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swim/bo-ptycho:main
swim/bo-ptycho:Si-2.1 swim/bo-ptycho:Si-2.0 swim/bo-ptycho:Si-1.2 swim/bo-ptycho:Si-1.0 swim/bo-ptycho:Si-1.1
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compare: swim/bo-ptycho:Si-2.1
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swim/bo-ptycho:main
swim/bo-ptycho:Si-2.1 swim/bo-ptycho:Si-2.0 swim/bo-ptycho:Si-1.2 swim/bo-ptycho:Si-1.0 swim/bo-ptycho:Si-1.1
7 Commits
961a6553b2 .. Si-2.1
Author SHA1 Message Date
swim b59516a4ec added example configs for silicon FIB lamella reconstructions 2026-08-18 10:44:00 +09:00
swim 5633b233d6 minor fix 2026-08-18 10:36:46 +09:00
swim 2a4a81a57d renamed bo to samplers 2026-08-18 10:34:15 +09:00
swim caa4ebd962 new todo 2026-08-18 10:30:30 +09:00
swim 8393d7f923 check for result directory deletion if run in interactive mode. Checks only if in a tty 2026-08-18 10:30:06 +09:00
swim f5e5df488f 2V job 2026-08-18 10:29:28 +09:00
swim 1dfa0db39e removed old examples 2026-08-18 10:28:28 +09:00
29 changed files with 102 additions and 613 deletions
Expand all files Collapse all files
TODO.md
+10 -12
View File
@@ -6,23 +6,21 @@
- write new `prepare_data.m`
- start fold_slice from config.yaml instead of setup.txt
- BO train_x/y transfer between engines for single job
- multi-GPU dispatcher
- synchronous batched BO
- asynchronous BO
- metric() function(s) for each ptycho engine
- FRC score
- separate `config` into `bo_config` and `ptycho_config`; let `BOEngine` have no knowledge of ptychography and vice versa.
- add GPU version of ExamplePtychoEngine
- change `PtychoEngine.metric()` to accept list of names and return dict
- rename `BOEngine` to `Sampler`
- organize results/
- possibly: `[dataset name]/[salient config]-[date]/`
# TODAY:
- separation of available GPUs and parallel BO batches
- prepare next batch for efficient GPU use
- `GridSampler`
- `.__init__()` should create a grid
- `.ask()` should remove those items from the grid
- change job.sub to job.sh
- dynamic jobname
- pre-check result directory
- clean up examples for Si-FIB paper version
# TODAY:
- rename `BOEngine` to `Sampler`
- separation of available GPUs and parallel sample batches
- prepare next batch for efficient GPU use
bo/__init__.py
-3
View File
@@ -1,3 +0,0 @@
from .base import BOEngine
from .random import RandomBOEngine
from .sobo import SingleObjectiveBOEngine
config.yaml
+13 -14
View File
@@ -1,11 +1,11 @@
job:
type: "random+sobo"
type: 'random+sobo'
random_iters: 16
sobo_iters: 512
sobo_iters: 128
io:
input_data_path: '/home/swim/shared/Si_project/data/Si30V3_2.mat'
result_dir: '/home/swim/bo-ptycho/results/Si30V3_2/260816'
input_data_path: '/home/swim/shared/Si_project/data/Si2V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/test'
verbosity: 1
ptycho:
@@ -14,14 +14,14 @@ ptycho:
params:
voltage: 200
alpha_max: 30
defocus: 200
rot_ang: 0.1
Nlayers: 30
thickness: 650
rbf: 38
tilt_x: 5
tilt_y: 3
scan_step_size: 0.35
defocus: -250
rot_ang: 0.3
Nlayers: 20
thickness: 250
rbf: 37
tilt_x: 2
tilt_y: 0
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
@@ -43,16 +43,15 @@ ptycho:
regularize_layers: 0.2
variable_probe: false
bo:
batch: 4
acquisition: 'ucb'
beta: 0.1
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
examples/260805-Si/Si_02V1_2.sub
-25
View File
@@ -1,25 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si2V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "2V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
cat examples/260805-Si/Si_02V1_2.yaml
python -u main.py examples/260805-Si/Si_02V1_2.yaml
date
echo "SLURM JOB FINISHED"
examples/260805-Si/Si_02V1_2.yaml
-59
View File
@@ -1,59 +0,0 @@
job:
type: "random+sobo"
random_iters: 30
sobo_iters: 300
io:
input_data_path: '/home/swim/Si_project/data/Si2V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260805-si/Si2V1_2'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice'
params:
voltage: 200
alpha_max: 30
defocus: -250
rot_ang: 0.3
Nlayers: 20
thickness: 250
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 2
tilt_y: 0
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
roi_label: '0_Ndp64'
diff_pattern_blur: 1
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
acquisition: 'ucb'
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
thickness:
radius: 100
train_x:
train_y:
examples/260805-Si/Si_05V1_2.sub
-25
View File
@@ -1,25 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si5V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "5V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
cat examples/260805-Si/Si_05V1_2.yaml
python -u main.py examples/260805-Si/Si_05V1_2.yaml
date
echo "SLURM JOB FINISHED"
examples/260805-Si/Si_05V1_2.yaml
-59
View File
@@ -1,59 +0,0 @@
job:
type: "random+sobo"
random_iters: 30
sobo_iters: 300
io:
input_data_path: '/home/swim/Si_project/data/Si5V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260805-si/Si5V1_2'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice'
params:
voltage: 200
alpha_max: 30
defocus: -200
rot_ang: 1
Nlayers: 20
thickness: 250
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 3
tilt_y: -1
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
roi_label: '0_Ndp64'
diff_pattern_blur: 1
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
acquisition: 'ucb'
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
thickness:
radius: 150
train_x:
train_y:
examples/260805-Si/Si_08V1_2.sub
-25
View File
@@ -1,25 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si8V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "8V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
cat examples/260805-Si/Si_08V1_2.yaml
python -u main.py examples/260805-Si/Si_08V1_2.yaml
date
echo "SLURM JOB FINISHED"
examples/260805-Si/Si_08V1_2.yaml
-59
View File
@@ -1,59 +0,0 @@
job:
type: "random+sobo"
random_iters: 30
sobo_iters: 300
io:
input_data_path: '/home/swim/Si_project/data/Si8V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260805-si/Si8V1_2'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice'
params:
voltage: 200
alpha_max: 30
defocus: -200
rot_ang: 1.3
Nlayers: 25
thickness: 350
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 4
tilt_y: 0
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
roi_label: '0_Ndp64'
diff_pattern_blur: 1
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
acquisition: 'ucb'
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
thickness:
radius: 150
train_x:
train_y:
examples/260805-Si/Si_30V3_2.sub
-25
View File
@@ -1,25 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si30V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "2V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
cat examples/260805-Si/Si_30V3_2.yaml
python -u main.py examples/260805-Si/Si_30V3_2.yaml
date
echo "SLURM JOB FINISHED"
examples/260805-Si/Si_30V3_2.yaml
-59
View File
@@ -1,59 +0,0 @@
job:
type: "random+sobo"
random_iters: 30
sobo_iters: 300
io:
input_data_path: '/home/swim/Si_project/data/Si30V3_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260805-si/Si30V3_2'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice'
params:
voltage: 200
alpha_max: 30
defocus: 200
rot_ang: 0.1
Nlayers: 30
thickness: 650
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 5
tilt_y: 3
scan_step_size: 0.35
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
roi_label: '0_Ndp64'
diff_pattern_blur: 1
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
acquisition: 'ucb'
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
thickness:
radius: 150
train_x:
train_y:
examples/260809-Si/Si_02V1_2.sub
-26
View File
@@ -1,26 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si2V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "2V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
YAML=examples/260809-Si/Si_02V1_2.yaml
cat $YAML
python -u main.py $YAML
date
echo "SLURM JOB FINISHED"
examples/260809-Si/Si_02V1_2.yaml
-59
View File
@@ -1,59 +0,0 @@
job:
type: "random+sobo"
random_iters: 100
sobo_iters: 1000
io:
input_data_path: '/home/swim/shared/Si_project/data/Si2V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260809-Si/Si2V1_2'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice-stable'
params:
voltage: 200
alpha_max: 30
defocus: -250
rot_ang: 0.3
Nlayers: 20
thickness: 250
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 2
tilt_y: 0
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
roi_label: '0_Ndp64'
diff_pattern_blur: 1
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
acquisition: 'ucb'
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
thickness:
radius: 100
train_x:
train_y:
examples/260809-Si/Si_05V1_2.sub
-26
View File
@@ -1,26 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si5V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "5V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
YAML=examples/260809-Si/Si_05V1_2.yaml
cat $YAML
python -u main.py $YAML
date
echo "SLURM JOB FINISHED"
examples/260809-Si/Si_08V1_2.sub
-26
View File
@@ -1,26 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si8V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "8V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
YAML=examples/260809-Si/Si_08V1_2.yaml
cat $YAML
python -u main.py $YAML
date
echo "SLURM JOB FINISHED"
examples/260809-Si/Si_30V3_2.sub
-26
View File
@@ -1,26 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si30V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:1
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "30V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
YAML=examples/260809-Si/Si_30V3_2.yaml
cat $YAML
python -u main.py $YAML
date
echo "SLURM JOB FINISHED"
examples/260812-Si/job.sub
-26
View File
@@ -1,26 +0,0 @@
#!/bin/bash
#SBATCH --job-name=Si2V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --gres=gpu:rtx-6000ada:4
#SBATCH --time=100:00:00
#SBATCH --output=/home/swim/slurm-logs/job_%j.log
echo "2V"
pwd
hostname
date
export PATH=/home/shared/MATLAB/R2021a/bin:$PATH
export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
source /home/swim/bo-ptycho/venv/bin/activate
YAML=examples/260812-Si/2V.yaml
cat $YAML
python -u main.py $YAML
date
echo "SLURM JOB FINISHED"
examples/260812-Si/2V.yaml → examples/silicon-fib/config-2V.yaml
+13 -12
View File
@@ -1,16 +1,16 @@
job:
type: "random+sobo"
random_iters: 8
type: 'random+sobo'
random_iters: 16
sobo_iters: 128
io:
input_data_path: '/home/swim/shared/Si_project/data/Si2V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260812-Si/Si2V1_2'
result_dir: '/home/swim/bo-ptycho/results/Si2V1_2/260817'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice-stable'
path: '/home/swim/fold_slice-park'
params:
voltage: 200
alpha_max: 30
@@ -19,16 +19,18 @@ ptycho:
Nlayers: 20
thickness: 250
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 2
tilt_y: 0
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
@@ -36,25 +38,24 @@ ptycho:
diff_pattern_blur: 1
probe_change_start: 1
object_change_start: 1
grouping: 512
probe_posiiton_search: 1
grouping: 64
probe_position_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
batch: 4
acquisition: 'ucb'
beta: 0.1
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
thickness:
radius: 100
radius: 150
train_x:
train_y:
examples/260809-Si/Si_30V3_2.yaml → examples/silicon-fib/config-30V.yaml
+17 -14
View File
@@ -1,34 +1,36 @@
job:
type: "random+sobo"
random_iters: 100
sobo_iters: 1000
random_iters: 16
sobo_iters: 512
io:
input_data_path: '/home/swim/shared/Si_project/data/Si30V3_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260809-Si/Si30V3_2'
result_dir: '/home/swim/bo-ptycho/results/Si30V3_2/260816'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice-stable'
path: '/home/swim/fold_slice-park'
params:
voltage: 200
alpha_max: 30
defocus: 175
defocus: 200
rot_ang: 0.1
Nlayers: 30
thickness: 680
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
thickness: 650
rbf: 38
tilt_x: 5
tilt_y: 3
scan_step_size: 0.35
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
@@ -37,23 +39,24 @@ ptycho:
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
probe_position_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
batch: 4
acquisition: 'ucb'
beta: 0.1
metric: 'log_fourier'
params:
alpha_max:
defocus:
radius: 50
radius: 100
rot_ang:
Nlayers:
radius: 5
type: int
thickness:
radius: 100
radius: 150
train_x:
train_y:
examples/260809-Si/Si_05V1_2.yaml → examples/silicon-fib/config-5V.yaml
+12 -9
View File
@@ -1,16 +1,16 @@
job:
type: "random+sobo"
random_iters: 100
sobo_iters: 1000
random_iters: 16
sobo_iters: 128
io:
input_data_path: '/home/swim/shared/Si_project/data/Si5V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260809-Si/Si5V1_2'
result_dir: '/home/swim/bo-ptycho/results/Si5V1_2/260815'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice-stable'
path: '/home/swim/fold_slice-park'
params:
voltage: 200
alpha_max: 30
@@ -19,16 +19,18 @@ ptycho:
Nlayers: 20
thickness: 250
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 3
tilt_y: -1
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
@@ -37,13 +39,14 @@ ptycho:
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
probe_position_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
batch: 4
acquisition: 'ucb'
beta: 0.1
metric: 'log_fourier'
params:
alpha_max:
examples/260809-Si/Si_08V1_2.yaml → examples/silicon-fib/config-8V.yaml
+13 -10
View File
@@ -1,16 +1,16 @@
job:
type: "random+sobo"
random_iters: 100
sobo_iters: 1000
random_iters: 16
sobo_iters: 128
io:
input_data_path: '/home/swim/shared/Si_project/data/Si8V1_2.mat'
result_dir: '/home/swim/bo-ptycho/results/260809-Si/Si8V1_2'
input_data_path: '/home/swim/shared/Si_project/data/Si8V2_2.mat'
result_dir: '/home/swim/bo-ptycho/results/Si8V2_2/260815'
verbosity: 1
ptycho:
engine: 'fold_slice'
path: '/home/swim/fold_slice-stable'
path: '/home/swim/fold_slice-park'
params:
voltage: 200
alpha_max: 30
@@ -19,16 +19,18 @@ ptycho:
Nlayers: 25
thickness: 350
rbf: 37
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
tilt_x: 4
tilt_y: 0
scan_step_size: 0.36
Niter: 100
Niter_save_results: 100
CBED_size: 192
ADU: 1
Nprobe: 1
N_scan_x: 64
N_scan_y: 64
extra_print_info: 'FIB'
scan_number: 1
gpu_id: 1
@@ -37,13 +39,14 @@ ptycho:
probe_change_start: 1
object_change_start: 1
grouping: 64
probe_posiiton_search: 1
probe_position_search: 1
regularize_layers: 0.2
variable_probe: false
bo:
mode: 'sobo'
batch: 4
acquisition: 'ucb'
beta: 0.1
metric: 'log_fourier'
params:
alpha_max:
job.sub
+1 -1
View File
@@ -1,5 +1,5 @@
#!/bin/bash
#SBATCH --job-name=Si30V
#SBATCH --job-name=Si2V
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=16
main.py
+6 -1
View File
@@ -11,10 +11,15 @@ def main(config_yaml):
result_dir = config["io"]["result_dir"]
if os.path.exists(result_dir):
if sys.stdin.isatty():
answer = input(f"Will delete {result_dir}: [y/N]\n> ").strip().lower() == 'y'
if not answer:
print("Aborted.")
return
shutil.rmtree(result_dir)
os.makedirs(result_dir, exist_ok=True)
shutil.copy(config_yaml, os.path.join(result_dir, os.path.basename(config_yaml)))
pipelines.job_types[config['job']['type']](config)
pipelines/batched_sobo.py
+3 -3
View File
@@ -2,7 +2,7 @@ import os
import traceback
import multiprocessing as mp
import bo
import samplers
import ptycho
def run_ptycho_worker(worker_id, gpu_token, job_config, metric, run_id, result_queue):
@@ -71,7 +71,7 @@ def sobo_pipeline(config):
############################ RANDOM SAMPLING ###############################
randombo = bo.RandomBOEngine(config)
randombo = samplers.RandomSampler(config)
for j in range(RANDOM_ITERS):
print(f"RANDOM sampling; iteration {j}")
@@ -81,7 +81,7 @@ def sobo_pipeline(config):
randombo.tell(job_config, y_value)
############################ SOBO SAMPLING ###############################
sobo = bo.SingleObjectiveBOEngine(config)
sobo = samplers.SOBOSampler(config)
sobo.train_x = randombo.train_x
sobo.train_y = randombo.train_y
pipelines/test.py
+1 -4
View File
@@ -1,9 +1,6 @@
import bo
import samplers
import ptycho
def test_pipeline(config):
pass
samplers/__init__.py
+8
View File
@@ -0,0 +1,8 @@
from .base import Sampler
from .random import RandomSampler
from .sobo import SOBOSampler
samplers = {
'sobo': SOBOSampler,
'random': RandomSampler,
}
bo/base.py → samplers/base.py
+1 -1
View File
@@ -3,7 +3,7 @@ import os
import numpy as np
class BOEngine(ABC):
class Sampler(ABC):
def __init__(self, config):
self.config = config
self.params = [key for key, spec in config["bo"]["params"].items() if spec is not None]
bo/random.py → samplers/random.py
+2 -2
View File
@@ -1,9 +1,9 @@
import copy
import numpy as np
from bo.base import BOEngine
from samplers.base import Sampler
class RandomBOEngine(BOEngine):
class RandomSampler(Sampler):
def __init__(self, config):
super().__init__(config)
bo/sobo.py → samplers/sobo.py
+2 -2
View File
@@ -15,10 +15,10 @@ from botorch.sampling.normal import SobolQMCNormalSampler
from botorch.utils.rounding import approximate_round
from bo.base import BOEngine
from samplers.base import Sampler
class SingleObjectiveBOEngine(BOEngine):
class SOBOSampler(Sampler):
def __init__(self, config):
super().__init__(config)
self.acquisition = config['bo']['acquisition']