Package to test causal discovery algorithm on simulated and real data

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• NBCB: https://link.springer.com/chapter/10.1007/978-3-030-86486-6_28
• PCTMI:
• TiMINO: https://proceedings.neurips.cc/paper/2013/file/47d1e990583c9c67424d369f3414728e-Paper.pdf
• VarLiNGAM: https://www.jmlr.org/papers/volume11/hyvarinen10a/hyvarinen10a.pdf
• PCMCICMIknn: http://proceedings.mlr.press/v124/runge20a/runge20a.pdf
• PCMCIParCorr: http://proceedings.mlr.press/v124/runge20a/runge20a.pdf
• oCSE: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.474.6986&rep=rep1&type=pdf
• tsFCI:
• DyNoTears: https://arxiv.org/pdf/2002.00498.pdf
• GrangerMV: https://pubmed.ncbi.nlm.nih.gov/20481753/
• GrangerPW
• TCDF:

Some algorithms are imported from other langauges such as R and Java

python3 test_simulated_data.py method structure n_samples num_processor verbose

• method: causal dicovery algorithms, choose from [GrangerPW, GrangerMV, TCDF, PCMCICMIknn, PCMCIParCorr, oCSE, PCTMI, tsFCI, VarLiNGAM, TiMINO, Dynotears]
• structure: causal structure, choose from [fork, v_structure, diamond, 7ts2h]
• n_samples: number of timestamps
• num_processor: number of processors

Example: python3 test_fmri.py "NBCB" "fork" 1000 1 1

python3 test_simulated_data.py method num_processor verbose

Example: python3 test_fmri.py "NBCB" 1 1