deg2rad(float(lamb21)),
-                np.deg2rad(float(beta22)), np.deg2rad(float(lamb22)),
-                all_points=True
-            )
-            geo_line_num = []
-            for beta, lamb in zip(beta_arr, lamb_arr):
-                point = ell.ell2cart(beta, lamb)
-                geo_line_num.append(point)
-
-            out2.append(
-                html.Div([
-                    html.Strong("Numerisch: "),
         html.Span(f"{aus.gms('α₁₂', alpha_1, 4)}, {aus.gms('α₂₁', alpha_2, 4)}, s = {s12:.4f} m"),
     ])
-            )
 
-        if "stochastisch" in method2:
+    store = {
-            beta0 = np.deg2rad(float(beta21))
+        "points": [("P1", p1, "black"), ("P2", p2, "#1f77b4")],
-            lamb0 = np.deg2rad(float(lamb21))
+        "polyline": polyline,
-            beta1 = np.deg2rad(float(beta22))
+        "color": "#1f77b4",
-            lamb1 = np.deg2rad(float(lamb22))
+    }
-            alpha_1, alpha_2, s12, geo_line_es = gha2_ES(
+    return out, store
-                ell,
-                ell.ell2cart(beta0, lamb0),
-                ell.ell2cart(beta1, lamb1),
-                all_points=True
-            )
 
-            alpha_1 = 1
+# @app.callback(
-            alpha_2 = 2
+#     Output("output-gha2-stoch", "children"),
-            out2.append(
+#     Output("store-gha2-stoch", "data"),
-                html.Div([
+#     Input("button-calc-gha2", "n_clicks"),
-                    html.Strong("Stochastisch (ES): "),
+#     State("input-GHA2-beta1", "value"),
-                    html.Span(f"{aus.gms('α₁₂', alpha_1, 4)}, {aus.gms('α₂₁', alpha_2, 4)}, s = {s12:.4f} m"),
+#     State("input-GHA2-lamb1", "value"),
-                ])
+#     State("input-GHA2-beta2", "value"),
-            )
+#     State("input-GHA2-lamb2", "value"),
+#     State("input-ax", "value"),
+#     State("input-ay", "value"),
+#     State("input-b", "value"),
+#     State("method-checklist-2", "value"),
+#     prevent_initial_call=True,
+# )
+# def compute_gha2_stoch(n2, beta1, lamb1, beta2, lamb2, ax, ay, b, method2):
+#     if not n2:
+#         return no_update, no_update
+#     if "numerisch" not in (method2 or []):
+#         return no_update, no_update
+#
+#     out = html.Div([
+#         html.Strong("Zweite Hauptaufgabe – Stochastisch (ES): "),
+#         html.Span("noch nicht implementiert...")
+#     ])
+#
+#     return out, {"points": None, "polyline": None, "color": "#9467bd"}
 
+@app.callback(
+    Output("ellipsoid-plot", "figure"),
+    Input("input-ax", "value"),
+    Input("input-ay", "value"),
+    Input("input-b", "value"),
+    Input("store-gha1-ana", "data"),
+    Input("store-gha1-num", "data"),
+    Input("store-gha2-num", "data"),
+    Input("store-gha2-stoch", "data"),
+)
+def render_all(ax, ay, b, store_gha1_ana, store_gha1_num, store_gha2_num, store_gha2_stoch):
+    if None in (ax, ay, b):
+        return go.Figure()
 
-        if not method2:
+    ell = EllipsoidTriaxial(ax, ay, b)
-            return html.Span("Bitte Berechnungsverfahren auswählen!", style={"color": "red"}), "", go.Figure()
+    fig = ellipsoid_figure(ell, title="")
-
-        fig = ellipsoid_figure(ell, title="Zweite Hauptaufgabe")
     fig = figure_constant_lines(fig, ell, "ell")
-        if "numerisch" in method2:
-            fig = figure_lines(fig, geo_line_num, "#ff8c00")
-        if "stochastisch" in method2:
-            fig = figure_lines(fig, geo_line_es, "#ff8c00")
-        fig = figure_points(fig, [("P1", p1, "black"), ("P2", p2, "red")])
 
-        return "", out2, fig
+    def add_from_store(store):
+        if not store:
+            return
+        pts = store.get("points")
+        if pts:
+            fig = figure_points(fig, pts)
+        line = store.get("polyline")
+        if line:
+            fig = figure_lines(fig, line, store.get("color", "#ff8c00"))
+        return fig
+
+    for st in (store_gha1_ana, store_gha1_num, store_gha2_num, store_gha2_stoch):
+        res = add_from_store(st)
+        if res is not None:
+            fig = res
+
+    return fig
 
-    return no_update, no_update, no_update
 
 
 if __name__ == "__main__":