/my_experiment

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my_experiment

  • the judgment of (r, s)-robust by Deep learning
  • here contains two branches that are my old codes just for memorizing =.=|

CheckRobustness.py

  • implemented from the paper 'Algorithms for DeterminingNetwork Robustness'

consensus_algo.py

  • superclass: NetworkAlgo
  • subclass: ArcpAlgo
  • subclass: LcpAlgo(ToDo)
  • subclass: RarcpAlgo(ToDo)
  • subclass: MedianConsensusAlgo(Todo)

tranin_data_generate.py

  • generate the (r, s)-robust network and save as csv file

data_processing.py

  • class DataGenerator: generate train and test data by a batch-like way
  • get_image_data: generate image data and save as a csv file
  • test_image: just have a glance at the how the images look like

cnn_with_tf.py and dnn_with_tf.py

  • the origin code to implement a deep learning model

graph.py

  • will modified it or just remove it
  • the original file from here

main.py

  • usage: firstly need to write a configurations file, see here, then just run python main.py

model

  • config.py: a configuration file, can be read from a json file
  • neural_network.py: generate a model
  • rbm.py see here
  • sdne.py see here
  • utils.py see here

data

  • include the network data distinguished by (r, s)-robust

assests