simpeg.maps.ComboMap#

class simpeg.maps.ComboMap(maps, **kwargs)[source]#

Bases: IdentityMap

Combination mapping constructed by joining a set of other mappings.

A ComboMap is a single mapping object made by joining a set of basic mapping operations by chaining them together, in order. When creating a ComboMap, the user provides a list of SimPEG mapping objects they wish to join. The order of the mappings in this list is from last to first; i.e. \([\mathbf{f}_n , ... , \mathbf{f}_2 , \mathbf{f}_1]\).

The combination mapping \(\mathbf{u}(\mathbf{m})\) that acts on a set of input model parameters \(\mathbf{m}\) is defined as:

\[\mathbf{u}(\mathbf{m}) = f_n(f_{n-1}(\cdots f_1(f_0(\mathbf{m}))))\]

Note that any time that you create your own combination mapping, be sure to test that the derivative is correct.

Parameters:

mapslist of simpeg.maps.IdentityMap: A list of SimPEG mapping objects. The ordering of the mapping objects in the list is from last applied to first applied!

Attributes

`is_linear`	Determine whether or not this mapping is a linear operation.
`mesh`	The mesh used for the mapping
`nP`	Number of parameters the mapping acts on.
`shape`	Dimensions of the mapping.

Methods

`deriv`(m[, v])	Derivative of the mapping with respect to the input parameters.
`dot`(map1)	Multiply two mappings to create a `simpeg.maps.ComboMap`.
`inverse`(D)	The transform inverse is not implemented.
`test`([m, num, random_seed])	Derivative test for the mapping.

Examples

Here we create a combination mapping that 1) projects a single scalar to a vector space of length 5, then takes the natural exponent.

>>> import numpy as np
>>> from simpeg.maps import ExpMap, Projection, ComboMap

>>> nP1 = 1
>>> nP2 = 5
>>> ind = np.zeros(nP1, dtype=int)

>>> projection_map = Projection(nP1, ind)
>>> projection_map.shape
(5, 1)

>>> exp_map = ExpMap(nP=5)
>>> exp_map.shape
(5, 5)

Recall that the order of the mapping objects is from last applied to first applied.

>>> map_list = [exp_map, projection_map]
>>> combo_map = ComboMap(map_list)
>>> combo_map.shape
(5, 1)

>>> m = np.array([2.])
>>> combo_map * m
array([7.3890561, 7.3890561, 7.3890561, 7.3890561, 7.3890561])

Galleries and Tutorials using `simpeg.maps.ComboMap`#

Maps: ComboMaps

3D DC inversion of Dipole Dipole array

2D inversion of Loop-Loop EM Data

2.5D DC Resistivity and IP Least-Squares Inversion

3D Least-Squares Inversion of DC and IP Data

Least-Squares 1D Inversion of Sounding Data

Sparse 1D Inversion of Sounding Data

Parametric 1D Inversion of Sounding Data

2.5D DC Resistivity Least-Squares Inversion

2.5D DC Resistivity Inversion with Sparse Norms

3D Least-Squares Inversion of DC Resistivity Data

Tensor Meshes

Cylindrical Meshes

Tree Meshes

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

simpeg.maps.ComboMap#

Galleries and Tutorials using simpeg.maps.ComboMap#

Galleries and Tutorials using `simpeg.maps.ComboMap`#