gplib | |
C1DAnisoMTSynthData | Calculate response of a 1D anisotropic model, code is based on Pek and Santos fortran code |
C1DMTSynthData | Calculate synthetic MT data for a 1D model using Cagniard's algorithm |
ThreeDMTModel | The class 3DMTModel manages 3D models for magnetotelluric model calculations, at this point this is only for file management and plotting purposes |
MagneticTF | Store th local magnetic transfer function (tipper) |
MTStation | The class MTStation is used to store the transfer functions and related information for a MT-site |
HasSameName | Returns if station a and b have the same name |
MTStationList | MTStationList holds a number of MTSites, usually associated with a single project, line, etc |
MTTensor | Stores MT-Tensor components at a single frequency, calculates derived quantities |
PTensorMTData | This class is for the special case where we only have phase tensor data and errors, but not the full impedance |
PTensorMTStation | |
BirrpAsciiFormat | BirrpAsciiFormat reads and stores MT data in the ascii format used by the birrp processing software |
CsvFormat | This class reads and writes data from Comma Separated Files CSV as produced by Excel etc. this particular flavour |
LemiTsFormat | Read and write ascii files produced by the LEMI instruments |
MtuFilter | Store the filter coefficients for one component of Phoenix mtu data |
MtuFormat | Read and write phoenix mtu binary files |
TimeSeries | This class is the base class for all classes dealing with MT time series |
TimeSeriesData | TimeSeriesData stores a pointer to the different components of magnetotelluric data and provides functions to read and write it to files |
AdaptiveFilter | A generic base class for all types of adaptive filters |
AMRLSCanceller | An implementation of the Recursive Least Squares filter with adptive memory as described in Hakin, p. 663 |
ApplyFilter | Apply an adaptive filter to a time-series |
IterDecon | The iterative deconvolution algorithm, mainly used for receiver function computation |
LMSCanceller | Implements a LMS adaptive filter |
LSSOFilter | Base class for least squares filter with a single output value |
RLSCanceller | Implements a recursive least-squares adaptive filter, as described in Haykin, p. 443 |
WienerFilter | This class is currently broken !!!!! |
WienerInterpolator | |
AnisoSurfaceWaveModel | A class to store information about anisotropic surface wave models |
AnisoSurfaceWaveObjective | This class calculates the misfit for anisotropic surface wave dispersion data |
AnisoSurfaceWaveSynthetic | Calculate synthetic anisotropic surface wave data |
CalcRecConf | |
CalcSpectralElement | This class calculates one spectral element of the receiver function from the two input spectral elements |
FkModel | A model for forward calculations with a wavenumber integration code, currently not in use and might be removed in a later version |
MoveoutCorrection | |
MultiAnisoSurfaceWaveObjective | Minimize the misfit for several surface wave dispersion curves simultaneously |
MultiRecCalc | This class implements the multi-site receiver function calculation in the frequency domain as suggested by Gurrolla 1995 |
ParkSurfaceWaveData | |
RecCalc | This class is used to calculate receiver functions from seismic data |
RecInvConf | |
ResPkModel | This class stores and writes model for the respktn 1D seismic code that we use for receiver function calculations |
RFVelCalc | This class implements the method to calculate absolute S-Wave velocities from Receiver function data as described by Sevnningsen and Jacobsen, GJI 2007 |
Sdisp96Model | This class can write files specific for the synthetic surface wave codes that are part of the computer programs in seismology |
SeismicDataComp | |
SeismicModel | The class SeismicModel is the base class for some of the model format for seismic codes |
SeismicStationList | Manages a collection of seismic traces, mainly provides functionality to read in data specified in a file with names |
CalcDensity | Calculate density from a given S-velocity, the formula is taken from Owen et al. JGR 89,7783-7795 and modified for vs |
CalcAngle1 | |
Pow10 | |
SurfaceWaveData | A class to read, write and store fundamental mode surface wave dispersion data |
SurfaceWaveModel | A class to store 1D model for calculation of synthetic surface wave data |
SurfaceWaveObjective | This class calculates the misfit between observed surface wave dispersion data and the data calculated from a seismic model |
SurfaceWaveSynthetic | Calculate synthetic fundamental mode Rayleigh phase velocity data from an isotropic 1D model |
SWAnisoRoughness | Calculate the roughness for anisotropic SW models |
SimpleLp | A simple low pass |
TimeSeriesComponent | TimeSeriesComponent is the base storage class for all types of time series data |
TsSpectrum | The class CTsSpectrum is used to calculate spectra from (real) time series data |
Hamming | This functor returns the weighting factor for the Hamming window, given the relative position relpos [0..1] in the time series |
Hanning | This functor returns the weighting factor for the Hanning window, given the relative position (0..1) in the time series |
Boxcar | A functor for the simple Boxcar function |
Steep | This functor rises steeply at the edges and then has a wide range where it is unity |
CosSq | The cosine squared windows of fixed width |
TruncCosSq | A variable width cosine squared window that is zero outside |
AnnealingGA | AnnealingGA implements a genetic algorithm with an annealing style objective function |
BinaryPopulation | A population that is encoded as a simple binary string |
BinaryTournamentSelect | Implements binary tournament selection for genetic algorithms |
BinaryTranscribe | BinaryTranscibe implements transcription for standard binary populations |
GAConf | |
CopyFromPointer | Copy the objective function within the shared pointer |
GenObjective | Generate a new copy of the Objective function vector |
GeneralGA | General genetic algorithm class |
GeneralObjective | The basic object for any objective function, mainly an interface class and some storage |
GeneralPopulation | The base class for the population of a genetic algorithm, implements storage and access functions |
GeneralPropagation | The base class for genetic algorithm propagation methods |
GeneralRNG | The base class for all random number generators, defines the basic interface |
GeneralSelect | GeneralSelect is the abstract base class for any selection mechanism in genetic algorithms |
GeneralTranscribe | General Transcribe base class for genetic algorithm parameter transcription |
GrayTranscribe | This class implements the Gray code representation of a binary string and the corresponding transcription |
dominates | Determines whether one vector of misfit values is partially less than the other |
ParetoGA | Implements a genetic algorithm based on the concept of pareto-optimality, best suited for multi-objective problems |
PlottableObjective | This only adds a few plotting functions to GeneralObjective to define a common interface |
SimpleSelect | This is a relatively simple selection scheme for the genetic algorithms |
StandardPropagation | This is the standard propagation class that generates a new population from the old one |
TestObjective | |
TestObjective2 | |
UniformRNG | Generate uniformly distributed random numbers, this is basically a wrapper for the boost random number generators, that is a little easier to use |
UniquePop | This class stores a single unique copy of each population member that is added to it |
FatalException | The basic exception class for all errors that arise in gplib |
BipolarActivationFunction | The bipolar activation function is a common function in NN applications |
GeneralActivationFunction | The base class for all activation functions in neural network |
GeneralLinearCombiner | A linear combiner as a component of a neural network |
GeneralNeuron | The base class for all neurons in a neural network |
IdentityActivationFunction | This activation function simply outputs its input |
InputNeuron | |
NeuralNetwork | |
SigmoidalNeuron | SigmoidalNeuron implements the main functionality of neurons in a neural network |
ArraySampleGenerator | Sequentially returns the elements of an array |
Bootstrap | Implementation of the Bootstrap error estimation method |
Jacknife | Implements the Jacknifing method of error estimation |
MTSampleGenerator | Generate random elements of a calculated quantity for MT impedance data |
StatErrEst | This class is used as a base for stochastic error estimation |
AbsVelRecObjective | This objective function calculates the weighted misfit for a receiver function and the corresponding absolute velocity transformation |
Aniso1DMTObjective | |
C1DMTObjective | C1DMTObjective is the base class for MT misfit calculations from 1D models, it provides common functionality to calculate the misfit of various MT parameters |
C1DRecObjective | Calculate the misfit between observed receiver function for a given 1D model by calculating a synthetic receiver function from that model |
CombinedRoughness | CombinedRoughness calculates the roughness of a joint MT- receiver functions model without consideration for different parameter ranges |
Iso1DMTObjective | This class implements the forward calculation for a 1D isotropic MT model |
IsoJointConf | |
MTAnisoRoughness | Caclulate the roughness for anisotropic MT models |
MTInvConf | |
MTRecObjective | |
MTRoughness | Calculate the roughness for the MT part of a joint MT-seismic model as used by 1dinvga |
Multi1DRecObjective | This class is used to model several receiver functions simultaneously |
PTensor1DMTObjective | This is a special objective function to fit phase tensor MT data |
SeismicModelDiff | SeismicModelDiff calculates the roughness of a joint MT- receiver functions model compared to a seismic model |
SurfInvConf | |
AnisoJointConf | |
AnisoGAJointConf | |
CCalcRecConf | |
ModelAnalysis | The class ModelAnalysis is used to calculate resolution matrix, nullspace and other parameters for model analyis |
SurfInvGaConf | |