theplu | The Department of Theoretical Physics namespace as we define it |
yat | Yat project namespace |
classifier | Classifier related classes |
BootstrapSampler | Class creating trainingset and validationset using bootstrapping |
ConsensusInputRanker | Robust algorithm to rank rows in a data matrix versus a target vector |
CrossValidationSampler | Class splitting a set into training set and validation set in a crossvalidation manner |
DataLookup1D | Class for general vector view |
DataLookupWeighted1D | Class for general weighted vector view |
EnsembleBuilder | Class for ensembles of supervised classifiers |
FeatureSelector | Interface class for FeatureSelection |
FeatureSelectorIR | FeatureSelector using an InputRanker |
FeatureSelectorRandom | Class for selection features by random |
GaussianKernelFunction | Class for Gaussian kernel calculations |
IGP | Class for In Group Proportions (IGP) |
IRRank | Functor retrieving minus rank from a InputRanker to build a ConsensusInputRanker |
IRRetrieve | Interface class for retrieving information from a InputRanker to build a ConsensusInputRanker |
InputRanker | Class for ranking rows in a matrix, using a Score and a target vector |
Kernel | Interface Class for Kernels |
KernelFunction | Interface class calculating elements in Kernel |
KernelLookup | Lookup into Kernel |
Kernel_MEV | Memory Efficient Kernel |
Kernel_SEV | Speed Efficient Kernel |
KNN | Nearest Neighbor Classifier |
NeighborWeightingConcept | Concept check for a Neighbor Weighting Method |
KNN_ReciprocalDistance | A model of the concept Neighbor Weighting Method to be used with KNN to weight the votes of the k nearest neighbors of a sample |
KNN_ReciprocalRank | A model of the concept Neighbor Weighting Method to be used with KNN to weight the votes of the k nearest neighbors of a sample |
KNN_Uniform | A model of the concept Neighbor Weighting Method to be used with KNN to weight the votes of the k nearest neighbors of a sample |
MatrixLookup | General view into utility::Matrix |
MatrixLookupWeighted | General view into utility::MatrixWeighted |
NBC | Naive Bayesian Classifier |
NCC | Nearest Centroid Classifier |
PolynomialKernelFunction | Class for polynomial kernel calculations |
SVM | Support Vector Machine |
SvmMultiClass | Support Vector Machine for more than two classes |
SVindex | |
Sampler | Interface class for dividing samples into training and validation |
SubsetGenerator | Class splitting Data into training and validation set |
SupervisedClassifier | Interface class for supervised classifiers that use data in a matrix format |
Target | Class for containing sample labels |
normalizer | Normalization of data |
detail | |
Centralizer | Centralize a range |
ColumnNormalizer | Using a functor T to normalize each column |
Gauss | Gaussian Normalizer |
qQuantileNormalizer | Perform Q-quantile normalization |
QuantileNormalizer | Perform quantile normalization |
RowNormalizer | Using a functor T to normalize each column |
Spearman | Replace elements with normalized rank |
Zscore | Zero mean and unity variance |
omic | Classes and functions related to genomics and proteomics |
BamFile | |
InBamFile | |
OutBamFile | |
BamHeader | |
BamRead | Class holding a bam query |
BamLessPos | |
BamLessEnd | |
BamReadIterator | Class to iterate through a InBamFile |
BamWriter | |
BamWriteIterator | Output iterator for bam file |
Codon | |
AminoAcidEqual | Functor comparing if two Codons translate to the same amino acid |
DNA | |
GenomicPosition | |
GFF | |
GFF2 | |
GFF3 | |
random | Random number distributions |
RNG | Random Number Generator |
RNG_state | Class holding state of a random generator |
Discrete | Discrete random number distributions |
Binomial | Binomial distribution |
DiscreteGeneral | General |
DiscreteUniform | Discrete uniform distribution |
Poisson | Poisson Distribution |
Continuous | Continuous random number distributions |
ContinuousUniform | Uniform distribution |
ContinuousGeneral | Generates numbers from a histogram in a continuous manner |
Exponential | Generator of random numbers from an exponential distribution |
Gaussian | Gaussian distribution |
regression | Statistical modeling of data |
AkimaInterpolation | Non-rounded Akima spline with natural boundary conditions |
AkimaPeriodicInterpolation | AkimaPeriodic interpolation |
CSplineInterpolation | Cubic spline with natural boundary conditions |
CSplinePeriodicInterpolation | Cubic spline with periodic boundary conditions |
GSLInterpolation | Base class for interfacing GSL interpolation |
Kernel | Interface Class for calculating the weights in a more general way than classical rectangular windows |
KernelBox | Class for KernelBox a.k.a. rectangular window |
KernelTriCube | Class for TriCubal kernel |
Linear | Linear regression |
LinearInterpolation | Linear interpolation |
LinearWeighted | Linear regression |
Local | Class for Locally weighted regression |
MultiDimensional | MultiDimesional fitting |
MultiDimensionalWeighted | MultiDimesional fitting |
Naive | Naive Regression |
NaiveWeighted | Naive fitting |
OneDimensional | Interface Class for One Dimensional fitting |
OneDimensionalWeighted | Interface Class for One Dimensional fitting in a weighted fashion |
Polynomial | Polynomial regression |
PolynomialInterpolation | Polynomial interpolation |
PolynomialWeighted | Polynomial Regression in weighted fashion |
TukeyBiweight | |
statistics | Statistical methods, classes, and functions |
AUC | Area Under ROC Curve |
averager_base | Base class for averager classes |
averager_base2 | Base class for averagers calculating mean and variance |
averager_base3 | |
averager_base4 | |
Average | Functor to take average of a range |
Averager | Class to calculate simple (first and second moments) averages |
Averager1 | Class to calculate mean |
Averager3 | Class to calculate 1st, 2nd, and 3rd central moments |
Averager4 | Class to calculate 1st, 2nd, 3rd, and 4th central moments |
AveragerPair | Class for taking care of mean and covariance of two variables |
AveragerWeighted | Class to calulate averages with weights |
AveragerPairWeighted | Class for taking care of mean and covariance of two variables in a weighted manner |
averager_traits | |
averager_traits< utility::unweighted_iterator_tag > | |
averager_traits< utility::weighted_iterator_tag > | |
averager | |
averager_pair | |
EuclideanDistance | Calculates the Euclidean distance between two points given by elements of ranges |
Fisher | Fisher's exact test |
FoldChange | Score given by the difference by the group means |
Histogram | Histograms provide a convenient way of presenting the distribution of a set of data |
Kendall | Kendall's tau rank coefficient |
KolmogorovSmirnov | Kolmogorov Smirnov Test |
Element | |
Pearson | Class for calculating Pearson correlation |
PearsonCorrelation | Class for calculating Pearson correlation |
PearsonDistance | Calculates the Pearson correlation distance between two points given by elements of ranges |
Percentiler | Functor to calculate percentile of a range |
ROC | Reciever Operating Characteristic |
SAMScore | Class for score used in Significance Analysis of Microarrays (SAM) |
Score | Interface Class for score classes |
Smoother | Estimating a distribution in a smooth fashion |
SNRScore | Class for score based on signal-to-noise ratio (SNRScore) |
Spearman | Spearman rank correlation coefficient |
TukeyBiweightEstimator | Tukey's Biweight Estimator |
tScore | Class for Fisher's t-test |
tTest | Class for Student's t-test |
VectorFunction | Interface Class for vector functors |
Max | Larget element |
Median | Median element |
Mean | Mean element |
Min | Smallest element |
Nth_Element | |
WilcoxonFoldChange | WilcoxonFoldChange |
utility | Miscellaneous functionality |
detail | |
weighted_iterator_traits_detail | |
weighted_iterator_traits_detail< T, typename boost::enable_if< typename boost::is_convertible< T, DataWeight > >::type > | |
unweighted_type_and | |
unweighted_type_and< unweighted_iterator_tag, unweighted_iterator_tag > | |
iter_has_mutable_data | |
iter_has_mutable_weight | |
is_weighted | |
is_unweighted | |
iterator_traits_detail | |
mutable_reference | |
mutable_reference< true > | |
iterator_traits_detail< Iter, typename boost::enable_if< is_weighted< Iter > >::type > | |
VectorPusher | |
VectorPusher< std::string > | |
Aligner | Aligning two sequences |
ColumnStream | |
CommandLine | Class for parsing the command line |
Container2D | Concept check for Container2D |
Mutable_Container2D | Concept check for Mutable Container2D |
TrivialIterator | Concept check for Trivial Iterator |
DataIteratorConcept | Concept check for Data Iterator |
DistanceConcept | Concept check for a Distance |
Container2DIterator | Iterator for a Container2D |
DataIterator | DataIterator |
DataWeight | Holds a pair of data and associated weight |
DataWeightProxy | Proxy class for DataWeight |
Deleter | Functor that deletes an object |
runtime_error | Class used for all runtime error detected within yat library |
cmd_error | Class used for error reported from Commandline or Option |
errno_error | Class that contains information reported via global variable errno |
GSL_error | Class for errors reported from underlying GSL calls |
IO_error | Class to report errors associated with IO operations |
FileUtil | Checking file/directory existence and access permissions |
GetlineIterator | Read from std::istream with std::getline |
Index | Class for storing indices of, e.g., a MatrixLookup |
unweighted_iterator_tag | |
weighted_iterator_tag | |
weighted_iterator_traits | |
weighted_if_any2 | |
weighted_if_any3 | |
iterator_traits | |
KernelPCA | Principal Component Analysis on a Kernel Matrix |
kNNI | KNNimpute |
Matrix | Interface to GSL matrix |
MatrixWeighted | Weighted Matrix |
NNI | Interface class for nearest neighbour imputation (NNI) algorithms |
Option | Container of variables for an option |
OptionArg | Option with argument |
OptionFile | Class for file related options |
OptionInFile | Class for file related options |
OptionOutFile | Class for file related options |
OptionHelp | Class for help option |
OptionSwitch | Class for switch option |
PCA | Principal Component Analysis |
Segment | Class for a Segment or Interval |
SegmentCompare | Functor using compare |
SegmentMap | Map of Segments |
SegmentSet | Set of Segments |
SegmentTree | Base Class for SegmentSet and SegmentMap |
SmartPtr | |
BasicStreamRedirect | Redirect a stream to another stream |
Range | A class for storing a shallow copy of a Range |
abs | |
Dereferencer | Adaptor between pointer and pointee interface |
compose_f_gx_hy | |
compose_f_gxy | |
compose_f_gx | |
Exp | |
Identity | Identity functor that returns its argument |
less_nan | Functor that behaves like std::less with the exception that it treates NaN as a number larger than infinity |
less_nan< DataWeight > | Specialization for DataWeight |
Log | |
pair_value_compare | Functor comparing pairs using second |
PairFirst | Functor that return std::pair.first |
PairSecond | Functor that return std::pair.second |
StrideIterator | Adaptor using a stride on underlying iterator |
SVD | Singular Value Decomposition |
TypeInfo | Wrapper class for storing std::type_info |
Vector | This is the yat interface to GSL vector |
VectorBase | This is the yat interface to GSL vector |
VectorConstView | Read-only view |
VectorMutable | This is the mutable interface to GSL vector |
VectorView | This is the yat interface to gsl_vector_view |
WeightedIterator | WeightedIterator |
WeightIterator | WeightIterator |
WeNNI | Weighted Nearest Neighbour Imputation |
noncopyable | |