From 17a59b031022d92b9972635e29de7fadd8d2fc36 Mon Sep 17 00:00:00 2001 From: Alex Date: Wed, 16 Sep 2026 10:51:26 +0200 Subject: [PATCH 1/7] Updated optuna study Reduces the parameter ranges for aberration coefficient and particle radii, removed optical axis position parameter from the Optuna search. --- ...27_characterizing_aberrations_optuna.ipynb | 1160 +++++++++-------- 1 file changed, 600 insertions(+), 560 deletions(-) diff --git a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb index 01aba69e..a3034068 100644 --- a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb +++ b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "ab9551f3", "metadata": {}, "outputs": [], @@ -40,10 +40,18 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 4, "id": "3f8be954", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0916 10:43:52.960000 25208 Lib\\site-packages\\torch\\utils\\flop_counter.py:29] triton not found; flop counting will not work for triton kernels\n" + ] + } + ], "source": [ "import random\n", "\n", @@ -62,14 +70,14 @@ "\n", "Here you gather all aberration types that DeepTrack2 can simulate into a list. \n", "\n", - "Aberrations in DeepTrack2 are wrappers of the more general `Zernike` feature, which introduces a phase to the pupil function based on the normalized Zernike polynomials. The property `coefficient` is a multiplier for the respective poynomial in the set of Zernike polynomials.\n", + "Aberrations in DeepTrack2 are wrappers of the more general `Zernike` feature, which introduces a phase to the pupil function based on the normalized Zernike polynomials. The property `coefficient` is a multiplier for the respective polynomial in the set of Zernike polynomials.\n", "\n", "See more details in [DTATo40_aberrations](../3-advanced-topics/DTATo40_aberrations.ipynb)." ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "id": "5b6e4fa0", "metadata": {}, "outputs": [], @@ -100,12 +108,12 @@ "\n", "* `optics`: Flourescence microscope with a pixel size of 0.1 microns and a 256x256 camera.\n", "\n", - "* `particle`: Spherical particle centered in the image with 1 micrometer radius.\n" + "* `particle`: Spherical particle centered in the image with 1e-6 meter radius.\n" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "id": "c183996e", "metadata": {}, "outputs": [], @@ -114,7 +122,7 @@ "\n", "# Define optics.\n", "optics = dt.Fluorescence(\n", - " magnification=10,\n", + " magnification=15,\n", " resolution=1e-6,\n", " wavelength=660e-9,\n", " output_region=(0, 0, IMAGE_SIZE, IMAGE_SIZE),\n", @@ -140,7 +148,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "79467d93", "metadata": {}, "outputs": [], @@ -149,7 +157,7 @@ "aberration = random.choice(aberration_types)\n", "\n", "# Pick a random aberration strength.\n", - "aberration = aberration(coefficient=lambda: (2 * np.random.rand() - 1) * 8)\n", + "aberration = aberration(coefficient=lambda: (2 * np.random.rand() - 1) * 4)\n", "\n", "# Modify the pupil of the microscope with the aberration.\n", "optics.pupil = aberration" @@ -165,7 +173,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "id": "db21e1da", "metadata": {}, "outputs": [ @@ -173,15 +181,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Name: HorizontalComa\n", - "Coefficient: 1.7301442345449196\n", + "Name: Defocus\n", + "Coefficient: 3.7549835225874\n", "Radius: 1e-06\n", - "Z: 0.0\n" + "\n" ] }, { "data": { - "image/png": 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", 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", 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" ] @@ -199,7 +207,6 @@ " f\"Name: {aberration.name()}\\n\"\n", " f\"Coefficient: {aberration.coefficient()}\\n\"\n", " f\"Radius: {particle.radius()}\\n\"\n", - " f\"Z: {particle.z()}\"\n", ")" ] }, @@ -218,16 +225,15 @@ "\n", "* Aberration category\n", "\n", - "* Aberration coefficient\n", - "\n", - "* Particle radii\n", + "* Aberration strength coefficient\n", "\n", - "* Z position of the particle (along the optical axis)\n" + "* Particle radii in meters\n", + "\n" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "id": "dc6d40e2", "metadata": {}, "outputs": [], @@ -236,7 +242,6 @@ " aberration_candidate, # Aberration category\n", " coefficient, # Aberration coefficient\n", " radius, # Particle radii\n", - " z, # Z position\n", "):\n", " # Get the aberration type and modify the pupil.\n", " simulated_aberration = aberration_candidate(coefficient=coefficient)\n", @@ -245,7 +250,7 @@ " # Instance the particle with the trial parameters.\n", " particle = dt.Sphere(\n", " radius=radius,\n", - " position=(IMAGE_SIZE // 2, IMAGE_SIZE // 2, z),\n", + " position=(IMAGE_SIZE // 2, IMAGE_SIZE // 2),\n", " intensity=1,\n", " )\n", "\n", @@ -267,7 +272,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "id": "14800637", "metadata": {}, "outputs": [], @@ -284,24 +289,26 @@ " )\n", "\n", " # Varies aberration strength.\n", - " coefficient = trial.suggest_float(\"coefficient\", -10, 10)\n", + " coefficient = trial.suggest_float(\"coefficient\", -4, 4)\n", "\n", " # Varies particle radius.\n", - " radius = trial.suggest_float(\"radius\", 1e-7, 2.1e-6)\n", - "\n", - " # Varies particle z-position.\n", - " z = trial.suggest_float(\"z\", -1, 1)\n", + " radius = trial.suggest_float(\"radius\", 0.8e-7, 1.2e-6)\n", "\n", " # Generates a simulated image with the parameters.\n", " simulated_image = simulate_aberrated_image(\n", " aberration_type,\n", " coefficient,\n", " radius,\n", - " z,\n", " )\n", "\n", " # Pixel-wise RMSE comparison between the reference and the simulated image.\n", - " loss = np.sqrt(np.mean(np.square(simulated_image - reference_image)))\n", + " loss = np.sqrt(\n", + " np.mean(\n", + " np.square(\n", + " simulated_image - reference_image\n", + " )\n", + " )\n", + " )\n", "\n", " return loss" ] @@ -318,7 +325,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "id": "bb23a687", "metadata": {}, "outputs": [ @@ -326,515 +333,515 @@ "name": "stderr", "output_type": "stream", "text": [ - "\u001b[32m[I 2026-06-18 22:24:10,436]\u001b[0m A new study created in memory with name: no-name-ba3494c1-d230-4d20-b22c-9560a2f277c7\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:10,584]\u001b[0m Trial 0 finished with value: 0.05396707412212997 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 2.6897167312905985, 'radius': 1.7760061614870141e-06, 'z': -0.064457224829926}. Best is trial 0 with value: 0.05396707412212997.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:10,666]\u001b[0m Trial 1 finished with value: 0.010852049919941337 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -3.1563378273746245, 'radius': 1.0568372391654512e-06, 'z': 0.6374068346508261}. Best is trial 1 with value: 0.010852049919941337.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:10,843]\u001b[0m Trial 2 finished with value: 0.05518128522898776 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': -2.3517160586848647, 'radius': 1.9217521875234188e-06, 'z': 0.38525754195199347}. Best is trial 1 with value: 0.010852049919941337.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:10,884]\u001b[0m Trial 3 finished with value: 0.014047214069580045 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 6.956977573257813, 'radius': 4.7353975889136423e-07, 'z': -0.8251491464740259}. Best is trial 1 with value: 0.010852049919941337.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:10,971]\u001b[0m Trial 4 finished with value: 0.024810663581116183 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': -0.9027200896396721, 'radius': 1.1231853571382542e-06, 'z': -0.16461781330644043}. Best is trial 1 with value: 0.010852049919941337.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,050]\u001b[0m Trial 5 finished with value: 0.008702310897207959 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -1.977546120322934, 'radius': 1.0520698395191867e-06, 'z': 0.9862888104856082}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,143]\u001b[0m Trial 6 finished with value: 0.014055277258110574 and parameters: {'aberration_name': 'Defocus', 'coefficient': 8.21678047241414, 'radius': 1.2416422763583993e-06, 'z': -0.16273307856900177}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,224]\u001b[0m Trial 7 finished with value: 0.01243384229019738 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -7.658095464133772, 'radius': 1.0867012849578157e-06, 'z': 0.9897711554465842}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,251]\u001b[0m Trial 8 finished with value: 0.01418212249106446 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.7069014081837466, 'radius': 2.441398688343476e-07, 'z': -0.033424093305673086}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,313]\u001b[0m Trial 9 finished with value: 0.011999212734099332 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.096700236737089, 'radius': 7.580566886940404e-07, 'z': -0.592456696614329}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,443]\u001b[0m Trial 10 finished with value: 0.0742641359316271 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -8.598516950559805, 'radius': 1.5756818733199728e-06, 'z': 0.3799497073022715}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,521]\u001b[0m Trial 11 finished with value: 0.011549370710848366 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -2.970848343061887, 'radius': 8.166446517375298e-07, 'z': 0.9552444809398245}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,644]\u001b[0m Trial 12 finished with value: 0.04625880139193418 and parameters: {'aberration_name': 'Piston', 'coefficient': -4.742006431109385, 'radius': 1.4077633992124539e-06, 'z': 0.6400273753296108}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,726]\u001b[0m Trial 13 finished with value: 0.013041884247289783 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -5.774723812655754, 'radius': 9.270941089458746e-07, 'z': 0.660331763380787}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,770]\u001b[0m Trial 14 finished with value: 0.012264985536290435 and parameters: {'aberration_name': 'Trefoil', 'coefficient': -0.06756311501989604, 'radius': 4.7401063913069717e-07, 'z': 0.6823628541340324}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,886]\u001b[0m Trial 15 finished with value: 0.01564841791530465 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': -9.967392968361144, 'radius': 1.4398770135321213e-06, 'z': 0.3661862596274079}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:11,942]\u001b[0m Trial 16 finished with value: 0.01090515933542628 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.4355848886883109, 'radius': 6.012860989058124e-07, 'z': 0.8079790121625264}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,019]\u001b[0m Trial 17 finished with value: 0.01139674146361128 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -5.023858124058294, 'radius': 9.6539761059147e-07, 'z': 0.1868844820332809}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,040]\u001b[0m Trial 18 finished with value: 0.014301587281750213 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 5.714286909993809, 'radius': 1.7558179899685613e-07, 'z': 0.575521199476192}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,203]\u001b[0m Trial 19 finished with value: 0.12218975152785692 and parameters: {'aberration_name': 'Piston', 'coefficient': -2.891509724806527, 'radius': 2.096877403601907e-06, 'z': 0.7973908574504449}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,298]\u001b[0m Trial 20 finished with value: 0.011425274886188361 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -6.416896725303754, 'radius': 1.2415599889541939e-06, 'z': 0.20025668422429077}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,352]\u001b[0m Trial 21 finished with value: 0.010329972926839293 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.604468801937621, 'radius': 6.360636059639953e-07, 'z': 0.8374578937524173}. Best is trial 5 with value: 0.008702310897207959.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,406]\u001b[0m Trial 22 finished with value: 0.008674610094888485 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2349320109844322, 'radius': 6.832927746515438e-07, 'z': 0.8648805348520785}. Best is trial 22 with value: 0.008674610094888485.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,461]\u001b[0m Trial 23 finished with value: 0.009186863660727105 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.1667156627099775, 'radius': 6.585469925813285e-07, 'z': 0.8493166825993896}. Best is trial 22 with value: 0.008674610094888485.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,501]\u001b[0m Trial 24 finished with value: 0.014067233603043126 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.984885740851656, 'radius': 4.3085849442428407e-07, 'z': 0.9882398965860077}. Best is trial 22 with value: 0.008674610094888485.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,562]\u001b[0m Trial 25 finished with value: 0.008008491986321113 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.5087836412636215, 'radius': 7.370099715126982e-07, 'z': 0.8141670922024467}. Best is trial 25 with value: 0.008008491986321113.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,630]\u001b[0m Trial 26 finished with value: 0.006769216028310272 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.3827527587030983, 'radius': 8.271384816532983e-07, 'z': 0.4850342079551113}. Best is trial 26 with value: 0.006769216028310272.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,665]\u001b[0m Trial 27 finished with value: 0.014154701416720677 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 4.981508573564033, 'radius': 3.0577026623022337e-07, 'z': 0.5059764564820943}. Best is trial 26 with value: 0.006769216028310272.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,732]\u001b[0m Trial 28 finished with value: 0.007957871014695632 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.0448135065055433, 'radius': 8.210222410276939e-07, 'z': 0.5111385484724353}. Best is trial 26 with value: 0.006769216028310272.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,800]\u001b[0m Trial 29 finished with value: 0.010023153052519466 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -0.687438889006144, 'radius': 8.240443617218455e-07, 'z': 0.21636983551999409}. Best is trial 26 with value: 0.006769216028310272.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,874]\u001b[0m Trial 30 finished with value: 0.006041985496887739 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.1947308929706253, 'radius': 9.136464323059647e-07, 'z': 0.04496807875458614}. Best is trial 30 with value: 0.006041985496887739.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:12,949]\u001b[0m Trial 31 finished with value: 0.005418381294331392 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.9332067155644277, 'radius': 9.32667552893995e-07, 'z': 0.017047171092918794}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,024]\u001b[0m Trial 32 finished with value: 0.006477499742731812 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.4046788010212783, 'radius': 9.044179272319746e-07, 'z': 0.02987453904069201}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,099]\u001b[0m Trial 33 finished with value: 0.005851896183169707 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.4342478046125717, 'radius': 9.663315307898447e-07, 'z': -0.3848181278423844}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,196]\u001b[0m Trial 34 finished with value: 0.00770988723351644 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 4.022247628168118, 'radius': 1.2141981912585389e-06, 'z': -0.39381827154658944}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,270]\u001b[0m Trial 35 finished with value: 0.011894667913307606 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 9.553756510708352, 'radius': 9.516432576563738e-07, 'z': 0.036236177115526735}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,344]\u001b[0m Trial 36 finished with value: 0.026686659066692167 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 6.347806097609244, 'radius': 9.83921017454602e-07, 'z': -0.4298405523888876}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,447]\u001b[0m Trial 37 finished with value: 0.01752753574877382 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.479060280495729, 'radius': 1.3882391281543698e-06, 'z': -0.3013775797024037}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,535]\u001b[0m Trial 38 finished with value: 0.009859687283950046 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.830369631988425, 'radius': 1.1297713574074389e-06, 'z': -0.9859229219325494}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,623]\u001b[0m Trial 39 finished with value: 0.010690243281999306 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 4.2794550219799605, 'radius': 1.1500591504282656e-06, 'z': 0.06609672704150753}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,777]\u001b[0m Trial 40 finished with value: 0.007834299068467556 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -3.7434789415710377, 'radius': 1.0112258456771865e-06, 'z': -0.20657100951867657}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,844]\u001b[0m Trial 41 finished with value: 0.007130413308015279 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.2517702139379472, 'radius': 8.791021150195956e-07, 'z': -0.6340227456375949}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,894]\u001b[0m Trial 42 finished with value: 0.01206008658695536 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.8380153924726537, 'radius': 5.272373244776877e-07, 'z': -0.08793535414314425}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:13,980]\u001b[0m Trial 43 finished with value: 0.010826053889030192 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.1561897883351264, 'radius': 1.060948988084678e-06, 'z': 0.10124503248779154}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,056]\u001b[0m Trial 44 finished with value: 0.012328999646087257 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -0.4846977360585838, 'radius': 8.731181877738016e-07, 'z': 0.3027717737126039}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,170]\u001b[0m Trial 45 finished with value: 0.04248343841170266 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 2.08074161205945, 'radius': 1.3315434451303321e-06, 'z': -0.6016917586689188}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,239]\u001b[0m Trial 46 finished with value: 0.008282827159470292 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -2.0167701152989745, 'radius': 7.706527131151165e-07, 'z': -0.06432656659985785}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,371]\u001b[0m Trial 47 finished with value: 0.032737726366874935 and parameters: {'aberration_name': 'Defocus', 'coefficient': -3.61166517586667, 'radius': 1.7485241440771306e-06, 'z': -0.23495774561830549}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,455]\u001b[0m Trial 48 finished with value: 0.012553917115992687 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 7.864179792297069, 'radius': 1.0638090417510012e-06, 'z': -0.4244701534848596}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,524]\u001b[0m Trial 49 finished with value: 0.013482210393059298 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 0.41794646219017006, 'radius': 8.941753817755976e-07, 'z': -0.7449895379682417}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,575]\u001b[0m Trial 50 finished with value: 0.012848682379241779 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.9410507238660917, 'radius': 5.228927024822042e-07, 'z': -0.3089130926221276}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,645]\u001b[0m Trial 51 finished with value: 0.006106597624684313 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.5011757356669448, 'radius': 8.88886319882317e-07, 'z': -0.6212992156747331}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,708]\u001b[0m Trial 52 finished with value: 0.009505347281732432 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -2.4473727531756166, 'radius': 7.525183386337276e-07, 'z': -0.8420560796700046}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,785]\u001b[0m Trial 53 finished with value: 0.017713284365377235 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 0.12667366900590166, 'radius': 9.881741317990299e-07, 'z': -0.006581085726558966}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,855]\u001b[0m Trial 54 finished with value: 0.013659067774071448 and parameters: {'aberration_name': 'Piston', 'coefficient': -4.612014577643571, 'radius': 8.629333442775743e-07, 'z': -0.5204422626898686}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:14,946]\u001b[0m Trial 55 finished with value: 0.014866001493231458 and parameters: {'aberration_name': 'Trefoil', 'coefficient': -1.4682815633675745, 'radius': 1.165866484672752e-06, 'z': 0.2956581050866571}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,008]\u001b[0m Trial 56 finished with value: 0.009131839416198223 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 1.1125439515969704, 'radius': 7.254500079124369e-07, 'z': -0.13073306570694318}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,084]\u001b[0m Trial 57 finished with value: 0.024961357704370617 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 5.371997565872546, 'radius': 9.237341278234202e-07, 'z': 0.09858979543560123}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,181]\u001b[0m Trial 58 finished with value: 0.00866118888792924 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.6109327220118983, 'radius': 1.2655716187999641e-06, 'z': -0.6725136164032721}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,235]\u001b[0m Trial 59 finished with value: 0.01115736030809319 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': -0.28136621321923183, 'radius': 6.042153751912796e-07, 'z': -0.5165960606293813}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,352]\u001b[0m Trial 60 finished with value: 0.011530100166933925 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -6.941104167610832, 'radius': 1.5368606321408488e-06, 'z': -0.811976573949551}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,433]\u001b[0m Trial 61 finished with value: 0.010791994800484877 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.2586829651513562, 'radius': 1.0334708235720012e-06, 'z': -0.6474736338104362}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,503]\u001b[0m Trial 62 finished with value: 0.009626548764917484 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -3.154029992092741, 'radius': 8.167610797650713e-07, 'z': -0.5267545580430081}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,598]\u001b[0m Trial 63 finished with value: 0.009349131465780291 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -3.9934303274011125, 'radius': 9.16857465984293e-07, 'z': -0.9232895728365873}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,660]\u001b[0m Trial 64 finished with value: 0.010538490380272087 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -2.6662630188401257, 'radius': 7.104427929203168e-07, 'z': 0.42468929362354635}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,751]\u001b[0m Trial 65 finished with value: 0.02017296646449475 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 0.8401777279130478, 'radius': 1.1019143749075617e-06, 'z': -0.7394495350044666}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,819]\u001b[0m Trial 66 finished with value: 0.008952153898526286 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 1.8642722958598739, 'radius': 8.636461642243215e-07, 'z': -0.34898694482134873}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,883]\u001b[0m Trial 67 finished with value: 0.007152193467166088 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.5676569105645377, 'radius': 7.996126775317509e-07, 'z': 0.15118635992922022}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:15,968]\u001b[0m Trial 68 finished with value: 0.017070361322379313 and parameters: {'aberration_name': 'Piston', 'coefficient': -0.7199396492516489, 'radius': 9.634546070131101e-07, 'z': -0.20315033500496366}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,076]\u001b[0m Trial 69 finished with value: 0.007807207109852339 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 4.6605764637424585, 'radius': 1.20080495405924e-06, 'z': -0.47514866750299506}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,136]\u001b[0m Trial 70 finished with value: 0.013151961147072563 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 2.244578266250604, 'radius': 6.576184143505015e-07, 'z': -0.008760176715546922}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,210]\u001b[0m Trial 71 finished with value: 0.006976452565413678 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.6408609086039292, 'radius': 8.119877727601378e-07, 'z': 0.13835047080223606}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,299]\u001b[0m Trial 72 finished with value: 0.01924919518208933 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -0.04319370167570458, 'radius': 1.0086651115096582e-06, 'z': 0.7239013779656358}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,374]\u001b[0m Trial 73 finished with value: 0.007065096119266777 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -2.2810240920340834, 'radius': 8.63369441878205e-07, 'z': 0.24463297343172544}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,447]\u001b[0m Trial 74 finished with value: 0.011629272039141462 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -5.653743447628438, 'radius': 8.216407005490608e-07, 'z': 0.23887909310328304}. Best is trial 31 with value: 0.005418381294331392.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,528]\u001b[0m Trial 75 finished with value: 0.005399686478017871 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.9222445479503456, 'radius': 9.431556445769832e-07, 'z': 0.43387920013036035}. Best is trial 75 with value: 0.005399686478017871.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,619]\u001b[0m Trial 76 finished with value: 0.025072184820542093 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': -3.2922469531103085, 'radius': 1.0982665313048486e-06, 'z': 0.4181737682988566}. Best is trial 75 with value: 0.005399686478017871.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,707]\u001b[0m Trial 77 finished with value: 0.00531088889547592 and parameters: {'aberration_name': 'Defocus', 'coefficient': 1.6131297987468975, 'radius': 9.436455254342921e-07, 'z': 0.5826785789312747}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,797]\u001b[0m Trial 78 finished with value: 0.011081550216282925 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.520689332828935, 'radius': 9.551255776396e-07, 'z': 0.593377606053204}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:16,892]\u001b[0m Trial 79 finished with value: 0.019062162218557336 and parameters: {'aberration_name': 'Defocus', 'coefficient': 0.5293930197161927, 'radius': 1.054834672482285e-06, 'z': 0.5456792042746721}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,003]\u001b[0m Trial 80 finished with value: 0.019956044238379794 and parameters: {'aberration_name': 'Defocus', 'coefficient': 1.556857501261023, 'radius': 1.2833000568130223e-06, 'z': 0.6967058398548833}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,077]\u001b[0m Trial 81 finished with value: 0.009313242118613708 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.6136009982407495, 'radius': 7.823245326370085e-07, 'z': 0.4991808911334254}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,159]\u001b[0m Trial 82 finished with value: 0.011370384488453011 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -0.7752451564620705, 'radius': 9.210359793250374e-07, 'z': 0.33748641267172486}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,228]\u001b[0m Trial 83 finished with value: 0.012287721630141232 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': -4.146173472608148, 'radius': 6.999818770448723e-07, 'z': 0.15793355788307104}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,332]\u001b[0m Trial 84 finished with value: 0.008802436677139966 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': -2.205792317442264, 'radius': 9.742057212971002e-07, 'z': -0.11380296701834261}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,443]\u001b[0m Trial 85 finished with value: 0.012993855813299164 and parameters: {'aberration_name': 'Defocus', 'coefficient': 0.9218232242925548, 'radius': 1.0179134245112462e-06, 'z': 0.4706431717849168}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,525]\u001b[0m Trial 86 finished with value: 0.006363793745350699 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.6345484036725137, 'radius': 8.413445239173159e-07, 'z': 0.6253285664495432}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,582]\u001b[0m Trial 87 finished with value: 0.011562071007234909 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.026870961114002556, 'radius': 5.717731680235645e-07, 'z': 0.7469631312274012}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,690]\u001b[0m Trial 88 finished with value: 0.007067556542146808 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.2375371646009796, 'radius': 1.160313504930042e-06, 'z': 0.6152592309982063}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,761]\u001b[0m Trial 89 finished with value: 0.00784192540904284 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.4370349697617242, 'radius': 7.512898924912455e-07, 'z': 0.9036829848289243}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,845]\u001b[0m Trial 90 finished with value: 0.01320477942885426 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -0.4674502502702427, 'radius': 9.019915429649509e-07, 'z': 0.4548073738746504}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:17,923]\u001b[0m Trial 91 finished with value: 0.006513226602944901 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.8629254958338148, 'radius': 8.510071996033903e-07, 'z': 0.04093179342532022}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,003]\u001b[0m Trial 92 finished with value: 0.00767575191969685 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.1411244762217643, 'radius': 8.710039807120654e-07, 'z': 0.6447780188007559}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,081]\u001b[0m Trial 93 finished with value: 0.007184199949759717 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -2.9110599373529884, 'radius': 9.441729273071785e-07, 'z': 0.061714240788416364}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,182]\u001b[0m Trial 94 finished with value: 0.006302700411053422 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -2.156466483290579, 'radius': 8.393741666348034e-07, 'z': -0.050764862376009426}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,283]\u001b[0m Trial 95 finished with value: 0.00814092134875866 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -1.9579406964940358, 'radius': 1.0362870161583935e-06, 'z': -0.052039630174588805}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,368]\u001b[0m Trial 96 finished with value: 0.007413708078832586 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -2.6137867464776576, 'radius': 8.455587599984386e-07, 'z': 0.01752540647673155}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,464]\u001b[0m Trial 97 finished with value: 0.009161487879394201 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -3.5639365311892828, 'radius': 9.111956390196536e-07, 'z': -0.2544152254426384}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,541]\u001b[0m Trial 98 finished with value: 0.015808112344317882 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 2.459606157794175, 'radius': 7.705015758124038e-07, 'z': -0.16511600912162902}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,643]\u001b[0m Trial 99 finished with value: 0.02272633365269004 and parameters: {'aberration_name': 'Piston', 'coefficient': 0.461219873218609, 'radius': 1.0790717802808603e-06, 'z': 0.108287346600994}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,737]\u001b[0m Trial 100 finished with value: 0.011758218756677836 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -4.712543723710116, 'radius': 9.990268015555564e-07, 'z': 0.045573253757969556}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,811]\u001b[0m Trial 101 finished with value: 0.00847031995732818 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.6711244978400082, 'radius': 7.325689893630279e-07, 'z': -0.03297911458657811}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,878]\u001b[0m Trial 102 finished with value: 0.009243777410711557 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.0146789602781, 'radius': 6.738997542491695e-07, 'z': 0.757664629981548}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:18,959]\u001b[0m Trial 103 finished with value: 0.006159856710632748 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -2.0628898841492216, 'radius': 8.382698907905479e-07, 'z': 0.5471257678724852}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,051]\u001b[0m Trial 104 finished with value: 0.005427576446499017 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -2.267323896234884, 'radius': 9.465959419318144e-07, 'z': 0.5548618101831981}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,136]\u001b[0m Trial 105 finished with value: 0.006823361553718644 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -2.848278702909756, 'radius': 9.40919174830431e-07, 'z': 0.3979676959349234}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,234]\u001b[0m Trial 106 finished with value: 0.010283229354195116 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -4.2052359452830865, 'radius': 1.1200324367136735e-06, 'z': 0.5780116746776743}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,313]\u001b[0m Trial 107 finished with value: 0.007629564818129047 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -3.223699920744862, 'radius': 9.931424501804808e-07, 'z': 0.6611880309442468}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,382]\u001b[0m Trial 108 finished with value: 0.005990229723193328 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.758061483186511, 'radius': 8.952446100348968e-07, 'z': 0.5292183641335921}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,445]\u001b[0m Trial 109 finished with value: 0.007262074324532494 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.869880154271994, 'radius': 7.793349102523158e-07, 'z': 0.5361507776596397}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,512]\u001b[0m Trial 110 finished with value: 0.005638712736609396 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 2.1798978527530144, 'radius': 8.981375593317782e-07, 'z': 0.33838505188024215}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,581]\u001b[0m Trial 111 finished with value: 0.00793411262506935 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.0250786480653247, 'radius': 8.921275959365108e-07, 'z': 0.3545887862744058}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,649]\u001b[0m Trial 112 finished with value: 0.010509959359265287 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.8400902854532877, 'radius': 8.310475923426481e-07, 'z': 0.5354962531962233}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,725]\u001b[0m Trial 113 finished with value: 0.010414354339183968 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.26068526456688, 'radius': 9.611092329239226e-07, 'z': 0.3035793915778958}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,807]\u001b[0m Trial 114 finished with value: 0.006804993020372551 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 2.8768027581691595, 'radius': 1.0386840727318718e-06, 'z': 0.45664876731483467}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,876]\u001b[0m Trial 115 finished with value: 0.010991153640225248 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 4.409723870742254, 'radius': 8.960560757768454e-07, 'z': 0.6857118629644414}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:19,943]\u001b[0m Trial 116 finished with value: 0.006905107571284629 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.9393151483406943, 'radius': 7.978735167792061e-07, 'z': 0.6222590865673083}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,020]\u001b[0m Trial 117 finished with value: 0.006010368435675246 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.626367872311922, 'radius': 9.832675627848125e-07, 'z': 0.5956101140612438}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,104]\u001b[0m Trial 118 finished with value: 0.005641360534030764 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.525233534399234, 'radius': 1.0693007054285546e-06, 'z': 0.5572064932055436}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,189]\u001b[0m Trial 119 finished with value: 0.026478073881546986 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 2.3232666968250344, 'radius': 1.085885790229124e-06, 'z': 0.5697996179715488}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,290]\u001b[0m Trial 120 finished with value: 0.0070121780185305425 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.6116087394598657, 'radius': 1.143382800321204e-06, 'z': 0.5068201726851698}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,374]\u001b[0m Trial 121 finished with value: 0.006133313958514866 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.695099231492912, 'radius': 9.876735758786525e-07, 'z': 0.4515331790843658}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,459]\u001b[0m Trial 122 finished with value: 0.006631227810045068 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.7177563479563696, 'radius': 9.473801010383018e-07, 'z': 0.36801729917229975}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,549]\u001b[0m Trial 123 finished with value: 0.007124195111929104 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.6225696179234774, 'radius': 1.0118882770209625e-06, 'z': 0.4305141673263766}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,630]\u001b[0m Trial 124 finished with value: 0.0077267332731887775 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.3998615253619717, 'radius': 9.748509987991933e-07, 'z': 0.5363749109086997}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,716]\u001b[0m Trial 125 finished with value: 0.007836012284845435 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 4.134394114035035, 'radius': 1.0639011464150396e-06, 'z': 0.5848584161650886}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,802]\u001b[0m Trial 126 finished with value: 0.005368086850970861 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.1412082866429474, 'radius': 1.0336219213664455e-06, 'z': 0.4814847558400886}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,902]\u001b[0m Trial 127 finished with value: 0.0251613021781966 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 0.8716538324903313, 'radius': 1.2172350660766877e-06, 'z': 0.4876059455310807}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:20,986]\u001b[0m Trial 128 finished with value: 0.00533581628490402 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.2354437256212796, 'radius': 1.0349554166930105e-06, 'z': 0.2819278778234605}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,076]\u001b[0m Trial 129 finished with value: 0.010022190709901272 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.078201158563929, 'radius': 1.1714026496683798e-06, 'z': 0.3242694752565}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,167]\u001b[0m Trial 130 finished with value: 0.006702722281625307 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.293164237372884, 'radius': 1.110642046178125e-06, 'z': 0.3880901656648239}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,271]\u001b[0m Trial 131 finished with value: 0.005951855305304531 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.7749682769555006, 'radius': 1.0239408661267596e-06, 'z': 0.2660174663909852}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,355]\u001b[0m Trial 132 finished with value: 0.00857014669803729 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.5320057409254764, 'radius': 1.0344614915084535e-06, 'z': 0.36708834146348424}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,432]\u001b[0m Trial 133 finished with value: 0.0076506139444212674 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.1634264750397456, 'radius': 9.451840444317932e-07, 'z': 0.2343436606848129}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,591]\u001b[0m Trial 134 finished with value: 0.1060709871415657 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.2064880248324923, 'radius': 2.086842349941114e-06, 'z': 0.24543599123869464}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,672]\u001b[0m Trial 135 finished with value: 0.008595030666488887 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 4.9228553451314525, 'radius': 1.072130869223472e-06, 'z': 0.19961947994930473}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,748]\u001b[0m Trial 136 finished with value: 0.008479676669852658 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.4899004686399833, 'radius': 9.159782580876318e-07, 'z': 0.29519920740182976}. Best is trial 77 with value: 0.00531088889547592.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,831]\u001b[0m Trial 137 finished with value: 0.005197972948539056 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.0767646136265836, 'radius': 1.0049876356635756e-06, 'z': 0.4911326724578296}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,914]\u001b[0m Trial 138 finished with value: 0.005367102955320423 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.040314111564633, 'radius': 1.0246789989189358e-06, 'z': 0.28664486169047576}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:21,998]\u001b[0m Trial 139 finished with value: 0.006127531156559333 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.8533290185246387, 'radius': 1.0256488707503213e-06, 'z': 0.4125248327460478}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,084]\u001b[0m Trial 140 finished with value: 0.007447043574668873 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.0285272482928955, 'radius': 1.1840980282795112e-06, 'z': 0.2873532380698204}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,173]\u001b[0m Trial 141 finished with value: 0.007122176992629291 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.169076121809514, 'radius': 1.1152130594271888e-06, 'z': 0.4785024520946681}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,248]\u001b[0m Trial 142 finished with value: 0.006523023455112332 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.5681982520822229, 'radius': 9.767201924003824e-07, 'z': 0.17387720835823767}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,330]\u001b[0m Trial 143 finished with value: 0.01765274249006523 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 0.8003071942538811, 'radius': 1.0465103882351146e-06, 'z': 0.26569392180007356}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,410]\u001b[0m Trial 144 finished with value: 0.013998963058132585 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': -8.771125934134231, 'radius': 9.298024430247959e-07, 'z': 0.3424062777424817}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,487]\u001b[0m Trial 145 finished with value: 0.006694742662601288 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.6140497076294538, 'radius': 9.970579018657738e-07, 'z': 0.5133967481513471}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,574]\u001b[0m Trial 146 finished with value: 0.007349081763858831 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.777979083473796, 'radius': 1.0719521978745526e-06, 'z': 0.5927643888850046}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,645]\u001b[0m Trial 147 finished with value: 0.008890609914191664 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.3269603268636967, 'radius': 8.828762057842008e-07, 'z': 0.39016940700001057}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,728]\u001b[0m Trial 148 finished with value: 0.005213652336711558 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.9833155807775562, 'radius': 1.0015111376789233e-06, 'z': 0.4462627393099042}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,824]\u001b[0m Trial 149 finished with value: 0.016353124807293725 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.1760705900803259, 'radius': 1.1224972945309113e-06, 'z': 0.43142658398067074}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,911]\u001b[0m Trial 150 finished with value: 0.005696558768014896 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.8922019679720758, 'radius': 1.0105858388577701e-06, 'z': 0.6415778315379554}. Best is trial 137 with value: 0.005197972948539056.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:22,986]\u001b[0m Trial 151 finished with value: 0.005110495228772275 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.9755540431263503, 'radius': 9.860375844389426e-07, 'z': 0.6575917369630151}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,067]\u001b[0m Trial 152 finished with value: 0.006379448250422097 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.898221943722041, 'radius': 1.0456383113311087e-06, 'z': 0.701734263177173}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,149]\u001b[0m Trial 153 finished with value: 0.005226145675438517 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.25110122636837, 'radius': 1.024889710267587e-06, 'z': 0.6634721616959799}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,229]\u001b[0m Trial 154 finished with value: 0.0051980796964335736 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.308330002897578, 'radius': 1.020135426571225e-06, 'z': 0.6364532926736514}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,303]\u001b[0m Trial 155 finished with value: 0.005466787220690144 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.166906178226445, 'radius': 9.416295559116352e-07, 'z': 0.7790722074230624}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,384]\u001b[0m Trial 156 finished with value: 0.022205044705047843 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 0.3914796274103469, 'radius': 1.0903483269391924e-06, 'z': 0.767373254566318}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,457]\u001b[0m Trial 157 finished with value: 0.005447662634419558 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.238990593302619, 'radius': 9.448211771608805e-07, 'z': 0.6555696397210535}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,531]\u001b[0m Trial 158 finished with value: 0.007406755910498523 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.2934548370687708, 'radius': 9.24483398930727e-07, 'z': 0.9002979005317857}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,604]\u001b[0m Trial 159 finished with value: 0.005366203097121866 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.2784226375781236, 'radius': 9.603112454781596e-07, 'z': 0.7138325449473806}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,678]\u001b[0m Trial 160 finished with value: 0.005338870626226244 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.180738799199433, 'radius': 9.445520204794417e-07, 'z': 0.7207174621575267}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,758]\u001b[0m Trial 161 finished with value: 0.005257422404479829 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.1947589724992818, 'radius': 9.51756149073172e-07, 'z': 0.7989137047597512}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,830]\u001b[0m Trial 162 finished with value: 0.006166360735425057 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.5936339160259911, 'radius': 9.594636445237858e-07, 'z': 0.8125247554038099}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:23,926]\u001b[0m Trial 163 finished with value: 0.005304993980804738 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.2233951514655534, 'radius': 9.520183616054832e-07, 'z': 0.7410724281246159}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,005]\u001b[0m Trial 164 finished with value: 0.006899409239596067 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.069403462719839, 'radius': 9.92968900049665e-07, 'z': 0.7080450305318182}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,084]\u001b[0m Trial 165 finished with value: 0.011493365783306543 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 0.982365970872003, 'radius': 9.738021842973668e-07, 'z': 0.7385605834522364}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,174]\u001b[0m Trial 166 finished with value: 0.009499385949924033 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.3540256496829928, 'radius': 1.0236372517349471e-06, 'z': 0.6659150545356074}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,261]\u001b[0m Trial 167 finished with value: 0.007366996106113324 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.2858588390901713, 'radius': 9.354470961067705e-07, 'z': 0.868410848339098}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,346]\u001b[0m Trial 168 finished with value: 0.008576167299892273 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.035499759287549, 'radius': 8.693244636529126e-07, 'z': 0.6750974585441453}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,439]\u001b[0m Trial 169 finished with value: 0.009668515311666853 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 6.101965505286545, 'radius': 1.0519816537240902e-06, 'z': 0.8120032624422086}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,520]\u001b[0m Trial 170 finished with value: 0.018531275014363656 and parameters: {'aberration_name': 'Piston', 'coefficient': 1.9677130637464906, 'radius': 9.950715676820823e-07, 'z': 0.7225241338644155}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,611]\u001b[0m Trial 171 finished with value: 0.005689282600364755 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.2726389059744823, 'radius': 9.41284963852259e-07, 'z': 0.7753407545827015}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,744]\u001b[0m Trial 172 finished with value: 0.006678524152710517 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.7364073954181727, 'radius': 9.476673951003488e-07, 'z': 0.8449961030283772}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,835]\u001b[0m Trial 173 finished with value: 0.006024352776202279 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.5191968959107771, 'radius': 9.04946565736497e-07, 'z': 0.7848350911371779}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:24,935]\u001b[0m Trial 174 finished with value: 0.008273265048982913 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 2.285593992701609, 'radius': 1.0135609932562683e-06, 'z': 0.6345772415480703}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,020]\u001b[0m Trial 175 finished with value: 0.023284407285149935 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.4317367892274744, 'radius': 9.618905869243338e-07, 'z': 0.7218970836863261}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,101]\u001b[0m Trial 176 finished with value: 0.0076112757520478014 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.932784912596811, 'radius': 1.0946554018822595e-06, 'z': 0.6714287430499326}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,169]\u001b[0m Trial 177 finished with value: 0.007238609317823118 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.448618128871508, 'radius': 8.697038853658052e-07, 'z': 0.6089672208193602}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,246]\u001b[0m Trial 178 finished with value: 0.01568535461321441 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 0.6816282198681609, 'radius': 9.214772741119648e-07, 'z': 0.7457689304663235}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,329]\u001b[0m Trial 179 finished with value: 0.007782234780632617 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.6663573820060824, 'radius': 1.0466864988951317e-06, 'z': 0.6487028939497939}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,404]\u001b[0m Trial 180 finished with value: 0.006675017725783313 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.8877210034308085, 'radius': 9.775915171152727e-07, 'z': 0.9092466583249653}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,472]\u001b[0m Trial 181 finished with value: 0.006536235365226578 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.267126580610076, 'radius': 8.805476472171401e-07, 'z': 0.7864823804899627}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,548]\u001b[0m Trial 182 finished with value: 0.005424298389183437 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.0369392855145945, 'radius': 9.242363112226318e-07, 'z': 0.48142193860714744}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,635]\u001b[0m Trial 183 finished with value: 0.005243743295423892 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.9672600484229568, 'radius': 1.0019948373766035e-06, 'z': 0.4745722676689825}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,719]\u001b[0m Trial 184 finished with value: 0.010141451516792311 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.202272938589948, 'radius': 1.0021581091556553e-06, 'z': 0.47975926419045944}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,740]\u001b[0m Trial 185 finished with value: 0.014262124606334253 and parameters: {'aberration_name': 'Defocus', 'coefficient': 1.6438003725361745, 'radius': 1.4628484119039156e-07, 'z': 0.5043674149723506}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,830]\u001b[0m Trial 186 finished with value: 0.005786776935137454 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.7348568197802297, 'radius': 1.0351616627209545e-06, 'z': 0.5688299157443382}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:25,925]\u001b[0m Trial 187 finished with value: 0.009372361585161974 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.8888989087279342, 'radius': 1.1300310864628365e-06, 'z': 0.6138684921846375}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,006]\u001b[0m Trial 188 finished with value: 0.013778993634340018 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 7.22599068583011, 'radius': 9.74793664226507e-07, 'z': 0.43852849192431476}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,094]\u001b[0m Trial 189 finished with value: 0.017741385522665087 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 1.047245227423632, 'radius': 1.0821776023438023e-06, 'z': 0.683130856198318}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,181]\u001b[0m Trial 190 finished with value: 0.006560960575050528 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.5040826238765908, 'radius': 9.184790966042798e-07, 'z': 0.5708176186769118}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,265]\u001b[0m Trial 191 finished with value: 0.005211659513816959 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.0931210800148947, 'radius': 9.466417766974175e-07, 'z': 0.5231991489874525}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,355]\u001b[0m Trial 192 finished with value: 0.005116664161784286 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.055456248075541, 'radius': 1.0041805580363748e-06, 'z': 0.5182071538811623}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,443]\u001b[0m Trial 193 finished with value: 0.01145853321447881 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 9.371231930019784, 'radius': 1.0066825271720835e-06, 'z': 0.46989219011411426}. Best is trial 151 with value: 0.005110495228772275.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,531]\u001b[0m Trial 194 finished with value: 0.0032354018636608153 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.621640403677029, 'radius': 1.0541184806495456e-06, 'z': 0.5248540793106797}. Best is trial 194 with value: 0.0032354018636608153.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,617]\u001b[0m Trial 195 finished with value: 0.0062149563229797295 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.4085811306099605, 'radius': 1.0760775003771885e-06, 'z': 0.5146287432777638}. Best is trial 194 with value: 0.0032354018636608153.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,653]\u001b[0m Trial 196 finished with value: 0.013393258050720102 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8462488768184895, 'radius': 3.922605607308424e-07, 'z': 0.4879687911287933}. Best is trial 194 with value: 0.0032354018636608153.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,740]\u001b[0m Trial 197 finished with value: 0.01851295433077848 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.3548370049985923, 'radius': 1.0294466396298854e-06, 'z': 0.41660205765561253}. Best is trial 194 with value: 0.0032354018636608153.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,818]\u001b[0m Trial 198 finished with value: 0.006699914541445772 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.9310570969722676, 'radius': 9.894826366642338e-07, 'z': 0.457297263930805}. Best is trial 194 with value: 0.0032354018636608153.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:26,904]\u001b[0m Trial 199 finished with value: 0.01578727390655603 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 0.8976178808265036, 'radius': 1.050296051126085e-06, 'z': 0.5452201492968893}. Best is trial 194 with value: 0.0032354018636608153.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,032]\u001b[0m Trial 200 finished with value: 0.04664005260289551 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.0235595178520787, 'radius': 1.693708769917662e-06, 'z': 0.5985192347628068}. Best is trial 194 with value: 0.0032354018636608153.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,124]\u001b[0m Trial 201 finished with value: 0.0017989101570296076 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.521632634891199, 'radius': 9.641728643849088e-07, 'z': 0.5316464923797193}. Best is trial 201 with value: 0.0017989101570296076.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,208]\u001b[0m Trial 202 finished with value: 0.0009842562784637323 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6201435128491233, 'radius': 9.770505929353618e-07, 'z': 0.5166871985649458}. Best is trial 202 with value: 0.0009842562784637323.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,304]\u001b[0m Trial 203 finished with value: 0.004914740697616474 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2903156833572202, 'radius': 1.002794782490289e-06, 'z': 0.5249778632730082}. Best is trial 202 with value: 0.0009842562784637323.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,406]\u001b[0m Trial 204 finished with value: 0.0022969066945642026 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5538482391302246, 'radius': 1.0115919999507941e-06, 'z': 0.5272228939629503}. Best is trial 202 with value: 0.0009842562784637323.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,513]\u001b[0m Trial 205 finished with value: 0.009535185038205093 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.447658087508539, 'radius': 1.150536905225895e-06, 'z': 0.528137775772839}. Best is trial 202 with value: 0.0009842562784637323.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,620]\u001b[0m Trial 206 finished with value: 0.008206881951004111 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3742789009548657, 'radius': 1.1065968154041253e-06, 'z': 0.5811215044115738}. Best is trial 202 with value: 0.0009842562784637323.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,723]\u001b[0m Trial 207 finished with value: 0.01184143472056533 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.8542837566242585, 'radius': 1.0242057905611118e-06, 'z': 0.5220474579679927}. Best is trial 202 with value: 0.0009842562784637323.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,819]\u001b[0m Trial 208 finished with value: 0.0025653885805020384 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7075437941361264, 'radius': 1.0592149565215135e-06, 'z': 0.5524911925016669}. Best is trial 202 with value: 0.0009842562784637323.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,901]\u001b[0m Trial 209 finished with value: 0.0007336127263344215 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6637459613938201, 'radius': 9.820695077624803e-07, 'z': 0.6224794581659185}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:27,988]\u001b[0m Trial 210 finished with value: 0.005883069634835567 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.179671277074619, 'radius': 9.873957463622886e-07, 'z': 0.6088764638847673}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,071]\u001b[0m Trial 211 finished with value: 0.0031583462237035433 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.666319917371181, 'radius': 1.0658109001924556e-06, 'z': 0.5528295497313679}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,158]\u001b[0m Trial 212 finished with value: 0.0028990022031391578 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7019147153432268, 'radius': 1.0674641548915813e-06, 'z': 0.5787277869124052}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,260]\u001b[0m Trial 213 finished with value: 0.004438686194199034 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5943066081735187, 'radius': 1.080416517476596e-06, 'z': 0.5554342540204126}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,344]\u001b[0m Trial 214 finished with value: 0.004205333033532755 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6202273975422825, 'radius': 1.0798716290904633e-06, 'z': 0.5539970571712399}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,428]\u001b[0m Trial 215 finished with value: 0.0042236891214552695 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6625443742476462, 'radius': 1.0842806315586192e-06, 'z': 0.5620769755533681}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,518]\u001b[0m Trial 216 finished with value: 0.007815433980478377 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5570579250403944, 'radius': 1.1438761305902178e-06, 'z': 0.5592459514464804}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,601]\u001b[0m Trial 217 finished with value: 0.01603015332984375 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.7230068965767015, 'radius': 1.0717160338820513e-06, 'z': 0.5344124598173468}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,691]\u001b[0m Trial 218 finished with value: 0.01633109811337912 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0703177572849354, 'radius': 1.1755280847904768e-06, 'z': 0.6279615412788131}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,774]\u001b[0m Trial 219 finished with value: 0.022336707235630943 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.292584045937359, 'radius': 1.0868576944792137e-06, 'z': 0.5609348200105828}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,863]\u001b[0m Trial 220 finished with value: 0.005840940685764553 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6559032811489303, 'radius': 1.121726705672262e-06, 'z': 0.517477645278373}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:28,948]\u001b[0m Trial 221 finished with value: 0.0032493426647486607 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.715969675250089, 'radius': 1.072636218939837e-06, 'z': 0.5870128696272315}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,037]\u001b[0m Trial 222 finished with value: 0.004702028389998051 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6793495375430898, 'radius': 1.100362976366358e-06, 'z': 0.5896224780880334}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,134]\u001b[0m Trial 223 finished with value: 0.01659696527021645 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.191071037332509, 'radius': 1.219610357394475e-06, 'z': 0.5870338128869262}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,218]\u001b[0m Trial 224 finished with value: 0.004193502527910779 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6961162571501829, 'radius': 1.0901061794208104e-06, 'z': 0.5586922812326452}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,300]\u001b[0m Trial 225 finished with value: 0.00500864036562327 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5967137667336977, 'radius': 1.0906668425260384e-06, 'z': 0.5549877599041169}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,389]\u001b[0m Trial 226 finished with value: 0.00746601306044188 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5296345872654267, 'radius': 1.129169920432902e-06, 'z': 0.5587054829474263}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,473]\u001b[0m Trial 227 finished with value: 0.017108660009830065 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.6253414676668417, 'radius': 1.0656343337134973e-06, 'z': 0.6260442472788004}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,563]\u001b[0m Trial 228 finished with value: 0.010398205124661022 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.1848766651642624, 'radius': 1.1039871941934052e-06, 'z': 0.538051255869489}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,653]\u001b[0m Trial 229 finished with value: 0.009641236054358102 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6480831077718068, 'radius': 1.1935427781343486e-06, 'z': 0.5986333022570893}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,743]\u001b[0m Trial 230 finished with value: 0.0078006431339850925 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6868989002122579, 'radius': 1.159602032830364e-06, 'z': 0.5083330497105311}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,826]\u001b[0m Trial 231 finished with value: 0.0032819131209374445 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7471379167732235, 'radius': 1.080764947546408e-06, 'z': 0.5555467277681441}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,909]\u001b[0m Trial 232 finished with value: 0.008680559508572992 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2792626947224481, 'radius': 1.089591626341373e-06, 'z': 0.5781983067888763}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:29,992]\u001b[0m Trial 233 finished with value: 0.002736906122635352 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7272785713550969, 'radius': 1.0658584381238134e-06, 'z': 0.6394249402142732}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,082]\u001b[0m Trial 234 finished with value: 0.01751398528964873 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.8251252392710059, 'radius': 1.127412313677083e-06, 'z': 0.5510214531092091}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,165]\u001b[0m Trial 235 finished with value: 0.002848878838134144 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7094299627151832, 'radius': 1.0648597295895467e-06, 'z': 0.5093257882455282}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,248]\u001b[0m Trial 236 finished with value: 0.004009086162395917 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5700687765310146, 'radius': 1.065933012893169e-06, 'z': 0.5065521840249778}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,332]\u001b[0m Trial 237 finished with value: 0.005729459581275576 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.4689909085157427, 'radius': 1.0771285473859221e-06, 'z': 0.6124732125704168}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,422]\u001b[0m Trial 238 finished with value: 0.013358267718007674 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.9896239660775943, 'radius': 1.103728452847244e-06, 'z': 0.5054090969244645}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,504]\u001b[0m Trial 239 finished with value: 0.0024722257708130087 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7222630105927481, 'radius': 1.0623651190584592e-06, 'z': 0.5786509244954513}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,603]\u001b[0m Trial 240 finished with value: 0.014645516250718539 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5303497512832822, 'radius': 1.260074661972338e-06, 'z': 0.5667963423576117}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,686]\u001b[0m Trial 241 finished with value: 0.002905353498303695 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7493399393201532, 'radius': 1.0706155148184313e-06, 'z': 0.6329394265944173}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,768]\u001b[0m Trial 242 finished with value: 0.0023258026508785287 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7484361050178825, 'radius': 1.0598079832659614e-06, 'z': 0.6000294091353663}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,852]\u001b[0m Trial 243 finished with value: 0.007380920148672274 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2831578839726046, 'radius': 1.0638053652367143e-06, 'z': 0.6022258814176982}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:30,942]\u001b[0m Trial 244 finished with value: 0.005606498831445354 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7469115511815405, 'radius': 1.1289475257656467e-06, 'z': 0.5572350853515359}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,025]\u001b[0m Trial 245 finished with value: 0.011816368427509244 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.9974371187841762, 'radius': 1.068507434611344e-06, 'z': 0.6511058148055172}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,115]\u001b[0m Trial 246 finished with value: 0.007748361240554026 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6933687679182405, 'radius': 1.161022282990697e-06, 'z': 0.5932564252611704}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,210]\u001b[0m Trial 247 finished with value: 0.020267996334165272 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.5762232193732094, 'radius': 1.1114634802636777e-06, 'z': 0.5367523251830906}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,293]\u001b[0m Trial 248 finished with value: 0.0066975174119581465 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3132549703770415, 'radius': 1.0498233734116303e-06, 'z': 0.6184560720642838}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,377]\u001b[0m Trial 249 finished with value: 0.0041006998921102 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7094480418765787, 'radius': 1.0936215147303162e-06, 'z': 0.5743701855109234}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,460]\u001b[0m Trial 250 finished with value: 0.004615320153678268 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6597080648289309, 'radius': 1.0982024775948131e-06, 'z': 0.5773418674355167}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,550]\u001b[0m Trial 251 finished with value: 0.015710108097712325 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0245104130272462, 'radius': 1.15726879433382e-06, 'z': 0.5745367668596645}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,641]\u001b[0m Trial 252 finished with value: 0.005018395252088638 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6397180057266811, 'radius': 1.1017079133459416e-06, 'z': 0.556462419278775}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,733]\u001b[0m Trial 253 finished with value: 0.029618363223890564 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.10447070726831575, 'radius': 1.197665317216405e-06, 'z': 0.5957614817642112}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,818]\u001b[0m Trial 254 finished with value: 0.0059622548772831525 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.4298059268685321, 'radius': 1.0744847109965174e-06, 'z': 0.48763461986289897}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,911]\u001b[0m Trial 255 finished with value: 0.005344470193046708 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7216733050405781, 'radius': 1.120143634081202e-06, 'z': 0.6334658252524559}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:31,996]\u001b[0m Trial 256 finished with value: 0.014440424027424152 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.7859655498966478, 'radius': 1.0615046200721729e-06, 'z': 0.5279785616037964}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,089]\u001b[0m Trial 257 finished with value: 0.011265637988371305 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.261085057607613, 'radius': 1.1399910878971846e-06, 'z': 0.5744967930295046}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,175]\u001b[0m Trial 258 finished with value: 0.003963263322056499 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6974617408282298, 'radius': 1.0823648645515313e-06, 'z': 0.5116644395764451}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,261]\u001b[0m Trial 259 finished with value: 0.010045426566528789 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0748845716151831, 'radius': 1.0498347713371182e-06, 'z': 0.4956605770965633}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,346]\u001b[0m Trial 260 finished with value: 0.0036372676704639123 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.82328030737475, 'radius': 1.0956231338687971e-06, 'z': 0.4552194267976367}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,438]\u001b[0m Trial 261 finished with value: 0.006994923144687529 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7998562698525586, 'radius': 1.1578619302622136e-06, 'z': 0.46166324163243594}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,522]\u001b[0m Trial 262 finished with value: 0.0035220985261067636 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8172658019932828, 'radius': 1.0889081243976586e-06, 'z': 0.6335959012799126}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,607]\u001b[0m Trial 263 finished with value: 0.005194780067092937 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.4308652659663803, 'radius': 1.0571818704608813e-06, 'z': 0.6370209208824896}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,691]\u001b[0m Trial 264 finished with value: 0.0035441303608933273 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8511255515232476, 'radius': 1.095827155445652e-06, 'z': 0.46265283979606087}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,783]\u001b[0m Trial 265 finished with value: 0.007069358779181467 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.4863075094372533, 'radius': 1.1784041707359246e-06, 'z': 0.44344317785984744}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,867]\u001b[0m Trial 266 finished with value: 0.0021235360743306164 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.920040192319409, 'radius': 1.0547393750677883e-06, 'z': 0.4083992143383296}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:32,951]\u001b[0m Trial 267 finished with value: 0.001880206079253306 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.924721232843247, 'radius': 1.046048584081451e-06, 'z': 0.40638256306597276}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,035]\u001b[0m Trial 268 finished with value: 0.006870196541812341 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.7044628135118955, 'radius': 1.0439886069530188e-06, 'z': 0.3824572360506158}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,120]\u001b[0m Trial 269 finished with value: 0.00212488772386922 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9847127302599787, 'radius': 1.0437091814191532e-06, 'z': 0.43140610236718974}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,204]\u001b[0m Trial 270 finished with value: 0.005979261611612722 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.5500468117337594, 'radius': 1.0412110437287251e-06, 'z': 0.4081867110828077}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,297]\u001b[0m Trial 271 finished with value: 0.004688682026744318 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9929222230333141, 'radius': 1.125179421520468e-06, 'z': 0.41105300970382674}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,381]\u001b[0m Trial 272 finished with value: 0.0017613821135554547 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9219870438806634, 'radius': 1.0407090842026395e-06, 'z': 0.4504719089135159}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,466]\u001b[0m Trial 273 finished with value: 0.006148607962123655 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.5782608243182743, 'radius': 1.0395999026869186e-06, 'z': 0.4445657147610964}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,549]\u001b[0m Trial 274 finished with value: 0.002650042110574379 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.062951055657044, 'radius': 1.0266554275248795e-06, 'z': 0.38285853341340453}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,632]\u001b[0m Trial 275 finished with value: 0.0025772694029409615 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.053532247695036, 'radius': 1.026408582500581e-06, 'z': 0.39510568606414154}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,716]\u001b[0m Trial 276 finished with value: 0.0027035023617396708 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0698745814998976, 'radius': 1.0272606182872951e-06, 'z': 0.4131874086226824}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,799]\u001b[0m Trial 277 finished with value: 0.004927881007066071 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.3666244547112347, 'radius': 1.0237779954897794e-06, 'z': 0.36307027800040453}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,881]\u001b[0m Trial 278 finished with value: 0.0020360112858054235 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9831204493390238, 'radius': 1.028858755324167e-06, 'z': 0.3883021436343621}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:33,965]\u001b[0m Trial 279 finished with value: 0.007415062498958797 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.7788800972874297, 'radius': 1.0179750586859995e-06, 'z': 0.34430850860987466}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,049]\u001b[0m Trial 280 finished with value: 0.003058999744873249 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.1106457318068554, 'radius': 1.0246688641097198e-06, 'z': 0.3734696750542418}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,131]\u001b[0m Trial 281 finished with value: 0.007723331101864026 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.840298154665285, 'radius': 1.0113723562387882e-06, 'z': 0.3920868341723141}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,208]\u001b[0m Trial 282 finished with value: 0.017875039612935566 and parameters: {'aberration_name': 'Piston', 'coefficient': 2.373322435882803, 'radius': 9.888983505120747e-07, 'z': 0.3193846641003167}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,291]\u001b[0m Trial 283 finished with value: 0.007744383812850543 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 2.1314521966462516, 'radius': 1.0202820778626703e-06, 'z': 0.35635521043399915}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,374]\u001b[0m Trial 284 finished with value: 0.002806891138446561 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0838161702988183, 'radius': 1.0414894800577453e-06, 'z': 0.385525353947724}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,457]\u001b[0m Trial 285 finished with value: 0.0057526800047127 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.5112995226124983, 'radius': 1.0392285193919359e-06, 'z': 0.3869884266383999}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,534]\u001b[0m Trial 286 finished with value: 0.003994259116735719 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.16391710634848, 'radius': 9.875359669979464e-07, 'z': 0.4148731316841064}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,636]\u001b[0m Trial 287 finished with value: 0.022232267155259982 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 1.0752338465886253, 'radius': 1.0298126092217759e-06, 'z': 0.33092376276074265}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,711]\u001b[0m Trial 288 finished with value: 0.009151071847195262 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.103993346334774, 'radius': 9.808785810613594e-07, 'z': 0.4404152172333974}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,795]\u001b[0m Trial 289 finished with value: 0.023640605803028937 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 2.1369120499748298, 'radius': 1.0411911456059094e-06, 'z': 0.3713095622245992}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,871]\u001b[0m Trial 290 finished with value: 0.006043906651991235 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.4641956584037428, 'radius': 9.803879984350514e-07, 'z': 0.40370254361107183}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:34,955]\u001b[0m Trial 291 finished with value: 0.0157692192670966 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.6443728128880954, 'radius': 1.0406236333689365e-06, 'z': 0.3858143627624764}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,058]\u001b[0m Trial 292 finished with value: 0.005058112053602066 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2790718837384754, 'radius': 1.0035318737126477e-06, 'z': 0.40336987465727164}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,143]\u001b[0m Trial 293 finished with value: 0.002307792578724019 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0124783345109143, 'radius': 1.0413770409570969e-06, 'z': 0.32417063182718264}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,219]\u001b[0m Trial 294 finished with value: 0.003416846717291886 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0701831382174216, 'radius': 9.771952326007992e-07, 'z': 0.29521416040653387}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,302]\u001b[0m Trial 295 finished with value: 0.00578650096726635 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.521785388876075, 'radius': 1.0445228596134932e-06, 'z': 0.33744244424527825}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,386]\u001b[0m Trial 296 finished with value: 0.008508496684940015 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 2.0442638958304213, 'radius': 1.0098548608081073e-06, 'z': 0.43293527076804267}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,468]\u001b[0m Trial 297 finished with value: 0.013381375950825352 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 1.243882618993879, 'radius': 1.0325821696753835e-06, 'z': 0.3633907237340019}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,545]\u001b[0m Trial 298 finished with value: 0.007944922252550864 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.799346131271162, 'radius': 9.676515680751345e-07, 'z': 0.43116326729518456}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,629]\u001b[0m Trial 299 finished with value: 0.009424591601458754 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.272424911303308, 'radius': 1.0537422418323272e-06, 'z': 0.31446051441381623}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,713]\u001b[0m Trial 300 finished with value: 0.0020710413003210866 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9788686629376135, 'radius': 1.0060266082612018e-06, 'z': 0.36489847677712406}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,789]\u001b[0m Trial 301 finished with value: 0.003389102015605623 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.1158296321201537, 'radius': 9.98641313999297e-07, 'z': 0.35982881212644746}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,865]\u001b[0m Trial 302 finished with value: 0.004583199201325355 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.271385798038381, 'radius': 9.750547427722214e-07, 'z': 0.40045667979745986}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:35,949]\u001b[0m Trial 303 finished with value: 0.005715696703908401 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.4957557550417215, 'radius': 1.0276823490018886e-06, 'z': 0.3323259667910831}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,027]\u001b[0m Trial 304 finished with value: 0.010940001401509927 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.7989624522330929, 'radius': 9.709434424908276e-07, 'z': 0.4679378025509366}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,116]\u001b[0m Trial 305 finished with value: 0.00469848222423218 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0492870373103864, 'radius': 1.1349617946347917e-06, 'z': 0.423284860735245}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,201]\u001b[0m Trial 306 finished with value: 0.007351927253347913 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.8046822300979586, 'radius': 1.0588646985148313e-06, 'z': 0.3740315420312755}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,284]\u001b[0m Trial 307 finished with value: 0.0024545810395903518 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0251001054434656, 'radius': 1.0068527456040233e-06, 'z': 0.47593968089334887}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,367]\u001b[0m Trial 308 finished with value: 0.005261021031272494 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.404152804920294, 'radius': 1.0074808600985626e-06, 'z': 0.45891036730111046}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,444]\u001b[0m Trial 309 finished with value: 0.005089494835927133 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.139481353496878, 'radius': 9.255990621336468e-07, 'z': 0.2664433818845473}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,604]\u001b[0m Trial 310 finished with value: 0.004095692868532096 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2992342795114342, 'radius': 9.661843844670983e-07, 'z': 0.3111534552576735}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,687]\u001b[0m Trial 311 finished with value: 0.008743842250240781 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.039998406652177, 'radius': 1.0007229282205682e-06, 'z': 0.3919364107124522}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,771]\u001b[0m Trial 312 finished with value: 0.0018565697376202639 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.919098455010865, 'radius': 1.047425409715838e-06, 'z': 0.4313248076393993}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,853]\u001b[0m Trial 313 finished with value: 0.007149425415349481 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 1.9550962205866778, 'radius': 1.0231902025217632e-06, 'z': 0.35477597918845183}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:36,932]\u001b[0m Trial 314 finished with value: 0.007350571951811575 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.6679070710801938, 'radius': 9.627600704896409e-07, 'z': 0.4275021304896103}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,018]\u001b[0m Trial 315 finished with value: 0.021003440389084648 and parameters: {'aberration_name': 'Piston', 'coefficient': 2.3284944831349996, 'radius': 1.047429386320489e-06, 'z': 0.47362627220590814}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,110]\u001b[0m Trial 316 finished with value: 0.029171411791520278 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 2.022131839449099, 'radius': 1.132080081396111e-06, 'z': 0.4109719514874334}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,195]\u001b[0m Trial 317 finished with value: 0.004712876366115957 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3375675405592615, 'radius': 1.0078750342204553e-06, 'z': 0.47004939224628484}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,273]\u001b[0m Trial 318 finished with value: 0.008388064846855588 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.854517743123232, 'radius': 9.080152392921792e-07, 'z': 0.36150141633293403}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,360]\u001b[0m Trial 319 finished with value: 0.002271453023137048 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9631373113592365, 'radius': 1.056430584004363e-06, 'z': 0.4381738225837601}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,391]\u001b[0m Trial 320 finished with value: 0.014034063279503578 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 1.3361037979582682, 'radius': 2.4287395008031787e-07, 'z': 0.4378496699708143}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,477]\u001b[0m Trial 321 finished with value: 0.006077055172116233 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.5743245868578786, 'radius': 1.0599907955114575e-06, 'z': 0.47687555409847815}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,570]\u001b[0m Trial 322 finished with value: 0.004422990091529335 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9247808951436625, 'radius': 1.1183966034865036e-06, 'z': 0.42863135308136197}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,649]\u001b[0m Trial 323 finished with value: 0.015923971011190162 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.3220131650635947, 'radius': 9.641823508666474e-07, 'z': 0.48088189514054636}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,734]\u001b[0m Trial 324 finished with value: 0.005582196184805391 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.4017580411900452, 'radius': 1.0591327080691279e-06, 'z': 0.39745658577253584}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,826]\u001b[0m Trial 325 finished with value: 0.008808781845425872 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.088089464907214, 'radius': 1.1255260689165377e-06, 'z': 0.4972781409003197}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,911]\u001b[0m Trial 326 finished with value: 0.0013843346043001087 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8994712648690606, 'radius': 1.0226286753878635e-06, 'z': 0.32756869309303294}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:37,988]\u001b[0m Trial 327 finished with value: 0.013557148242080742 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': -9.609648382554262, 'radius': 9.434008821505055e-07, 'z': 0.27678170681924413}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,065]\u001b[0m Trial 328 finished with value: 0.00912196288302294 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 2.346379588082399, 'radius': 9.819181957972853e-07, 'z': 0.21305656831922917}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,150]\u001b[0m Trial 329 finished with value: 0.009668332724115216 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.986740059340782, 'radius': 1.0152289120158265e-06, 'z': 0.29899829225900676}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,233]\u001b[0m Trial 330 finished with value: 0.00236885100724928 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0188568841078376, 'radius': 1.0115850758858338e-06, 'z': 0.3467767861735332}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,312]\u001b[0m Trial 331 finished with value: 0.008182822475557934 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.765917367946132, 'radius': 9.291758036158164e-07, 'z': 0.327088009496642}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,389]\u001b[0m Trial 332 finished with value: 0.002590342308790443 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0027036789273325, 'radius': 9.947268257490969e-07, 'z': 0.3239892634719061}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,467]\u001b[0m Trial 333 finished with value: 0.00999571651602809 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.342369016772346, 'radius': 9.838424401967132e-07, 'z': 0.2594143805350846}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,545]\u001b[0m Trial 334 finished with value: 0.006652059374384567 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.4017256822370654, 'radius': 9.165861778125845e-07, 'z': 0.33754203002591976}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,622]\u001b[0m Trial 335 finished with value: 0.003291372238678288 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.1032327379050546, 'radius': 9.987843548461258e-07, 'z': 0.32896794095284765}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,700]\u001b[0m Trial 336 finished with value: 0.008151075570687293 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.8440983153679085, 'radius': 9.68341011506321e-07, 'z': 0.3795309909549505}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,785]\u001b[0m Trial 337 finished with value: 0.002144557041533942 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9915489039388155, 'radius': 1.0186362238835594e-06, 'z': 0.3087358979156193}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,862]\u001b[0m Trial 338 finished with value: 0.0030768114872812046 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3821610104023794, 'radius': 9.516566080348822e-07, 'z': 0.254700945613677}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:38,931]\u001b[0m Trial 339 finished with value: 0.004861904210142765 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9406480303196063, 'radius': 8.928850261411143e-07, 'z': 0.2892513337911499}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,014]\u001b[0m Trial 340 finished with value: 0.013449542605894848 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -6.970073457174138, 'radius': 1.0083562164362401e-06, 'z': 0.3189766562542482}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,099]\u001b[0m Trial 341 finished with value: 0.005439709936636274 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.4368427824648853, 'radius': 1.0158374559941193e-06, 'z': 0.2405952525720223}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,176]\u001b[0m Trial 342 finished with value: 0.008361618220102273 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.9499701536223575, 'radius': 9.495012543858622e-07, 'z': 0.3571607679395218}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,252]\u001b[0m Trial 343 finished with value: 0.007235744872238273 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 1.9014000583216035, 'radius': 9.957819036769658e-07, 'z': 0.4287064045357779}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,335]\u001b[0m Trial 344 finished with value: 0.0046119435225154895 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.406476574038607, 'radius': 1.0342146155667347e-06, 'z': 0.32077787364593285}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,413]\u001b[0m Trial 345 finished with value: 0.007960959484087636 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.509240926667646, 'radius': 9.748865931090664e-07, 'z': 0.39507483352735406}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,502]\u001b[0m Trial 346 finished with value: 0.0036448182715043648 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.899638536705741, 'radius': 1.103025237763805e-06, 'z': 0.3509806539667671}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,584]\u001b[0m Trial 347 finished with value: 0.02006995027926869 and parameters: {'aberration_name': 'Piston', 'coefficient': 2.2511115292008133, 'radius': 1.0274290796326072e-06, 'z': 0.29605993554652227}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,662]\u001b[0m Trial 348 finished with value: 0.00888046533031713 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.8883877325424456, 'radius': 9.186104969026733e-07, 'z': 0.44109079068013973}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,746]\u001b[0m Trial 349 finished with value: 0.02346345034028075 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 1.3813737046758625, 'radius': 1.046014276648625e-06, 'z': 0.21874849476045827}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,821]\u001b[0m Trial 350 finished with value: 0.007810093318856468 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0240967510385888, 'radius': 9.742924916122124e-07, 'z': 0.40915103275457465}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,905]\u001b[0m Trial 351 finished with value: 0.0034190300268151386 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8480319799300187, 'radius': 1.094554644668228e-06, 'z': 0.36233250745898427}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:39,988]\u001b[0m Trial 352 finished with value: 0.015187716315793852 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.6007072092412664, 'radius': 1.015095099150549e-06, 'z': 0.4503139355055209}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,073]\u001b[0m Trial 353 finished with value: 0.0049754450893850655 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.396675022780635, 'radius': 1.0582781143873796e-06, 'z': 0.40374962773763656}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,149]\u001b[0m Trial 354 finished with value: 0.018477793426183536 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 1.4859179911213385, 'radius': 9.514838504867629e-07, 'z': 0.32930943918874905}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,301]\u001b[0m Trial 355 finished with value: 0.07435042182452846 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0080899046445713, 'radius': 2.06217995133403e-06, 'z': 0.37181917976852535}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,384]\u001b[0m Trial 356 finished with value: 0.0075819766270901505 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.7858684530152207, 'radius': 1.004114500940409e-06, 'z': 0.28810919663488355}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,454]\u001b[0m Trial 357 finished with value: 0.0034799008800254646 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.4954643795275804, 'radius': 8.896670162458771e-07, 'z': 0.4529659637522756}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,537]\u001b[0m Trial 358 finished with value: 0.010429194025670881 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.5694651734102214, 'radius': 1.0646651905607154e-06, 'z': 0.48356796954480946}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,628]\u001b[0m Trial 359 finished with value: 0.009254276002135126 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 2.3086011454614344, 'radius': 1.1117734988109272e-06, 'z': 0.40103134908015664}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,753]\u001b[0m Trial 360 finished with value: 0.037335496430789 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 1.852349466062556, 'radius': 1.6204289053600338e-06, 'z': 0.3488818061827029}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,836]\u001b[0m Trial 361 finished with value: 0.011720660067487013 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.912446569795373, 'radius': 1.037592574872795e-06, 'z': 0.44073469535120124}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:40,925]\u001b[0m Trial 362 finished with value: 0.006093818115940012 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.2456016525499383, 'radius': 1.1585663475526083e-06, 'z': 0.30253505042531303}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,002]\u001b[0m Trial 363 finished with value: 0.005413577398337208 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2159618164051307, 'radius': 9.887105040769546e-07, 'z': 0.49552631752000675}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,080]\u001b[0m Trial 364 finished with value: 0.007915054105064576 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.706529809676064, 'radius': 9.313802948247561e-07, 'z': 0.4182141146130225}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,163]\u001b[0m Trial 365 finished with value: 0.0033066981857106494 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9048521145142705, 'radius': 1.0864835952164e-06, 'z': 0.36838836378838363}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,246]\u001b[0m Trial 366 finished with value: 0.0025551421956052063 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5470422160136956, 'radius': 1.0224742371877254e-06, 'z': 0.47374077211312304}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,323]\u001b[0m Trial 367 finished with value: 0.015096190119256536 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.5416863077946401, 'radius': 9.957574437959594e-07, 'z': 0.47340480829797393}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,399]\u001b[0m Trial 368 finished with value: 0.002245911121754865 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.4692116430692532, 'radius': 9.51611887595254e-07, 'z': 0.4263490188647837}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,468]\u001b[0m Trial 369 finished with value: 0.006101509688070337 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0419070097788867, 'radius': 8.784288243188432e-07, 'z': 0.45359192740368237}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,546]\u001b[0m Trial 370 finished with value: 0.0022645648334961763 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.4729445225045485, 'radius': 9.435140777741133e-07, 'z': 0.5115776966288659}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,656]\u001b[0m Trial 371 finished with value: 0.048365617758352124 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.2906257075655174, 'radius': 1.4490135015371453e-06, 'z': 0.5019641037560881}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,732]\u001b[0m Trial 372 finished with value: 0.002948891713677377 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3963444173929151, 'radius': 9.274405690517692e-07, 'z': 0.5095464729209606}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,801]\u001b[0m Trial 373 finished with value: 0.006183902836173719 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0487786614732446, 'radius': 8.363351071840739e-07, 'z': 0.49014049259890535}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,878]\u001b[0m Trial 374 finished with value: 0.0026059381817784494 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.581329421048064, 'radius': 9.174097114341975e-07, 'z': 0.4382303758413211}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:41,955]\u001b[0m Trial 375 finished with value: 0.005808003521621158 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 1.4731595617972628, 'radius': 9.546127621006858e-07, 'z': 0.5160976093510449}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,032]\u001b[0m Trial 376 finished with value: 0.010149255851965867 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.8179482655828109, 'radius': 9.539276160985056e-07, 'z': 0.46637485129369816}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,101]\u001b[0m Trial 377 finished with value: 0.014373872173444012 and parameters: {'aberration_name': 'Piston', 'coefficient': 1.371254013470719, 'radius': 8.893313033578952e-07, 'z': 0.1774970636282804}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,197]\u001b[0m Trial 378 finished with value: 0.005287098470822954 and parameters: {'aberration_name': 'Defocus', 'coefficient': 1.7118912912246314, 'radius': 9.680928774251527e-07, 'z': 0.24243615311542993}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,267]\u001b[0m Trial 379 finished with value: 0.004978482989671239 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.2342819137908463, 'radius': 8.58583205378852e-07, 'z': 0.4173490619087351}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,343]\u001b[0m Trial 380 finished with value: 0.014922186734117807 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.5561377207950067, 'radius': 9.968893657839076e-07, 'z': 0.5172147839891638}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,420]\u001b[0m Trial 381 finished with value: 0.015910587892158563 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.014132284076877388, 'radius': 9.367861327530539e-07, 'z': 0.4645049597606833}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,497]\u001b[0m Trial 382 finished with value: 0.022285374232059504 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 2.4320614352224585, 'radius': 9.841157351539127e-07, 'z': 0.3209426278322014}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,580]\u001b[0m Trial 383 finished with value: 0.0008396423324189602 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8111948705691625, 'radius': 1.0214140500546025e-06, 'z': 0.40105174836056023}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,665]\u001b[0m Trial 384 finished with value: 0.02285595436422044 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 1.6576727867973289, 'radius': 1.045169126932502e-06, 'z': 0.43189700714790974}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,757]\u001b[0m Trial 385 finished with value: 0.012685243892845385 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0681402787722523, 'radius': 1.1136968338989326e-06, 'z': 0.3848239360270605}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,907]\u001b[0m Trial 386 finished with value: 0.04414002058468524 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.1759041239697288, 'radius': 1.919672607787845e-06, 'z': 0.47725632076950175}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:42,993]\u001b[0m Trial 387 finished with value: 0.0016920993850487375 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8071598171003225, 'radius': 1.0446029276912795e-06, 'z': 0.4199475792642297}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,079]\u001b[0m Trial 388 finished with value: 0.0051714236152205625 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.49970763648147, 'radius': 1.0743367948491085e-06, 'z': 0.5273212418533291}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,165]\u001b[0m Trial 389 finished with value: 0.01576424397530673 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.644732684895885, 'radius': 1.0393756169525468e-06, 'z': 0.4375934243974065}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,252]\u001b[0m Trial 390 finished with value: 0.0035686670910165 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8056220234860383, 'radius': 1.0883702483864864e-06, 'z': 0.5129569820854296}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,330]\u001b[0m Trial 391 finished with value: 0.005147286057616062 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.1482065594406454, 'radius': 9.082659117146533e-07, 'z': 0.4627054644419769}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,409]\u001b[0m Trial 392 finished with value: 0.005769715385841676 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.3842299668261155, 'radius': 9.62593309739526e-07, 'z': 0.4221866066662614}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,494]\u001b[0m Trial 393 finished with value: 0.009824350518031986 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 1.560817911085754, 'radius': 1.0061008117927164e-06, 'z': 0.4913111198106505}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,585]\u001b[0m Trial 394 finished with value: 0.005579375945512156 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7567219348876992, 'radius': 1.1329222826060363e-06, 'z': 0.37247112536452304}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,670]\u001b[0m Trial 395 finished with value: 0.009105866349268516 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 2.2010143135706195, 'radius': 1.066977511119653e-06, 'z': 0.4066254388388063}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,755]\u001b[0m Trial 396 finished with value: 0.010334395355291594 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.975332674104139, 'radius': 1.0255382499543394e-06, 'z': 0.5350421346610567}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,833]\u001b[0m Trial 397 finished with value: 0.006996304503256413 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.6094305174964796, 'radius': 9.669002661623755e-07, 'z': 0.3511995215830937}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:43,917]\u001b[0m Trial 398 finished with value: 0.006263133192712872 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.298601844640547, 'radius': 1.043007417883816e-06, 'z': 0.4627023201926497}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,009]\u001b[0m Trial 399 finished with value: 0.004097637998879487 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8521679181964041, 'radius': 1.104549980069955e-06, 'z': 0.43911246767773865}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,101]\u001b[0m Trial 400 finished with value: 0.006695281943219818 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.219960733538772, 'radius': 1.1831856612917865e-06, 'z': 0.495640455187801}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,180]\u001b[0m Trial 401 finished with value: 0.014162860669771219 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 8.82977075120913, 'radius': 9.96838574297411e-07, 'z': 0.3834258157209774}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,258]\u001b[0m Trial 402 finished with value: 0.0034157904218037947 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3497130867872618, 'radius': 9.191815292399315e-07, 'z': 0.2710446731963589}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,344]\u001b[0m Trial 403 finished with value: 0.007116161508525176 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.759554301415155, 'radius': 1.059685724724087e-06, 'z': 0.5341877437891571}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,423]\u001b[0m Trial 404 finished with value: 0.011561325843584616 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.7226204656760634, 'radius': 9.543146417493256e-07, 'z': 0.35515668897065633}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,506]\u001b[0m Trial 405 finished with value: 0.0011983224361965254 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8767919761138179, 'radius': 1.0151329998916032e-06, 'z': 0.41296379288697765}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,583]\u001b[0m Trial 406 finished with value: 0.0022815306576749986 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9782517179287957, 'radius': 9.974139150612792e-07, 'z': 0.4093819794691463}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,652]\u001b[0m Trial 407 finished with value: 0.008542893778648645 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.414510021451558, 'radius': 8.829188580365831e-07, 'z': 0.40375940056818216}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,730]\u001b[0m Trial 408 finished with value: 0.008696799805599334 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 2.0953695302546618, 'radius': 9.40642568134593e-07, 'z': 0.3426183253418072}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,807]\u001b[0m Trial 409 finished with value: 0.008909819792868324 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.066608162256701, 'radius': 9.90634001980915e-07, 'z': 0.4133081281668425}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,883]\u001b[0m Trial 410 finished with value: 0.01770407592722211 and parameters: {'aberration_name': 'Piston', 'coefficient': 2.6232387198171856, 'radius': 9.80973452467504e-07, 'z': 0.36675973293084846}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:44,960]\u001b[0m Trial 411 finished with value: 0.003953060097232143 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9485056237253033, 'radius': 9.240653936279736e-07, 'z': 0.3045870544346506}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,044]\u001b[0m Trial 412 finished with value: 0.004070366211827635 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.255945543854019, 'radius': 1.033843796805991e-06, 'z': 0.4306506254473829}. Best is trial 209 with value: 0.0007336127263344215.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,120]\u001b[0m Trial 413 finished with value: 0.0006094505564661494 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7891030519282909, 'radius': 9.96859688596017e-07, 'z': 0.37966630503509}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,198]\u001b[0m Trial 414 finished with value: 0.0022278448399331934 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.870379016121273, 'radius': 9.634847903358402e-07, 'z': 0.3930092176126901}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,268]\u001b[0m Trial 415 finished with value: 0.016650221468327793 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 1.2030691618418077, 'radius': 8.896843345879593e-07, 'z': 0.3303625930220591}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,345]\u001b[0m Trial 416 finished with value: 0.001868080523560786 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7978791785265573, 'radius': 9.529778606399831e-07, 'z': 0.3761974309565665}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,421]\u001b[0m Trial 417 finished with value: 0.01683293290514885 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 1.5410589219677535, 'radius': 9.111842045883492e-07, 'z': 0.3897757277056114}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,498]\u001b[0m Trial 418 finished with value: 0.007682031933072987 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.9587002537489219, 'radius': 9.420098934778068e-07, 'z': 0.39809536760277925}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,569]\u001b[0m Trial 419 finished with value: 0.004977337973376001 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8152336232552135, 'radius': 8.612095176289275e-07, 'z': 0.2911954517729589}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,646]\u001b[0m Trial 420 finished with value: 0.003241987583328401 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3748269396996984, 'radius': 9.693915173990472e-07, 'z': 0.3647243764961855}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,715]\u001b[0m Trial 421 finished with value: 0.012445508589512506 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -0.2051432657280583, 'radius': 8.327771880331333e-07, 'z': 0.4246559273589435}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,792]\u001b[0m Trial 422 finished with value: 0.006608726614443317 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.5282434820585733, 'radius': 9.60529223549734e-07, 'z': -0.9170701418126678}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,869]\u001b[0m Trial 423 finished with value: 0.005934182250330581 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 1.794601311889923, 'radius': 9.044270618413412e-07, 'z': 0.3918733681736724}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:45,946]\u001b[0m Trial 424 finished with value: 0.005031778487180432 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.303708183834898, 'radius': 9.833173403490902e-07, 'z': 0.3203054820324281}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,023]\u001b[0m Trial 425 finished with value: 0.006612662696833133 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0819175106872518, 'radius': 9.490531881800337e-07, 'z': 0.43111994315614277}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,101]\u001b[0m Trial 426 finished with value: 0.01436524213740762 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.37718969452288476, 'radius': 9.291387636126589e-07, 'z': 0.3738048799787811}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,177]\u001b[0m Trial 427 finished with value: 0.00856229769661908 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.9932433896268984, 'radius': 9.992251465053922e-07, 'z': 0.2746656567976538}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,246]\u001b[0m Trial 428 finished with value: 0.003930721403565047 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5350346340915328, 'radius': 8.724340723420781e-07, 'z': 0.34509355560514715}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,323]\u001b[0m Trial 429 finished with value: 0.002614419081953283 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.965461482050757, 'radius': 9.776027069208907e-07, 'z': 0.44836355318413207}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,408]\u001b[0m Trial 430 finished with value: 0.009893763407973542 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 2.7044600214203376, 'radius': 1.0280694287153253e-06, 'z': 0.39269927552333717}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,492]\u001b[0m Trial 431 finished with value: 0.004226044879116667 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.2463433562366983, 'radius': 1.086131914845293e-06, 'z': 0.43737192800982116}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,568]\u001b[0m Trial 432 finished with value: 0.0022465637199795985 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5097688667611802, 'radius': 9.393650479715565e-07, 'z': 0.3674043892824776}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,638]\u001b[0m Trial 433 finished with value: 0.009847367942145309 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.7037015739582249, 'radius': 8.966531420689416e-07, 'z': 0.3247612963261399}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,715]\u001b[0m Trial 434 finished with value: 0.005104453729125159 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.187278974646469, 'radius': 9.450298152688755e-07, 'z': 0.368920677672756}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,791]\u001b[0m Trial 435 finished with value: 0.0026527561559681417 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5174639536819434, 'radius': 9.212640500473754e-07, 'z': 0.4076574842749767}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,870]\u001b[0m Trial 436 finished with value: 0.009801614732542901 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.8531074957424759, 'radius': 9.561570321242712e-07, 'z': 0.2984126085471611}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:46,943]\u001b[0m Trial 437 finished with value: 0.005416513603543333 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8299835153051645, 'radius': 8.602202780386929e-07, 'z': 0.37239518410171724}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,020]\u001b[0m Trial 438 finished with value: 0.003928236843863109 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3644665003891168, 'radius': 9.965803037674465e-07, 'z': 0.33385295685676225}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,097]\u001b[0m Trial 439 finished with value: 0.007569995229462904 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.3014750353959976, 'radius': 9.250033134426398e-07, 'z': 0.22339360554700424}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,160]\u001b[0m Trial 440 finished with value: 0.006858533122915433 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.8846083250636738, 'radius': 7.969181216700227e-07, 'z': 0.4143577256437018}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,238]\u001b[0m Trial 441 finished with value: 0.010829186735818678 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.6229101337385856, 'radius': 9.754795186735122e-07, 'z': 0.44063524055289804}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,322]\u001b[0m Trial 442 finished with value: 0.00907961385598053 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 2.5889526458556955, 'radius': 1.0181195623927963e-06, 'z': 0.36418923080100785}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,392]\u001b[0m Trial 443 finished with value: 0.005570704507515269 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0996761770738448, 'radius': 8.930558078644423e-07, 'z': 0.4027418986875218}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,469]\u001b[0m Trial 444 finished with value: 0.004128080930310472 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.1452122280736385, 'radius': 9.644108099361e-07, 'z': 0.26534127327802687}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,553]\u001b[0m Trial 445 finished with value: 0.0197136647779678 and parameters: {'aberration_name': 'Piston', 'coefficient': 1.6308950785609702, 'radius': 1.0218702091120103e-06, 'z': 0.4501853202294517}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,630]\u001b[0m Trial 446 finished with value: 0.021260671020809807 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 1.4715239345192095, 'radius': 9.975000649916515e-07, 'z': 0.33453482158290965}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,715]\u001b[0m Trial 447 finished with value: 0.007337207517697441 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.7959519189316047, 'radius': 1.0477456465171612e-06, 'z': 0.47988136516792734}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,792]\u001b[0m Trial 448 finished with value: 0.004245507237624772 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0458148162272383, 'radius': 9.339561630500372e-07, 'z': 0.3868910500654559}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,896]\u001b[0m Trial 449 finished with value: 0.039021578533948886 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 1.1934726270889264, 'radius': 1.3080366353113172e-06, 'z': 0.4591065449093953}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:47,974]\u001b[0m Trial 450 finished with value: 0.013608739761423346 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.5720223964106115, 'radius': 9.671872647488226e-07, 'z': 0.3518412074776765}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,061]\u001b[0m Trial 451 finished with value: 0.005037255874738539 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.3757776327898696, 'radius': 1.0192962405988437e-06, 'z': 0.3029843939194425}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,107]\u001b[0m Trial 452 finished with value: 0.013645071661201803 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.1906196145695636, 'radius': 4.5335641143999913e-07, 'z': 0.4199336917777988}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,179]\u001b[0m Trial 453 finished with value: 0.012969040407079734 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -5.227252270882071, 'radius': 8.527604836143112e-07, 'z': 0.38893602259510945}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,267]\u001b[0m Trial 454 finished with value: 0.0035412838923894988 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7052832369270023, 'radius': 1.0799975636847507e-06, 'z': 0.4603519530753205}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,346]\u001b[0m Trial 455 finished with value: 0.002156588174697515 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9501833094220393, 'radius': 9.913420175092351e-07, 'z': 0.33919385812243}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,426]\u001b[0m Trial 456 finished with value: 0.010941233447530068 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 0.9526798076829065, 'radius': 9.101961031492435e-07, 'z': 0.4215055372627262}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,506]\u001b[0m Trial 457 finished with value: 0.0033819322518785088 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3761082268517129, 'radius': 9.81093209805471e-07, 'z': 0.365528678575316}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,587]\u001b[0m Trial 458 finished with value: 0.008009185902242501 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 1.7553972561472775, 'radius': 9.223549755647438e-07, 'z': 0.4693006593691382}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,666]\u001b[0m Trial 459 finished with value: 0.0047459167436325 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.223741904742633, 'radius': 9.54517275861126e-07, 'z': 0.9980114278086971}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,751]\u001b[0m Trial 460 finished with value: 0.006496896481500584 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.583397824007113, 'radius': 1.002465076108961e-06, 'z': 0.4053667301578608}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,822]\u001b[0m Trial 461 finished with value: 0.003914545937360607 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.471582608337179, 'radius': 8.733738196799874e-07, 'z': 0.28625092947637154}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,908]\u001b[0m Trial 462 finished with value: 0.020506096524824862 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.2030748345941048, 'radius': 1.045796082919401e-06, 'z': 0.49159033315390627}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:48,987]\u001b[0m Trial 463 finished with value: 0.0026611201599821806 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9136665222716551, 'radius': 9.494114115535796e-07, 'z': 0.3462767926697025}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,065]\u001b[0m Trial 464 finished with value: 0.007452276827157299 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.0816380637215572, 'radius': 9.935024474064146e-07, 'z': 0.4372282311049729}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,158]\u001b[0m Trial 465 finished with value: 0.008164966104950521 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.960212097999804, 'radius': 1.1141082033919067e-06, 'z': 0.3970198334218038}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,243]\u001b[0m Trial 466 finished with value: 0.005003052888974262 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.3777558331459057, 'radius': 1.0233444627165993e-06, 'z': 0.36930331634458746}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,314]\u001b[0m Trial 467 finished with value: 0.003593291256053 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6538319463811695, 'radius': 8.957116239098731e-07, 'z': 0.43621632180220565}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,391]\u001b[0m Trial 468 finished with value: 0.01197112792925952 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.7223507953900368, 'radius': 9.733281055506327e-07, 'z': -0.7173797331694265}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,478]\u001b[0m Trial 469 finished with value: 0.0026970553514094123 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.026523186345745, 'radius': 1.0644641166900896e-06, 'z': 0.3203253672796328}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,557]\u001b[0m Trial 470 finished with value: 0.003549083067912431 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.3235971923475982, 'radius': 9.40036300394988e-07, 'z': 0.4938672820983495}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,644]\u001b[0m Trial 471 finished with value: 0.0059963326873087724 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.5412381362025718, 'radius': 1.0248383220797774e-06, 'z': 0.3932675565708647}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,729]\u001b[0m Trial 472 finished with value: 0.007444805910910211 and parameters: {'aberration_name': 'Defocus', 'coefficient': 1.8417422456836334, 'radius': 1.0850516577478857e-06, 'z': 0.4521648909083255}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,822]\u001b[0m Trial 473 finished with value: 0.016765171923239498 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.472446152022618, 'radius': 1.1376519859336687e-06, 'z': 0.3567409850309109}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:49,924]\u001b[0m Trial 474 finished with value: 0.009285473733566148 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.9707857316934572, 'radius': 1.0008361920025473e-06, 'z': 0.25197320635709636}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,001]\u001b[0m Trial 475 finished with value: 0.008424922129138082 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 2.1783259199456557, 'radius': 9.737686941556466e-07, 'z': 0.3045311497532861}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,079]\u001b[0m Trial 476 finished with value: 0.01516986611964595 and parameters: {'aberration_name': 'Piston', 'coefficient': 1.7982471277190728, 'radius': 9.140528622171376e-07, 'z': 0.4975682749660531}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,148]\u001b[0m Trial 477 finished with value: 0.009940798628179454 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.8355598987699087, 'radius': 8.156339108098039e-07, 'z': 0.4174584498011289}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,232]\u001b[0m Trial 478 finished with value: 0.025799153937814505 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 2.3272214534532565, 'radius': 1.0617241466787943e-06, 'z': 0.3459186406867365}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,316]\u001b[0m Trial 479 finished with value: 0.0024900150797140795 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5531185662282954, 'radius': 1.0223426198130397e-06, 'z': 0.45953542353993215}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,395]\u001b[0m Trial 480 finished with value: 0.005711102911189718 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.1365841420330673, 'radius': 9.485847216718334e-07, 'z': 0.381162354528936}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,479]\u001b[0m Trial 481 finished with value: 0.009661659107591767 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.3371739456975122, 'radius': 1.099818548022897e-06, 'z': 0.5168665653119566}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,556]\u001b[0m Trial 482 finished with value: 0.002691163847909379 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.0278565187216655, 'radius': 9.989364338197602e-07, 'z': 0.41466237682499546}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,640]\u001b[0m Trial 483 finished with value: 0.03170055870034403 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 5.483528987143133, 'radius': 1.0540491534790794e-06, 'z': 0.3192773185859006}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,717]\u001b[0m Trial 484 finished with value: 0.015400484978951981 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.43767832689877895, 'radius': 9.709329654676347e-07, 'z': 0.4676106536145471}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,788]\u001b[0m Trial 485 finished with value: 0.006284923696343508 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.4442523566719745, 'radius': 8.889720389262357e-07, 'z': 0.38587660851965294}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,873]\u001b[0m Trial 486 finished with value: 0.005906869004300117 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.5363481801812138, 'radius': 1.0384861571177445e-06, 'z': 0.2773578537429689}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:50,950]\u001b[0m Trial 487 finished with value: 0.013733604140873037 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -7.899341218921146, 'radius': 9.379764112543521e-07, 'z': 0.4304925075434728}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,033]\u001b[0m Trial 488 finished with value: 0.0011911864528117095 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.8730808722237293, 'radius': 1.0226178310802269e-06, 'z': 0.35026075520646466}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,124]\u001b[0m Trial 489 finished with value: 0.004037093755846837 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.1586089839482625, 'radius': 1.1002789347727032e-06, 'z': 0.3417039178584262}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,265]\u001b[0m Trial 490 finished with value: 0.07126580119358754 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 1.8665697037870306, 'radius': 1.8361231834095377e-06, 'z': 0.25348250495901486}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,357]\u001b[0m Trial 491 finished with value: 0.010586412020335405 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 2.5098092898310966, 'radius': 1.148716355895058e-06, 'z': 0.3109383359562364}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,435]\u001b[0m Trial 492 finished with value: 0.008874886893480944 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.0579984979480344, 'radius': 9.906879149196117e-07, 'z': 0.3642592295473509}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,519]\u001b[0m Trial 493 finished with value: 0.002138919185159207 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.9255513274416816, 'radius': 1.0617060080472097e-06, 'z': 0.18795017342773404}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,603]\u001b[0m Trial 494 finished with value: 0.008868087960392236 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.1961533601432597, 'radius': 1.0677146752069915e-06, 'z': 0.0656527332197627}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,696]\u001b[0m Trial 495 finished with value: 0.005017789966945513 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.6861295993791192, 'radius': 1.1089080880233817e-06, 'z': 0.141819791472132}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,795]\u001b[0m Trial 496 finished with value: 0.0220303558575862 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.8612137682198011, 'radius': 1.2171466793709515e-06, 'z': 0.1915798845437322}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,878]\u001b[0m Trial 497 finished with value: 0.004017462368049301 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.2517165048113505, 'radius': 1.0503991702520335e-06, 'z': 0.09519900620626094}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:51,970]\u001b[0m Trial 498 finished with value: 0.007445539906875616 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.6742182672349113, 'radius': 1.160535238338566e-06, 'z': 0.27946104479025363}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n", - "\u001b[32m[I 2026-06-18 22:24:52,054]\u001b[0m Trial 499 finished with value: 0.005722145358654656 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.5031019631385072, 'radius': 1.0845393412658888e-06, 'z': 0.35796706646643833}. Best is trial 413 with value: 0.0006094505564661494.\u001b[0m\n" + "\u001b[32m[I 2026-09-16 10:43:58,185]\u001b[0m A new study created in memory with name: no-name-03dd0578-c9b3-4fe9-a974-7b9b6f15bcb4\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:43:58,402]\u001b[0m Trial 0 finished with value: 0.0075278218659645 and parameters: {'aberration_name': 'Defocus', 'coefficient': -1.4653083437103556, 'radius': 2.1526021439189786e-07}. Best is trial 0 with value: 0.0075278218659645.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:43:58,960]\u001b[0m Trial 1 finished with value: 0.004774327877852035 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.3597794363902205, 'radius': 7.587276720928664e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:43:59,632]\u001b[0m Trial 2 finished with value: 0.007786665822138796 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 1.2016115358189356, 'radius': 8.553590917517387e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:00,199]\u001b[0m Trial 3 finished with value: 0.01592847130812383 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -3.1662184549083072, 'radius': 7.826373895258204e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:00,496]\u001b[0m Trial 4 finished with value: 0.007112661245346729 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.083694822362175, 'radius': 4.379891789013984e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:00,873]\u001b[0m Trial 5 finished with value: 0.009472238365970623 and parameters: {'aberration_name': 'Piston', 'coefficient': -0.008065660465414126, 'radius': 5.63784201750632e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:00,970]\u001b[0m Trial 6 finished with value: 0.007604749437438492 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': -3.1890862945287966, 'radius': 1.3124373867369735e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:01,683]\u001b[0m Trial 7 finished with value: 0.027856532559191235 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 1.8563001325906194, 'radius': 1.0259083632598927e-06}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:02,088]\u001b[0m Trial 8 finished with value: 0.009113156720791892 and parameters: {'aberration_name': 'Defocus', 'coefficient': -0.4633961402488911, 'radius': 5.801927743266537e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:02,190]\u001b[0m Trial 9 finished with value: 0.007611684489857893 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.3145908139032025, 'radius': 1.0186494338354274e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:02,349]\u001b[0m Trial 10 finished with value: 0.007569814987310243 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 0.9619735393176589, 'radius': 1.674517043313699e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:02,787]\u001b[0m Trial 11 finished with value: 0.0060560951117008465 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.7957198076102903, 'radius': 6.127283215942676e-07}. Best is trial 1 with value: 0.004774327877852035.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:03,394]\u001b[0m Trial 12 finished with value: 0.004584881949362759 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.3395952546133922, 'radius': 7.835711245646629e-07}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:04,180]\u001b[0m Trial 13 finished with value: 0.005176611890184957 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.993162782987291, 'radius': 9.494812719653018e-07}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:04,683]\u001b[0m Trial 14 finished with value: 0.00625250006388913 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.9776004484398817, 'radius': 6.016543413672916e-07}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:04,947]\u001b[0m Trial 15 finished with value: 0.007152845017355168 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 2.402469709946705, 'radius': 3.804801638082881e-07}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:05,620]\u001b[0m Trial 16 finished with value: 0.007912498387111298 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.416390662383709, 'radius': 1.1199668475796583e-06}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:06,146]\u001b[0m Trial 17 finished with value: 0.005870200010713549 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 2.5365772963139115, 'radius': 8.070234075271257e-07}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:06,578]\u001b[0m Trial 18 finished with value: 0.012132722646730846 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 0.3565069043428526, 'radius': 6.936987124890848e-07}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:07,237]\u001b[0m Trial 19 finished with value: 0.03174912006398514 and parameters: {'aberration_name': 'Piston', 'coefficient': 0.1812664227634433, 'radius': 1.0893969690563266e-06}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:07,854]\u001b[0m Trial 20 finished with value: 0.018964612380014446 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.2530465600854606, 'radius': 1.0349370888566145e-06}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:08,377]\u001b[0m Trial 21 finished with value: 0.007875663892432015 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.9449139874470704, 'radius': 8.608478855933069e-07}. Best is trial 12 with value: 0.004584881949362759.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:09,014]\u001b[0m Trial 22 finished with value: 0.004251028436019884 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.3861306581822337, 'radius': 9.187496448636737e-07}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:09,595]\u001b[0m Trial 23 finished with value: 0.004357470844146599 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.202387707124376, 'radius': 8.939340284518247e-07}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:10,257]\u001b[0m Trial 24 finished with value: 0.0072971827872533096 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.8646091966812257, 'radius': 1.0390379422923101e-06}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:10,816]\u001b[0m Trial 25 finished with value: 0.0204352998285409 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.8150387908828223, 'radius': 8.874401916259035e-07}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:11,581]\u001b[0m Trial 26 finished with value: 0.014586167549269068 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.5023855018434533, 'radius': 1.1931826049321338e-06}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:12,176]\u001b[0m Trial 27 finished with value: 0.005017078793978654 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.9414796865494957, 'radius': 1.056493074404494e-06}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:12,679]\u001b[0m Trial 28 finished with value: 0.021787766336831143 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 0.21739588946084742, 'radius': 9.221675654219934e-07}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:13,078]\u001b[0m Trial 29 finished with value: 0.008482971960813412 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.5982157125717418, 'radius': 7.278056235353572e-07}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:13,761]\u001b[0m Trial 30 finished with value: 0.03357254004946946 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 0.7395192757880196, 'radius': 1.1837198122220315e-06}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:14,192]\u001b[0m Trial 31 finished with value: 0.013547370436405253 and parameters: {'aberration_name': 'Piston', 'coefficient': 2.977099642978521, 'radius': 7.199421535970058e-07}. Best is trial 22 with value: 0.004251028436019884.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:14,733]\u001b[0m Trial 32 finished with value: 0.004079045351851002 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.661838341657917, 'radius': 9.059585813096472e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:15,255]\u001b[0m Trial 33 finished with value: 0.004301534156762208 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.3120603421833135, 'radius': 9.104185521399894e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:15,705]\u001b[0m Trial 34 finished with value: 0.00502138430075389 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.9144904372360125, 'radius': 7.518493861555247e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:16,305]\u001b[0m Trial 35 finished with value: 0.013686150709306674 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.9732380971691819, 'radius': 1.0640222416786225e-06}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:16,925]\u001b[0m Trial 36 finished with value: 0.0042157212007013925 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.343784558942699, 'radius': 8.908829120703737e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:17,507]\u001b[0m Trial 37 finished with value: 0.00960893363711346 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 2.3336308240385257, 'radius': 9.215053659486122e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:18,093]\u001b[0m Trial 38 finished with value: 0.014120474891842523 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.3498298151915806, 'radius': 9.423733667004451e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:18,572]\u001b[0m Trial 39 finished with value: 0.006390996896795245 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.114040549186239, 'radius': 8.055967080685941e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:18,931]\u001b[0m Trial 40 finished with value: 0.005688486793735083 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.2081446424404736, 'radius': 6.330125127678604e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:19,454]\u001b[0m Trial 41 finished with value: 0.004438590209678566 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.204300704994005, 'radius': 8.145605436867909e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:19,972]\u001b[0m Trial 42 finished with value: 0.02272248934782177 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.25689810255059, 'radius': 9.325087980591623e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:20,472]\u001b[0m Trial 43 finished with value: 0.009895984827416196 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.3094604863615378, 'radius': 8.024782843036613e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:21,036]\u001b[0m Trial 44 finished with value: 0.005415628026870351 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.881498262676149, 'radius': 9.437576119842817e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:21,599]\u001b[0m Trial 45 finished with value: 0.004100822768059109 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.844058876536284, 'radius': 9.522164467292568e-07}. Best is trial 32 with value: 0.004079045351851002.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:22,142]\u001b[0m Trial 46 finished with value: 0.004069609253161522 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.8794865785977923, 'radius': 9.411757699045341e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:22,692]\u001b[0m Trial 47 finished with value: 0.0040858545610410035 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.9201377172290943, 'radius': 9.50541158897916e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:23,409]\u001b[0m Trial 48 finished with value: 0.008051130544607986 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.7964081081097834, 'radius': 1.1867534310025305e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:24,070]\u001b[0m Trial 49 finished with value: 0.0313769923362161 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.3983976499808293, 'radius': 1.0859162784716843e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:24,666]\u001b[0m Trial 50 finished with value: 0.025086544281291267 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.9412506522887734, 'radius': 9.76004645758046e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:25,247]\u001b[0m Trial 51 finished with value: 0.0069317723634726 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.2683356070237393, 'radius': 8.937089278118401e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:25,921]\u001b[0m Trial 52 finished with value: 0.009101250681544005 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.1440827615174616, 'radius': 1.1436015945540028e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:26,422]\u001b[0m Trial 53 finished with value: 0.004347261298447131 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.6017055915509335, 'radius': 8.27022836620379e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:26,981]\u001b[0m Trial 54 finished with value: 0.004076116298954717 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.946007499383674, 'radius': 9.462540052991228e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:27,613]\u001b[0m Trial 55 finished with value: 0.03406763845802169 and parameters: {'aberration_name': 'Piston', 'coefficient': 2.379735028429568, 'radius': 1.1257888412349379e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:28,117]\u001b[0m Trial 56 finished with value: 0.005154948052680582 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.5932900341128757, 'radius': 7.508089407139079e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:28,677]\u001b[0m Trial 57 finished with value: 0.004989828503349792 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.7240625689658917, 'radius': 8.468928144561259e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:29,263]\u001b[0m Trial 58 finished with value: 0.00526842770448936 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.2812547648498946, 'radius': 1.004483058766529e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:29,856]\u001b[0m Trial 59 finished with value: 0.004079150446183514 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.9508574916109196, 'radius': 9.485752974074561e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:30,379]\u001b[0m Trial 60 finished with value: 0.004162969368647256 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.9472889513919456, 'radius': 8.80672978184931e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:30,881]\u001b[0m Trial 61 finished with value: 0.004091260022688943 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.848365143420435, 'radius': 8.990568975626604e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:31,480]\u001b[0m Trial 62 finished with value: 0.0042264181518144525 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.712642803100189, 'radius': 9.656252054223107e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:32,097]\u001b[0m Trial 63 finished with value: 0.00683943458849302 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.6204934364872887, 'radius': 1.1238849206091932e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:32,673]\u001b[0m Trial 64 finished with value: 0.004573239410728573 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.455510397603063, 'radius': 9.787306671023737e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:33,063]\u001b[0m Trial 65 finished with value: 0.005887491579106202 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.616859671834775, 'radius': 6.131084476510751e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:33,718]\u001b[0m Trial 66 finished with value: 0.02553340431446751 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.002425088535939, 'radius': 9.864809960517542e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:34,211]\u001b[0m Trial 67 finished with value: 0.005531710229799665 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.6368946204024604, 'radius': 6.700421359096466e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:34,952]\u001b[0m Trial 68 finished with value: 0.014415004506355644 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 2.786517076327673, 'radius': 1.135649515528743e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:35,439]\u001b[0m Trial 69 finished with value: 0.005166265736244878 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.934898341595666, 'radius': 8.308255730837593e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:36,106]\u001b[0m Trial 70 finished with value: 0.008427974150909331 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.472341919615391, 'radius': 1.0128848057163865e-06}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:36,647]\u001b[0m Trial 71 finished with value: 0.007167627353727508 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 2.7624331801093445, 'radius': 9.035058371758539e-07}. Best is trial 46 with value: 0.004069609253161522.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:37,256]\u001b[0m Trial 72 finished with value: 0.0008807490103079809 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.616467323357515, 'radius': 1.016913395510368e-06}. Best is trial 72 with value: 0.0008807490103079809.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:37,834]\u001b[0m Trial 73 finished with value: 0.028032492327089834 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.694120070178907, 'radius': 1.0274194945058054e-06}. Best is trial 72 with value: 0.0008807490103079809.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:38,418]\u001b[0m Trial 74 finished with value: 0.01044870352903558 and parameters: {'aberration_name': 'Defocus', 'coefficient': 1.8383382830331518, 'radius': 9.789517363530312e-07}. Best is trial 72 with value: 0.0008807490103079809.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:39,006]\u001b[0m Trial 75 finished with value: 0.0005263934105703747 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.639249225284666, 'radius': 1.0001495005373742e-06}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:39,631]\u001b[0m Trial 76 finished with value: 0.006923668691722803 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.9606538188722453, 'radius': 1.1305626679337846e-06}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:40,239]\u001b[0m Trial 77 finished with value: 0.007992874647074957 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.6787293775681413, 'radius': 1.098596640749038e-06}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:40,889]\u001b[0m Trial 78 finished with value: 0.006671607381875643 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.41720615124749, 'radius': 1.1951709690257695e-06}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:41,506]\u001b[0m Trial 79 finished with value: 0.0016086673630542644 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.552938022748969, 'radius': 1.0380554694930411e-06}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:41,988]\u001b[0m Trial 80 finished with value: 0.002874821811678827 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.0967410947824057, 'radius': 8.51115898610247e-07}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:42,522]\u001b[0m Trial 81 finished with value: 0.0011746241850814135 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.486934406244757, 'radius': 9.428402592182288e-07}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:43,139]\u001b[0m Trial 82 finished with value: 0.0018613824969763524 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6699887722500066, 'radius': 1.0685846723041408e-06}. Best is trial 75 with value: 0.0005263934105703747.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:43,753]\u001b[0m Trial 83 finished with value: 0.00047748798523153694 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6374236959559916, 'radius': 9.940392452115152e-07}. Best is trial 83 with value: 0.00047748798523153694.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:44,350]\u001b[0m Trial 84 finished with value: 0.003679926185125939 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.216256739079732, 'radius': 1.056597278924981e-06}. Best is trial 83 with value: 0.00047748798523153694.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:44,880]\u001b[0m Trial 85 finished with value: 0.0019832927047041178 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.2303408221431784, 'radius': 9.571870037651885e-07}. Best is trial 83 with value: 0.00047748798523153694.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:45,539]\u001b[0m Trial 86 finished with value: 0.002316465057882675 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6089066014269804, 'radius': 1.0765151014222131e-06}. Best is trial 83 with value: 0.00047748798523153694.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:46,200]\u001b[0m Trial 87 finished with value: 0.0009968447505481245 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.5297025803190127, 'radius': 9.520058187147411e-07}. Best is trial 83 with value: 0.00047748798523153694.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:46,789]\u001b[0m Trial 88 finished with value: 0.004648981897414732 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.7292848931987352, 'radius': 9.763757437277388e-07}. Best is trial 83 with value: 0.00047748798523153694.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:47,430]\u001b[0m Trial 89 finished with value: 0.002202752525739321 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.783555253395967, 'radius': 1.088427122657369e-06}. Best is trial 83 with value: 0.00047748798523153694.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:47,985]\u001b[0m Trial 90 finished with value: 2.8453997490064933e-05 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7619762556747203, 'radius': 9.98432831120346e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:48,609]\u001b[0m Trial 91 finished with value: 0.002230914256034263 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.1731981895428674, 'radius': 9.575467181406522e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:49,051]\u001b[0m Trial 92 finished with value: 0.003926750234020711 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.8407434208302957, 'radius': 7.815892730931256e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:49,590]\u001b[0m Trial 93 finished with value: 0.0007450765640262581 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9447681809807147, 'radius': 9.98108273459344e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:50,137]\u001b[0m Trial 94 finished with value: 0.0020510045004834914 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.565621561980024, 'radius': 8.883472669707568e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:50,724]\u001b[0m Trial 95 finished with value: 0.0006616715600680787 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.934202962611567, 'radius': 1.002903291102084e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:51,341]\u001b[0m Trial 96 finished with value: 0.0007378501610259306 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9481570278590534, 'radius': 1.0205436275962803e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:51,894]\u001b[0m Trial 97 finished with value: 0.000988407831194199 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.584850374382474, 'radius': 9.473989236903269e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:52,610]\u001b[0m Trial 98 finished with value: 0.006002154200397947 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.9934237021576675, 'radius': 1.101168109218828e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:53,280]\u001b[0m Trial 99 finished with value: 0.0006405260219062241 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.934621309771553, 'radius': 1.0104136128789696e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:53,837]\u001b[0m Trial 100 finished with value: 0.00117522086746278 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7398519424525287, 'radius': 9.414533398610823e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:54,424]\u001b[0m Trial 101 finished with value: 0.005366410807733627 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.8903913060665003, 'radius': 1.0036088573044237e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:54,993]\u001b[0m Trial 102 finished with value: 0.004214633310848095 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.974948276689185, 'radius': 1.0259407414528148e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:55,423]\u001b[0m Trial 103 finished with value: 0.0039780795123263955 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.844805617595145, 'radius': 7.818875651210168e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:56,024]\u001b[0m Trial 104 finished with value: 0.0008462380730845325 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.5278015399614433, 'radius': 9.839907008220603e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:56,598]\u001b[0m Trial 105 finished with value: 0.002842874766824392 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.3533087242737425, 'radius': 8.35626650463205e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:57,273]\u001b[0m Trial 106 finished with value: 0.01186680121684227 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.1747785888467357, 'radius': 1.0976485073243122e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:57,898]\u001b[0m Trial 107 finished with value: 0.005391176604912604 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.365793960662818, 'radius': 1.1488683184444392e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:58,397]\u001b[0m Trial 108 finished with value: 0.004121081901490167 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.624505947089497, 'radius': 8.841647165604817e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:59,019]\u001b[0m Trial 109 finished with value: 0.007716357935128744 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.466851907109212, 'radius': 1.0420142282851309e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:44:59,725]\u001b[0m Trial 110 finished with value: 0.00394211299955228 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.900651782240665, 'radius': 1.1632653481498795e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:00,331]\u001b[0m Trial 111 finished with value: 0.0005724255155868825 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9109501345419653, 'radius': 1.0144670667587416e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:01,011]\u001b[0m Trial 112 finished with value: 3.894283578931125e-05 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.759887263899609, 'radius': 9.936134380288543e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:01,619]\u001b[0m Trial 113 finished with value: 0.0001951333295151542 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.780750491603274, 'radius': 1.00828060775348e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:02,214]\u001b[0m Trial 114 finished with value: 0.0007805067141664032 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.95555570228374, 'radius': 1.0256575606309843e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:02,808]\u001b[0m Trial 115 finished with value: 0.0011580297709842034 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.983612671248052, 'radius': 1.0518557207358852e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:03,401]\u001b[0m Trial 116 finished with value: 0.0025956524079363665 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.2397928101955706, 'radius': 1.0132147494548708e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:03,916]\u001b[0m Trial 117 finished with value: 0.0025777127357087324 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.969386556964886, 'radius': 8.888451613225923e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:04,541]\u001b[0m Trial 118 finished with value: 0.004104986294891838 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.3988362946734174, 'radius': 1.1078188336283924e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:05,092]\u001b[0m Trial 119 finished with value: 0.0005186778671317115 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8286602502473945, 'radius': 9.835139597538173e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:05,644]\u001b[0m Trial 120 finished with value: 0.0010688598619049805 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9615237973703263, 'radius': 9.73821843409624e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:06,199]\u001b[0m Trial 121 finished with value: 0.0019485026270563922 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.314884497295667, 'radius': 9.016504213195141e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:06,775]\u001b[0m Trial 122 finished with value: 0.001406470112957183 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.401704838809378, 'radius': 9.849062867661066e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:07,370]\u001b[0m Trial 123 finished with value: 0.028335802909686063 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.8838369956252667, 'radius': 1.0353414070331783e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:07,984]\u001b[0m Trial 124 finished with value: 0.005387690624340511 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.6220769880854644, 'radius': 9.950200349131888e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:08,593]\u001b[0m Trial 125 finished with value: 0.0060343619876039156 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.970087691783645, 'radius': 1.0844590916898472e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:09,142]\u001b[0m Trial 126 finished with value: 0.004404328758761303 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.7646424157992313, 'radius': 9.968256400121733e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:09,724]\u001b[0m Trial 127 finished with value: 0.0005813847582770195 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8610580903939344, 'radius': 1.022687612505549e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:10,326]\u001b[0m Trial 128 finished with value: 0.028747052156315636 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.4224095969876993, 'radius': 1.0421919927152248e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:10,867]\u001b[0m Trial 129 finished with value: 0.005657200462411005 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.3389296046320736, 'radius': 9.63028672579858e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:11,433]\u001b[0m Trial 130 finished with value: 0.0055812316097311725 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.8808069912753203, 'radius': 1.0624593813139705e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:11,940]\u001b[0m Trial 131 finished with value: 0.004826607589811286 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.5392994610234756, 'radius': 9.237624229282113e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:12,476]\u001b[0m Trial 132 finished with value: 0.000379205250718846 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7171811457678934, 'radius': 9.785285870544798e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:13,057]\u001b[0m Trial 133 finished with value: 0.0006893756580263609 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8848170847981844, 'radius': 1.026849507640676e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:13,602]\u001b[0m Trial 134 finished with value: 0.0033542593627297287 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.9097326280620326, 'radius': 9.505686000086854e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:14,260]\u001b[0m Trial 135 finished with value: 0.008196588514634503 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.947032991606122, 'radius': 1.161846828215922e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:14,766]\u001b[0m Trial 136 finished with value: 0.0029528079158483832 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.9514048962368644, 'radius': 9.153655610792846e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:15,423]\u001b[0m Trial 137 finished with value: 0.00013876520154603862 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7883909828592257, 'radius': 1.0024602167543553e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:16,046]\u001b[0m Trial 138 finished with value: 0.005274580752776384 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.742221681438902, 'radius': 9.676388434567143e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:16,650]\u001b[0m Trial 139 finished with value: 0.0036127541469208367 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.9672536543060675, 'radius': 9.918134776595734e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:17,218]\u001b[0m Trial 140 finished with value: 0.0020243576321241734 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.986160460859077, 'radius': 9.254385810632529e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:17,793]\u001b[0m Trial 141 finished with value: 0.006079906894187977 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.4203946073115006, 'radius': 1.0130663590212736e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:18,400]\u001b[0m Trial 142 finished with value: 0.03104896960776873 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.301818180023003, 'radius': 1.0786479132005153e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:18,967]\u001b[0m Trial 143 finished with value: 0.005866801534228542 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.2727890290700237, 'radius': 1.0371992975001633e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:19,541]\u001b[0m Trial 144 finished with value: 0.0299214745977409 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.375481990418795, 'radius': 1.0619686114412185e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:20,085]\u001b[0m Trial 145 finished with value: 9.695495484414777e-05 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.751731716067665, 'radius': 9.91103732250418e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:20,598]\u001b[0m Trial 146 finished with value: 0.0016148297438240745 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6925910684816254, 'radius': 9.123789230614822e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:21,187]\u001b[0m Trial 147 finished with value: 0.0011517044234222807 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.785933810696899, 'radius': 1.0479931756904103e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:21,698]\u001b[0m Trial 148 finished with value: 0.004144777393303635 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.4733229137826878, 'radius': 9.045782555571758e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:22,283]\u001b[0m Trial 149 finished with value: 0.002583041228503549 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.445394568042463, 'radius': 1.0599816966159557e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:22,925]\u001b[0m Trial 150 finished with value: 0.006532519695376678 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.659806892582827, 'radius': 1.0519478664972147e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:23,417]\u001b[0m Trial 151 finished with value: 0.0027992569837447055 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7239491435716543, 'radius': 8.496079897604009e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:24,036]\u001b[0m Trial 152 finished with value: 0.03297586661890808 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.939690596854627, 'radius': 1.1077656529340621e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:24,657]\u001b[0m Trial 153 finished with value: 0.02775478593629125 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.4859516645396824, 'radius': 1.0223366522460045e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:25,296]\u001b[0m Trial 154 finished with value: 0.0006606986030945518 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7663999104675128, 'radius': 9.64600020494242e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:25,826]\u001b[0m Trial 155 finished with value: 0.003927523640877815 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.859560085244329, 'radius': 9.646462770376242e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:26,442]\u001b[0m Trial 156 finished with value: 0.010796110925398571 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.1804159369522678, 'radius': 1.1059370826917232e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:26,976]\u001b[0m Trial 157 finished with value: 0.0003920835134905356 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.734172887672349, 'radius': 9.775293853435008e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:27,522]\u001b[0m Trial 158 finished with value: 0.0001487795894616237 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7162334784023274, 'radius': 9.95372058599576e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:28,060]\u001b[0m Trial 159 finished with value: 0.0005337879911891222 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.744900142318256, 'radius': 9.690403636425272e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:28,636]\u001b[0m Trial 160 finished with value: 0.024875526053119608 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.678567667134409, 'radius': 9.729120226572565e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:29,218]\u001b[0m Trial 161 finished with value: 0.027746453094851197 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.774660262646313, 'radius': 1.0235706562296921e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:29,759]\u001b[0m Trial 162 finished with value: 0.025636435088500203 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.2232750825246863, 'radius': 9.90498707969296e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:30,308]\u001b[0m Trial 163 finished with value: 0.00018267815196666367 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7105227050951153, 'radius': 9.9980576753417e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:30,895]\u001b[0m Trial 164 finished with value: 0.005793864951897166 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.612436434572261, 'radius': 1.016943299846187e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:31,510]\u001b[0m Trial 165 finished with value: 0.008317091733406222 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.607971322190345, 'radius': 1.1020944134302292e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:32,060]\u001b[0m Trial 166 finished with value: 0.00047492664262846463 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.780231569630992, 'radius': 9.792776596120476e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:32,710]\u001b[0m Trial 167 finished with value: 0.004584600210773101 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.617869575500495, 'radius': 9.501887414671094e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:33,250]\u001b[0m Trial 168 finished with value: 0.0036513932769688313 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.5383362078158433, 'radius': 9.681772758444084e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:33,826]\u001b[0m Trial 169 finished with value: 0.0017999709828935275 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.4195353272072078, 'radius': 1.0187449262719296e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:34,326]\u001b[0m Trial 170 finished with value: 0.00425627904315156 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.5869408159280955, 'radius': 9.115998178706589e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:34,867]\u001b[0m Trial 171 finished with value: 0.0001508793056234998 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7182091199569878, 'radius': 9.994903113793929e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:35,442]\u001b[0m Trial 172 finished with value: 0.008357853969206137 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.0820987244247067, 'radius': 1.0173109945811727e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:35,994]\u001b[0m Trial 173 finished with value: 0.00591687121801699 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.0882574838243664, 'radius': 9.48318835694141e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:36,560]\u001b[0m Trial 174 finished with value: 0.00027359645434534404 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.782827540620685, 'radius': 9.90557681418455e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:37,109]\u001b[0m Trial 175 finished with value: 0.004420667397948439 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.914191511646945, 'radius': 9.594478686539883e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:37,769]\u001b[0m Trial 176 finished with value: 0.00401744212035076 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.664099094508915, 'radius': 1.1423418086221494e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:38,286]\u001b[0m Trial 177 finished with value: 0.020371863079601635 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.66162454131296, 'radius': 8.851103762395618e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:38,878]\u001b[0m Trial 178 finished with value: 0.0003938371875242202 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.691971361421617, 'radius': 1.0044479197903795e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:39,427]\u001b[0m Trial 179 finished with value: 0.000395897001179193 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6567321380856113, 'radius': 9.976032920050276e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:39,977]\u001b[0m Trial 180 finished with value: 2.972956410470117e-05 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7476970662532336, 'radius': 9.98773293139753e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:40,626]\u001b[0m Trial 181 finished with value: 0.0021115549236216022 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9809019221965003, 'radius': 1.0953553574610515e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:41,206]\u001b[0m Trial 182 finished with value: 0.0056658834139823476 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.465454012937297, 'radius': 9.842065048845744e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:41,744]\u001b[0m Trial 183 finished with value: 0.0005138468829926294 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6288648347631374, 'radius': 9.95814405529812e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:42,244]\u001b[0m Trial 184 finished with value: 0.005122935861306695 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.734785849454463, 'radius': 9.322293687883063e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:42,785]\u001b[0m Trial 185 finished with value: 0.0002827604722898363 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6783050700454822, 'radius': 9.916543540617408e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:43,376]\u001b[0m Trial 186 finished with value: 0.003201219556661882 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.5783127255687392, 'radius': 1.0495495334393603e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:43,927]\u001b[0m Trial 187 finished with value: 0.02373882730368093 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.353522421707915, 'radius': 9.537954746230291e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:44,523]\u001b[0m Trial 188 finished with value: 0.006330706119283582 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.593951081328051, 'radius': 1.0299680623708385e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:45,069]\u001b[0m Trial 189 finished with value: 0.007334625042138249 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.062787331020424, 'radius': 9.695024330749807e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:45,661]\u001b[0m Trial 190 finished with value: 0.0029646337790447106 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.291798951621126, 'radius': 1.00155761692981e-06}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:46,222]\u001b[0m Trial 191 finished with value: 0.002263015022273862 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.2162636631285175, 'radius': 9.847301530836581e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:46,769]\u001b[0m Trial 192 finished with value: 0.005375401260614819 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.459038643224092, 'radius': 9.405493590842685e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:47,311]\u001b[0m Trial 193 finished with value: 0.026099415282926617 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.6103248562950188, 'radius': 9.948979683570803e-07}. Best is trial 90 with value: 2.8453997490064933e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:47,921]\u001b[0m Trial 194 finished with value: 2.7321741232219593e-05 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.748384690806743, 'radius': 9.950419321413887e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:48,530]\u001b[0m Trial 195 finished with value: 0.006578955332872823 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.7590853579669297, 'radius': 1.0886702095456212e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:49,102]\u001b[0m Trial 196 finished with value: 0.001086051052322082 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.5107984377150006, 'radius': 1.0016189493178846e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:49,668]\u001b[0m Trial 197 finished with value: 0.023853084265730195 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.952981947091458, 'radius': 9.557726966133923e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:50,198]\u001b[0m Trial 198 finished with value: 0.02309247066123496 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.685540169449164, 'radius': 9.385895712678842e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:50,735]\u001b[0m Trial 199 finished with value: 0.0042376309424812545 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.94470244692618, 'radius': 9.893584304166218e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:51,269]\u001b[0m Trial 200 finished with value: 0.024858297597182312 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.5256451267969737, 'radius': 9.71883270348135e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:51,861]\u001b[0m Trial 201 finished with value: 0.0006635087013649032 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6250781937018703, 'radius': 1.006434978216242e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:52,411]\u001b[0m Trial 202 finished with value: 0.00418711973817888 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.9054719193980354, 'radius': 9.97576129386463e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:53,010]\u001b[0m Trial 203 finished with value: 0.006200342186909177 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.76148736351124, 'radius': 1.0661802028911081e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:53,521]\u001b[0m Trial 204 finished with value: 0.001638919879825963 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.336520532230504, 'radius': 9.308029601887194e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:54,103]\u001b[0m Trial 205 finished with value: 0.003951755570871607 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.9144128267841625, 'radius': 1.049033005264856e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:54,652]\u001b[0m Trial 206 finished with value: 0.00017055294661107176 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.779219629773747, 'radius': 9.910893529792836e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:55,243]\u001b[0m Trial 207 finished with value: 0.004070148500650421 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.9785662438286433, 'radius': 9.396152674045469e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:55,802]\u001b[0m Trial 208 finished with value: 0.00038878458416918274 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.683901657984894, 'radius': 9.765894757085006e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:56,338]\u001b[0m Trial 209 finished with value: 0.006471614618474505 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.2714643157501815, 'radius': 9.733993751373837e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:56,903]\u001b[0m Trial 210 finished with value: 0.029154799622259458 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.133291955142697, 'radius': 1.0461127833375783e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:57,445]\u001b[0m Trial 211 finished with value: 0.004954318566937992 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.6832591694881116, 'radius': 9.898041455257569e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:58,042]\u001b[0m Trial 212 finished with value: 0.0012702996598567809 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.643253501940289, 'radius': 1.0371221180670384e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:58,628]\u001b[0m Trial 213 finished with value: 0.004905443691908386 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.693067967336142, 'radius': 1.0290452479536284e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:59,244]\u001b[0m Trial 214 finished with value: 0.0014908598047943806 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9896159224741825, 'radius': 9.548293016655162e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:45:59,805]\u001b[0m Trial 215 finished with value: 0.00013016099057063744 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7208111628635603, 'radius': 9.954409592358583e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:00,352]\u001b[0m Trial 216 finished with value: 0.0011800465623544724 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.4353508791629697, 'radius': 9.617014838318518e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:00,903]\u001b[0m Trial 217 finished with value: 0.0005639328191745881 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6247847348850506, 'radius': 9.688029904715824e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:01,445]\u001b[0m Trial 218 finished with value: 0.00423383091318805 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.6419903262281013, 'radius': 9.590482011105593e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:01,987]\u001b[0m Trial 219 finished with value: 0.005087588518789659 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.735188958489767, 'radius': 9.134344377023622e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:02,610]\u001b[0m Trial 220 finished with value: 0.0003288008739431578 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6650717020931327, 'radius': 9.897364299373783e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:03,193]\u001b[0m Trial 221 finished with value: 0.0003074385300924505 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7938173928307375, 'radius': 9.86598525859038e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:03,787]\u001b[0m Trial 222 finished with value: 0.026856184090301462 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.999737944897087, 'radius': 1.008937097141696e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:04,417]\u001b[0m Trial 223 finished with value: 0.022714059795913174 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.6582324793678547, 'radius': 9.315080268945801e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:04,624]\u001b[0m Trial 224 finished with value: 0.007466401084284733 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -1.1592814525348332, 'radius': 2.7397682656960864e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:05,218]\u001b[0m Trial 225 finished with value: 0.005421844970856108 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.9440471481601644, 'radius': 1.0167994419279747e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:05,787]\u001b[0m Trial 226 finished with value: 0.004689627745434923 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.9672371237227346, 'radius': 1.0382503380990962e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:06,364]\u001b[0m Trial 227 finished with value: 0.005084707635436162 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.505856725162466, 'radius': 1.02141895337776e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:06,902]\u001b[0m Trial 228 finished with value: 0.005551270973576314 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.651614643644838, 'radius': 9.9691956380467e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:07,440]\u001b[0m Trial 229 finished with value: 0.025529681453600312 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.2913120620306247, 'radius': 9.853734497685558e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:08,061]\u001b[0m Trial 230 finished with value: 0.00683376229175246 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.4120055805025995, 'radius': 1.0668119779109954e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:08,703]\u001b[0m Trial 231 finished with value: 0.0077564060304953645 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.3141429778421627, 'radius': 1.0350340287382384e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:09,245]\u001b[0m Trial 232 finished with value: 0.0014586056864474613 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.828153584381087, 'radius': 9.342342015360039e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:09,812]\u001b[0m Trial 233 finished with value: 0.00011131980088498384 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.779013357204766, 'radius': 9.965169916748329e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:10,362]\u001b[0m Trial 234 finished with value: 0.00026251942868004997 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.804804188754636, 'radius': 9.9186420271205e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:10,921]\u001b[0m Trial 235 finished with value: 0.005169714244183337 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.823220040857525, 'radius': 9.627020249624232e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:11,421]\u001b[0m Trial 236 finished with value: 0.021796828021992055 and parameters: {'aberration_name': 'Piston', 'coefficient': -2.958468760926044, 'radius': 9.146707058778686e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:12,004]\u001b[0m Trial 237 finished with value: 0.00021113919746684694 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7584010784495137, 'radius': 9.901482623911958e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:12,503]\u001b[0m Trial 238 finished with value: 0.0015429980115407285 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.5408499294810363, 'radius': 9.144939460225815e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:13,040]\u001b[0m Trial 239 finished with value: 0.004590325623924453 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.499995563834934, 'radius': 9.84864721657799e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:13,662]\u001b[0m Trial 240 finished with value: 0.00234612741262278 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.357029559281819, 'radius': 1.0286070375609573e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:14,272]\u001b[0m Trial 241 finished with value: 0.02647967491668039 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.785173083131124, 'radius': 1.0033746673507173e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:14,846]\u001b[0m Trial 242 finished with value: 0.024180275178725546 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.970209781584802, 'radius': 9.57939292890036e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:15,247]\u001b[0m Trial 243 finished with value: 0.011882937360049474 and parameters: {'aberration_name': 'Piston', 'coefficient': -2.15175808110674, 'radius': 6.684218413317479e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:15,841]\u001b[0m Trial 244 finished with value: 0.004306940854846458 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.993133153193382, 'radius': 1.0014613900207277e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:16,361]\u001b[0m Trial 245 finished with value: 0.004402886145408587 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.699630997418871, 'radius': 9.158497653319395e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:16,706]\u001b[0m Trial 246 finished with value: 0.006596554504953594 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': -3.9172012719881724, 'radius': 5.674490720831308e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:17,266]\u001b[0m Trial 247 finished with value: 0.005119030919083415 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.565661921502845, 'radius': 9.683777797458346e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:17,863]\u001b[0m Trial 248 finished with value: 0.006002455009536824 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.791634544581256, 'radius': 1.0521682812611266e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:18,529]\u001b[0m Trial 249 finished with value: 0.00016855168070129445 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8016973926489666, 'radius': 1.00083379623751e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:19,154]\u001b[0m Trial 250 finished with value: 0.0002508752072163038 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.715943422362802, 'radius': 1.0040508952340887e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:19,821]\u001b[0m Trial 251 finished with value: 0.0009146225273615172 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7108265862020002, 'radius': 1.0297660708588612e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:20,379]\u001b[0m Trial 252 finished with value: 0.00019808738208471814 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.800895888733846, 'radius': 9.936542196373196e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:21,000]\u001b[0m Trial 253 finished with value: 0.021769041644577204 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -0.5559999260552061, 'radius': 1.0079037065715734e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:21,646]\u001b[0m Trial 254 finished with value: 0.006610416013578007 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.376427293313112, 'radius': 1.0034102398481152e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:22,365]\u001b[0m Trial 255 finished with value: 0.0038352154260276046 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.2898983902125467, 'radius': 1.0826725661210578e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:22,968]\u001b[0m Trial 256 finished with value: 0.0009480226689337119 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9728276607535706, 'radius': 9.901659842096181e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:23,605]\u001b[0m Trial 257 finished with value: 0.006550835268529233 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.4331587747694234, 'radius': 1.0511577303400653e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:24,217]\u001b[0m Trial 258 finished with value: 0.004077748473357519 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.991114595294145, 'radius': 1.0075366406421567e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:24,836]\u001b[0m Trial 259 finished with value: 0.0058498669784038575 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.6869870540568135, 'radius': 1.0271170617100472e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:25,465]\u001b[0m Trial 260 finished with value: 0.005838120206246005 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.3110182128892482, 'radius': 9.541726926401777e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:26,021]\u001b[0m Trial 261 finished with value: 0.025528367007966436 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.3619224521545306, 'radius': 9.863521791788966e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:26,615]\u001b[0m Trial 262 finished with value: 0.005047023572857116 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -3.5794575572145857, 'radius': 1.0266869630412409e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:27,197]\u001b[0m Trial 263 finished with value: 0.029839770019900173 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.9505973278761966, 'radius': 1.059677485852206e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:27,495]\u001b[0m Trial 264 finished with value: 0.0067163442422844225 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': -2.227400109405417, 'radius': 4.951190091113761e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:28,088]\u001b[0m Trial 265 finished with value: 0.0015937665450055974 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.772255736342763, 'radius': 1.0631752747184533e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:28,665]\u001b[0m Trial 266 finished with value: 0.0011433612548405003 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.630288994673861, 'radius': 9.378749627744143e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:29,462]\u001b[0m Trial 267 finished with value: 0.03548163187747449 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -1.6440685650809497, 'radius': 1.1478536968867052e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:30,201]\u001b[0m Trial 268 finished with value: 0.00020215523764796815 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.810513869010679, 'radius': 1.0025553756281628e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:30,858]\u001b[0m Trial 269 finished with value: 0.02717954498545004 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.44642380270834, 'radius': 1.0114272688801163e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:31,487]\u001b[0m Trial 270 finished with value: 0.0044014681927772885 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.3481664070850674, 'radius': 9.396062267356193e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:31,764]\u001b[0m Trial 271 finished with value: 0.008030485050660806 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 2.0641707976957084, 'radius': 4.424790144881809e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:32,507]\u001b[0m Trial 272 finished with value: 0.0036738824400998154 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.6930326613736466, 'radius': 1.0099569585256807e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:33,104]\u001b[0m Trial 273 finished with value: 0.0017670451349746658 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.3485337102566644, 'radius': 9.933531090512901e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:33,739]\u001b[0m Trial 274 finished with value: 0.004277627618407956 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.9866465502282704, 'radius': 1.0152373709818421e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:34,363]\u001b[0m Trial 275 finished with value: 0.0005702904433901644 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.782170202359045, 'radius': 1.0209058307863515e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:35,021]\u001b[0m Trial 276 finished with value: 0.01865407019971125 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': -1.099203054517906, 'radius': 1.048727864048006e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:35,802]\u001b[0m Trial 277 finished with value: 0.016031088724518534 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -2.079908304861703, 'radius': 1.1961078669049215e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:36,363]\u001b[0m Trial 278 finished with value: 0.0010050880409393796 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8551385969030165, 'radius': 9.580916447695052e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:36,600]\u001b[0m Trial 279 finished with value: 0.007223981902110692 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.099369598629382, 'radius': 3.998232637840947e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:37,317]\u001b[0m Trial 280 finished with value: 0.001978305031239967 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.4768102612173633, 'radius': 1.0410577055178476e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:37,648]\u001b[0m Trial 281 finished with value: 0.009024624054115516 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 2.759508543011529, 'radius': 5.367308541639743e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:38,243]\u001b[0m Trial 282 finished with value: 0.00018900532577260834 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7958333051805013, 'radius': 1.005943292421563e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:38,731]\u001b[0m Trial 283 finished with value: 0.019368366970339935 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': -2.8269159718622263, 'radius': 8.655629482668287e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:38,989]\u001b[0m Trial 284 finished with value: 0.007385775923609135 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -2.7609391052571177, 'radius': 2.9301969996055964e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:39,600]\u001b[0m Trial 285 finished with value: 0.00031202823025676483 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7424245348712235, 'radius': 1.0102819586144511e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:39,884]\u001b[0m Trial 286 finished with value: 0.008088143518917358 and parameters: {'aberration_name': 'Piston', 'coefficient': -0.7229813620569159, 'radius': 4.6113647487364993e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:40,469]\u001b[0m Trial 287 finished with value: 0.0010018862360250715 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.484944146843033, 'radius': 9.782849621337316e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:41,174]\u001b[0m Trial 288 finished with value: 0.002809334373342774 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.4389957421165436, 'radius': 1.0856920646138436e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:41,828]\u001b[0m Trial 289 finished with value: 0.005949237321876289 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.751977331905191, 'radius': 1.0435017566023587e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:42,467]\u001b[0m Trial 290 finished with value: 0.0005775439768408628 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8609141616952103, 'radius': 9.856991334594725e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:43,104]\u001b[0m Trial 291 finished with value: 0.00017598222398482023 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.785406615110671, 'radius': 1.0060139104490795e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:43,187]\u001b[0m Trial 292 finished with value: 0.0076180135276540835 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -1.1354759929343647, 'radius': 8.064373831456344e-08}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:43,784]\u001b[0m Trial 293 finished with value: 0.0035339086044447296 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.133869564564935, 'radius': 1.0359583255565487e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:44,106]\u001b[0m Trial 294 finished with value: 0.007576362238099918 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.005361467505225, 'radius': 5.69083791302254e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:44,706]\u001b[0m Trial 295 finished with value: 0.00024129609112110597 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8184236578596904, 'radius': 1.0049642824532377e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:45,331]\u001b[0m Trial 296 finished with value: 0.0051973288507350425 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.937795473729948, 'radius': 9.842964255775597e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:46,064]\u001b[0m Trial 297 finished with value: 0.023239127670086818 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.553994471453714, 'radius': 9.442371046257227e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:46,415]\u001b[0m Trial 298 finished with value: 0.008580020556959653 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.645716127307272, 'radius': 4.927029001259428e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:47,130]\u001b[0m Trial 299 finished with value: 0.006305247125363202 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.293704525170485, 'radius': 1.0124577020453204e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:47,576]\u001b[0m Trial 300 finished with value: 0.006555273959848935 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.7215027731193568, 'radius': 6.613719824882636e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:48,363]\u001b[0m Trial 301 finished with value: 0.0014462892842712124 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.451159093832349, 'radius': 1.0075970728754374e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:49,071]\u001b[0m Trial 302 finished with value: 0.00099831407334067 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.907906030168748, 'radius': 1.0444566766790935e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:49,723]\u001b[0m Trial 303 finished with value: 0.0017885450702717857 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6031912167228066, 'radius': 1.0533912658921395e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:50,422]\u001b[0m Trial 304 finished with value: 0.0028500903390684717 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.791201592991699, 'radius': 1.1120136972308592e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:51,170]\u001b[0m Trial 305 finished with value: 0.029643330681682126 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.8560107688190595, 'radius': 1.0550825191716545e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:51,734]\u001b[0m Trial 306 finished with value: 0.0032505799578368562 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.9145275207752195, 'radius': 9.26782049522048e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:52,466]\u001b[0m Trial 307 finished with value: 0.005677903407799377 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.6111524386037033, 'radius': 1.0688224086651458e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:52,604]\u001b[0m Trial 308 finished with value: 0.007600442810794851 and parameters: {'aberration_name': 'Defocus', 'coefficient': 0.6218911815976259, 'radius': 1.4469010232100522e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:53,261]\u001b[0m Trial 309 finished with value: 0.0014274910450638313 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9813619027151623, 'radius': 1.064713532842495e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:53,884]\u001b[0m Trial 310 finished with value: 0.0054636571705421084 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.5483923388742036, 'radius': 9.66415846027825e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:54,542]\u001b[0m Trial 311 finished with value: 0.0001933265028732938 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.798304456855384, 'radius': 1.0057185739322401e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:55,259]\u001b[0m Trial 312 finished with value: 0.004748025905825734 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.139696047570825, 'radius': 9.382090044663733e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:55,666]\u001b[0m Trial 313 finished with value: 0.00830441341272944 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 0.3529633938989563, 'radius': 4.909949591747258e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:56,228]\u001b[0m Trial 314 finished with value: 0.011213695371744168 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': -0.7051195060993196, 'radius': 7.471474791501654e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:56,865]\u001b[0m Trial 315 finished with value: 0.026091276840267824 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.8682408355124256, 'radius': 9.95972266056123e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:57,594]\u001b[0m Trial 316 finished with value: 0.0011880504997179612 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.626700957589748, 'radius': 1.0284943939303652e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:58,672]\u001b[0m Trial 317 finished with value: 0.024223435427402483 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.6632522218801107, 'radius': 9.629077779480237e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:59,275]\u001b[0m Trial 318 finished with value: 0.024858297597182312 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.8019847095121038, 'radius': 9.70880825522004e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:46:59,808]\u001b[0m Trial 319 finished with value: 0.0158473984636832 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 0.22123709653416862, 'radius': 7.811595193946102e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:00,477]\u001b[0m Trial 320 finished with value: 0.004225801579565408 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.510531714165992, 'radius': 9.389380231348271e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:01,138]\u001b[0m Trial 321 finished with value: 0.004063304744994054 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.7246385884058957, 'radius': 9.390844515192446e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:01,245]\u001b[0m Trial 322 finished with value: 0.0076100417926289205 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 1.3306489867865943, 'radius': 1.0523924897579903e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:01,715]\u001b[0m Trial 323 finished with value: 0.005190696512356232 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.353551582100891, 'radius': 6.971769122646827e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:02,426]\u001b[0m Trial 324 finished with value: 0.0014100072534557102 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.372292227047605, 'radius': 9.624177651561866e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:03,087]\u001b[0m Trial 325 finished with value: 0.025013966097160893 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 0.5940524388740606, 'radius': 1.02132595791544e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:03,783]\u001b[0m Trial 326 finished with value: 0.023904969482465878 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 1.2344308975172138, 'radius': 1.1240122779329866e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:04,514]\u001b[0m Trial 327 finished with value: 0.0030474568605620943 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.460406618174737, 'radius': 1.0822100142361717e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:05,192]\u001b[0m Trial 328 finished with value: 0.005847486683434755 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.66207199057613, 'radius': 1.0851230579809644e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:05,837]\u001b[0m Trial 329 finished with value: 0.005394283893661174 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.4179102428669674, 'radius': 1.0309923040375447e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:06,393]\u001b[0m Trial 330 finished with value: 0.005061698901004751 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.7814314741892714, 'radius': 8.87818279253048e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:07,056]\u001b[0m Trial 331 finished with value: 0.00474219811730729 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.746720767008673, 'radius': 1.0237502912085967e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:07,754]\u001b[0m Trial 332 finished with value: 0.0031296056592436407 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.0928707364221717, 'radius': 1.00300662543615e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:08,393]\u001b[0m Trial 333 finished with value: 0.0007036049646231314 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6813082474302257, 'radius': 9.582458622063047e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:09,072]\u001b[0m Trial 334 finished with value: 0.00027661942828250297 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8302350823151374, 'radius': 1.005998835312949e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:09,761]\u001b[0m Trial 335 finished with value: 0.00023351223129496645 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.809827477808612, 'radius': 9.974647536995064e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:10,431]\u001b[0m Trial 336 finished with value: 0.024198349766058985 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 0.01675212544272989, 'radius': 9.617346535473e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:11,102]\u001b[0m Trial 337 finished with value: 0.000950962286122866 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.926102334321637, 'radius': 9.744274376684505e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:11,792]\u001b[0m Trial 338 finished with value: 0.02984866449034732 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.683984296866916, 'radius': 1.0595193315345012e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:12,472]\u001b[0m Trial 339 finished with value: 0.003755248895791976 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.27472376861847, 'radius': 9.161397632080674e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:12,747]\u001b[0m Trial 340 finished with value: 0.007181958410334762 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 1.558886520202616, 'radius': 3.943007772112507e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:13,241]\u001b[0m Trial 341 finished with value: 0.005174732963266489 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -3.035288738498419, 'radius': 7.549477227444421e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:13,922]\u001b[0m Trial 342 finished with value: 0.00547395258956512 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.7198351098754645, 'radius': 1.018827437094129e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:14,629]\u001b[0m Trial 343 finished with value: 0.0008388182550078152 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9918796203596116, 'radius': 1.011794201447085e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:15,087]\u001b[0m Trial 344 finished with value: 0.010366672630933412 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -0.805267250383121, 'radius': 6.717144579233723e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:15,220]\u001b[0m Trial 345 finished with value: 0.007600655390856647 and parameters: {'aberration_name': 'Piston', 'coefficient': -0.009001989389506278, 'radius': 1.4326166402358503e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:15,809]\u001b[0m Trial 346 finished with value: 0.0022832425238576886 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.135707911717983, 'radius': 9.262268625267773e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:16,255]\u001b[0m Trial 347 finished with value: 0.010989255694677496 and parameters: {'aberration_name': 'Piston', 'coefficient': 0.5483889499114264, 'radius': 6.30110344631935e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:16,940]\u001b[0m Trial 348 finished with value: 0.0014386745655842654 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.5263122226735324, 'radius': 1.0236405479157744e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:17,391]\u001b[0m Trial 349 finished with value: 0.016416056652658866 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -1.2198985558116886, 'radius': 7.952147083510265e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:17,921]\u001b[0m Trial 350 finished with value: 0.021826884711895776 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.8681160140772564, 'radius': 9.162121703647753e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:18,539]\u001b[0m Trial 351 finished with value: 0.0009242291859431963 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8044675706480686, 'radius': 1.039895994753478e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:19,132]\u001b[0m Trial 352 finished with value: 0.008621769209954996 and parameters: {'aberration_name': 'Defocus', 'coefficient': -1.9952365406607575, 'radius': 9.552440512389145e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:19,690]\u001b[0m Trial 353 finished with value: 0.0015142599729288996 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.906789542119226, 'radius': 9.385196553986476e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:20,322]\u001b[0m Trial 354 finished with value: 0.0007023447884610083 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6627317254611946, 'radius': 1.01694273822817e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:21,077]\u001b[0m Trial 355 finished with value: 0.013421302265009802 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 1.2681056572011922, 'radius': 1.0840093584503928e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:21,659]\u001b[0m Trial 356 finished with value: 0.0008755108065527789 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.573532909913399, 'radius': 9.552844120892885e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:21,852]\u001b[0m Trial 357 finished with value: 0.007425755471545966 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -2.7782685787192873, 'radius': 3.023104769103762e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:22,442]\u001b[0m Trial 358 finished with value: 0.02609387673851043 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.7920373492218893, 'radius': 9.93551380466649e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:23,034]\u001b[0m Trial 359 finished with value: 0.02182205202861562 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': -3.9965541066562262, 'radius': 9.143333413662593e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:23,794]\u001b[0m Trial 360 finished with value: 0.011800384450081943 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': -3.4496430833878455, 'radius': 1.1745565165057049e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:23,924]\u001b[0m Trial 361 finished with value: 0.007585065023392273 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -3.916165366799558, 'radius': 1.5559730918565112e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:24,504]\u001b[0m Trial 362 finished with value: 0.0009315272915425353 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.502630583755736, 'radius': 9.791918315564045e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:25,104]\u001b[0m Trial 363 finished with value: 0.005133270671867678 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.8221546846304664, 'radius': 1.0213419204974943e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:25,665]\u001b[0m Trial 364 finished with value: 0.0004868729613549121 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8639916341481153, 'radius': 9.928673878281577e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:26,374]\u001b[0m Trial 365 finished with value: 0.030518604848128343 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.887002124829355, 'radius': 1.0710966417315417e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:26,993]\u001b[0m Trial 366 finished with value: 0.02741421570921946 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.2256066399813252, 'radius': 1.0184311970593023e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:27,661]\u001b[0m Trial 367 finished with value: 0.005664160815973968 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.951723383651269, 'radius': 1.0428394715330428e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:28,345]\u001b[0m Trial 368 finished with value: 0.02723063071148081 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 2.681320130521095, 'radius': 1.0164923477873065e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:28,521]\u001b[0m Trial 369 finished with value: 0.007498737971133521 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -0.46940064288997396, 'radius': 2.552050856054793e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:28,696]\u001b[0m Trial 370 finished with value: 0.007477066936656441 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': -1.8778690377033374, 'radius': 2.597429554349301e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:29,290]\u001b[0m Trial 371 finished with value: 0.0010788107139168327 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7786348831740324, 'radius': 9.493720251300539e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:29,826]\u001b[0m Trial 372 finished with value: 0.001662979124679256 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7991631320897126, 'radius': 9.165494086814911e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:29,960]\u001b[0m Trial 373 finished with value: 0.007579213277489734 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -1.9778050663077344, 'radius': 1.858720812763736e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:30,612]\u001b[0m Trial 374 finished with value: 0.001988271099901358 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.331599953285495, 'radius': 1.0062761174052725e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:31,280]\u001b[0m Trial 375 finished with value: 0.019804613761976786 and parameters: {'aberration_name': 'Piston', 'coefficient': -1.9522380036730376, 'radius': 8.719155307749461e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:31,920]\u001b[0m Trial 376 finished with value: 0.005429179228931575 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.7741562389291206, 'radius': 9.99500905724198e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:32,167]\u001b[0m Trial 377 finished with value: 0.007195504593094311 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -1.9203482643999201, 'radius': 3.7377494315147636e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:32,414]\u001b[0m Trial 378 finished with value: 0.007318092010721871 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.1586082241102535, 'radius': 3.346618315783356e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:33,062]\u001b[0m Trial 379 finished with value: 0.0045004042262352315 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.8878031251399108, 'radius': 1.0169582202669907e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:33,820]\u001b[0m Trial 380 finished with value: 0.001871784082566384 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.841367759692491, 'radius': 1.0797117254393366e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:34,420]\u001b[0m Trial 381 finished with value: 0.0250933668359542 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 0.9547565453327195, 'radius': 9.757503429864405e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:35,107]\u001b[0m Trial 382 finished with value: 0.009761624207999508 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.130052282931497, 'radius': 1.069982177049524e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:35,702]\u001b[0m Trial 383 finished with value: 0.005386450203445059 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.2946493160711534, 'radius': 9.232863910563796e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:35,988]\u001b[0m Trial 384 finished with value: 0.007682996240945004 and parameters: {'aberration_name': 'Defocus', 'coefficient': -0.0019512723457499445, 'radius': 3.913345658672067e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:36,681]\u001b[0m Trial 385 finished with value: 0.0002942878442209474 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.8245058158095135, 'radius': 1.009475674626878e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:37,042]\u001b[0m Trial 386 finished with value: 0.00816832551974096 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -1.0709685767651425, 'radius': 4.712903581557104e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:37,318]\u001b[0m Trial 387 finished with value: 0.007153392408122092 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.457745624052995, 'radius': 3.894196878692629e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:38,077]\u001b[0m Trial 388 finished with value: 0.0009342677561244377 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.576620934997829, 'radius': 1.0107620847773092e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:38,686]\u001b[0m Trial 389 finished with value: 0.001275186431039483 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.954040252077087, 'radius': 9.631002681226087e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:38,822]\u001b[0m Trial 390 finished with value: 0.007585294149775615 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.205691817691823, 'radius': 1.558974249232992e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:39,508]\u001b[0m Trial 391 finished with value: 0.00414103937807166 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.9125422587372323, 'radius': 9.639580449073826e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:40,121]\u001b[0m Trial 392 finished with value: 0.0013957259247834462 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6332348840509088, 'radius': 1.0420754719020067e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:40,729]\u001b[0m Trial 393 finished with value: 0.0005281264367268555 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6120312842489684, 'radius': 9.868189953499671e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:41,298]\u001b[0m Trial 394 finished with value: 0.0014241106038034718 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.503580888572337, 'radius': 9.272811635333338e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:41,864]\u001b[0m Trial 395 finished with value: 0.003969127483581923 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.7483371497113307, 'radius': 9.834831109829202e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:42,584]\u001b[0m Trial 396 finished with value: 0.0008388092732568013 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9776261464636113, 'radius': 1.0247748023526871e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:43,030]\u001b[0m Trial 397 finished with value: 0.00553823214046545 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 2.8062867620416565, 'radius': 7.244960462173855e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:43,726]\u001b[0m Trial 398 finished with value: 0.02717954498545004 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.9975010593900957, 'radius': 1.0150541963774318e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:43,827]\u001b[0m Trial 399 finished with value: 0.00761120500519906 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -3.541564208912223, 'radius': 9.799484484022798e-08}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:44,135]\u001b[0m Trial 400 finished with value: 0.006926183437528528 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -3.453060576625954, 'radius': 4.830991943789445e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:44,707]\u001b[0m Trial 401 finished with value: 0.0021548007781033067 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.2174626315667116, 'radius': 9.743477000401218e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:45,395]\u001b[0m Trial 402 finished with value: 0.005252616499168852 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.9860230975438378, 'radius': 1.0551888781520877e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:46,118]\u001b[0m Trial 403 finished with value: 0.027468531702179274 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 0.8700147328655974, 'radius': 1.080572121328707e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:46,820]\u001b[0m Trial 404 finished with value: 0.008286591190692982 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.2826098312643914, 'radius': 1.0461346266645074e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:47,465]\u001b[0m Trial 405 finished with value: 0.002503770762272825 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.4275172555610114, 'radius': 1.0529721821517123e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:48,090]\u001b[0m Trial 406 finished with value: 0.029272950636464026 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.545744959054483, 'radius': 1.0504706854945855e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:48,742]\u001b[0m Trial 407 finished with value: 0.005827467025919151 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.930483114506481, 'radius': 1.1035985572824538e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:49,324]\u001b[0m Trial 408 finished with value: 0.004456224773162991 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -3.9838925509063428, 'radius': 9.72689082388861e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:49,554]\u001b[0m Trial 409 finished with value: 0.007631042597578032 and parameters: {'aberration_name': 'Piston', 'coefficient': -1.6388696882392815, 'radius': 3.7746198060158305e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:50,111]\u001b[0m Trial 410 finished with value: 0.0013814648302962352 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.431969948495208, 'radius': 9.939209264782098e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:50,661]\u001b[0m Trial 411 finished with value: 0.0039436619780087055 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.8279366341591454, 'radius': 9.635023623558947e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:51,074]\u001b[0m Trial 412 finished with value: 0.012851015912599541 and parameters: {'aberration_name': 'Piston', 'coefficient': -0.15966234850957364, 'radius': 6.9624566246569e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:51,631]\u001b[0m Trial 413 finished with value: 0.0001038737177402172 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.755832805764673, 'radius': 9.919228176353372e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:52,359]\u001b[0m Trial 414 finished with value: 0.032831930243544534 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.6695410347350945, 'radius': 1.10686801360411e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:52,530]\u001b[0m Trial 415 finished with value: 0.007526769743333389 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 2.3595462841366137, 'radius': 2.162844736589539e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:53,106]\u001b[0m Trial 416 finished with value: 0.006190916215487854 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.169305185461183, 'radius': 9.90467678751979e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:53,513]\u001b[0m Trial 417 finished with value: 0.013315773079094533 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': -3.232412370926438, 'radius': 7.097364474425318e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:54,189]\u001b[0m Trial 418 finished with value: 0.0018979460938827013 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.658175958953155, 'radius': 1.0686996357601294e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:54,845]\u001b[0m Trial 419 finished with value: 0.014388370010430094 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.2823367597432864, 'radius': 1.1838655304411982e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:55,406]\u001b[0m Trial 420 finished with value: 0.005050875039354829 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.9063372152747577, 'radius': 8.756507597374622e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:56,088]\u001b[0m Trial 421 finished with value: 0.005495876654832026 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.2158603827562806, 'radius': 1.0099648084950527e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:56,211]\u001b[0m Trial 422 finished with value: 0.007586042070754985 and parameters: {'aberration_name': 'Defocus', 'coefficient': 2.9927894780403794, 'radius': 1.593049853057845e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:56,707]\u001b[0m Trial 423 finished with value: 0.004439011303847279 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -2.82572956536485, 'radius': 8.209376985668153e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:57,289]\u001b[0m Trial 424 finished with value: 0.004076919034098327 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.8951042616073863, 'radius': 9.85010313078038e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:57,899]\u001b[0m Trial 425 finished with value: 0.0010078398679576612 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.987788447674404, 'radius': 1.039812386106873e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:58,470]\u001b[0m Trial 426 finished with value: 0.005425221402110017 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.523256151055662, 'radius': 9.757766489328497e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:59,122]\u001b[0m Trial 427 finished with value: 0.016721004121475678 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.660994965141547, 'radius': 1.0723664340769317e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:47:59,757]\u001b[0m Trial 428 finished with value: 0.0008539397106577492 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.946820055332606, 'radius': 9.896880282316061e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:00,423]\u001b[0m Trial 429 finished with value: 0.029458233834543785 and parameters: {'aberration_name': 'Piston', 'coefficient': -0.6868935481845015, 'radius': 1.052671998554194e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:01,043]\u001b[0m Trial 430 finished with value: 0.002703613010184605 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 2.936868733594414, 'radius': 1.0250366639176256e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:01,681]\u001b[0m Trial 431 finished with value: 0.0026205279330982654 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.2912833907116976, 'radius': 1.0266082352367825e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:02,268]\u001b[0m Trial 432 finished with value: 0.019859697004316862 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.3509933678751824, 'radius': 9.037007171749552e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:02,963]\u001b[0m Trial 433 finished with value: 0.007414906686395223 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 3.5327327688576657, 'radius': 1.06051423230208e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:03,567]\u001b[0m Trial 434 finished with value: 0.0023501852691870232 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7627718053884256, 'radius': 8.772324128029455e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:04,124]\u001b[0m Trial 435 finished with value: 0.006391048887591075 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': 3.392255269002184, 'radius': 9.954770191778903e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:04,759]\u001b[0m Trial 436 finished with value: 0.0006037133996863306 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.811430347389171, 'radius': 1.0243010660821897e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:05,357]\u001b[0m Trial 437 finished with value: 0.004635395596511322 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.5914931842005897, 'radius': 1.000007468725248e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:05,789]\u001b[0m Trial 438 finished with value: 0.01278263953166579 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -3.715076270200325, 'radius': 6.89796123687064e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:06,323]\u001b[0m Trial 439 finished with value: 0.021523663495597645 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.4925334482385963, 'radius': 9.091687736986236e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:06,705]\u001b[0m Trial 440 finished with value: 0.006215462351780925 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.35750913784001, 'radius': 5.458286740867763e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:07,123]\u001b[0m Trial 441 finished with value: 0.006338255863986376 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 1.8394627984100076, 'radius': 5.602296004729903e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:07,702]\u001b[0m Trial 442 finished with value: 0.0005781084637531991 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.6179401221856127, 'radius': 9.685166481167611e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:08,284]\u001b[0m Trial 443 finished with value: 0.023507730493039742 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.152252499695109, 'radius': 9.476273444826453e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:08,889]\u001b[0m Trial 444 finished with value: 0.0001454616043654817 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.748411350646537, 'radius': 1.0042808807471607e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:09,496]\u001b[0m Trial 445 finished with value: 0.0029182743079055372 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.392067705510166, 'radius': 1.0279348694407507e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:10,005]\u001b[0m Trial 446 finished with value: 0.004360343662595756 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -3.169731512350372, 'radius': 8.503270058817286e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:10,369]\u001b[0m Trial 447 finished with value: 0.00777304449369626 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': -0.8108556454480286, 'radius': 5.774136360628073e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:11,059]\u001b[0m Trial 448 finished with value: 0.0012632278066035455 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7327323907830707, 'radius': 1.0458789167561075e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:11,692]\u001b[0m Trial 449 finished with value: 0.0017064130597309812 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.46515730529925, 'radius': 1.023893123488548e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:11,944]\u001b[0m Trial 450 finished with value: 0.00745670285993348 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 0.5303093234067553, 'radius': 3.988469109497286e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:12,472]\u001b[0m Trial 451 finished with value: 0.0050126497495509795 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.971796377538901, 'radius': 9.320962896504514e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:12,708]\u001b[0m Trial 452 finished with value: 0.007655951672611565 and parameters: {'aberration_name': 'Piston', 'coefficient': 2.140517886635612, 'radius': 3.8425223090680087e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:13,259]\u001b[0m Trial 453 finished with value: 0.0009405521907045271 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.99437070484079, 'radius': 9.93482422421682e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:13,966]\u001b[0m Trial 454 finished with value: 0.03126771939654018 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -0.6019670482955379, 'radius': 1.0842955529669644e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:14,672]\u001b[0m Trial 455 finished with value: 0.032007976558778066 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -0.5842843089724755, 'radius': 1.1944964518045141e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:15,292]\u001b[0m Trial 456 finished with value: 0.000707197050941654 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.717202402018956, 'radius': 1.0216963062281685e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:15,888]\u001b[0m Trial 457 finished with value: 0.004341217295049652 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.7556766152885928, 'radius': 9.907976113806795e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:16,323]\u001b[0m Trial 458 finished with value: 0.009563761626204752 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': -0.5029899391934943, 'radius': 6.45093243594311e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:17,016]\u001b[0m Trial 459 finished with value: 0.0033685882337904515 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.6879717557775287, 'radius': 1.0731236016602771e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:17,150]\u001b[0m Trial 460 finished with value: 0.007600655390856647 and parameters: {'aberration_name': 'Piston', 'coefficient': -0.8423075343218982, 'radius': 1.4860952843562522e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:17,779]\u001b[0m Trial 461 finished with value: 5.269166960695064e-05 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.763811008899023, 'radius': 9.971419257764881e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:18,474]\u001b[0m Trial 462 finished with value: 0.028029472727488174 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.745312702905886, 'radius': 1.0274906282176555e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:18,987]\u001b[0m Trial 463 finished with value: 0.004073011045090236 and parameters: {'aberration_name': 'Trefoil', 'coefficient': 3.7815171657139848, 'radius': 9.049058274919111e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:19,300]\u001b[0m Trial 464 finished with value: 0.007301196017960526 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 0.9539607261166345, 'radius': 4.779590095040358e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:19,875]\u001b[0m Trial 465 finished with value: 0.0007236188459918109 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.7240855793325522, 'radius': 9.621842782508484e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:20,444]\u001b[0m Trial 466 finished with value: 0.0012247337522288927 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.729148701605653, 'radius': 9.36063725461212e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:21,006]\u001b[0m Trial 467 finished with value: 0.0007726719789821867 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.544090255432012, 'radius': 9.762933439578566e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:21,798]\u001b[0m Trial 468 finished with value: 0.003024825660791454 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.604617557051251, 'radius': 1.101336718719499e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:22,300]\u001b[0m Trial 469 finished with value: 0.004817552750125374 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -3.7691501299337915, 'radius': 7.694658400920388e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:22,545]\u001b[0m Trial 470 finished with value: 0.0073218436188545 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.55159995986066, 'radius': 3.4130120827619876e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:23,135]\u001b[0m Trial 471 finished with value: 0.004941263668106059 and parameters: {'aberration_name': 'ObliqueAstigmatism', 'coefficient': -3.413418404106074, 'radius': 9.177657823146445e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:23,343]\u001b[0m Trial 472 finished with value: 0.007539161209383681 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 2.1198860549948484, 'radius': 2.1586380049726186e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:24,024]\u001b[0m Trial 473 finished with value: 0.027759376954905768 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.2774925655983047, 'radius': 1.0226822480387902e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:24,639]\u001b[0m Trial 474 finished with value: 0.026649504956035998 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': 3.55059902799921, 'radius': 1.0055639511229502e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:25,273]\u001b[0m Trial 475 finished with value: 0.003286850612754705 and parameters: {'aberration_name': 'SphericalAberration', 'coefficient': 3.4451185659361134, 'radius': 9.912679243587289e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:25,466]\u001b[0m Trial 476 finished with value: 0.007521160162285639 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 2.9922505645860213, 'radius': 2.4536817344595816e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:25,826]\u001b[0m Trial 477 finished with value: 0.00996600011793662 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': 3.327886872578323, 'radius': 5.820349330892761e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:26,557]\u001b[0m Trial 478 finished with value: 0.0018231583165704225 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.2605351627527215, 'radius': 9.434693379526972e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:27,030]\u001b[0m Trial 479 finished with value: 0.006776597314614378 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 2.2605320054298543, 'radius': 7.567539205204336e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:27,475]\u001b[0m Trial 480 finished with value: 0.007339192420899632 and parameters: {'aberration_name': 'Trefoil', 'coefficient': -1.5519901889022074, 'radius': 7.126644073037616e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:27,573]\u001b[0m Trial 481 finished with value: 0.007604403171222424 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 0.3930070174467855, 'radius': 1.1728852538859776e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:28,097]\u001b[0m Trial 482 finished with value: 0.01238001545856628 and parameters: {'aberration_name': 'Defocus', 'coefficient': 0.9759480183868819, 'radius': 8.183874841898023e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:28,700]\u001b[0m Trial 483 finished with value: 0.0012020903656705004 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.9829834667501403, 'radius': 9.687352082090214e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:28,904]\u001b[0m Trial 484 finished with value: 0.007518256898782242 and parameters: {'aberration_name': 'HorizontalTilt', 'coefficient': -0.46188384040865044, 'radius': 2.922792049400306e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:29,002]\u001b[0m Trial 485 finished with value: 0.007617847047979231 and parameters: {'aberration_name': 'Piston', 'coefficient': 0.974819501428742, 'radius': 9.00767007824817e-08}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:29,098]\u001b[0m Trial 486 finished with value: 0.007605038189011224 and parameters: {'aberration_name': 'Defocus', 'coefficient': -2.600283360138565, 'radius': 1.3078475136943325e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:29,650]\u001b[0m Trial 487 finished with value: 0.004885068037700021 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': 3.2394588085472753, 'radius': 9.705975476356973e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:29,982]\u001b[0m Trial 488 finished with value: 0.006868925837801683 and parameters: {'aberration_name': 'ObliqueTrefoil', 'coefficient': -1.4213858901200447, 'radius': 5.26469739364839e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:30,643]\u001b[0m Trial 489 finished with value: 0.028032492327089834 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.2101030104487682, 'radius': 1.0269293443100748e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:31,284]\u001b[0m Trial 490 finished with value: 0.00018047501640273733 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.799656971126225, 'radius': 9.995858315430945e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:31,857]\u001b[0m Trial 491 finished with value: 0.020532060079160745 and parameters: {'aberration_name': 'Piston', 'coefficient': 3.917331863538644, 'radius': 8.903194558634683e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:32,503]\u001b[0m Trial 492 finished with value: 0.0006900844638975382 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.618748591163599, 'radius': 1.0046022790075009e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:32,883]\u001b[0m Trial 493 finished with value: 0.009835809899590093 and parameters: {'aberration_name': 'VerticalTilt', 'coefficient': -0.399823652803523, 'radius': 5.807548183413349e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:33,527]\u001b[0m Trial 494 finished with value: 0.005148889741335801 and parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 3.995844400123226, 'radius': 9.82056222973188e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:34,207]\u001b[0m Trial 495 finished with value: 0.0010683916211509268 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.857498788273763, 'radius': 1.0490460393464224e-06}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:34,845]\u001b[0m Trial 496 finished with value: 0.0002183327536747837 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.702318132250822, 'radius': 9.873543332611795e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:34,985]\u001b[0m Trial 497 finished with value: 0.0075696203396586415 and parameters: {'aberration_name': 'Astigmatism', 'coefficient': 2.4820481087295585, 'radius': 1.6950717472932063e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:35,606]\u001b[0m Trial 498 finished with value: 0.0051810755113156646 and parameters: {'aberration_name': 'VerticalComa', 'coefficient': 3.7270815807204727, 'radius': 9.483148965584326e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n", + "\u001b[32m[I 2026-09-16 10:48:36,205]\u001b[0m Trial 499 finished with value: 0.001046429741336579 and parameters: {'aberration_name': 'Defocus', 'coefficient': 3.499418137110228, 'radius': 9.531023725776148e-07}. Best is trial 194 with value: 2.7321741232219593e-05.\u001b[0m\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "Best Loss: 0.0006094505564661494\n", - "Best parameters: {'aberration_name': 'HorizontalComa', 'coefficient': 1.7891030519282909, 'radius': 9.96859688596017e-07, 'z': 0.37966630503509}\n" + "Best Loss: 2.7321741232219593e-05\n", + "Best parameters: {'aberration_name': 'Defocus', 'coefficient': 3.748384690806743, 'radius': 9.950419321413887e-07}\n" ] } ], @@ -859,15 +866,15 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 13, "id": "07154378", "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -877,10 +884,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "Name: HorizontalComa vs HorizontalComa\n", - "Coefficient: 1.7301442345449196 vs 1.7891030519282909\n", - "Radius: 1e-06 vs 9.96859688596017e-07\n", - "Z: 0.0 vs 0.37966630503509\n" + "Parameter Predicted Ground Truth \n", + "-------------------------------------------------------\n", + "Aberration Defocus Defocus \n", + "Coefficient 3.7549835225874 3.7484 \n", + "Radius 1e-06 0.0000 \n" ] } ], @@ -896,20 +904,35 @@ "aberration_class = next(\n", " cls for cls in aberration_types if cls.__name__ == predicted_aberration\n", ")\n", + "\n", "# Create aberration instance.\n", "predicted_aberration = aberration_class(coefficient=coeff)\n", "\n", "optics.pupil = predicted_aberration\n", + "\n", "predicted_particle = dt.Sphere(\n", " radius=best_params[\"radius\"],\n", - " position=(IMAGE_SIZE // 2, IMAGE_SIZE // 2, best_params[\"z\"]),\n", + " position=(IMAGE_SIZE // 2, IMAGE_SIZE // 2),\n", " intensity=1,\n", ")\n", "\n", "# Generate predicted image.\n", "predicted_image = optics(predicted_particle).resolve().squeeze()\n", "\n", - "fig, ax = plt.subplots(1, 2, figsize=(18, 5))\n", + "# Calculate difference.\n", + "difference = predicted_image - reference_image\n", + "\n", + "# Fitness history.\n", + "trials = [\n", + " trial for trial in study.trials\n", + " if trial.state == optuna.trial.TrialState.COMPLETE\n", + "]\n", + "\n", + "fitness = [trial.value for trial in trials]\n", + "trial_numbers = [trial.number for trial in trials]\n", + "\n", + "fig, ax = plt.subplots(1, 4, figsize=(22, 5))\n", + "\n", "ax[0].imshow(reference_image, cmap=\"gray\")\n", "ax[0].set_title(f\"Ground truth: {aberration.name()}\")\n", "ax[0].axis(\"off\")\n", @@ -918,31 +941,48 @@ "ax[1].set_title(f\"Predicted: {predicted_aberration.name()}\")\n", "ax[1].axis(\"off\")\n", "\n", + "max_diff = np.max(np.abs(difference))\n", + "\n", + "im = ax[2].imshow(\n", + " difference,\n", + " cmap=\"coolwarm\",\n", + " vmin=-max_diff,\n", + " vmax=max_diff,\n", + ")\n", + "ax[2].set_title(\"Difference\")\n", + "ax[2].axis(\"off\")\n", + "fig.colorbar(im, ax=ax[2], fraction=0.046, pad=0.04)\n", + "\n", + "ax[3].semilogy(trial_numbers, fitness)\n", + "ax[3].scatter(\n", + " study.best_trial.number,\n", + " study.best_trial.value,\n", + " zorder=3,\n", + " c=\"red\",\n", + " label=\"Best Fit\",\n", + ")\n", + "ax[3].legend()\n", + "ax[3].set_xlabel(\"Trial\")\n", + "ax[3].set_ylabel(\"Fitness\")\n", + "ax[3].set_title(\"Fitness history\")\n", + "ax[3].grid(alpha=0.3)\n", + "\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "print(\n", - " f\"Name: {aberration.name()} vs {best_params['aberration_name']}\\n\"\n", - " f\"Coefficient: {aberration.coefficient()} vs {best_params['coefficient']}\\n\"\n", - " f\"Radius: {particle.radius()} vs {best_params['radius']}\\n\"\n", - " f\"Z: {particle.z()} vs {best_params['z']}\"\n", + " f\"{'Parameter':<15} {'Predicted':<20} {'Ground Truth':<20}\\n\"\n", + " f\"{'-' * 55}\\n\"\n", + " f\"{'Aberration':<15} {aberration.name():<20} {best_params['aberration_name']:<20}\\n\"\n", + " f\"{'Coefficient':<15} {aberration.coefficient():<20} {best_params['coefficient']:<20.4f}\\n\"\n", + " f\"{'Radius':<15} {particle.radius():<20} {best_params['radius']:<20.4f}\"\n", ")" ] - }, - { - "cell_type": "markdown", - "id": "2ff91fe9", - "metadata": {}, - "source": [ - "-# TODO: Check the results, they don't seem very consistent.\n", - "\n", - "-# TODO: Check the value of z. Is it in meters? why does this need to be optimized? or is it in pixels? in any case, this needs to be explained." - ] } ], "metadata": { "kernelspec": { - "display_name": "deeptrack2", + "display_name": ".venv-deeptrack (3.11.9)", "language": "python", "name": "python3" }, @@ -956,7 +996,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.14" + "version": "3.11.9" } }, "nbformat": 4, From 250230b9407848c6c62e4483909dfcbab93e082d Mon Sep 17 00:00:00 2001 From: Alex Date: Wed, 16 Sep 2026 11:29:12 +0200 Subject: [PATCH 2/7] fixed rounding error --- ...DTGS127_characterizing_aberrations_optuna.ipynb | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb index a3034068..f6b3a1c7 100644 --- a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb +++ b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb @@ -866,7 +866,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 14, "id": "07154378", "metadata": {}, "outputs": [ @@ -886,9 +886,9 @@ "text": [ "Parameter Predicted Ground Truth \n", "-------------------------------------------------------\n", - "Aberration Defocus Defocus \n", - "Coefficient 3.7549835225874 3.7484 \n", - "Radius 1e-06 0.0000 \n" + "Aberration Defocus Defocus\n", + "Coefficient 3.7549835225874 3.748384690806743\n", + "Radius 1e-06 9.950419321413887e-07\n" ] } ], @@ -973,9 +973,9 @@ "print(\n", " f\"{'Parameter':<15} {'Predicted':<20} {'Ground Truth':<20}\\n\"\n", " f\"{'-' * 55}\\n\"\n", - " f\"{'Aberration':<15} {aberration.name():<20} {best_params['aberration_name']:<20}\\n\"\n", - " f\"{'Coefficient':<15} {aberration.coefficient():<20} {best_params['coefficient']:<20.4f}\\n\"\n", - " f\"{'Radius':<15} {particle.radius():<20} {best_params['radius']:<20.4f}\"\n", + " f\"{'Aberration':<15} {aberration.name():<20} {best_params['aberration_name']}\\n\"\n", + " f\"{'Coefficient':<15} {aberration.coefficient():<20} {best_params['coefficient']}\\n\"\n", + " f\"{'Radius':<15} {particle.radius():<20} {best_params['radius']}\"\n", ")" ] } From 79b39e403ebcb1608fdef2d0f5acfca641aeb819 Mon Sep 17 00:00:00 2001 From: Jiacheng Huang <31703396+JChonpca@users.noreply.github.com> Date: Wed, 16 Sep 2026 15:07:55 +0200 Subject: [PATCH 3/7] Apply suggestion from @JChonpca typo --- .../DTGS127_characterizing_aberrations_optuna.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb index f6b3a1c7..2f272976 100644 --- a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb +++ b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb @@ -35,7 +35,7 @@ "id": "d0edb3ce", "metadata": {}, "source": [ - "This tutorial demonstrates how to identify the aberration type and aberration coefficient of an optical device using the image of a centered particle. DeepTrack2 lets you simulate a number of different optical aberrations, which you can use to identify aberrations you may find experimental setups using various methods." + "This tutorial demonstrates how to identify the aberration type and aberration coefficient of an optical device using the image of a centered particle. DeepTrack2 lets you simulate a number of different optical aberrations, which you can use to identify aberrations you may find in experimental setups using various methods." ] }, { From 46d34f6b4d810c08b9277b750a20f0a969c3373d Mon Sep 17 00:00:00 2001 From: Jiacheng Huang <31703396+JChonpca@users.noreply.github.com> Date: Wed, 16 Sep 2026 15:13:10 +0200 Subject: [PATCH 4/7] Apply suggestion from @JChonpca typo --- .../DTGS127_characterizing_aberrations_optuna.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb index 2f272976..bdb6c9f9 100644 --- a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb +++ b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb @@ -106,7 +106,7 @@ "\n", "Define the features needed for this example:\n", "\n", - "* `optics`: Flourescence microscope with a pixel size of 0.1 microns and a 256x256 camera.\n", + "* `optics`: Fluorescence microscope with a pixel size of 0.1 microns and a 256x256 camera.\n", "\n", "* `particle`: Spherical particle centered in the image with 1e-6 meter radius.\n" ] From c15f36ab78b499058178d18438ced59203d6580f Mon Sep 17 00:00:00 2001 From: Jiacheng Huang <31703396+JChonpca@users.noreply.github.com> Date: Wed, 16 Sep 2026 15:19:31 +0200 Subject: [PATCH 5/7] Apply suggestion from @JChonpca --- .../DTGS127_characterizing_aberrations_optuna.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb index bdb6c9f9..5c55086b 100644 --- a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb +++ b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb @@ -143,7 +143,7 @@ "source": [ "## 3. Combining the Features\n", "\n", - "To image the particle throught the aberrated microscope, choose a random aberration from the list and modify the pupil function of the `optics` microscope with `optics.pupil`." + "To image the particle through the aberrated microscope, choose a random aberration from the list and modify the pupil function of the `optics` microscope with `optics.pupil`." ] }, { From 6f78e102afef2fbd4cf757b4e669c07ca2660f73 Mon Sep 17 00:00:00 2001 From: Jiacheng Huang <31703396+JChonpca@users.noreply.github.com> Date: Wed, 16 Sep 2026 15:34:45 +0200 Subject: [PATCH 6/7] Apply suggestion from @JChonpca --- .../DTGS127_characterizing_aberrations_optuna.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb index 5c55086b..04656642 100644 --- a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb +++ b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb @@ -320,7 +320,7 @@ "source": [ "## 6. Running the Optimization\n", "\n", - "You are now ready to run the Optuna study, which you will do for a numebr of trials set by `n_trials`. At each iteration the loss along with the parameters will be printed which allows you to track the progress." + "You are now ready to run the Optuna study, which you will do for a number of trials set by `n_trials`. At each iteration, the loss along with the parameters will be printed, which allows you to track the progress." ] }, { From dd84cfb01711a1ac86c65e7c96e5798fe51cd256 Mon Sep 17 00:00:00 2001 From: Alex Date: Wed, 16 Sep 2026 16:27:58 +0200 Subject: [PATCH 7/7] implemented feedback from @mirjagranfors and @edudc --- ...27_characterizing_aberrations_optuna.ipynb | 32 +++++++++---------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb index 04656642..243f4364 100644 --- a/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb +++ b/tutorials/1-getting-started/DTGS127_characterizing_aberrations_optuna.ipynb @@ -35,7 +35,7 @@ "id": "d0edb3ce", "metadata": {}, "source": [ - "This tutorial demonstrates how to identify the aberration type and aberration coefficient of an optical device using the image of a centered particle. DeepTrack2 lets you simulate a number of different optical aberrations, which you can use to identify aberrations you may find in experimental setups using various methods." + "This tutorial demonstrates how to identify the type and coefficient of an optical aberration using the image of a centered particle. You first simulate a reference image of the particle imaged through a microscope with a randomly chosen aberration, then use Optuna to search over aberration type, coefficient, and particle radius to find the simulated image that best matches the reference image, and finally compare the best-fit aberration against the reference image." ] }, { @@ -106,9 +106,9 @@ "\n", "Define the features needed for this example:\n", "\n", - "* `optics`: Fluorescence microscope with a pixel size of 0.1 microns and a 256x256 camera.\n", + "* `optics`: Fluorescence microscope with a pixel size of 66 nm and a 256x256 output image size.\n", "\n", - "* `particle`: Spherical particle centered in the image with 1e-6 meter radius.\n" + "* `particle`: Spherical particle centered in the image with a 1 micron radius.\n" ] }, { @@ -219,7 +219,7 @@ "\n", "Optuna is a hyperparameter optimization framework which lets you explore a large number of parameters with a variety of search methods.\n", "\n", - "In this tutorial, you will use the default [Tree-Structured Parzen Estimator](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.TPESampler.html#optuna.samplers.TPESampler) and restrict the search space to four parameters and use a simple RMSE loss function.\n", + "In this tutorial, you will use the default [Tree-Structured Parzen Estimator](https://optuna.readthedocs.io/en/stable/reference/samplers/generated/optuna.samplers.TPESampler.html#optuna.samplers.TPESampler), restrict the search space to three parameters and score each candidate image with a simple RMSE loss function, which measures the average pixel-wise intensity difference between the candidate image and the reference image generated above.\n", "\n", "The search parameters are:\n", "\n", @@ -227,21 +227,21 @@ "\n", "* Aberration strength coefficient\n", "\n", - "* Particle radii in meters\n", + "* Particle radius in meters\n", "\n" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "dc6d40e2", "metadata": {}, "outputs": [], "source": [ "def simulate_aberrated_image(\n", - " aberration_candidate, # Aberration category\n", - " coefficient, # Aberration coefficient\n", - " radius, # Particle radii\n", + " aberration_candidate, # Aberration category\n", + " coefficient, # Aberration coefficient\n", + " radius, # Particle radius\n", "):\n", " # Get the aberration type and modify the pupil.\n", " simulated_aberration = aberration_candidate(coefficient=coefficient)\n", @@ -272,13 +272,13 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "14800637", "metadata": {}, "outputs": [], "source": [ "def objective(trial):\n", - " \"\"\"Optuna bjective function for aberration and particle parameters.\"\"\"\n", + " \"\"\"Optuna objective function for aberration and particle parameters.\"\"\"\n", "\n", " # Varies aberration type using the list defined at the start.\n", " aberration_name = trial.suggest_categorical(\n", @@ -288,13 +288,13 @@ " cls for cls in aberration_types if cls.__name__ == aberration_name\n", " )\n", "\n", - " # Varies aberration strength.\n", + " # Vary aberration strength.\n", " coefficient = trial.suggest_float(\"coefficient\", -4, 4)\n", "\n", - " # Varies particle radius.\n", + " # Vary particle radius.\n", " radius = trial.suggest_float(\"radius\", 0.8e-7, 1.2e-6)\n", "\n", - " # Generates a simulated image with the parameters.\n", + " # Generate a simulated image with the parameters.\n", " simulated_image = simulate_aberrated_image(\n", " aberration_type,\n", " coefficient,\n", @@ -866,7 +866,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "07154378", "metadata": {}, "outputs": [ @@ -971,7 +971,7 @@ "plt.show()\n", "\n", "print(\n", - " f\"{'Parameter':<15} {'Predicted':<20} {'Ground Truth':<20}\\n\"\n", + " f\"{'Parameter':<15} {'Ground Truth':<20} {'Predicted':<20}\\n\"\n", " f\"{'-' * 55}\\n\"\n", " f\"{'Aberration':<15} {aberration.name():<20} {best_params['aberration_name']}\\n\"\n", " f\"{'Coefficient':<15} {aberration.coefficient():<20} {best_params['coefficient']}\\n\"\n",