OOC-class(ontoTools)
OOC-class()所属R语言包:ontoTools
Class "OOC" object-ontology complex
类“正交码”对象的本体复杂
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Object that binds ontology (structured vocabulary) with
对象,结合本体(结构化的词汇)
类的对象----------Objects from the Class----------
Objects can be created by calls of the form new("OOC", ...).
创建对象可以通过检测的形式new("OOC", ...)。
插槽----------Slots----------
ontology: Object of class "ontology" instance of ontoTools:ntology
ontology类"ontology"ontoTools的实例对象::本体
OOmap: Object of class "namedSparse" SparseM::matrix.csr bound with dimnames facilities
OOmap:对象类"namedSparse"的SparseM :: matrix.csr约束dimnames设施
方法----------Methods----------
coverageMat signature(x = "OOC"): return a namedSparse incidence matrix with r,c element indicating whether term c covers
coverageMatsignature(x = "OOC"):返回与R namedSparse发病率矩阵,C元素说明是否术语C涉及
ontology signature(x = "OOC"): accessor
本体signature(x = "OOC"):存取
OOmap signature(x = "OOC"): accessor
OOmapsignature(x = "OOC"):存取
show signature(object = "OOC"): concise printer
显示signature(object = "OOC"):简洁打印机“
作者(S)----------Author(s)----------
VJ Carey <stvjc@channing.harvard.edu>
举例----------Examples----------
data(litOnto)
g1 <- new("rootedDAG", DAG=litOnto, root="A")
o1 <- new("ontology", name="demo", version="0.1",
rDAG=g1)
kvlist <- list(W="E", X="K", Y="B", Z=c("D","G"))
litMap <- otkvList2namedSparse( names(kvlist), LETTERS[1:12], kvlist )
print(litMap)
ooc1 <- makeOOC( o1, litMap )
show(ooc1)
print(coverageMat(ooc1))
# note the following will be slow with large OOCs[注意以下几点将是缓慢的大光正交码]
print(conceptProbs(ooc1))
# for larger OOCs it is useful to precompute the accessibility[较大的光正交码,它是非常有用的预先计算的辅助]
# matrix of the ontology and the map from objects to terms -- these[矩阵的本体和从对象方面的图 - 这些]
# can be supplied as additional arguments to conceptProbs[可提供额外的参数作为conceptProbs]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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