Umrechnungs-Test, Tabellen

conversions_test.py

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+import time
+import pickle
+import numpy as np
+from numpy import nan
+import winkelumrechnungen as wu
+import os
+from contextlib import contextmanager, redirect_stdout, redirect_stderr
+from itertools import product
+import pandas as pd
+
+from ellipsoide import EllipsoidTriaxial
+
+# ellips = "KarneyTest2024"
+# ellips = "BursaSima1980"
+ellips = "Fiction"
+
+ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name(ellips)
+
+
+def deg_range(start, stop, step):
+    return [float(x) for x in range(start, stop + step, step)]
+
+def asymptotic_range(start, direction="up", max_decimals=4):
+    values = []
+    for d in range(0, max_decimals + 1):
+        step = 10 ** -d
+        if direction == "up":
+            values.append(start + (1 - step))
+        else:
+            values.append(start - (1 - step))
+    return values
+
+
+beta_5_85 = deg_range(5, 85, 5)
+lambda_5_85 = deg_range(5, 85, 5)
+
+beta_5_90 = deg_range(5, 90, 5)
+lambda_5_90 = deg_range(5, 90, 5)
+
+beta_0_90 = deg_range(0, 90, 5)
+lambda_0_90 = deg_range(0, 90, 5)
+
+beta_90 = [90.0]
+lambda_90 = [90.0]
+beta_0 = [0.0]
+lambda_0 = [0.0]
+
+beta_asym_89 = asymptotic_range(89.0, direction="up")
+lambda_asym_0 = asymptotic_range(1.0, direction="down")
+
+groups = {
+    1: list(product(beta_5_85, lambda_5_85)),
+    # 2: list(product(beta_0, lambda_0_90)),
+    # 3: list(product(beta_5_85, lambda_0)),
+    # 4: list(product(beta_90, lambda_5_90)),
+    # 5: list(product(beta_asym_89, lambda_asym_0)),
+    # 6: list(product(beta_5_85, lambda_90)),
+    7: list(product(lambda_asym_0, lambda_0_90)),
+    # 8: list(product(beta_0_90, lambda_asym_0)),
+    # 9: list(product(beta_asym_89, lambda_0_90)),
+    # 10: list(product(beta_0_90, beta_asym_89)),
+}
+
+for nr, points in groups.items():
+    points_cart = []
+    for point in points:
+        beta, lamb = point
+        cart = ell.ell2cart(wu.deg2rad(beta), wu.deg2rad(lamb))
+        points_cart.append(cart)
+    groups[nr] = points_cart
+
+results = {}
+
+for nr, points in groups.items():
+    group_results = {"ell": [],
+                     "para": [],
+                     "geod": []}
+    for point in points:
+        elli = ell.cart2ell(point)
+        cart_elli = ell.ell2cart(elli[0], elli[1])
+        group_results["ell"].append(np.linalg.norm(point - cart_elli, axis=-1))
+
+        para = ell.cart2para(point)
+        cart_para = ell.para2cart(para[0], para[1])
+        group_results["para"].append(np.linalg.norm(point - cart_para, axis=-1))
+
+        geod = ell.cart2geod(point, "ligas3")
+        cart_geod = ell.geod2cart(geod[0], geod[1], geod[2])
+        group_results["geod"].append(np.linalg.norm(point - cart_geod, axis=-1))
+
+    group_results["ell"] = np.array(group_results["ell"])
+    group_results["para"] = np.array(group_results["para"])
+    group_results["geod"] = np.array(group_results["geod"])
+    results[nr] = group_results
+
+with open(f"conversion_results_{ellips}.pkl", "wb") as f:
+    pickle.dump(results, f)
+
+df = pd.DataFrame({
+    "Gruppe": [nr for nr in results.keys()],
+    "max_Δr_ell": [f"{max(result["ell"]):.3g}" for result in results.values()],
+    "max_Δr_para": [f"{max(result["para"]):.3g}" for result in results.values()],
+    "max_Δr_geod": [f"{max(result["geod"]):.3g}" for result in results.values()]
+})
+
+print(df)