1 %define ADD_CNINFERENCE_DOC(classname...) 2 %feature("docstring") gum::credal::classname::dynamicExpMax 3 " 4 Get the upper dynamic expectation of a given variable prefix. 5 6 Parameters 7 ---------- 8 varName : str 9 the variable name prefix which upper expectation we want. 10 11 Returns 12 ------- 13 double 14 a constant reference to the variable upper expectation over all time steps. 15 " 16 17 %feature("docstring") gum::credal::classname::dynamicExpMin 18 " 19 Get the lower dynamic expectation of a given variable prefix. 20 21 Parameters 22 ---------- 23 varName : str 24 the variable name prefix which lower expectation we want. 25 26 Returns 27 ------- 28 double 29 a constant reference to the variable lower expectation over all time steps. 30 " 31 32 %feature("docstring") gum::credal::classname::eraseAllEvidence 33 " 34 Erase all inference related data to perform another one. 35 36 You need to insert evidence again if needed but modalities are kept. You can insert new ones by using the appropriate method which will delete the old ones. 37 " 38 39 %feature("docstring") gum::credal::classname::insertEvidenceFile 40 " 41 Insert evidence from file. 42 43 Parameters 44 ---------- 45 path : str 46 the path to the evidence file. 47 " 48 49 %feature("docstring") gum::credal::classname::insertModalsFile 50 " 51 Insert variables modalities from file to compute expectations. 52 53 Parameters 54 ---------- 55 path : str 56 The path to the modalities file. 57 " 58 59 %feature("docstring") gum::credal::classname::makeInference 60 " 61 Starts the inference. 62 " 63 64 %feature("docstring") gum::credal::classname::marginalMax 65 " 66 Get the upper marginals of a given node id. 67 68 Parameters 69 ---------- 70 id : int 71 the node id which upper marginals we want. 72 varName : str 73 the variable name which upper marginals we want. 74 75 Returns 76 ------- 77 list 78 a constant reference to this node upper marginals. 79 80 Raises 81 ------ 82 pyAgrum.IndexError 83 If the node does not belong to the Credal network 84 " 85 86 %feature("docstring") gum::credal::classname::marginalMin 87 " 88 Get the lower marginals of a given node id. 89 90 Parameters 91 ---------- 92 id : int 93 the node id which lower marginals we want. 94 varName : str 95 the variable name which lower marginals we want. 96 97 Returns 98 ------- 99 list 100 a constant reference to this node lower marginals. 101 102 Raises 103 ------ 104 pyAgrum.IndexError 105 If the node does not belong to the Credal network 106 " 107 108 %feature("docstring") gum::credal::classname::saveInference 109 " 110 Saves marginals. 111 112 Parameters 113 ---------- 114 path : str 115 The path to the file to save marginals. 116 " 117 118 %feature("docstring") gum::credal::classname::setRepetitiveInd 119 " 120 Parameters 121 ---------- 122 flag : bool 123 True if repetitive independence is to be used, false otherwise. Only usefull with dynamic networks. 124 " 125 126 %feature("docstring") gum::credal::classname::inferenceType 127 " 128 Returns 129 ------- 130 int 131 the inference type 132 " 133 %enddef 134 135 ADD_CNINFERENCE_DOC(CNMonteCarloSampling<double>) 136 ADD_CNINFERENCE_DOC(CNLoopyPropagation<double>) 137