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WIP: Implement bootstrap#107

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mjwen merged 85 commits intoopenkim:masteropenkim/kliff:masterfrom yonatank93:implement_bootstrapyonatank93/kliff:implement_bootstrapCopy head branch name to clipboardApr 4, 2023

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Commits on Jan 9, 2023

• Initial version of bootstrap class for empirical model

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• get_compute_arguments can return a flat or nested list

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• Add has_opt_params_bounds method to _WrapperCalculator

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Commits on Jan 10, 2023

• Initial updates on the neural network calculator

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• Initial working script for bootstrap neural network

  

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Commits on Jan 12, 2023

• MOdify the default bootstrap cas generator for empirical model

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• Cache the initial parameter guess for empirical model

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• Add an option to input initial guess in each step

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Commits on Jan 13, 2023

• Reset the parameters for NN and empirical model

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• Clean up

  

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• Fix the list of residual function when using _WrapperCalculator

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Commits on Mar 14, 2023

• Documentation for bootstrap sampler clas for empirical models

  

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• Initial draft of bootstrap example for empirical model

  

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Commits on Mar 16, 2023

• Test for bootstrap empirical model

  

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• BUG: default generator function for empirical model when using multiple calculators

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• Documentation for bootstrap NN class

  

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• Test for bootstrap neural network model

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• Clean up and update documentation

  

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Commits on Mar 17, 2023

• Work out the compatibility with CalculatorTorchSeparateSpecies

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• Finallyze the draft of bootstrap example

  

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• Refactoring

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• Run pre-commit

  

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Commits on Mar 20, 2023

• Add callback function to bootstrap empirical model

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Commits on Mar 21, 2023

• Apply changes based on minor feedback

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Commits on Mar 24, 2023

• DOC: convert to google style

  

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• Add additional argument for default bootstrap dataset generator

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• BUG: Fix get parameter and update parameter

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Commits on Mar 26, 2023

• DOC: Convert to googledoc style

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• Fix example for the documentation page

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• Add an option to specify callback function for NN case

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• Also import each bootstrap class for empirical and NN models

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• DOC: Add page about bootstrapping

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Commits on Mar 27, 2023

• Revert back the change to use torch.Tensor

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• TST: Tests for retrieving and updating NN model parameters

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Commits on Mar 28, 2023

• DOC: Add the shape of numpy array.

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• Remove commands that are not needed

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• DOC: Fix typos

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Commits on Apr 4, 2023

• Add a default random seed and use a local random seed generator

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• Remove pretraining before running bootstrap and added notes about

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• Update how to compute sigma in MagnitudeInverseWeight

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• Update due to DeprecationWarning

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• Initial version of bootstrap class for empirical model

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• get_compute_arguments can return a flat or nested list

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• Add has_opt_params_bounds method to _WrapperCalculator

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• Initial updates on the neural network calculator

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• Initial working script for bootstrap neural network

  

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• MOdify the default bootstrap cas generator for empirical model

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• Cache the initial parameter guess for empirical model

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• Add an option to input initial guess in each step

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• Reset the parameters for NN and empirical model

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• Clean up

  

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• Fix the list of residual function when using _WrapperCalculator

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• Documentation for bootstrap sampler clas for empirical models

  

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• Initial draft of bootstrap example for empirical model

  

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• Test for bootstrap empirical model

  

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• BUG: default generator function for empirical model when using multiple calculators

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• Documentation for bootstrap NN class

  

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• Test for bootstrap neural network model

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• Clean up and update documentation

  

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• Work out the compatibility with CalculatorTorchSeparateSpecies

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• Finallyze the draft of bootstrap example

  

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• Refactoring

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• Run pre-commit

  

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• Add callback function to bootstrap empirical model

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• Apply changes based on minor feedback

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• DOC: convert to google style

  

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• Add additional argument for default bootstrap dataset generator

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• BUG: Fix get parameter and update parameter

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• DOC: Convert to googledoc style

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• Fix example for the documentation page

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• Add an option to specify callback function for NN case

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• Also import each bootstrap class for empirical and NN models

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• DOC: Add page about bootstrapping

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• Revert back the change to use torch.Tensor

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• TST: Tests for retrieving and updating NN model parameters

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• DOC: Add the shape of numpy array.

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• Remove commands that are not needed

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• DOC: Fix typos

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• Add a default random seed and use a local random seed generator

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• Remove pretraining before running bootstrap and added notes about

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• Update how to compute sigma in MagnitudeInverseWeight

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• Update due to DeprecationWarning

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• Merge branch 'implement_bootstrap' of https://github.com/yonatank93/kliff into implement_bootstrap

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• Build documentation

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