21#ifndef mia_core_ica_template_hh
22#define mia_core_ica_template_hh
28#ifndef EXPORT_TDataSeriesICA
30# define EXPORT_TDataSeriesICA __declspec(dllimport)
33# define EXPORT_TDataSeriesICA __attribute__((visibility("default")))
35# define EXPORT_TDataSeriesICA
69 typedef typename Data::Pointer
PData;
81 TDataSeriesICA(
const CIndepCompAnalysisFactory& icatool,
const std::vector<Data>& initializer,
bool strip_mean);
89 bool run(
size_t ncomponents,
bool strip_mean,
bool ica_normalize,
90 std::vector<std::vector<float>> guess = std::vector<std::vector<float>>());
172 PIndepCompAnalysis m_analysis;
173 typedef typename Data::dimsize_type dimsize_type;
Templated representation of a ICA series analyis.
Data get_mix(size_t idx) const
CSlopeColumns get_mixing_curves() const
const Data & get_mean_image() const
void set_approach(CIndepCompAnalysis::EApproach approach)
void set_mixing_series(size_t index, const std::vector< float > &series)
void set_max_iterations(int n)
Data get_partial_mix(size_t idx, const IndexSet &comps) const
CIndepCompAnalysis::IndexSet IndexSet
TDataSeriesICA(const CIndepCompAnalysisFactory &icatool, const std::vector< Data > &initializer, bool strip_mean)
ICA initialization.
PData get_feature_image(size_t idx) const
PData get_delta_feature(const IndexSet &plus, const IndexSet &minus) const
Data get_incomplete_mix(size_t idx, const IndexSet &skip) const
std::vector< float > get_mixing_curve(unsigned idx) const
void normalize_Mix()
Normalizes the Mixing Matrix columns to have zero mean.
bool run(size_t ncomponents, bool strip_mean, bool ica_normalize, std::vector< std::vector< float > > guess=std::vector< std::vector< float > >())
#define NS_MIA_BEGIN
conveniance define to start the mia namespace
#define NS_MIA_END
conveniance define to end the mia namespace
std::vector< std::vector< float > > CSlopeColumns
class to store the ICA weight matrix
#define EXPORT_TDataSeriesICA