Make summarize estimator group correctly for robustness checks.

[ml_measurement_error_public.git] / simulations / Makefile

diff --git a/simulations/Makefile b/simulations/Makefile
index 1cab47320e5238ff9afa7b6938003a56136aa34f..3e8fdd5c24a391171bf1f9e47de85140b9c96515 100644 (file)
--- a/simulations/Makefile
+++ b/simulations/Makefile
@@ -36,7 +36,7 @@ example_1.feather: 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
+       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
@@ -66,10 +66,10 @@ example_3.feather: 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":${seeds}, "outfile":["example_4.feather"], "z_bias":[0.5]}' --outfile example_4_jobs
+       sbatch --wait --verbose run_job.sbatch grid_sweep.py --command "Rscript 04_depvar_differential.R" --arg_dict '{"N":${Ns},"Bxy":[0.7],"Bzy":[-0.7],"m":${ms}, "seed":${seeds}, "outfile":["example_4.feather"], "z_bias":[0.3], "prediction_accuracy":[0.73]}' --outfile example_4_jobs
 
 example_4.feather: example_4_jobs
-       rm -f example_4.feather 
+       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
@@ -86,41 +86,6 @@ remembr.RDS:example_1.feather example_2.feather example_3.feather example_4.feat
        ${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
 
@@ -210,7 +175,7 @@ robustness_2_dv_jobs_p3: grid_sweep.py 03_depvar.R simulation_base.R grid_sweep.
 
 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_dv.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 $@
+       ${srun} $< --command 'Rscript 03_depvar.R'  --arg_dict '{"N":${Ns},"m":${ms}, "seed":${seeds}, "outfile":["robustness_2_dv.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 $@
 
 robustness_2_dv.feather: robustness_2_dv_jobs_p1 robustness_2_dv_jobs_p2 robustness_2_dv_jobs_p3 robustness_2_dv_jobs_p4
        $(eval END_1!=cat robustness_2_dv_jobs_p1 | wc -l)
@@ -361,8 +326,22 @@ robustness_4_dv.RDS: plot_dv_example.R robustness_4_dv.feather
        rm -f $@
        ${srun} Rscript $< --infile $(word 2, $^) --name "robustness_4" --remember-file $@
 
+
+
+clean_main:
+       rm -f remembr.RDS
+       rm -f example_1_jobs
+       rm -f example_2_jobs
+       rm -f example_3_jobs
+       rm -f example_4_jobs
+       rm -f example_1.feather
+       rm -f example_2.feather
+       rm -f example_3.feather
+       rm -f example_4.feather
+
+
 #      
-clean:
+clean_all:
        rm *.feather
        rm -f remembr.RDS
        rm -f remembr*.RDS