+
+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: 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":[0.6,0.73,0.8,0.85,0.9,0.95]}' --outfile $@
+
+
+
+START=1
+END=$(shell cat robustness_2_jobs | wc -l)
+STEP=1000
+ITEMS=$(shell seq $(START) $(STEP) $(END))
+
+robustness_2.feather: robustness_2_jobs
+ $(foreach item,$(ITEMS),sbatch --wait --verbose --array=$(shell expr $(item))-$(shell expr $(item) + $(STEP)) run_simulation.sbatch 0 $<)
+
+#