API Reference

I/O Management

• pyengnet.File: Class used to manage file I/O operations and data visualization.

• pyengnet.File.load(): Load dataset from a txt or csv file.

• pyengnet.File.saveFile(): Save network to file (can be used to store full and/or pruned networks)

• pyengnet.File.showGraph(): Display a specific network

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Ensemble

• pyengnet.Engnet: Class in charge of controlling the execution of the EnGNet algorithm.

• pyengnet.Engnet.process(): Function that runs the EngNet algorithm. Depending on the parameters of this function, the algorithm will be executed in parallel with CPU processors or GPU devices.

• pyengnet.Kendall: Kendall measurement is coded in a parallel ecosystem with CPUs.

• pyengnet.NMI: NMI measurement is coded in a parallel ecosystem with CPUs.

• pyengnet.Spearman: Spearman measurement is coded in a parallel ecosystem with CPUs.

• pyengnet.src.correlations: Execution of Kendall, NMI, and Spearman measures under a parallel multi-GPU ecosystem (CUDA). In addition, it detects those pairs of genes that exceed the threshold for major voting.

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All Models

• pyengnet package
  • Submodules
  • pyengnet.Dataset module
    • Dataset
      • Dataset.column_size
      • Dataset.data
      • Dataset.filePath
      • Dataset.gene
      • Dataset.hub_threshold
      • Dataset.kendall_threshold
      • Dataset.ncores
      • Dataset.nmi_threshold
      • Dataset.readded_edges_threshold
      • Dataset.row_size
      • Dataset.spearman_threshold
  • pyengnet.Engnet module
  • pyengnet.File module
  • pyengnet.Kendall module
  • pyengnet.NMI module
    • NMI
      • NMI.process()
  • pyengnet.Normalization module
    • Normalization
      • Normalization.normalizedArray()
  • pyengnet.Spearman module
  • pyengnet.version module
  • Module contents