# This file was automatically generated by SWIG (http://www.swig.org).
# Version 1.3.36
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# Don't modify this file, modify the SWIG interface instead.

Modules
		AUREA.learner._tst new

Classes
		TST __builtin__.object DoubleVector IntVector tst_PySwigIterator   class DoubleVector(__builtin__.object)       Methods defined here: __del__ lambda self __delitem__(*args) __delslice__(*args) __getitem__(*args) __getslice__(*args) __init__(self, *args) __iter__(self) __len__(*args) __nonzero__(*args) __repr__ = _swig_repr(self) __setitem__(*args) __setslice__(*args) append(*args) assign(*args) back(*args) begin(*args) capacity(*args) clear(*args) empty(*args) end(*args) erase(*args) front(*args) get_allocator(*args) insert(*args) iterator(*args) pop(*args) pop_back(*args) push_back(*args) rbegin(*args) rend(*args) reserve(*args) resize(*args) size(*args) swap(*args) Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined) thisown The membership flag Data and other attributes defined here: __swig_destroy__ = <built-in function delete_DoubleVector>   class IntVector(__builtin__.object)       Methods defined here: __del__ lambda self __delitem__(*args) __delslice__(*args) __getitem__(*args) __getslice__(*args) __init__(self, *args) __iter__(self) __len__(*args) __nonzero__(*args) __repr__ = _swig_repr(self) __setitem__(*args) __setslice__(*args) append(*args) assign(*args) back(*args) begin(*args) capacity(*args) clear(*args) empty(*args) end(*args) erase(*args) front(*args) get_allocator(*args) insert(*args) iterator(*args) pop(*args) pop_back(*args) push_back(*args) rbegin(*args) rend(*args) reserve(*args) resize(*args) size(*args) swap(*args) Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined) thisown The membership flag Data and other attributes defined here: __swig_destroy__ = <built-in function delete_IntVector>   class TST     Top Scoring Triplets class.   This class runs the top scoring triplets algorithm described in The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA I mutations by Lin et al in BMC Bioinformatics 2009, 10:256 http://www.biomedcentral.com/1471-2105/10/256   This code uses slightly modified code from  https://jshare.johnshopkins.edu/dnaiman1/public_html/rxa/ which is  the code described in the above mentioned paper.     Methods defined here: __init__(self, data, numGenes, classSizes, filter) Initializes the object.  data is an IntVector containing the microarray data and should be generated by the dataPackager class. classSizes is an intvector  containing the size of the 2 classes, class 1 and class 2 respectively. addUnclassified(self, unclassifiedVector) Stores unclassified vector as self.unclassified_data_vector classify(self) Returns a list of classifications based on the maxscores. 0 means the first class, 1 means the second class. compute_ptable(self) Stores the counts for the various orderings(in the case of multiple orderings) in their respective class generates self.ptable which is ordered: [     ordering1[                 class1 [p(1,2,3), p(1,3,2), p(2,1,3), p(2,3,1), p(3,1,2), p(3,2,1)],                 class2 [p(1,2,3), p(1,3,2), p(2,1,3), p(2,3,1), p(3,1,2), p(3,2,1)]     ]     ordering2 [         ....     ],     ... ] convertToDataIndex(self, sample_index, gene_index) This translates the sample_index and gene index into a self.data index crossValidate(self, k=10) Performs k-fold cross validation (k is an integer [2,samplesize]) Returns the Matthews correlation coefficient.(-1.0, 1.0) distance(self, v1, v2) Returns the square of the euclidian distance between v1 and v2 getMaxScores(self) Returns a list of the top scoring triplets indices ptable_entry(self, s1, s2, s3) Builds a list that contains the index of matching orderings. If there is an equality then the list could be longer than 1. train(self) Runs the c code tst algorithm. fills the self.maxScore1,2,3 with the triplets. May have multiple so self.maxScore1[0] is the first element of the  first triplet, self.maxScore1[1] is the first element of the second triplet, etc.   class tst_PySwigIterator(__builtin__.object)       Methods defined here: __add__(*args) __del__ lambda self __eq__(*args) __iadd__(*args) __init__(self, *args, **kwargs) __isub__(*args) __iter__(self) __ne__(*args) __repr__ = _swig_repr(self) __sub__(*args) advance(*args) copy(*args) decr(*args) distance(*args) equal(*args) incr(*args) next(*args) previous(*args) value(*args) Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined) thisown The membership flag Data and other attributes defined here: __swig_destroy__ = <built-in function delete_tst_PySwigIterator>

Functions
		DoubleVector_swigregister(...) IntVector_swigregister(...) crossValidate(...) runTST(...) tst_PySwigIterator_swigregister(...)