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⚠️ This repo contains an experimental prototype for SimPEG's new inversion framework.

inversion-ideas documentation

  • User Guide
  • API Reference
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  • User Guide
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Section Navigation

  • Objective functions
    • inversion_ideas.DataMisfit
    • inversion_ideas.SimpleSmallness
    • inversion_ideas.SimpleFlatness
    • inversion_ideas.Smallness
    • inversion_ideas.Flatness
    • inversion_ideas.SparseSmallness
  • Minimizers
    • inversion_ideas.minimize.GaussNewtonConjugateGradient
    • inversion_ideas.minimize.conjugate_gradient
    • inversion_ideas.minimize.backtracking_line_search
  • Preconditioners
    • inversion_ideas.BFGSPreconditioner
    • inversion_ideas.JacobiPreconditioner
    • inversion_ideas.get_jacobi_preconditioner
  • Directives
    • inversion_ideas.directives
    • inversion_ideas.directives.Irls
  • Conditions
    • inversion_ideas.conditions
    • inversion_ideas.conditions.ChiTarget
    • inversion_ideas.conditions.CustomCondition
    • inversion_ideas.conditions.ObjectiveChanged
    • inversion_ideas.conditions.ModelChanged
  • Simulations
    • inversion_ideas.wrap_simulation
    • inversion_ideas.WrappedSimulation
    • inversion_ideas.LinearRegressor
  • Inversions and Recipes
    • inversion_ideas.Inversion
    • inversion_ideas.InversionLog
    • inversion_ideas.InversionLogRich
    • inversion_ideas.create_l2_inversion
    • inversion_ideas.create_sparse_inversion
    • inversion_ideas.create_tikhonov_regularization
  • Custom linear operators
    • inversion_ideas.operators
    • inversion_ideas.operators.Identity
    • inversion_ideas.operators.get_diagonal
  • Utilities
    • inversion_ideas.utils
    • inversion_ideas.utils.estimate_tradeoff_parameter
    • inversion_ideas.utils.get_largest_eigenvalue
    • inversion_ideas.utils.get_sensitivity_weights
    • inversion_ideas.utils.get_logger
    • inversion_ideas.utils.Counter
  • Hyperparameters
    • inversion_ideas.hyperparams.CooledMultiplier
    • inversion_ideas.hyperparams.SensitivityWeights
  • Decorators
    • inversion_ideas.decorators
    • inversion_ideas.decorators.cache_on_model
    • inversion_ideas.decorators.debug
    • inversion_ideas.decorators.CountCalls
  • Errors and warnings
    • inversion_ideas.errors
    • inversion_ideas.errors.ConvergenceError
    • inversion_ideas.errors.ConvergenceWarning
    • inversion_ideas.errors.NotInitializedError
  • Base submodule
    • inversion_ideas.base
    • inversion_ideas.base.Objective
    • inversion_ideas.base.Scaled
    • inversion_ideas.base.Combo
    • inversion_ideas.base.Simulation
    • inversion_ideas.base.Minimizer
    • inversion_ideas.base.MinimizerResult
    • inversion_ideas.base.Condition
    • inversion_ideas.base.Directive
    • inversion_ideas.base.Multiplier
    • inversion_ideas.base.WrappedArray
  • API Reference
  • Minimizers

Minimizers#

Minimizer classes:

minimize.GaussNewtonConjugateGradient(*[, ...])

Minimize non-linear objective functions using a Gauss-Newton Conjugate Gradient.

Minimizer functions:

minimize.conjugate_gradient(objective, ...)

Minimize objective function with a Conjugate Gradient method.

Functions related to minimizers:

minimize.backtracking_line_search(phi, ...)

Implement the backtracking line search algorithm.

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