CityLearn

Getting started

  • Installation
  • Your first simulation
  • Features and configuration
  • Moving an existing project to CityLearn v3

Configure and run

  • Running Simulations
  • Schema Reference
  • Dataset Reference
  • Data Unit Contract
  • Flat and Entity Interfaces
  • Observations Reference
  • Actions Reference
  • Multi-Community Reference
  • Robustness Reference

Evaluate

  • Baselines
  • KPIs
  • How to read the scorecard
  • Default scorecard KPI names
  • KPIs Reference
  • KPI v2 Naming Tree

Visualize

  • CityLearn UI

Concepts and tutorials

  • Core concepts
  • Examples and tutorials
  • Command Line Interface
  • Python API
    • citylearn package
      • Subpackages
        • citylearn.agents package
        • citylearn.end_use_load_profiles package
        • citylearn.internal package
        • citylearn.utils package
      • Submodules
  • The CityLearn Challenge

Project

  • Publications and applications
  • References
  • Contributing
  • Validation and performance
  • Developer Guide
  • Publishing CityLearn
  • Releases
  • Earlier releases
CityLearn
  • citylearn
  • citylearn package
  • citylearn.end_use_load_profiles package
  • citylearn.end_use_load_profiles.lstm_model package
  • Edit on GitHub

citylearn.end_use_load_profiles.lstm_model package

Submodules

  • citylearn.end_use_load_profiles.lstm_model.model module
    • LSTM
      • LSTM.forward()
      • LSTM.init_hidden()
  • citylearn.end_use_load_profiles.lstm_model.model_generation module
    • eval()
    • run()
    • train()
  • citylearn.end_use_load_profiles.lstm_model.model_generation_wrapper module
    • get_model()
    • run_one_model()
    • set_random_seeds()
  • citylearn.end_use_load_profiles.lstm_model.preprocessing module
    • dataset_dataloader()
    • preprocess_df()
    • sliding_windows()
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© Copyright 2023, Jose Ramon Vazquez-Canteli, Kingsley Nweye, Zoltan Nagy.

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