diff --git a/examples/KN/bash.sh b/examples/KN/bash.sh new file mode 100644 index 0000000..3a7b647 --- /dev/null +++ b/examples/KN/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_injection_Bu2019lm/log.out +#SBATCH --job-name=injection_Bu2019lm + +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 injection_Bu2019lm.py + +echo "DONE" \ No newline at end of file diff --git a/examples/KN/injection_Bu2019lm.py b/examples/KN/injection_Bu2019lm.py index 6de1fe9..10538a5 100644 --- a/examples/KN/injection_Bu2019lm.py +++ b/examples/KN/injection_Bu2019lm.py @@ -16,7 +16,7 @@ from fiesta.inference.lightcurve_model import BullaLightcurveModel from fiesta.inference.likelihood import EMLikelihood -from fiesta.inference.prior import Uniform, Composite +from fiesta.inference.prior import Uniform, CompositePrior from fiesta.inference.injection import InjectionRecovery from fiesta.inference.fiesta import Fiesta from fiesta.utils import load_event_data @@ -72,7 +72,7 @@ ########################### model = BullaLightcurveModel(name, - f"../trained_models/{name}/", + f"../../lightcurve_models/KN/{name}/", filters) injection_dict = {"KNtheta": 30.0, @@ -105,7 +105,7 @@ luminosity_distance ] -prior = Composite(prior_list) +prior = CompositePrior(prior_list) detection_limit = None likelihood = EMLikelihood(model, @@ -193,7 +193,7 @@ ax.set_ylabel(filter_name) ax.invert_yaxis() -plt.savefig(f"./figures/test_injection_{name}_data.png", bbox_inches = 'tight') +plt.savefig(os.path.join(outdir, f"test_injection_{name}_data.png"), bbox_inches = 'tight') plt.close() # Fixed names: do not include them in the plotting, as will break corner diff --git a/examples/KN/load_data.py b/examples/KN/load_data.py deleted file mode 100644 index fc66f3e..0000000 --- a/examples/KN/load_data.py +++ /dev/null @@ -1,50 +0,0 @@ -""" -Example showing how to load the data -""" - -import os -import numpy as np -import matplotlib.pyplot as plt -import corner - -params = {"axes.grid": True, - "text.usetex" : True, - "font.family" : "serif", - "ytick.color" : "black", - "xtick.color" : "black", - "axes.labelcolor" : "black", - "axes.edgecolor" : "black", - "font.serif" : ["Computer Modern Serif"], - "xtick.labelsize": 16, - "ytick.labelsize": 16, - "axes.labelsize": 16, - "legend.fontsize": 16, - "legend.title_fontsize": 16, - "figure.titlesize": 16} - -plt.rcParams.update(params) - -default_corner_kwargs = dict(bins=40, - smooth=1., - label_kwargs=dict(fontsize=16), - title_kwargs=dict(fontsize=16), - color="blue", - plot_density=True, - plot_datapoints=False, - fill_contours=True, - max_n_ticks=4, - min_n_ticks=3, - save=False, - truth_color="red") - -# Load the samples -data = np.load("./outdir_AT2017gfo_Bu2019lm/results_production.npz") -chains = data["chains"] -labels = ["KNphi", "KNtheta", "log10_mej_dyn", "log10_mej_wind", "d_L"] - -# # Make the cornerplot -# print("Plotting corner . . .") -# corner.corner(chains, labels = labels, hist_kwargs={'density': True}, **default_corner_kwargs) -# plt.savefig("./test.png", bbox_inches = 'tight') -# plt.close() -# print("Plotting corner . . . done") \ No newline at end of file diff --git a/examples/KN/outdir_injection_Bu2019lm/injection_Bu2019lm_corner.png b/examples/KN/outdir_injection_Bu2019lm/injection_Bu2019lm_corner.png index e653f99..c098c25 100644 Binary files a/examples/KN/outdir_injection_Bu2019lm/injection_Bu2019lm_corner.png and b/examples/KN/outdir_injection_Bu2019lm/injection_Bu2019lm_corner.png differ diff --git a/examples/KN/outdir_injection_Bu2019lm/log.out b/examples/KN/outdir_injection_Bu2019lm/log.out new file mode 100644 index 0000000..c496d73 --- /dev/null +++ b/examples/KN/outdir_injection_Bu2019lm/log.out @@ -0,0 +1,37 @@ +Thu Dec 19 16:49:10 CET 2024 +NVIDIA A100-SXM4-40GB +GPU found? [cuda(id=0)] +Loaded SurrogateLightcurveModel with filters ['ps1__g', 'ps1__r', 'ps1__i', 'ps1__z', 'ps1__y', '2massj', '2massh', '2massks', 'sdssu'] +Creating injection with filters: ['ps1__g', 'ps1__r', 'ps1__i', 'ps1__z', 'ps1__y', '2massj', '2massh', '2massks', 'sdssu'] +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%| | 0/3 [00:00