hookeai
1.0.0

Getting started

  • Overview
  • Installation

Features

  • Overview
  • Data generation
  • Material model architectures
  • Local material model updating
  • Global material model updating
  • Data analysis and visualization tools
  • Tensorial algebra and matrix operations
  • Other utilities

API

  • Code
    • hookeai.data_generation
    • hookeai.ioput
    • hookeai.material_model_finder
    • hookeai.miscellaneous
    • hookeai.model_architectures
    • hookeai.simulators
      • hookeai.simulators.fetorch
      • hookeai.simulators.links
        • hookeai.simulators.links.discretization
        • hookeai.simulators.links.links
        • hookeai.simulators.links.models
        • hookeai.simulators.links.utilities
    • hookeai.time_series_data
    • hookeai.utilities

License

  • MIT License
hookeai
  • hookeai
  • hookeai.simulators
  • hookeai.simulators.links
  • hookeai.simulators.links.utilities
  • hookeai.simulators.links.utilities.links_out_to_dataset
  • hookeai.simulators.links.utilities.links_out_to_dataset.build_dataset

hookeai.simulators.links.utilities.links_out_to_dataset.build_dataset¶

build_dataset(links_out_file_paths, n_dim)[source]¶

Build time series data set from set of Links Gauss point ‘.out’ files.

Parameters:
  • links_out_file_paths (tuple) – Links Gauss point ‘.out’ data file paths.

  • n_dim (int) – Number of spatial dimensions.

Returns:

dataset – Time series data set. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

Return type:

torch.utils.data.Dataset

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