다음과 같은 스크립트가 있습니다.
for simplify in 0.1 ;do
for lmbda in 0.9 1.1 1.3;do
for mu in 2.1 3.4 4.2;do
rm eci.out;
csce.py --mu $mu --lmbda $lmbda --simplify $simplify \
--favor-low-energy 0.01 --bias-stable \
--save-energies ce-energies.dat --save-weights ce-weights.dat \
--casm-eci-file eci.in eci.out --save-hull ce-hull.dat \
--preserve-ground-state 100
done
done
done
순차적으로 실행하면 출력됩니다.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.0002 --lmbda 0.005 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.0002, lambda = 0.005, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.03952735 0.04380240 0.02230235 -0.00185235
230 clusters 0.03734292 0.04294355 0.02049885 -0.00162721
Leave-one-out CV score wrt. input : 13.8588
Leave-one-out CV score wrt. full fit: 0.2201
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.0002 --lmbda 0.5 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.0002, lambda = 0.5, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.04017143 0.04451601 0.02267050 -0.00188774
219 clusters 0.03826959 0.04392544 0.02088397 -0.00166322
Leave-one-out CV score wrt. input : 7.9875
Leave-one-out CV score wrt. full fit: 0.1674
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.002 --lmbda 0.5 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.002, lambda = 0.5, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.14367173 0.15893736 0.07206284 -0.00912716
237 clusters 0.12351319 0.17167930 0.05376677 -0.00158861
Leave-one-out CV score wrt. input : 5.4561
Leave-one-out CV score wrt. full fit: 0.1119
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.002 --lmbda 0.005 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.002, lambda = 0.005, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.14299857 0.15820042 0.07228279 -0.00898964
237 clusters 0.12292319 0.17103283 0.05359447 -0.00138365
Leave-one-out CV score wrt. input : 5.3224
Leave-one-out CV score wrt. full fit: 0.1104
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.02 --lmbda 0.5 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.02, lambda = 0.5, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.19027749 0.20991052 0.09677830 -0.01602039
237 clusters 0.17531289 0.27618581 0.06910020 0.00220309
Leave-one-out CV score wrt. input : 2.4223
Leave-one-out CV score wrt. full fit: 0.0638
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.2 --lmbda 0.5 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.2, lambda = 0.5, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.26328087 0.28804954 0.15654138 -0.03325137
237 clusters 0.20897747 0.39607952 0.07887236 0.00877210
Leave-one-out CV score wrt. input : 1.9517
Leave-one-out CV score wrt. full fit: 0.0477
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.02 --lmbda 0.005 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.02, lambda = 0.005, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.18831434 0.20789816 0.09380533 -0.01523797
237 clusters 0.17809687 0.28067519 0.06919726 0.00308981
Leave-one-out CV score wrt. input : 2.4420
Leave-one-out CV score wrt. full fit: 0.0642
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.0002 --lmbda 0.05 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.0002, lambda = 0.05, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.03972713 0.04402288 0.02232628 -0.00187813
220 clusters 0.03735457 0.04295330 0.02008527 -0.00161760
Leave-one-out CV score wrt. input : 9.9223
Leave-one-out CV score wrt. full fit: 0.1863
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.2 --lmbda 0.005 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.2, lambda = 0.005, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.23518508 0.25836295 0.13669345 -0.02483126
237 clusters 0.21460451 0.36901059 0.08558721 0.00618068
Leave-one-out CV score wrt. input : 1.7372
Leave-one-out CV score wrt. full fit: 0.0490
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.002 --lmbda 0.05 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.002, lambda = 0.05, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.14375418 0.15902969 0.07218794 -0.00912434
237 clusters 0.12364959 0.17204399 0.05379933 -0.00144881
Leave-one-out CV score wrt. input : 5.5220
Leave-one-out CV score wrt. full fit: 0.1124
Writing CV energies to file `cv-energies.dat'.
/home1/03631/key01027/local_python_lib/bin/csce.py --mu 0.02 --lmbda 0.05 --simplify 0.1 --favor-low-energy 0.01 --bias-stable --save-energies ce-energies.dat --save-weights ce-weights.dat --casm-eci-file eci.in eci.out --save-hull ce-hull.dat --preserve-ground-state 100
Split-Bregman Input Parameters: mu = 0.02, lambda = 0.05, eci_cutoff = 1e-08
Attempting to simplify the CE using a target RMSE of 0.1
Warning: Unable to achieve target RMSE of 0.1
RMSE RMSE (no wght) MAE ME
237 clusters 0.19066043 0.21033595 0.09672442 -0.01606650
237 clusters 0.17565376 0.27643274 0.06917755 0.00238796
Leave-one-out CV score wrt. input : 2.4257
Leave-one-out CV score wrt. full fit: 0.0639
Writing CV energies to file `cv-energies.dat'.
그러나 계산을 보다 효율적으로 만들기 위해 "&"를 사용하여 동시에 실행할 수 있다는 것을 알고 있습니다.
for simplify in 0.1 ;do
for lmbda in 0.9 1.1 1.3;do
for mu in 2.1 3.4 4.2;do
rm eci.out;
csce.py --mu $mu --lmbda $lmbda --simplify $simplify \
--favor-low-energy 0.01 --bias-stable \
--save-energies ce-energies.dat --save-weights ce-weights.dat \
--casm-eci-file eci.in eci.out --save-hull ce-hull.dat \
--preserve-ground-state 100 &
done
done
done
하지만 출력이 엉망이 됩니다. 동시에 실행하면서 출력을 순서대로 유지하려면 어떻게 해야 합니까? 감사해요.
답변1
이러한 명령을 모두 분기하면 분기가 순차적으로 실행되지 않기 때문에 STDOUT에 대한 출력이 순서대로 실행되지 않습니다.
모든 호출을 csce.py단일 파일로 리디렉션한 다음 해당 파일을 추적할 수 있습니다. 파일 이름의 루프 변수를 사용하여 어떤 파일이 어떤 프로세스를 나타내는지 알아보세요.
그러나 확장성과 제어를 위해서는 다음을 사용하세요.GNU 병렬시도해 볼 가치가 있을 수도 있습니다.
그런데 파일 이름은 *.dat호출 매개변수에 의존하지 않으므로 Python 스크립트의 작동 방식에 따라 이러한 파일은 스크립트를 호출할 때마다 손상(덮어쓰기)되거나 커질 수 있습니다.
답변2
예, GNU Parallel은 잘 작동하지만 & 연산자를 통해 수행하려면 리소스가 동일한 stdout을 공유하므로 포크된 프로세스가 리소스를 얻은 경우에만 실행된다는 점을 알아야 합니다. 혼란스럽다.