simpeg.maps.InjectActiveCells#

class simpeg.maps.InjectActiveCells(mesh, indActive=None, valInactive=0.0, nC=None)[source]#

Bases: IdentityMap

Map active cells model to all cell of a mesh.

The InjectActiveCells class is used to define the mapping when the model consists of physical property values for a set of active mesh cells; e.g. cells below topography. For a discrete set of model parameters \(\mathbf{m}\) defined on a set of active cells, the mapping \(\mathbf{u}(\mathbf{m})\) is defined as:

\[\mathbf{u}(\mathbf{m}) = \mathbf{Pm} + \mathbf{d}\, m_\perp\]

where \(\mathbf{P}\) is a (nC , nP) projection matrix from active cells to all mesh cells, and \(\mathbf{d}\) is a (nC , 1) matrix that projects the inactive cell value \(m_\perp\) to all inactive mesh cells.

Parameters:
meshdiscretize.BaseMesh

A discretize mesh

indActivenumpy.ndarray

Active cells array. Can be a boolean numpy.ndarray of length mesh.nC or a numpy.ndarray of int containing the indices of the active cells.

valInactivefloat or numpy.ndarray

The physical property value assigned to all inactive cells in the mesh

Attributes

indActive

Returns:

is_linear

Determine whether or not this mapping is a linear operation.

mesh

The mesh used for the mapping

nP

Number of parameters the model acts on.

shape

Dimensions of the mapping

valInactive

The physical property value assigned to all inactive cells in the mesh.

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(u)

Recover the model parameters (active cells) from a set of physical property values defined on the entire mesh.

test([m, num, random_seed])

Derivative test for the mapping.

Galleries and Tutorials using simpeg.maps.InjectActiveCells#

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

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

Predict Response from a Conductive and Magnetically Viscous Earth

Predict Response from a Conductive and Magnetically Viscous Earth

Method of Equivalent Sources for Removing VRM Responses

Method of Equivalent Sources for Removing VRM Responses

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 Casing Example

Heagy et al., 2017 Casing Example

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

Forward Simulation of VRM Response on a Tree Mesh

Forward Simulation of VRM Response on a Tree Mesh

Forward Simulation Including Inductive Response

Forward Simulation Including Inductive Response

Forward Simulation of Gravity Anomaly Data on a Tensor Mesh

Forward Simulation of Gravity Anomaly Data on a Tensor Mesh

Forward Simulation of Gradiometry Data on a Tree Mesh

Forward Simulation of Gradiometry Data on a Tree Mesh

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

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

3D Forward Simulation on a Cylindrical Mesh

3D Forward Simulation on a Cylindrical Mesh

3D Forward Simulation on a Tree Mesh

3D Forward Simulation on a Tree Mesh

3D Forward Simulation for Transient Response on a Cylindrical Mesh

3D Forward Simulation for Transient Response on a Cylindrical Mesh

3D Forward Simulation with User-Defined Waveforms

3D Forward Simulation with User-Defined Waveforms

2.5D Forward Simulation of a DCIP Line

2.5D Forward Simulation of a DCIP Line

DC/IP Forward Simulation in 3D

DC/IP Forward Simulation in 3D

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

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data

Tensor Meshes

Tensor Meshes

Cylindrical Meshes

Cylindrical Meshes

Tree Meshes

Tree Meshes

Forward Simulation of Total Magnetic Intensity Data

Forward Simulation of Total Magnetic Intensity Data

Forward Simulation of Gradiometry Data for Magnetic Vector Models

Forward Simulation of Gradiometry Data for Magnetic Vector Models

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

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

DC Resistivity Forward Simulation in 2.5D

DC Resistivity Forward Simulation in 2.5D

DC Resistivity Forward Simulation in 3D

DC Resistivity Forward Simulation in 3D

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