All GRB examples look fine to me

ThibeauWouters · Dec 19, 2024 · d90fba9 · d90fba9
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diff --git a/examples/GRB/bash.sh b/examples/GRB/bash.sh
@@ -0,0 +1,27 @@
+#!/bin/bash -l
+#Set job requirements
+#SBATCH -N 1
+#SBATCH -n 1
+#SBATCH -p gpu
+#SBATCH -t 00:30:00
+#SBATCH --gpus-per-node=1
+#SBATCH --cpus-per-gpu=1
+#SBATCH --mem-per-gpu=5G
+#SBATCH --output=outdir_GRB170817_tophat/log.out
+#SBATCH --job-name=GRB170817
+
+now=$(date)
+echo "$now"
+
+# Loading modules
+# module load 2024
+# module load Python/3.10.4-GCCcore-11.3.0
+conda activate /home/twouters2/miniconda3/envs/ninjax
+
+# Display GPU name
+nvidia-smi --query-gpu=name --format=csv,noheader
+
+# Run the script
+python run_GRB170817_tophat.py
+
+echo "DONE"
diff --git a/examples/GRB/injection_gaussian/corner.png b/examples/GRB/injection_gaussian/corner.png
diff --git a/examples/GRB/injection_gaussian/lightcurves.png b/examples/GRB/injection_gaussian/lightcurves.png
diff --git a/examples/GRB/injection_gaussian/log.out b/examples/GRB/injection_gaussian/log.out
@@ -0,0 +1,64 @@
+Thu Dec 19 17:46:39 CET 2024
+NVIDIA A100-SXM4-40GB
+GPU found? [cuda(id=0)]
+Loaded SurrogateLightcurveModel with filters ['radio-3GHz', 'radio-6GHz', 'X-ray-1keV', 'bessellv'].
+Converting error budget to dictionary.
+NOTE: No detection limit is given. Putting it to infinity.
+Loading and preprocessing observations in likelihood . . .
+Loading and preprocessing observations in likelihood . . . DONE
+INFO: Using MALA as local sampler
+Setting up a single Gaussian distribution
+No autotune found, use input sampler_params
+Training normalizing flow
+Tuning global sampler:   0%|          | 0/7 [00:00<?, ?it/s]Tuning global sampler:  14%|█▍        | 1/7 [00:47<04:46, 47.76s/it]Tuning global sampler:  29%|██▊       | 2/7 [00:50<01:45, 21.00s/it]Tuning global sampler:  43%|████▎     | 3/7 [00:52<00:50, 12.58s/it]Tuning global sampler:  57%|█████▋    | 4/7 [00:54<00:25,  8.50s/it]Tuning global sampler:  71%|███████▏  | 5/7 [00:57<00:12,  6.25s/it]Tuning global sampler:  86%|████████▌ | 6/7 [00:59<00:04,  4.89s/it]Tuning global sampler: 100%|██████████| 7/7 [01:01<00:00,  4.03s/it]Tuning global sampler: 100%|██████████| 7/7 [01:01<00:00,  8.80s/it]
+Compiling MALA body
+Starting Production run
+Production run:   0%|          | 0/3 [00:00<?, ?it/s]Production run:  33%|███▎      | 1/3 [00:00<00:01,  1.60it/s]Production run:  67%|██████▋   | 2/3 [00:01<00:00,  1.60it/s]Production run: 100%|██████████| 3/3 [00:01<00:00,  1.60it/s]Production run: 100%|██████████| 3/3 [00:01<00:00,  1.60it/s]
+Training summary
+==========
+inclination_EM: 0.214 +/- 0.204
+log10_E0: 54.721 +/- 1.193
+thetaCore: 0.215 +/- 0.127
+alphaWing: 2.141 +/- 0.752
+log10_n0: -1.354 +/- 1.631
+p: 2.589 +/- 0.102
+log10_epsilon_e: -2.107 +/- 0.648
+log10_epsilon_B: -5.277 +/- 1.683
+Log probability: -1550.697 +/- 12224.367
+Local acceptance: 0.381 +/- 0.486
+Global acceptance: 0.180 +/- 0.384
+Max loss: 11.349, Min loss: 3.928
+Production summary
+==========
+inclination_EM: 0.139 +/- 0.088
+log10_E0: 55.129 +/- 0.681
+thetaCore: 0.146 +/- 0.050
+alphaWing: 2.176 +/- 0.725
+log10_n0: -1.815 +/- 1.418
+p: 2.603 +/- 0.018
+log10_epsilon_e: -2.114 +/- 0.522
+log10_epsilon_B: -5.498 +/- 1.494
+Log probability: -12.507 +/- 1.690
+Local acceptance: 0.285 +/- 0.451
+Global acceptance: 0.338 +/- 0.473
+Saving samples to ./injection_gaussian/results_training.npz
+Saving samples to ./injection_gaussian/results_production.npz
+Total runtime: 1.0 m 19.91 s
+Plotting lightcurves
+Plotting lightcurves . . . done
+DONE
+DONE
+
+JOB STATISTICS
+==============
+Job ID: 9119701
+Cluster: snellius
+User/Group: twouters2/twouters2
+State: COMPLETED (exit code 0)
+Nodes: 1
+Cores per node: 18
+CPU Utilized: 00:01:53
+CPU Efficiency: 5.81% of 00:32:24 core-walltime
+Job Wall-clock time: 00:01:48
+Memory Utilized: 1.54 GB
+Memory Efficiency: 30.86% of 5.00 GB

diff --git a/examples/GRB/injection_tophat/corner.png b/examples/GRB/injection_tophat/corner.png
diff --git a/examples/GRB/injection_tophat/lightcurves.png b/examples/GRB/injection_tophat/lightcurves.png
diff --git a/examples/GRB/injection_tophat/log.out b/examples/GRB/injection_tophat/log.out
@@ -0,0 +1,62 @@
+Thu Dec 19 17:38:06 CET 2024
+NVIDIA A100-SXM4-40GB
+GPU found? [cuda(id=0)]
+Loaded SurrogateLightcurveModel with filters ['radio-3GHz', 'radio-6GHz', 'X-ray-1keV', 'bessellv'].
+Converting error budget to dictionary.
+NOTE: No detection limit is given. Putting it to infinity.
+Loading and preprocessing observations in likelihood . . .
+Loading and preprocessing observations in likelihood . . . DONE
+INFO: Using MALA as local sampler
+Setting up a single Gaussian distribution
+No autotune found, use input sampler_params
+Training normalizing flow
+Tuning global sampler:   0%|          | 0/7 [00:00<?, ?it/s]Tuning global sampler:  14%|█▍        | 1/7 [00:53<05:23, 53.96s/it]Tuning global sampler:  29%|██▊       | 2/7 [00:56<01:57, 23.49s/it]Tuning global sampler:  43%|████▎     | 3/7 [00:58<00:54, 13.74s/it]Tuning global sampler:  57%|█████▋    | 4/7 [01:00<00:27,  9.16s/it]Tuning global sampler:  71%|███████▏  | 5/7 [01:02<00:13,  6.74s/it]Tuning global sampler:  86%|████████▌ | 6/7 [01:04<00:05,  5.17s/it]Tuning global sampler: 100%|██████████| 7/7 [01:07<00:00,  4.18s/it]Tuning global sampler: 100%|██████████| 7/7 [01:07<00:00,  9.59s/it]
+Compiling MALA body
+Starting Production run
+Production run:   0%|          | 0/3 [00:00<?, ?it/s]Production run:  33%|███▎      | 1/3 [00:00<00:01,  1.97it/s]Production run:  67%|██████▋   | 2/3 [00:01<00:00,  1.97it/s]Production run: 100%|██████████| 3/3 [00:01<00:00,  1.97it/s]Production run: 100%|██████████| 3/3 [00:01<00:00,  1.97it/s]
+Training summary
+==========
+inclination_EM: 0.472 +/- 0.254
+log10_E0: 53.771 +/- 1.152
+thetaCore: 0.153 +/- 0.121
+log10_n0: -1.269 +/- 1.361
+p: 2.467 +/- 0.110
+log10_epsilon_e: -1.212 +/- 0.529
+log10_epsilon_B: -4.616 +/- 1.669
+Log probability: -1434.384 +/- 10642.869
+Local acceptance: 0.183 +/- 0.387
+Global acceptance: 0.282 +/- 0.450
+Max loss: 9.741, Min loss: 1.378
+Production summary
+==========
+inclination_EM: 0.339 +/- 0.056
+log10_E0: 54.048 +/- 0.617
+thetaCore: 0.097 +/- 0.017
+log10_n0: -1.707 +/- 0.918
+p: 2.469 +/- 0.017
+log10_epsilon_e: -1.240 +/- 0.152
+log10_epsilon_B: -4.511 +/- 1.341
+Log probability: -11.601 +/- 1.869
+Local acceptance: 0.112 +/- 0.315
+Global acceptance: 0.608 +/- 0.488
+Saving samples to ./injection_tophat/results_training.npz
+Saving samples to ./injection_tophat/results_production.npz
+Total runtime: 1.0 m 18.61 s
+Plotting lightcurves
+Plotting lightcurves . . . done
+DONE
+DONE
+
+JOB STATISTICS
+==============
+Job ID: 9119646
+Cluster: snellius
+User/Group: twouters2/twouters2
+State: COMPLETED (exit code 0)
+Nodes: 1
+Cores per node: 18
+CPU Utilized: 00:01:54
+CPU Efficiency: 5.92% of 00:32:06 core-walltime
+Job Wall-clock time: 00:01:47
+Memory Utilized: 1.39 GB
+Memory Efficiency: 27.77% of 5.00 GB

diff --git a/examples/GRB/outdir_GRB170817_tophat/corner.png b/examples/GRB/outdir_GRB170817_tophat/corner.png
diff --git a/examples/GRB/outdir_GRB170817_tophat/lightcurves.png b/examples/GRB/outdir_GRB170817_tophat/lightcurves.png
diff --git a/examples/GRB/outdir_GRB170817_tophat/log.out b/examples/GRB/outdir_GRB170817_tophat/log.out
@@ -0,0 +1,62 @@
+Thu Dec 19 17:56:44 CET 2024
+NVIDIA A100-SXM4-40GB
+GPU found? [cuda(id=0)]
+Loaded SurrogateLightcurveModel with filters ['radio-3GHz', 'radio-6GHz', 'X-ray-1keV', 'bessellv']
+Converting error budget to dictionary.
+NOTE: No detection limit is given. Putting it to infinity.
+Loading and preprocessing observations in likelihood . . .
+Loading and preprocessing observations in likelihood . . . DONE
+INFO: Using MALA as local sampler
+Setting up a single Gaussian distribution
+No autotune found, use input sampler_params
+Training normalizing flow
+Tuning global sampler:   0%|          | 0/7 [00:00<?, ?it/s]Tuning global sampler:  14%|█▍        | 1/7 [00:49<04:57, 49.55s/it]Tuning global sampler:  29%|██▊       | 2/7 [00:51<01:47, 21.47s/it]Tuning global sampler:  43%|████▎     | 3/7 [00:53<00:49, 12.48s/it]Tuning global sampler:  57%|█████▋    | 4/7 [00:55<00:25,  8.36s/it]Tuning global sampler:  71%|███████▏  | 5/7 [00:56<00:11,  5.99s/it]Tuning global sampler:  86%|████████▌ | 6/7 [00:58<00:04,  4.56s/it]Tuning global sampler: 100%|██████████| 7/7 [01:00<00:00,  3.65s/it]Tuning global sampler: 100%|██████████| 7/7 [01:00<00:00,  8.65s/it]
+Compiling MALA body
+Starting Production run
+Production run:   0%|          | 0/3 [00:00<?, ?it/s]Production run:  33%|███▎      | 1/3 [00:00<00:00,  4.46it/s]Production run:  67%|██████▋   | 2/3 [00:00<00:00,  4.29it/s]Production run: 100%|██████████| 3/3 [00:00<00:00,  4.24it/s]Production run: 100%|██████████| 3/3 [00:00<00:00,  4.27it/s]
+Training summary
+==========
+inclination_EM: 0.370 +/- 0.185
+log10_E0: 53.264 +/- 1.349
+thetaCore: 0.227 +/- 0.068
+log10_n0: -3.481 +/- 1.962
+p: 2.149 +/- 0.132
+log10_epsilon_e: -2.420 +/- 1.418
+log10_epsilon_B: -3.904 +/- 2.005
+Log probability: -465.326 +/- 3419.754
+Local acceptance: 0.415 +/- 0.493
+Global acceptance: 0.201 +/- 0.400
+Max loss: 9.719, Min loss: 1.823
+Production summary
+==========
+inclination_EM: 0.332 +/- 0.118
+log10_E0: 53.533 +/- 1.128
+thetaCore: 0.224 +/- 0.065
+log10_n0: -3.972 +/- 1.801
+p: 2.113 +/- 0.056
+log10_epsilon_e: -2.568 +/- 1.515
+log10_epsilon_B: -3.780 +/- 2.058
+Log probability: -13.369 +/- 1.754
+Local acceptance: 0.391 +/- 0.488
+Global acceptance: 0.328 +/- 0.470
+Saving samples to ./outdir_GRB170817_tophat/results_training.npz
+Saving samples to ./outdir_GRB170817_tophat/results_production.npz
+Total runtime: 1.0 m 10.91 s
+Plotting lightcurves
+Plotting lightcurves . . . done
+DONE
+DONE
+
+JOB STATISTICS
+==============
+Job ID: 9119871
+Cluster: snellius
+User/Group: twouters2/twouters2
+State: COMPLETED (exit code 0)
+Nodes: 1
+Cores per node: 18
+CPU Utilized: 00:01:38
+CPU Efficiency: 5.61% of 00:29:06 core-walltime
+Job Wall-clock time: 00:01:37
+Memory Utilized: 983.49 MB
+Memory Efficiency: 19.21% of 5.00 GB

diff --git a/examples/GRB/run_GRB170817_tophat.py b/examples/GRB/run_GRB170817_tophat.py
@@ -11,7 +11,7 @@
 
 from fiesta.inference.lightcurve_model import AfterglowpyLightcurvemodel
 from fiesta.inference.likelihood import EMLikelihood
-from fiesta.inference.prior import Uniform, Composite
+from fiesta.inference.prior import Uniform, CompositePrior
 from fiesta.inference.fiesta import Fiesta
 from fiesta.utils import load_event_data
 
@@ -67,7 +67,7 @@
 ##############
 
 name = "tophat"
-model_dir = f"../trained_models/afterglowpy/{name}/"
+model_dir = f"../../lightcurve_models/afterglowpy/{name}/"
 FILTERS = ["radio-3GHz", "radio-6GHz", "X-ray-1keV", "bessellv"]
 
 model = AfterglowpyLightcurvemodel(name,
@@ -79,7 +79,7 @@
 ### DATA ###
 ############
 
-data = load_event_data("./data/GRB170817A.dat") # only one filter of the GRB170817A data
+data = load_event_data("../data/GRB170817A.dat") # only one filter of the GRB170817A data
 
 #############################
 ### PRIORS AND LIKELIHOOD ###
@@ -105,7 +105,7 @@
             #   luminosity_distance
 ]
 
-prior = Composite(prior_list)
+prior = CompositePrior(prior_list)
 
 detection_limit = None
 likelihood = EMLikelihood(model,