swim/bo-ptycho
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swim
2026-07-30 20:58:21 +09:00
parent 19f3cff188
commit 72f9cbb154
3 changed files with 26 additions and 14 deletions
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config.yaml
+4 -4
View File
@@ -1,7 +1,7 @@
io: io:
input_data_path: '/home/swim/Si_project/data/Si2V1_1.mat' input_data_path: '/home/swim/Si_project/data/Si2V1_1.mat'
result_dir: '/home/swim/bo-ptycho/results/260730' result_dir: '/home/swim/bo-ptycho/results/260730-2V'
verbosity: 0 verbosity: 1
ptycho: ptycho:
engine: 'fold_slice' engine: 'fold_slice'
@@ -21,7 +21,7 @@ ptycho:
tilt_y: 0 tilt_y: 0
scan_step_size: 0.36 scan_step_size: 0.36
Niter: 100 Niter: 100
Niter_save_results: 50 Niter_save_results: 100
CBED_size: 192 CBED_size: 192
ADU: 1 ADU: 1
extra_print_info: '' extra_print_info: ''
@@ -38,7 +38,7 @@ ptycho:
bo: bo:
parallel_jobs: 1 parallel_jobs: 1
max_iterations: 64 max_iterations: 300
mode: 'sobo' mode: 'sobo'
acquisition: 'ucb' acquisition: 'ucb'
params: params:
job.sub
+2 -2
View File
@@ -1,5 +1,5 @@
#!/bin/bash #!/bin/bash
#SBATCH --job-name=Si2V1 #SBATCH --job-name=Si2V
#SBATCH --nodes=1 #SBATCH --nodes=1
#SBATCH --ntasks=1 #SBATCH --ntasks=1
#SBATCH --cpus-per-task=1 #SBATCH --cpus-per-task=1
@@ -7,7 +7,7 @@
#SBATCH --time=100:00:00 #SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log #SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "Si_2V_1" echo "2V"
pwd pwd
hostname hostname
date date
main.py
+20 -8
View File
@@ -17,26 +17,38 @@ def main(config_yaml):
shutil.copy(config_yaml, os.path.join(result_dir, os.path.basename(config_yaml))) shutil.copy(config_yaml, os.path.join(result_dir, os.path.basename(config_yaml)))
# RANDOM BO SAMPLING PREPARATIONS; 20 SAMPLES # RANDOM BO SAMPLING PREPARATIONS; 20 SAMPLES
J = 20
randombo = bo.RandomBOEngine(config) randombo = bo.RandomBOEngine(config)
for j in range(20):
print(f"RANDOM sampling iteration {j+1}") bo_txt = os.path.join(result_dir, "bo.txt")
with open(bo_txt, "w") as f:
f.write(f" iter\tmetric\t{"\t".join([p[:7] for p in randombo.params])}\n")
for j in range(J):
print(f"RANDOM sampling iteration {j}")
job_config = randombo.ask() job_config = randombo.ask()
ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config) ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config)
ptycho_engine.run() ptycho_engine.run(run_id=f"bo-{j:03d}")
y_value = -np.log(ptycho_engine.metric()) y_value = ptycho_engine._metric
randombo.tell(job_config, y_value) randombo.tell(job_config, y_value)
with open(bo_txt, "a") as f:
p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in randombo.params]
f.write(f"{j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")
# MAIN SINGLE OBJECTIVE BAYESIAN OPTIMIZATION # MAIN SINGLE OBJECTIVE BAYESIAN OPTIMIZATION
sobo = bo.SingleObjectiveBOEngine(config) sobo = bo.SingleObjectiveBOEngine(config)
sobo.train_x = randombo.train_x sobo.train_x = randombo.train_x
sobo.train_y = randombo.train_y sobo.train_y = randombo.train_y
for j in range(config['bo']['max_iterations']): for j in range(J, J + config['bo']['max_iterations'] + 1):
print(f"SOBO sampling iteration {j+1}") print(f"SOBO sampling iteration {j}")
job_config = sobo.ask() job_config = sobo.ask()
ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config) ptycho_engine = ptycho.FoldSlicePtychoEngine(job_config)
ptycho_engine.run(header=f"[BO {j:03d}] ") ptycho_engine.run(run_id=f"bo-{j:03d}")
y_value = -np.log(ptycho_engine.metric()) y_value = ptycho_engine._metric
sobo.tell(job_config, y_value) sobo.tell(job_config, y_value)
with open(bo_txt, "a") as f:
p = [f'{job_config['ptycho']['params'][key]:.2f}' for key in sobo.params]
f.write(f"{j: 8d}\t{y_value:.4f}\t{"\t".join(p)}\n")
if __name__ == "__main__": if __name__ == "__main__":
if len(sys.argv) != 2: if len(sys.argv) != 2: