我有一个脚本看起来像：
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
顺序运行时，会输出
/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'.
然而，为了使计算更有效，我知道我们可以与“&”同时运行它：
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
但这样它的输出就会变得混乱......我能做什么才能使其输出在同时运行这些的同时按顺序排列？谢谢。
答案1
如果您分叉所有这些命令，则 STDOUT 的输出将不按顺序，因为分叉不会按顺序运行。
您可以将所有调用重定向csce.py到单个文件，然后跟踪这些文件。使用文件名的循环变量来了解哪个文件代表哪个进程。
但为了可扩展性和控制，使用GNU并行可能值得尝试。
顺便说一句，文件的名称*.dat不取决于调用的参数，因此根据 python 脚本的工作方式，这些文件可能会被破坏（覆盖）或随着每次调用脚本而增长。
答案2
是的，GNU并行会很好地工作，但是如果你想通过&运算符来做到这一点，你需要知道分叉进程只有在获得资源时才会运行，因为资源共享相同的标准输出，所以输出看起来很混乱。