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_plot_tfact
  • hookeai.simulators.links.utilities.links_plot_tfact.scale_tfact_hist

hookeai.simulators.links.utilities.links_plot_tfact.scale_tfact_hist¶

scale_tfact_hist(tfact_hist, scale_factor=1.0)[source]¶

Perform linear scaling of total load factor history.

Parameters:
  • tfact_hist (np.ndarray(2d)) – Total load factor history stored as numpy.ndarray(2d) of shape (n_time, 2), where the discrete time is stored in array[:, 0] and the total load factor in array[:, 1].

  • scale_factor (float, default=1.0) – Linear scaling factor.

Returns:

tfact_hist_scaled – Total load factor history stored as numpy.ndarray(2d) of shape (n_time, 2), where the discrete time is stored in array[:, 0] and the total load factor in array[:, 1].

Return type:

np.ndarray(2d)

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© Copyright 2025, Bernardo Ferreira.

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