SHELL=bash Ns=[1000, 5000, 10000] ms=[100, 200, 400] seeds=[$(shell seq -s, 1 500)] explained_variances=[0.1] all:remembr.RDS remember_irr.RDS supplement: remember_robustness_misspec.RDS srun=sbatch --wait --verbose run_job.sbatch joblists:example_1_jobs example_2_jobs example_3_jobs # test_true_z_jobs: test_true_z.R simulation_base.R # sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript test_true_z.R" --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["test_true_z.feather"], "y_explained_variancevari":${explained_variances}, "Bzx":${Bzx}}' --outfile test_true_z_jobsb # test_true_z.feather: test_true_z_jobs # rm -f test_true_z.feather # sbatch --wait --verbose --array=1-3000 run_simulation.sbatch 0 test_true_z_jobs # sbatch --wait --verbose --array=3001-6001 run_simulation.sbatch 0 test_true_z_jobs example_1_jobs: 01_two_covariates.R simulation_base.R grid_sweep.py pl_methods.R sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 01_two_covariates.R" --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["example_1.feather"], "y_explained_variance":${explained_variances}, "Bzx":[1]}' --outfile example_1_jobs example_1.feather: example_1_jobs rm -f example_1.feather sbatch --wait --verbose --array=1-1000 run_simulation.sbatch 0 example_1_jobs sbatch --wait --verbose --array=1001-2000 run_simulation.sbatch 0 example_1_jobs sbatch --wait --verbose --array=2001-3000 run_simulation.sbatch 0 example_1_jobs sbatch --wait --verbose --array=3001-4000 run_simulation.sbatch 0 example_1_jobs sbatch --wait --verbose --array=4001-$(shell cat example_1_jobs | wc -l) run_simulation.sbatch 0 example_1_jobs example_2_jobs: 02_indep_differential.R simulation_base.R grid_sweep.py pl_methods.R sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 02_indep_differential.R" --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["example_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[1], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y*z*x"]}' --outfile example_2_jobs example_2.feather: example_2_jobs rm -f example_2.feather sbatch --wait --verbose --array=1-1000 run_simulation.sbatch 0 example_2_jobs sbatch --wait --verbose --array=1001-2000 run_simulation.sbatch 0 example_2_jobs sbatch --wait --verbose --array=2001-3000 run_simulation.sbatch 0 example_2_jobs sbatch --wait --verbose --array=3001-4000 run_simulation.sbatch 0 example_2_jobs sbatch --wait --verbose --array=4001-$(shell cat example_2_jobs | wc -l) run_simulation.sbatch 0 example_2_jobs # example_2_B_jobs: example_2_B.R # sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript example_2_B.R" --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["example_2_B.feather"]}' --outfile example_2_B_jobs # example_2_B.feather: example_2_B_jobs # rm -f example_2_B.feather # sbatch --wait --verbose --array=1-3000 run_simulation.sbatch 0 example_2_B_jobs example_3_jobs: 03_depvar.R simulation_base.R grid_sweep.py pl_methods.R sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 03_depvar.R" --arg_dict '{"N":${Ns},"m":${ms}, "Bxy":[0.7],"Bzy":[-0.7],"seed":${seeds}, "outfile":["example_3.feather"], "y_explained_variance":${explained_variances}}' --outfile example_3_jobs example_3.feather: example_3_jobs rm -f example_3.feather sbatch --wait --verbose --array=1-1000 run_simulation.sbatch 0 example_3_jobs sbatch --wait --verbose --array=1001-2000 run_simulation.sbatch 0 example_3_jobs sbatch --wait --verbose --array=2001-3000 run_simulation.sbatch 0 example_3_jobs sbatch --wait --verbose --array=3001-4000 run_simulation.sbatch 0 example_3_jobs sbatch --wait --verbose --array=4001-$(shell cat example_3_jobs | wc -l) run_simulation.sbatch 0 example_3_jobs example_4_jobs: 04_depvar_differential.R simulation_base.R grid_sweep.py pl_methods.R sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 04_depvar_differential.R" --arg_dict '{"N":${Ns},"Bxy":[0.7],"Bzy":[-0.7],"m":${ms}, "seed":${seeds}, "outfile":["example_4.feather"], "z_bias":[0.5]}' --outfile example_4_jobs example_4.feather: example_4_jobs rm -f example_4.feather sbatch --wait --verbose --array=1-1000 run_simulation.sbatch 0 example_4_jobs sbatch --wait --verbose --array=1001-2000 run_simulation.sbatch 0 example_4_jobs sbatch --wait --verbose --array=2001-3000 run_simulation.sbatch 0 example_4_jobs sbatch --wait --verbose --array=3001-4000 run_simulation.sbatch 0 example_4_jobs sbatch --wait --verbose --array=4001-$(shell cat example_4_jobs | wc -l) run_simulation.sbatch 0 example_4_jobs remembr.RDS:example_1.feather example_2.feather example_3.feather example_4.feather plot_example.R plot_dv_example.R summarize_estimator.R rm -f remembr.RDS ${srun} Rscript plot_example.R --infile example_1.feather --name "plot.df.example.1" ${srun} Rscript plot_example.R --infile example_2.feather --name "plot.df.example.2" ${srun} Rscript plot_dv_example.R --infile example_3.feather --name "plot.df.example.3" ${srun} Rscript plot_dv_example.R --infile example_4.feather --name "plot.df.example.4" irr_Ns = [1000] irr_ms = [150,300,600] irr_seeds=${seeds} irr_explained_variances=${explained_variances} irr_coder_accuracy=[0.80] example_5_jobs: 05_irr_indep.R irr_simulation_base.R grid_sweep.py pl_methods.R measerr_methods.R sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 05_irr_indep.R" --arg_dict '{"N":${irr_Ns},"m":${irr_ms}, "seed":${irr_seeds}, "outfile":["example_5.feather"], "y_explained_variance":${irr_explained_variances}, "coder_accuracy":${irr_coder_accuracy}}' --outfile example_5_jobs example_5.feather:example_5_jobs rm -f example_5.feather sbatch --wait --verbose --array=1-1000 run_simulation.sbatch 0 example_5_jobs sbatch --wait --verbose --array=1001-$(shell cat example_5_jobs | wc -l) run_simulation.sbatch 1000 example_5_jobs # sbatch --wait --verbose --array=2001-3000 run_simulation.sbatch 2000 example_5_jobs # sbatch --wait --verbose --array=3001-4000 run_simulation.sbatch 3000 example_5_jobs # sbatch --wait --verbose --array=2001-$(shell cat example_5_jobs | wc -l) run_simulation.sbatch 4000 example_5_jobs # example_6_jobs: 06_irr_dv.R irr_dv_simulation_base.R grid_sweep.py pl_methods.R # sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 06_irr_dv.R" --arg_dict '{"N":${irr_Ns},"m":${irr_ms}, "seed":${irr_seeds}, "outfile":["example_6.feather"], "y_explained_variance":${irr_explained_variances},"coder_accuracy":${irr_coder_accuracy}}' --outfile example_6_jobs # example_6.feather:example_6_jobs # rm -f example_6.feather # sbatch --wait --verbose --array=1-1000 run_simulation.sbatch 0 example_6_jobs # sbatch --wait --verbose --array=1001-2000 run_simulation.sbatch 1000 example_6_jobs # sbatch --wait --verbose --array=2001-$(shell cat example_6_jobs | wc -l) run_simulation.sbatch 2000 example_6_jobs remember_irr.RDS: example_5.feather plot_irr_example.R plot_irr_dv_example.R summarize_estimator.R rm -f remember_irr.RDS sbatch --wait --verbose run_job.sbatch Rscript plot_irr_example.R --infile example_5.feather --name "plot.df.example.5" # sbatch --wait --verbose run_job.sbatch Rscript plot_irr_dv_example.R --infile example_6.feather --name "plot.df.example.6" robustness_1_jobs: 02_indep_differential.R simulation_base.R grid_sweep.py sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 02_indep_differential.R" --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_1.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~1"]}' --outfile robustness_1_jobs robustness_1.feather: robustness_1_jobs rm -f robustness_1.feather sbatch --wait --verbose --array=1-1000 run_simulation.sbatch 0 robustness_1_jobs sbatch --wait --verbose --array=1001-2000 run_simulation.sbatch 0 robustness_1_jobs sbatch --wait --verbose --array=2001-3000 run_simulation.sbatch 0 robustness_1_jobs sbatch --wait --verbose --array=3001-4000 run_simulation.sbatch 0 robustness_1_jobs sbatch --wait --verbose --array=4001-$(shell cat robustness_1_jobs | wc -l) run_simulation.sbatch 0 robustness_1_jobs robustness_1.RDS: robustness_1.feather rm -f robustness_1.RDS ${srun} Rscript plot_example.R --infile $< --name "robustness_1" --remember-file $@ robustness_1_dv_jobs: simulation_base.R 04_depvar_differential.R grid_sweep.py ${srun} bash -c "source ~/.bashrc && grid_sweep.py --command 'Rscript 04_depvar_differential.R' --arg_dict \"{'N':${Ns},'m':${ms}, 'seed':${seeds}, 'outfile':['robustness_1_dv.feather'], 'y_explained_variance':${explained_variances}, 'proxy_formula':['w_pred~y']}\" --outfile robustness_1_dv_jobs" robustness_1_dv.feather: robustness_1_dv_jobs rm -f robustness_1_dv.feather sbatch --wait --verbose --array=1-$(shell cat example_3_jobs | wc -l) run_simulation.sbatch 0 robustness_1_dv_jobs robustness_1_dv.RDS: robustness_1_dv.feather rm -f $@ ${srun} Rscript plot_dv_example.R --infile $< --name "robustness_1_dv" --outfile $@ robustness_2_jobs_p1: grid_sweep.py 01_two_covariates.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.60,0.65]}' --outfile $@ robustness_2_jobs_p2: grid_sweep.py 01_two_covariates.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.70,0.75]}' --outfile $@ robustness_2_jobs_p3: grid_sweep.py 01_two_covariates.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.80,0.85]}' --outfile $@ robustness_2_jobs_p4: grid_sweep.py 01_two_covariates.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.90,0.95]}' --outfile $@ START=0 END_1=$(shell cat robustness_2_jobs_p1 | wc -l) END_2=$(shell cat robustness_2_jobs_p2 | wc -l) END_3=$(shell cat robustness_2_jobs_p3 | wc -l) END_4=$(shell cat robustness_2_jobs_p4 | wc -l) STEP=1000 ONE=1 ITEMS_1=$(shell seq $(START) $(STEP) $(END_1)) ITEMS_2=$(shell seq $(START) $(STEP) $(END_2)) ITEMS_3=$(shell seq $(START) $(STEP) $(END_3)) ITEMS_4=$(shell seq $(START) $(STEP) $(END_4)) robustness_2.feather: robustness_2_jobs_p1 robustness_2_jobs_p2 robustness_2_jobs_p3 robustness_2_jobs_p4 $(foreach item,$(ITEMS_1),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_jobs_p1) $(foreach item,$(ITEMS_2),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_jobs_p2;) $(foreach item,$(ITEMS_3),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_jobs_p3;) $(foreach item,$(ITEMS_4),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_jobs_p4;) robustness_2_dv_jobs_p1: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.60,0.65]}' --outfile $@ robustness_2_dv_jobs_p2: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.70,0.75]}' --outfile $@ robustness_2_dv_jobs_p3: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.80,0.85]}' --outfile $@ robustness_2_dv_jobs_p4: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.90,0.95]}' --outfile $@ START=0 END_1=$(shell cat robustness_2_dv_jobs_p1 | wc -l) END_2=$(shell cat robustness_2_dv_jobs_p2 | wc -l) END_3=$(shell cat robustness_2_dv_jobs_p3 | wc -l) END_4=$(shell cat robustness_2_dv_jobs_p4 | wc -l) STEP=1000 ONE=1 ITEMS_1=$(shell seq $(START) $(STEP) $(END_1)) ITEMS_2=$(shell seq $(START) $(STEP) $(END_2)) ITEMS_3=$(shell seq $(START) $(STEP) $(END_3)) ITEMS_4=$(shell seq $(START) $(STEP) $(END_4)) robustness_2_dv.feather: robustness_2_dv_jobs_p1 robustness_2_dv_jobs_p2 robustness_2_dv_jobs_p3 robustness_2_dv_jobs_p4 $(foreach item,$(ITEMS_1),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_dv_jobs_p1) $(foreach item,$(ITEMS_2),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_dv_jobs_p2;) $(foreach item,$(ITEMS_3),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_dv_jobs_p3;) $(foreach item,$(ITEMS_4),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_2_dv_jobs_p4;) robustness_3_jobs_p1: grid_sweep.py 01_two_covariates.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_3.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3],"Px":[0.5,0.6], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.85]}' --outfile $@ robustness_3_jobs_p2: grid_sweep.py 01_two_covariates.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_3.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3],"Px":[0.7,0.8], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.85]}' --outfile $@ robustness_3_jobs_p3: grid_sweep.py 01_two_covariates.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 01_two_covariates.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_3.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3],"Px":[0.9,0.95], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.85]}' --outfile $@ START=0 END_1=$(shell cat robustness_3_jobs_p1 | wc -l) END_2=$(shell cat robustness_3_jobs_p2 | wc -l) END_3=$(shell cat robustness_3_jobs_p3 | wc -l) STEP=1000 ONE=1 ITEMS_1=$(shell seq $(START) $(STEP) $(END_1)) ITEMS_2=$(shell seq $(START) $(STEP) $(END_2)) ITEMS_3=$(shell seq $(START) $(STEP) $(END_3)) robustness_3.feather: robustness_3_jobs_p1 robustness_3_jobs_p2 robustness_3_jobs_p3 $(foreach item,$(ITEMS_1),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_3_jobs_p1) $(foreach item,$(ITEMS_2),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_3_jobs_p2;) $(foreach item,$(ITEMS_3),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_3_jobs_p3;) robustness_3_dv_jobs_p1: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_3.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3],"B0":[0.5,0.6], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.85]}' --outfile $@ robustness_3_dv_jobs_p2: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_3.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3],"B0":[0.7,0.8], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.85]}' --outfile $@ robustness_3_dv_jobs_p3: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_3.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "B0":[0.9,0.95], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.85]}' --outfile $@ START=0 END_1=$(shell cat robustness_3_dv_jobs_p1 | wc -l) END_2=$(shell cat robustness_3_dv_jobs_p2 | wc -l) END_3=$(shell cat robustness_3_dv_jobs_p3 | wc -l) STEP=1000 ONE=1 ITEMS_1=$(shell seq $(START) $(STEP) $(END_1)) ITEMS_2=$(shell seq $(START) $(STEP) $(END_2)) ITEMS_3=$(shell seq $(START) $(STEP) $(END_3)) robustness_3_dv.feather: robustness_3_dv_jobs_p1 robustness_3_dv_jobs_p2 robustness_3_dv_jobs_p3 $(foreach item,$(ITEMS_1),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_3_dv_jobs_p1) $(foreach item,$(ITEMS_2),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_3_dv_jobs_p2;) $(foreach item,$(ITEMS_3),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_3_dv_jobs_p3;) robustness_4_jobs_p1: grid_sweep.py 02_indep_differential.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 02_indep_differential.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.85],y_bias=[-1,-0.85]}' --outfile $@ robustness_4_jobs_p2: grid_sweep.py 02_indep_differential.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 02_indep_differential.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.85], y_bias=[-0.70,-0.55]}' --outfile $@ robustness_4_jobs_p3: grid_sweep.py 02_indep_differential.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 02_indep_differential.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.85],y_bias=[-0.4,-0.25]}' --outfile $@ robustness_4_jobs_p4: grid_sweep.py 02_indep_differential.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 02_indep_differential.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "outcome_formula":["y~x+z"], "proxy_formula":["w_pred~y+x"], "truth_formula":["x~z"], "prediction_accuracy":[0.85],y_bias=[-0.1,0]}' --outfile $@ START=0 END_1=$(shell cat robustness_4_jobs_p1 | wc -l) END_2=$(shell cat robustness_4_jobs_p2 | wc -l) END_3=$(shell cat robustness_4_jobs_p3 | wc -l) END_4=$(shell cat robustness_4_jobs_p3 | wc -l) STEP=1000 ONE=1 ITEMS_1=$(shell seq $(START) $(STEP) $(END_1)) ITEMS_2=$(shell seq $(START) $(STEP) $(END_2)) ITEMS_3=$(shell seq $(START) $(STEP) $(END_3)) ITEMS_4=$(shell seq $(START) $(STEP) $(END_4)) robustness_4.feather: robustness_4_jobs_p1 robustness_4_jobs_p2 robustness_4_jobs_p3 $(foreach item,$(ITEMS_1),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_4_jobs_p1) $(foreach item,$(ITEMS_2),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_4_jobs_p2;) $(foreach item,$(ITEMS_3),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_4_jobs_p3;) robustness_4_dv_jobs_p1: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3],"B0":[0.5] "outcome_formula":["y~x+z"], "prediction_accuracy":[0.85],z_bias=[0,0.1]}' --outfile $@ robustness_4_dv_jobs_p2: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3],"B0":[0.5] "outcome_formula":["y~x+z"], "prediction_accuracy":[0.85],z_bias=[0.25,0.4]}' --outfile $@ robustness_4_dv_jobs_p3: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "B0":[0.5], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.85],z_bias=[0.55,0.7]}' --outfile $@ robustness_4_dv_jobs_p4: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.py rm -f $@ ${srun} $< --command 'Rscript 03_depvar.R' --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_4.feather"],"y_explained_variance":${explained_variances}, "Bzy":[-0.3],"Bxy":[0.3],"Bzx":[0.3], "B0":[0.5], "outcome_formula":["y~x+z"], "prediction_accuracy":[0.85],z_bias=[0.85,1]}' --outfile $@ START=0 END_1=$(shell cat robustness_4_dv_jobs_p1 | wc -l) END_2=$(shell cat robustness_4_dv_jobs_p2 | wc -l) END_3=$(shell cat robustness_4_dv_jobs_p3 | wc -l) STEP=1000 ONE=1 ITEMS_1=$(shell seq $(START) $(STEP) $(END_1)) ITEMS_2=$(shell seq $(START) $(STEP) $(END_2)) ITEMS_3=$(shell seq $(START) $(STEP) $(END_3)) robustness_4_dv.feather: robustness_4_dv_jobs_p1 robustness_4_dv_jobs_p2 robustness_4_dv_jobs_p3 $(foreach item,$(ITEMS_1),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_4_dv_jobs_p1) $(foreach item,$(ITEMS_2),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_4_dv_jobs_p2;) $(foreach item,$(ITEMS_3),sbatch --wait --verbose --array=$(shell expr $(item) + $(ONE))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 robustness_4_dv_jobs_p3;) # clean: rm *.feather rm -f remembr.RDS rm -f example_*_jobs # sbatch --wait --verbose --array=3001-6001 run_simulation.sbatch 0 example_2_B_jobs # example_2_B_mecor_jobs: # sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript example_2_B_mecor.R" --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["example_2_B_mecor.feather"]}' --outfile example_2_B_mecor_jobs # example_2_B_mecor.feather:example_2_B_mecor.R example_2_B_mecor_jobs # rm -f example_2_B_mecor.feather # sbatch --wait --verbose --array=1-3000 run_simulation.sbatch 0 example_2_B_mecor_jobs # sbatch --wait --verbose --array=3001-6001 run_simulation.sbatch 0 example_2_B_mecor_jobs .PHONY: supplement