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nochmal

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Hendrik Möllersmann
2026-02-07 22:03:07 +01:00
parent 3fd967e843
commit 02ce0c0b4a
1 changed files with 242 additions and 206 deletions
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Tests/algorithms_test.ipynb
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@@ -3,8 +3,8 @@
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@@ -14,13 +14,13 @@
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@@ -56,13 +56,13 @@
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@@ -75,7 +75,7 @@
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@@ -88,13 +88,13 @@
"source": [ "source": [
"# dsPart = [60, 125, 600, 1250, 6000, 60000] entspricht bei der Erde ca. 100km, 50km, 10km, 5km, 1km, 100m\n", "# dsPart = [60, 125, 600, 1250, 6000, 60000] entspricht bei der Erde ca. 100km, 50km, 10km, 5km, 1km, 100m\n",
"\n", "\n",
"steps_gha1_num = [20, 50, 100, 200, 500, 1000, 5000]\n", "steps_gha1_num = [200, 500, 1000, 5000, 10000]\n",
"maxM_gha1_ana = [20, 50]\n", "maxM_gha1_ana = [20, 50, 80]\n",
"parts_gha1_ana = [2, 8]\n", "parts_gha1_ana = [2, 8, 32]\n",
"dsPart_gha1_ES = [60, 600, 1250]\n", "dsPart_gha1_ES = [60, 600, 1250]\n",
"dsPart_gha1_approx = [600, 1250, 6000]\n", "dsPart_gha1_approx = [600, 1250, 6000]\n",
"\n", "\n",
"steps_gha2_num = [200, 500, 1000]\n", "steps_gha2_num = [200, 500, 1000, 5000, 10000]\n",
"dsPart_gha2_ES = [60, 600, 1250]\n", "dsPart_gha2_ES = [60, 600, 1250]\n",
"dsPart_gha2_approx = [600, 1250, 6000]" "dsPart_gha2_approx = [600, 1250, 6000]"
], ],
@@ -105,224 +105,206 @@
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"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"# test = \"Karney\"\n", "test = \"Karney\"\n",
"# test = \"Panou\"\n", "# test = \"Panou\"\n",
"test = \"Random\"\n", "# test = \"Random\"\n",
"\n", "\n",
"if test == \"Karney\":\n", "def build_examples(test):\n",
" ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name(\"KarneyTest2024\")\n", " if test == \"Karney\":\n",
" examples = get_examples_karney(4, seed=42)\n", " ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name(\"KarneyTest2024\")\n",
"elif test == \"Panou\":\n", " examples = get_examples_karney(4, seed=42)\n",
" ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name(\"BursaSima1980round\")\n", " elif test == \"Panou\":\n",
" tables = get_tables_panou()\n", " ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name(\"BursaSima1980round\")\n",
" table_indices = []\n", " tables = get_tables_panou()\n",
" examples = []\n", " table_indices = []\n",
" for i, table in enumerate(tables):\n", " examples = []\n",
" for example in table:\n", " for i, table in enumerate(tables):\n",
" table_indices.append(i+1)\n", " for example in table:\n",
" examples.append(example)\n", " table_indices.append(i+1)\n",
"elif test == \"Random\":\n", " examples.append(example)\n",
" ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name(\"BursaSima1980round\")\n", " elif test == \"Random\":\n",
" examples = []\n", " ell: EllipsoidTriaxial = EllipsoidTriaxial.init_name(\"BursaSima1980round\")\n",
" random.seed(42)\n", " examples = []\n",
" for _ in range(50):\n", " random.seed(42)\n",
" beta0 = wu.deg2rad(random.randint(-90, 90))\n", " for _ in range(50):\n",
" lamb0 = wu.deg2rad(random.randint(-179, 180))\n", " beta0 = wu.deg2rad(random.randint(-90, 90))\n",
" alpha0_ell = wu.deg2rad(random.randint(0, 359))\n", " lamb0 = wu.deg2rad(random.randint(-179, 180))\n",
" s = random.randint(10000, int(np.pi*ell.b))\n", " alpha0_ell = wu.deg2rad(random.randint(0, 359))\n",
" examples.append([beta0, lamb0, alpha0_ell, s])\n", " s = random.randint(10000, int(np.pi*ell.b))\n",
" pass" " examples.append([beta0, lamb0, alpha0_ell, s])\n",
" pass\n",
" return examples\n",
"examples = build_examples(test)"
], ],
"id": "6770dbd57d475127", "id": "6770dbd57d475127",
"outputs": [], "outputs": [],
"execution_count": 9 "execution_count": 5
}, },
{ {
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"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"results = {}\n", "def execute_results(test, examples):\n",
"for i, example in enumerate(examples):\n", " results = {}\n",
" print(f\"----- Beispiel {i+1}/{len(examples)}\")\n", " for i, example in enumerate(examples):\n",
" example_results = {}\n", " print(f\"----- Beispiel {i+1}/{len(examples)}\")\n",
" example_results = {}\n",
"\n", "\n",
" if test != \"Random\":\n", " if test != \"Random\":\n",
" beta0, lamb0, alpha0_ell, beta1, lamb1, alpha1_ell, s = example\n", " beta0, lamb0, alpha0_ell, beta1, lamb1, alpha1_ell, s = example\n",
" P0 = ell.ell2cart(beta0, lamb0)\n", " P0 = ell.ell2cart(beta0, lamb0)\n",
" P1 = ell.ell2cart(beta1, lamb1)\n", " P1 = ell.ell2cart(beta1, lamb1)\n",
" _, _, alpha0_para = alpha_ell2para(ell, beta0, lamb0, alpha0_ell)\n", " _, _, alpha0_para = alpha_ell2para(ell, beta0, lamb0, alpha0_ell)\n",
" else:\n", " else:\n",
" beta0, lamb0, alpha0_ell, s = example\n", " beta0, lamb0, alpha0_ell, s = example\n",
" P0 = ell.ell2cart(beta0, lamb0)\n", " P0 = ell.ell2cart(beta0, lamb0)\n",
" _, _, alpha0_para = alpha_ell2para(ell, beta0, lamb0, alpha0_ell)\n", " _, _, alpha0_para = alpha_ell2para(ell, beta0, lamb0, alpha0_ell)\n",
"\n", "\n",
" # try:\n", " # try:\n",
" # P1, alpha1_para = gha1_ana(ell, P0, alpha0_para, s, maxM=80, maxPartCircum=8)\n", " # P1, alpha1_para = gha1_ana(ell, P0, alpha0_para, s, maxM=80, maxPartCircum=8)\n",
" # beta1, lamb1 = ell.cart2ell(P1)\n", " # beta1, lamb1 = ell.cart2ell(P1)\n",
" # u1, v1 = ell.cart2para(P1)\n", " # u1, v1 = ell.cart2para(P1)\n",
" # _, _, alpha1_ell = alpha_para2ell(ell, u1, v1, alpha1_para)\n", " # _, _, alpha1_ell = alpha_para2ell(ell, u1, v1, alpha1_para)\n",
" # except Exception as e:\n", " # except Exception as e:\n",
" # print(\"Referenz-Berechnung analytisch fehlgeschlagen: \", e)\n", " # print(\"Referenz-Berechnung analytisch fehlgeschlagen: \", e)\n",
" # continue\n", " # continue\n",
"\n", "\n",
" try:\n", " try:\n",
" P1, alpha1_ell = gha1_num(ell, P0, alpha0_ell, s, num=10000)\n", " P1, alpha1_ell = gha1_num(ell, P0, alpha0_ell, s, num=10000)\n",
" beta1, lamb1 = ell.cart2ell(P1)\n", " beta1, lamb1 = ell.cart2ell(P1)\n",
" except Exception as e:\n", " except Exception as e:\n",
" print(\"Referenz-Berechnung numerisch fehlgeschlagen: \", e)\n", " print(\"Referenz-Berechnung numerisch fehlgeschlagen: \", e)\n",
" continue\n", " continue\n",
"\n", "\n",
" for steps in steps_gha1_num:\n", " for steps in steps_gha1_num:\n",
" start = time.perf_counter()\n",
" try:\n",
" P1_num, alpha1_num_1 = gha1_num(ell, P0, alpha0_ell, s, num=steps)\n",
" print(f\"GHA1_num_{steps}\", P1_num)\n",
" end = time.perf_counter()\n",
" beta1_num, lamb1_num = ell.cart2ell(P1_num)\n",
" d_beta1 = abs(beta1_num - beta1)\n",
" d_lamb1 = abs(lamb1_num - lamb1)\n",
" d_alpha1 = abs(alpha1_num_1 - alpha1_ell)\n",
" d_time = end - start\n",
" example_results[f\"GHA1_num_{steps}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n",
" except Exception as e:\n",
" print(e)\n",
" example_results[f\"GHA1_num_{steps}\"] = (nan, nan, nan, nan)\n",
"\n",
" for maxM in maxM_gha1_ana:\n",
" for parts in parts_gha1_ana:\n",
" start = time.perf_counter()\n", " start = time.perf_counter()\n",
" try:\n", " try:\n",
" P1_ana, alpha1_ana_para = gha1_ana(ell, P0, alpha0_para, s, maxM=maxM, maxPartCircum=parts)\n", " P1_num, alpha1_num_1 = gha1_num(ell, P0, alpha0_ell, s, num=steps)\n",
" print(f\"GHA1_num_{steps}\", P1_num)\n",
" end = time.perf_counter()\n", " end = time.perf_counter()\n",
" beta1_ana, lamb1_ana = ell.cart2ell(P1_ana)\n", " beta1_num, lamb1_num = ell.cart2ell(P1_num)\n",
" u1_ana, v1_ana = ell.cart2para(P1_ana)\n", " d_beta1 = abs(beta1_num - beta1)\n",
" _, _, alpha1_ana_ell = alpha_para2ell(ell, u1_ana, v1_ana, alpha1_ana_para)\n", " d_lamb1 = abs(lamb1_num - lamb1)\n",
" d_beta1 = abs(beta1_ana - beta1)\n", " d_alpha1 = abs(alpha1_num_1 - alpha1_ell)\n",
" d_lamb1 = abs(lamb1_ana - lamb1)\n",
" d_alpha1 = abs(alpha1_ana_ell - alpha1_ell)\n",
" d_time = end - start\n", " d_time = end - start\n",
" example_results[f\"GHA1_ana_{maxM}_{parts}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n", " example_results[f\"GHA1_num_{steps}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n",
" except Exception as e:\n", " except Exception as e:\n",
" print(e)\n", " print(e)\n",
" example_results[f\"GHA1_ana_{maxM}_{parts}\"] = (nan, nan, nan, nan)\n", " example_results[f\"GHA1_num_{steps}\"] = (nan, nan, nan, nan)\n",
"\n", "\n",
" for dsPart in dsPart_gha1_ES:\n", " for maxM in maxM_gha1_ana:\n",
" ds = ell.ax/dsPart\n", " for parts in parts_gha1_ana:\n",
" start = time.perf_counter()\n", " start = time.perf_counter()\n",
" try:\n", " try:\n",
" P1_ES, alpha1_ES = gha1_ES(ell, beta0, lamb0, alpha0_ell, s, maxSegLen=ds)\n", " P1_ana, alpha1_ana_para = gha1_ana(ell, P0, alpha0_para, s, maxM=maxM, maxPartCircum=parts)\n",
" end = time.perf_counter()\n", " end = time.perf_counter()\n",
" beta1_ES, lamb1_ES = ell.cart2ell(P1_ES)\n", " beta1_ana, lamb1_ana = ell.cart2ell(P1_ana)\n",
" d_beta1 = abs(beta1_ES - beta1)\n", " u1_ana, v1_ana = ell.cart2para(P1_ana)\n",
" d_lamb1 = abs(lamb1_ES - lamb1)\n", " _, _, alpha1_ana_ell = alpha_para2ell(ell, u1_ana, v1_ana, alpha1_ana_para)\n",
" d_alpha1 = abs(alpha1_ES - alpha1_ell)\n", " d_beta1 = abs(beta1_ana - beta1)\n",
" d_time = end - start\n", " d_lamb1 = abs(lamb1_ana - lamb1)\n",
" example_results[f\"GHA1_ES_{dsPart}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n", " d_alpha1 = abs(alpha1_ana_ell - alpha1_ell)\n",
" except Exception as e:\n", " d_time = end - start\n",
" print(e)\n", " example_results[f\"GHA1_ana_{maxM}_{parts}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n",
" example_results[f\"GHA1_ES_{dsPart}\"] = (nan, nan, nan, nan)\n", " except Exception as e:\n",
" print(e)\n",
" example_results[f\"GHA1_ana_{maxM}_{parts}\"] = (nan, nan, nan, nan)\n",
"\n", "\n",
" for dsPart in dsPart_gha1_approx:\n", " for dsPart in dsPart_gha1_ES:\n",
" ds = ell.ax/dsPart\n", " ds = ell.ax/dsPart\n",
" start = time.perf_counter()\n", " start = time.perf_counter()\n",
" try:\n", " try:\n",
" P1_approx, alpha1_approx = gha1_approx(ell, P0, alpha0_ell, s, ds=ds)\n", " P1_ES, alpha1_ES = gha1_ES(ell, beta0, lamb0, alpha0_ell, s, maxSegLen=ds)\n",
" end = time.perf_counter()\n", " end = time.perf_counter()\n",
" beta1_approx, lamb1_approx = ell.cart2ell(P1_approx)\n", " beta1_ES, lamb1_ES = ell.cart2ell(P1_ES)\n",
" d_beta1 = abs(beta1_approx - beta1)\n", " d_beta1 = abs(beta1_ES - beta1)\n",
" d_lamb1 = abs(lamb1_approx - lamb1)\n", " d_lamb1 = abs(lamb1_ES - lamb1)\n",
" d_alpha1 = abs(alpha1_approx - alpha1_ell)\n", " d_alpha1 = abs(alpha1_ES - alpha1_ell)\n",
" d_time = end - start\n", " d_time = end - start\n",
" example_results[f\"GHA1_approx_{dsPart}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n", " example_results[f\"GHA1_ES_{dsPart}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n",
" except Exception as e:\n", " except Exception as e:\n",
" print(e)\n", " print(e)\n",
" example_results[f\"GHA1_approx_{dsPart}\"] = (nan, nan, nan, nan)\n", " example_results[f\"GHA1_ES_{dsPart}\"] = (nan, nan, nan, nan)\n",
"\n", "\n",
" # ----------------------------------------------\n", " for dsPart in dsPart_gha1_approx:\n",
" ds = ell.ax/dsPart\n",
" start = time.perf_counter()\n",
" try:\n",
" P1_approx, alpha1_approx = gha1_approx(ell, P0, alpha0_ell, s, ds=ds)\n",
" end = time.perf_counter()\n",
" beta1_approx, lamb1_approx = ell.cart2ell(P1_approx)\n",
" d_beta1 = abs(beta1_approx - beta1)\n",
" d_lamb1 = abs(lamb1_approx - lamb1)\n",
" d_alpha1 = abs(alpha1_approx - alpha1_ell)\n",
" d_time = end - start\n",
" example_results[f\"GHA1_approx_{dsPart}\"] = (d_beta1, d_lamb1, d_alpha1, d_time)\n",
" except Exception as e:\n",
" print(e)\n",
" example_results[f\"GHA1_approx_{dsPart}\"] = (nan, nan, nan, nan)\n",
"\n", "\n",
" for steps in steps_gha2_num:\n", " # ----------------------------------------------\n",
" start = time.perf_counter()\n",
" try:\n",
" with warnings.catch_warnings():\n",
" warnings.simplefilter(\"ignore\", RuntimeWarning)\n",
" alpha0_num, alpha1_num_2, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=steps)\n",
" print(alpha0_num, alpha1_num_2, s_num)\n",
" end = time.perf_counter()\n",
" d_alpha0 = abs(alpha0_num - alpha0_ell)\n",
" d_alpha1 = abs(alpha1_num_2 - alpha1_ell)\n",
" d_s = abs(s_num - s)\n",
" d_time = end - start\n",
" example_results[f\"GHA2_num_{steps}\"] = (d_alpha0, d_alpha1, d_s, d_time)\n",
" except Exception as e:\n",
" print(e)\n",
" example_results[f\"GHA2_num_{steps}\"] = (nan, nan, nan, nan)\n",
"\n", "\n",
" for dsPart in dsPart_gha2_ES:\n", " for steps in steps_gha2_num:\n",
" ds = ell.ax/dsPart\n", " start = time.perf_counter()\n",
" start = time.perf_counter()\n", " try:\n",
" try:\n", " with warnings.catch_warnings():\n",
" with suppress_print():\n", " warnings.simplefilter(\"ignore\", RuntimeWarning)\n",
" alpha0_ES, alpha1_ES, s_ES = gha2_ES(ell, P0, P1, maxSegLen=ds)\n", " alpha0_num, alpha1_num_2, s_num = gha2_num(ell, beta0, lamb0, beta1, lamb1, n=steps)\n",
" end = time.perf_counter()\n", " print(alpha0_num, alpha1_num_2, s_num)\n",
" d_alpha0 = abs(alpha0_ES - alpha0_ell)\n", " end = time.perf_counter()\n",
" d_alpha1 = abs(alpha1_ES - alpha1_ell)\n", " d_alpha0 = abs(alpha0_num - alpha0_ell)\n",
" d_s = abs(s_ES - s)\n", " d_alpha1 = abs(alpha1_num_2 - alpha1_ell)\n",
" d_time = end - start\n", " d_s = abs(s_num - s)\n",
" example_results[f\"GHA2_ES_{dsPart}\"] = (d_alpha0, d_alpha1, d_s, d_time)\n", " d_time = end - start\n",
" except Exception as e:\n", " example_results[f\"GHA2_num_{steps}\"] = (d_alpha0, d_alpha1, d_s, d_time)\n",
" print(e)\n", " except Exception as e:\n",
" example_results[f\"GHA2_ES_{dsPart}\"] = (nan, nan, nan, nan)\n", " print(e)\n",
" example_results[f\"GHA2_num_{steps}\"] = (nan, nan, nan, nan)\n",
"\n", "\n",
" for dsPart in dsPart_gha2_approx:\n", " for dsPart in dsPart_gha2_ES:\n",
" ds = ell.ax/dsPart\n", " ds = ell.ax/dsPart\n",
" start = time.perf_counter()\n", " start = time.perf_counter()\n",
" try:\n", " try:\n",
" alpha0_approx, alpha1_approx, s_approx = gha2_approx(ell, P0, P1, ds=ds)\n", " with suppress_print():\n",
" end = time.perf_counter()\n", " alpha0_ES, alpha1_ES, s_ES = gha2_ES(ell, P0, P1, maxSegLen=ds)\n",
" d_alpha0 = abs(alpha0_approx - alpha0_ell)\n", " end = time.perf_counter()\n",
" d_alpha1 = abs(alpha1_approx - alpha1_ell)\n", " d_alpha0 = abs(alpha0_ES - alpha0_ell)\n",
" d_s = abs(s_approx - s)\n", " d_alpha1 = abs(alpha1_ES - alpha1_ell)\n",
" d_time = end - start\n", " d_s = abs(s_ES - s)\n",
" example_results[f\"GHA2_approx_{dsPart}\"] = (d_alpha0, d_alpha1, d_s, d_time)\n", " d_time = end - start\n",
" except Exception as e:\n", " example_results[f\"GHA2_ES_{dsPart}\"] = (d_alpha0, d_alpha1, d_s, d_time)\n",
" print(e)\n", " except Exception as e:\n",
" example_results[f\"GHA2_approx_{dsPart}\"] = (nan, nan, nan, nan)\n", " print(e)\n",
" example_results[f\"GHA2_ES_{dsPart}\"] = (nan, nan, nan, nan)\n",
"\n", "\n",
" results[f\"beta0: {wu.rad2deg(beta0):.3f}, lamb0: {wu.rad2deg(lamb0):.3f}, alpha0: {wu.rad2deg(alpha0_ell):.3f}, s: {s}\"] = example_results" " for dsPart in dsPart_gha2_approx:\n",
" ds = ell.ax/dsPart\n",
" start = time.perf_counter()\n",
" try:\n",
" alpha0_approx, alpha1_approx, s_approx = gha2_approx(ell, P0, P1, ds=ds)\n",
" end = time.perf_counter()\n",
" d_alpha0 = abs(alpha0_approx - alpha0_ell)\n",
" d_alpha1 = abs(alpha1_approx - alpha1_ell)\n",
" d_s = abs(s_approx - s)\n",
" d_time = end - start\n",
" example_results[f\"GHA2_approx_{dsPart}\"] = (d_alpha0, d_alpha1, d_s, d_time)\n",
" except Exception as e:\n",
" print(e)\n",
" example_results[f\"GHA2_approx_{dsPart}\"] = (nan, nan, nan, nan)\n",
"\n",
" results[f\"beta0: {wu.rad2deg(beta0):.3f}, lamb0: {wu.rad2deg(lamb0):.3f}, alpha0: {wu.rad2deg(alpha0_ell):.3f}, s: {s}\"] = example_results\n",
" return results\n",
"results = execute_results(test, examples)"
], ],
"id": "fc45e0f618a0e4d8", "id": "fc45e0f618a0e4d8",
"outputs": [ "outputs": [],
{ "execution_count": null
"name": "stdout",
"output_type": "stream",
"text": [
"----- Beispiel 1/4\n",
"----- Beispiel 2/4\n",
"----- Beispiel 3/4\n",
"Analytische Methode ist explodiert, Punkt liegt nicht mehr auf dem Ellipsoid\n",
"Analytische Methode ist explodiert, Punkt liegt nicht mehr auf dem Ellipsoid\n",
"Analytische Methode ist explodiert, Punkt liegt nicht mehr auf dem Ellipsoid\n",
"Fehler in der Umrechnung cart2ell\n",
"----- Beispiel 4/4\n",
"Analytische Methode ist explodiert, Punkt liegt nicht mehr auf dem Ellipsoid\n",
"Analytische Methode ist explodiert, Punkt liegt nicht mehr auf dem Ellipsoid\n",
"Analytische Methode ist explodiert, Punkt liegt nicht mehr auf dem Ellipsoid\n",
"Fehler in der Umrechnung cart2ell\n"
]
}
],
"execution_count": 15
}, },
{ {
"metadata": {}, "metadata": {},
@@ -330,31 +312,85 @@
"outputs": [], "outputs": [],
"execution_count": null, "execution_count": null,
"source": [ "source": [
"# with open(f\"gha_results{test}.pkl\", \"wb\") as f:\n", "def save_results(test, results):\n",
"# pickle.dump(results, f)" " with open(f\"gha_results{test}.pkl\", \"wb\") as f:\n",
" pickle.dump(results, f)\n",
"# save_results(test, results)"
], ],
"id": "74fbd4d33c288839" "id": "74fbd4d33c288839"
}, },
{
"metadata": {},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": [
"test = \"Panou\"\n",
"examples_panou = build_examples(test)\n",
"results_panou = execute_results(test, examples_panou)\n",
"save_results(test, results_panou)"
],
"id": "58697308664fa539"
},
{
"metadata": {},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": [
"test = \"Karney\"\n",
"examples_karney = build_examples(test)\n",
"results_karney = execute_results(test, examples_karney)\n",
"save_results(test, results_karney)"
],
"id": "5d35a01ba8d6e2b1"
},
{
"metadata": {},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": [
"test = \"Random\"\n",
"examples_random = build_examples(test)\n",
"results_random = execute_results(test, examples_random)\n",
"save_results(test, results_random)"
],
"id": "848eab44283945c6"
},
{ {
"metadata": { "metadata": {
"ExecuteTime": { "ExecuteTime": {
"end_time": "2026-02-06T21:26:49.148361Z", "end_time": "2026-02-07T21:00:12.376487Z",
"start_time": "2026-02-06T21:26:48.975151Z" "start_time": "2026-02-07T21:00:12.071794Z"
} }
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"with open(f\"gha_results{test}.pkl\", \"rb\") as f:\n", "with open(f\"gha_results{test}_all.pkl\", \"rb\") as f:\n",
" results = pickle.load(f)" " results = pickle.load(f)"
], ],
"id": "4c20a0579c0f7038", "id": "4c20a0579c0f7038",
"outputs": [], "outputs": [
{
"ename": "FileNotFoundError",
"evalue": "[Errno 2] No such file or directory: 'gha_resultsKarney.pkl'",
"output_type": "error",
"traceback": [
"\u001B[31m---------------------------------------------------------------------------\u001B[39m",
"\u001B[31mFileNotFoundError\u001B[39m Traceback (most recent call last)",
"\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[6]\u001B[39m\u001B[32m, line 1\u001B[39m\n\u001B[32m----> \u001B[39m\u001B[32m1\u001B[39m \u001B[38;5;28;01mwith\u001B[39;00m \u001B[38;5;28;43mopen\u001B[39;49m\u001B[43m(\u001B[49m\u001B[33;43mf\u001B[39;49m\u001B[33;43m\"\u001B[39;49m\u001B[33;43mgha_results\u001B[39;49m\u001B[38;5;132;43;01m{\u001B[39;49;00m\u001B[43mtest\u001B[49m\u001B[38;5;132;43;01m}\u001B[39;49;00m\u001B[33;43m.pkl\u001B[39;49m\u001B[33;43m\"\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[33;43m\"\u001B[39;49m\u001B[33;43mrb\u001B[39;49m\u001B[33;43m\"\u001B[39;49m\u001B[43m)\u001B[49m \u001B[38;5;28;01mas\u001B[39;00m f:\n\u001B[32m 2\u001B[39m results = pickle.load(f)\n",
"\u001B[36mFile \u001B[39m\u001B[32m~\\PythonInterpreter\\Lib\\site-packages\\IPython\\core\\interactiveshell.py:343\u001B[39m, in \u001B[36m_modified_open\u001B[39m\u001B[34m(file, *args, **kwargs)\u001B[39m\n\u001B[32m 336\u001B[39m \u001B[38;5;28;01mif\u001B[39;00m file \u001B[38;5;129;01min\u001B[39;00m {\u001B[32m0\u001B[39m, \u001B[32m1\u001B[39m, \u001B[32m2\u001B[39m}:\n\u001B[32m 337\u001B[39m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\n\u001B[32m 338\u001B[39m \u001B[33mf\u001B[39m\u001B[33m\"\u001B[39m\u001B[33mIPython won\u001B[39m\u001B[33m'\u001B[39m\u001B[33mt let you open fd=\u001B[39m\u001B[38;5;132;01m{\u001B[39;00mfile\u001B[38;5;132;01m}\u001B[39;00m\u001B[33m by default \u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m 339\u001B[39m \u001B[33m\"\u001B[39m\u001B[33mas it is likely to crash IPython. If you know what you are doing, \u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m 340\u001B[39m \u001B[33m\"\u001B[39m\u001B[33myou can use builtins\u001B[39m\u001B[33m'\u001B[39m\u001B[33m open.\u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m 341\u001B[39m )\n\u001B[32m--> \u001B[39m\u001B[32m343\u001B[39m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mio_open\u001B[49m\u001B[43m(\u001B[49m\u001B[43mfile\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43m*\u001B[49m\u001B[43margs\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43m*\u001B[49m\u001B[43m*\u001B[49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n",
"\u001B[31mFileNotFoundError\u001B[39m: [Errno 2] No such file or directory: 'gha_resultsKarney.pkl'"
]
}
],
"execution_count": 6 "execution_count": 6
}, },
{ {
"metadata": { "metadata": {
"ExecuteTime": { "ExecuteTime": {
"end_time": "2026-02-07T17:02:37.451141Z", "end_time": "2026-02-07T20:59:54.841038500Z",
"start_time": "2026-02-07T17:02:15.854020Z" "start_time": "2026-02-07T17:02:15.854020Z"
} }
}, },