# ################# small experiment 1000 samples 1000 timeout
python experiments/plot_experiment.py --methods dagTFRC sparserc varlingam d_varlingam dynotears nts-notears tsfci pcmci TCDF --number_of_lags 2 --samples 1 --timesteps 1000 --nodes 20 30 50 100 200 500 1000  --runs 5 --sparsity 0.05 --timeout 10000 --rotate True

################# varying nodes: large experiment 10000 samples 10000 timeout
python experiments/plot_experiment.py --methods dagTFRC sparserc varlingam d_varlingam dynotears nts-notears tsfci pcmci TCDF  --number_of_lags 2 --samples 10 --timesteps 1000 --nodes 20 30 50 100 200 500 1000 2000 4000 --runs 5 --sparsity 0.05 --timeout 10000 --rotate True
python experiments/plot_experiment.py --methods dagTFRC sparserc varlingam d_varlingam dynotears nts-notears tsfci pcmci TCDF  --number_of_lags 2 --samples 10 --timesteps 1000 --nodes 20 30 50 100 200 500 1000 2000 4000 --runs 5 --sparsity 0.05 --timeout 10000 --legend True

# ################## varying samples: large experiment 10000 samples 10000 timeout
python experiments/plot_experiment.py --methods dagTFRC sparserc varlingam d_varlingam dynotears nts-notears tsfci pcmci TCDF --number_of_lags 2 --samples 1 2 3 5 10 20 --timesteps 1000 --nodes 500  --runs 5 --sparsity 0.05 --timeout 10000

# ################# larger lag 
python experiments/plot_experiment.py --methods dagTFRC sparserc varlingam d_varlingam dynotears nts-notears tsfci pcmci TCDF --number_of_lags 5 --weight_bounds 0.1 0.2 --samples 10 --timesteps 1000 --nodes 20 30 50 100 200 500 1000 2000 --runs 5 --sparsity 0.05 --timeout 10000

# ############### lag sensitivity # first uncomment accuracy vs param
python experiments/plot_experiment.py --methods dagTFRC sparserc varlingam  --number_of_lags 3 --weight_bounds 0.1 0.2 --samples 10 --timesteps 1000 --nodes 1000 --runs 5 --sparsity 0.05 --timeout 10000
python experiments/plot_experiment.py --methods dagTFRC sparserc varlingam  --number_of_lags 3 --weight_bounds 0.1 0.2 --samples 10 --timesteps 1000 --nodes 1000 --runs 5 --sparsity 0.05 --timeout 10000  --legend True

# ################# Finance CPT
#best
python experiments/print_table_tex.py --dataset finance --methods dagTFRC sparserc varlingam d_varlingam TCDF
# appendix 
python experiments/print_table_tex.py --dataset finance --methods dynotears nts-notears tsfci pcmci

# ################# Stocks 
python experiments/plot_stocks.py --methods  dagTFRC sparserc varlingam dynotears pcmci TCDF  --runs 1
