.ONESHELL:
SHELL=bash

Ns=[1000,5000,10000]
ms=[100,200,400,1000]
seeds=[$(shell seq -s, 1 500)]
explained_variances=[0.1]

all:main
main:remembr.rds 

srun=sbatch --wait --verbose skx_dev.sbatch
skx_pylauncher_limit=40

joblists:example_1_jobs example_2_jobs example_3_jobs

grid_sweep_script=../simulations/grid_sweep.py 

example_1_jobs: 01_indep_differential.R simulation_base.R ${grid_sweep_script} skx_dev.sbatch ../misclassificationmodels
	${srun} uv run ${grid_sweep_script} --command 01_indep_differential.R --arg_dict '{"N":${Ns},"m":${ms},"seed":${seeds},"outfile":["example_1.feather"],"y_explained_variance":${explained_variances},"Bzx":[1],"prediction_accuracy":[0.825]}' --outfile example_1_jobs --remember_file=remember_grid_sweep.rds

example_1.feather: example_1_jobs my_pylauncher.py
	sbatch -J "multiple iv measerr correction" spr_2.sbatch my_pylauncher.py $< --cores 1

remembr.rds:example_1.feather 
# 	rm -f remembr.RDS
# 	${srun} Rscript plot_example.R --infile example_1.feather --name "plot.df.example.1"


clean_main:
	rm -f example_1_jobs
	rm -f example_1.feather
#	
clean_all: clean_main
	rm *.feather
	rm -f remembr.RDS
	rm -f remembr*.RDS
	rm -f robustness*.RDS
	rm -f example_*_jobs
	rm -f robustness_*_jobs_*