#include <mia/core/ica.hh>
Definition at line 37 of file core/ica.hh.
◆ IndexSet
defines a set of indices used for mixing
Definition at line 53 of file core/ica.hh.
◆ Pointer
◆ EApproach
Separation approach to be used.
| Enumerator |
|---|
| appr_defl | Deflation approach - each component is extimated separately
|
| appr_symm | Symmetric approach thet estimates all components at the same time
|
| appr_unknown | |
Definition at line 44 of file core/ica.hh.
◆ ~CIndepCompAnalysis()
| virtual mia::CIndepCompAnalysis::~CIndepCompAnalysis |
( |
| ) |
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virtual |
◆ get_delta_feature()
| virtual std::vector< float > mia::CIndepCompAnalysis::get_delta_feature |
( |
const IndexSet & | plus, |
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const IndexSet & | minus ) const |
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pure virtual |
Evaluate a mix of the feature signals by adding and subtractig individual features.
- Parameters
-
| plus | features o be added |
| minus | features to be subtracted |
- Returns
- the feature mix
References get_delta_feature().
Referenced by get_delta_feature().
◆ get_feature_row()
| virtual std::vector< float > mia::CIndepCompAnalysis::get_feature_row |
( |
unsigned int | row | ) |
const |
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pure virtual |
◆ get_incomplete_mix()
| virtual std::vector< float > mia::CIndepCompAnalysis::get_incomplete_mix |
( |
unsigned int | idx, |
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const IndexSet & | skip ) const |
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pure virtual |
Evaluate an incomplete mixed signal. Here the features are given that are not to be used.
- See also
- get_partial_mix
- Parameters
-
| idx | series index |
| skip | a set of feature indices that will be skipped when evaluating the mix |
- Returns
- the mixed signal
References get_incomplete_mix().
Referenced by get_incomplete_mix().
◆ get_mix()
| virtual std::vector< float > mia::CIndepCompAnalysis::get_mix |
( |
unsigned int | idx | ) |
const |
|
pure virtual |
- Returns
- the complete mixed signal at series index idx
References get_mix().
Referenced by get_mix().
◆ get_mix_series()
| virtual std::vector< float > mia::CIndepCompAnalysis::get_mix_series |
( |
unsigned int | row | ) |
const |
|
pure virtual |
◆ get_mixing_curves()
| virtual CSlopeColumns mia::CIndepCompAnalysis::get_mixing_curves |
( |
| ) |
const |
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pure virtual |
◆ get_ncomponents()
| virtual unsigned int mia::CIndepCompAnalysis::get_ncomponents |
( |
| ) |
const |
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pure virtual |
◆ get_partial_mix()
| virtual std::vector< float > mia::CIndepCompAnalysis::get_partial_mix |
( |
unsigned int | idx, |
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const IndexSet & | use ) const |
|
pure virtual |
Evaluate an incomplete mixed signal. Here the features are given that are used to create the mix.
- See also
- get_incomplete_mix
- Parameters
-
| idx | series index |
| use | the set of feature indices that will be used to evaluate the mix |
- Returns
- an incolmplete mixed signal.
References get_partial_mix().
Referenced by get_partial_mix().
◆ initialize()
| virtual void mia::CIndepCompAnalysis::initialize |
( |
unsigned int | series_length, |
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unsigned int | slice_size ) |
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pure virtual |
◆ normalize_ICs()
| virtual void mia::CIndepCompAnalysis::normalize_ICs |
( |
| ) |
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pure virtual |
Normalize the ICs in the following manner: Scale and shift the range of the ICs to [-1, 1] Scale the mixing curved to compensate for the required scaling move the means of the time points to compensate for the shifting.
References normalize_ICs().
Referenced by normalize_ICs().
◆ normalize_Mix()
| virtual std::vector< float > mia::CIndepCompAnalysis::normalize_Mix |
( |
| ) |
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pure virtual |
Normalize the mixing curves to have a zero mean. As a result a mean image is created that containes the sum of the ICs weighted by the required mean shift.
References normalize_Mix().
Referenced by normalize_Mix().
◆ run()
| virtual bool mia::CIndepCompAnalysis::run |
( |
unsigned int | nica, |
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|
std::vector< std::vector< float > > | guess ) |
|
pure virtual |
Run the independed component analysis using the given numbers of components
- Parameters
-
| nica | number of indentepended components |
| guess | initial guess for the ICA, pass an empty vector of you don't want to use this feature |
References run().
Referenced by run().
◆ set_approach()
| virtual void mia::CIndepCompAnalysis::set_approach |
( |
EApproach | approach | ) |
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pure virtual |
Set the ICA approach to either FICA_APPROACH_DEFL(default) or FICA_APPROACH_SYMM.
- Parameters
-
References set_approach().
Referenced by set_approach().
◆ set_deterministic_seed()
| virtual void mia::CIndepCompAnalysis::set_deterministic_seed |
( |
int | seed | ) |
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pure virtual |
◆ set_max_iterations()
| virtual void mia::CIndepCompAnalysis::set_max_iterations |
( |
int | n | ) |
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pure virtual |
◆ set_mixing_series()
| virtual void mia::CIndepCompAnalysis::set_mixing_series |
( |
unsigned int | index, |
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const std::vector< float > & | series ) |
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pure virtual |
◆ set_row()
template<class Iterator>
| void mia::CIndepCompAnalysis::set_row |
( |
unsigned | row, |
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Iterator | begin, |
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Iterator | end ) |
Set on row of input data
- Template Parameters
-
| Iterator | input data iterator, must follow the model of a forward iterator |
- Parameters
-
| row | index of the input slice |
| begin | start iterator of input data |
| end | end iterator of input data |
References set_row().
Referenced by set_row().
The documentation for this class was generated from the following file: