# SimPEG.objective_function.ComboObjectiveFunction#

class SimPEG.objective_function.ComboObjectiveFunction(objfcts: = None, multipliers=None, unpack_on_add=True)[source]#

Composite for multiple objective functions.

This class allows the creation of an objective function $$\phi$$ which is the sum of a list of other objective functions $$\phi_i$$. Each objective function has associated with it a multiplier $$c_i$$ such that

$\phi = \sum_{i = 1}^N c_i \phi_i$
Parameters:
objfctsNone or list of SimPEG.objective_function.BaseObjectiveFunction, optional

List containing the objective functions that will live inside the composite class. If None, an empty list will be created.

multipliersNone or list of int, optional

List containing the multipliers for each objective function in objfcts. If None, a list full of ones with the same length as objfcts will be created.

Whether to unpack the multiple objective functions when adding them to another objective function, or to add them as a whole.

Examples

Build a simple combo objective function:

>>> objective_fun_a = L2ObjectiveFunction(nP=3)
>>> objective_fun_b = L2ObjectiveFunction(nP=3)
>>> combo = ComboObjectiveFunction([objective_fun_a, objective_fun_b], [1, 0.5])
>>> print(len(combo))
2
>>> print(combo.multipliers)
[1, 0.5]


Combo objective functions are also created after adding two objective functions:

>>> combo = 2 * objective_fun_a + 3.5 * objective_fun_b
>>> print(len(combo))
2
>>> print(combo.multipliers)
[2, 3.5]


We could add two combo objective functions as well:

>>> objective_fun_c = L2ObjectiveFunction(nP=3)
>>> objective_fun_d = L2ObjectiveFunction(nP=3)
>>> combo_1 = 4.3 * objective_fun_a + 3 * objective_fun_b
>>> combo_2 = 1.5 * objective_fun_c + 0.5 * objective_fun_d
>>> combo = combo_1 + combo_2
>>> print(len(combo))
4
>>> print(combo.multipliers)
[4.3, 3, 1.5, 0.5]


We can choose to not unpack the objective functions when creating the combo. For example:

>>> objective_fun_a = L2ObjectiveFunction(nP=3)
>>> objective_fun_b = L2ObjectiveFunction(nP=3)
>>> objective_fun_c = L2ObjectiveFunction(nP=3)
>>>
>>> # Create a ComboObjectiveFunction that won't unpack
>>> combo_1 = ComboObjectiveFunction(
...     objfcts=[objective_fun_a, objective_fun_b],
...     multipliers=[0.1, 1.2],
... )
>>> combo_2 = combo_1 + objective_fun_c
>>> print(len(combo_2))
2


Attributes

 W Full weighting matrix for the combo objective function. mapping Mapping from the model to the quantity evaluated in the object function. multipliers Multipliers for the objective functions. nP Number of model parameters.

Methods

 __call__(m[, f]) Evaluate the objective functions for a given model. deriv(m[, f]) Gradient of the objective function evaluated for the model provided. deriv2(m[, v, f]) Hessian of the objective function evaluated for the model provided. get_functions_of_type(fun_class) Return objective functions of a given type(s). map_class alias of IdentityMap test([x, num]) Run a convergence test on both the first and second derivatives.

## Galleries and Tutorials using SimPEG.objective_function.ComboObjectiveFunction#

Maps: ComboMaps

Maps: ComboMaps

PF: Gravity: Tiled Inversion Linear

PF: Gravity: Tiled Inversion Linear

Magnetic inversion on a TreeMesh

Magnetic inversion on a TreeMesh

Magnetic inversion on a TreeMesh

Magnetic inversion on a TreeMesh

Magnetic Amplitude inversion on a TreeMesh

Magnetic Amplitude inversion on a TreeMesh

3D DC inversion of Dipole Dipole array

3D DC inversion of Dipole Dipole array

Parametric DC inversion with Dipole Dipole array

Parametric DC inversion with Dipole Dipole array

2D inversion of Loop-Loop EM Data

2D inversion of Loop-Loop EM Data

EM: TDEM: 1D: Inversion

EM: TDEM: 1D: Inversion

EM: TDEM: 1D: Inversion with VTEM waveform

EM: TDEM: 1D: Inversion with VTEM waveform

FLOW: Richards: 1D: Inversion

FLOW: Richards: 1D: Inversion

Petrophysically guided inversion (PGI): Linear example

Petrophysically guided inversion (PGI): Linear example

Petrophysically guided inversion: Joint linear example with nonlinear relationships

Petrophysically guided inversion: Joint linear example with nonlinear relationships

Heagy et al., 2017 1D RESOLVE and SkyTEM Bookpurnong Inversions

Heagy et al., 2017 1D RESOLVE and SkyTEM Bookpurnong Inversions

Heagy et al., 2017 1D RESOLVE Bookpurnong Inversion

Heagy et al., 2017 1D RESOLVE Bookpurnong Inversion

Heagy et al., 2017 1D FDEM and TDEM inversions

Heagy et al., 2017 1D FDEM and TDEM inversions

PF: Gravity: Laguna del Maule Bouguer Gravity

PF: Gravity: Laguna del Maule Bouguer Gravity

Straight Ray with Volume Data Misfit Term

Straight Ray with Volume Data Misfit Term

Linear Least-Squares Inversion

Linear Least-Squares Inversion

Sparse Inversion with Iteratively Re-Weighted Least-Squares

Sparse Inversion with Iteratively Re-Weighted Least-Squares

1D Inversion of for a Single Sounding

1D Inversion of for a Single Sounding

Joint PGI of Gravity + Magnetic on an Octree mesh using full petrophysical information

Joint PGI of Gravity + Magnetic on an Octree mesh using full petrophysical information

Joint PGI of Gravity + Magnetic on an Octree mesh without petrophysical information

Joint PGI of Gravity + Magnetic on an Octree mesh without petrophysical information

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data

2.5D DC Resistivity and IP Least-Squares Inversion

2.5D DC Resistivity and IP Least-Squares Inversion

3D Least-Squares Inversion of DC and IP Data

3D Least-Squares Inversion of DC and IP Data

Sparse Norm Inversion of 2D Seismic Tomography Data

Sparse Norm Inversion of 2D Seismic Tomography Data

Least-Squares Inversion of Gravity Anomaly Data

Least-Squares Inversion of Gravity Anomaly Data

Sparse Norm Inversion of Gravity Anomaly Data

Sparse Norm Inversion of Gravity Anomaly Data

Least-Squares 1D Inversion of Sounding Data

Least-Squares 1D Inversion of Sounding Data

Sparse 1D Inversion of Sounding Data

Sparse 1D Inversion of Sounding Data

Parametric 1D Inversion of Sounding Data

Parametric 1D Inversion of Sounding Data

2.5D DC Resistivity Least-Squares Inversion

2.5D DC Resistivity Least-Squares Inversion

2.5D DC Resistivity Inversion with Sparse Norms

2.5D DC Resistivity Inversion with Sparse Norms

3D Least-Squares Inversion of DC Resistivity Data

3D Least-Squares Inversion of DC Resistivity Data

1D Inversion of Time-Domain Data for a Single Sounding

1D Inversion of Time-Domain Data for a Single Sounding

Sparse Norm Inversion for Total Magnetic Intensity Data on a Tensor Mesh

Sparse Norm Inversion for Total Magnetic Intensity Data on a Tensor Mesh