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annotate service/mqtt_to_rdf/inference.py @ 1588:0757fafbfdab

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WIP inferencer - partial var and function support
author drewp@bigasterisk.com
date Thu, 02 Sep 2021 01:58:31 -0700
parents 9a3a18c494f9
children 5c1055be3c36
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1 """
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2 copied from reasoning 2021-08-29. probably same api. should
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3 be able to lib/ this out
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4 """
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5 import itertools
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6 import logging
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7 from dataclasses import dataclass
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8 from decimal import Decimal
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9 from typing import Dict, Iterator, List, Set, Tuple, cast
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10 from urllib.request import OpenerDirector
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11
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12 from prometheus_client import Summary
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13 from rdflib import BNode, Graph, Literal, Namespace
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14 from rdflib.collection import Collection
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15 from rdflib.graph import ConjunctiveGraph
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16 from rdflib.term import Node, Variable
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17
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18 log = logging.getLogger('infer')
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19
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20 Triple = Tuple[Node, Node, Node]
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21 Rule = Tuple[Graph, Node, Graph]
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22
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23 READ_RULES_CALLS = Summary('read_rules_calls', 'calls')
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24
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25 ROOM = Namespace("http://projects.bigasterisk.com/room/")
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26 LOG = Namespace('http://www.w3.org/2000/10/swap/log#')
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27 MATH = Namespace('http://www.w3.org/2000/10/swap/math#')
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28
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29
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30 @dataclass
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31 class _RuleMatch:
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32 """one way that a rule can match the working set"""
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33 vars: Dict[Variable, Node]
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34
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35
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36 class Inference:
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37
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38 def __init__(self) -> None:
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39 self.rules = ConjunctiveGraph()
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40
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41 def setRules(self, g: ConjunctiveGraph):
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42 self.rules = g
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43
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44 def infer(self, graph: Graph):
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45 """
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46 returns new graph of inferred statements.
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47 """
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48 log.info(f'Begin inference of graph len={len(graph)} with rules len={len(self.rules)}:')
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49
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50 workingSet = ConjunctiveGraph()
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51 if isinstance(graph, ConjunctiveGraph):
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52 workingSet.addN(graph.quads())
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53 else:
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54 for triple in graph:
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55 workingSet.add(triple)
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56
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57 implied = ConjunctiveGraph()
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58
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59 bailout_iterations = 100
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60 delta = 1
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61 while delta > 0 and bailout_iterations > 0:
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62 bailout_iterations -= 1
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63 delta = -len(implied)
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64 self._iterateAllRules(workingSet, implied)
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65 delta += len(implied)
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66 log.info(f' this inference round added {delta} more implied stmts')
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67 log.info(f'{len(implied)} stmts implied:')
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68 for st in implied:
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69 log.info(f' {st}')
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70 return implied
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71
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72 def _iterateAllRules(self, workingSet, implied):
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73 for r in self.rules:
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74 if r[1] == LOG['implies']:
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75 applyRule(r[0], r[2], workingSet, implied)
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76 else:
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77 log.info(f' {r} not a rule?')
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78
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79
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80 def applyRule(lhs: Graph, rhs: Graph, workingSet, implied):
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81 for bindings in findCandidateBindings(lhs, workingSet):
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82 log.debug(f' - rule gave {bindings=}')
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83 for newStmt in withBinding(rhs, bindings):
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84 workingSet.add(newStmt)
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85 implied.add(newStmt)
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86
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87
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88 def findCandidateBindings(lhs: Graph, workingSet: Graph) -> Iterator[Dict[Variable, Node]]:
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89 varsToBind: Set[Variable] = set()
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90 staticRuleStmts = []
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91 for ruleStmt in lhs:
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92 varsInStmt = [v for v in ruleStmt if isinstance(v, Variable)]
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93 varsToBind.update(varsInStmt)
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94 if (not varsInStmt # ok
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95 and not any(isinstance(t, BNode) for t in ruleStmt) # approx
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96 ):
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97 staticRuleStmts.append(ruleStmt)
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98
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99 if someStaticStmtDoesntMatch(staticRuleStmts, workingSet):
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100 log.debug('static shortcircuit')
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101 return
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102
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103 # the total set of terms each variable could possibly match
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104 candidateTermMatches: Dict[Variable, Set[Node]] = findCandidateTermMatches(lhs, workingSet)
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105
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106 orderedVars, orderedValueSets = organize(candidateTermMatches)
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107
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108 log.debug(f' {orderedVars=}')
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109 log.debug(f'{orderedValueSets=}')
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110
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111 for perm in itertools.product(*orderedValueSets):
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112 binding: Dict[Variable, Node] = dict(zip(orderedVars, perm))
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113 log.debug(f'{binding=} but lets look for funcs')
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114 for v, val in inferredFuncBindings(lhs, binding): # loop this until it's done
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115 log.debug(f'ifb tells us {v}={val}')
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116 binding[v] = val
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117 if not verifyBinding(lhs, binding, workingSet): # fix this
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118 log.debug(f'verify culls')
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119 continue
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120 yield binding
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121
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122
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123 def inferredFuncBindings(lhs: Graph, bindingsBefore) -> Iterator[Tuple[Variable, Node]]:
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124 for stmt in lhs:
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125 if stmt[1] not in inferredFuncs:
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126 continue
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127 if not isinstance(stmt[2], Variable):
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128 continue
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129
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130 x = stmt[0]
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131 if isinstance(x, Variable):
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132 x = bindingsBefore[x]
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133 yield stmt[2], inferredFuncObject(x, stmt[1], lhs, bindingsBefore)
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134
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135
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136 def findCandidateTermMatches(lhs: Graph, workingSet: Graph) -> Dict[Variable, Set[Node]]:
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137 candidateTermMatches: Dict[Variable, Set[Node]] = {}
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138
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139 for r in lhs:
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140 for w in workingSet:
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141 bindingsFromStatement: Dict[Variable, Set[Node]] = {}
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142 for rterm, wterm in zip(r, w):
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143 if isinstance(rterm, Variable):
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144 bindingsFromStatement.setdefault(rterm, set()).add(wterm)
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145 elif rterm != wterm:
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146 break
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147 else:
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148 for v, vals in bindingsFromStatement.items():
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149 candidateTermMatches.setdefault(v, set()).update(vals)
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150 return candidateTermMatches
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151
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152
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153 def withBinding(rhs: Graph, bindings: Dict[Variable, Node]) -> Iterator[Triple]:
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154 for stmt in rhs:
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155 stmt = list(stmt)
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156 for i, t in enumerate(stmt):
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157 if isinstance(t, Variable):
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158 try:
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159 stmt[i] = bindings[t]
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160 except KeyError:
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161 # stmt is from another rule that we're not applying right now
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162 break
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163 else:
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164 yield cast(Triple, stmt)
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165
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166
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167 def verifyBinding(lhs: Graph, binding: Dict[Variable, Node], workingSet: Graph) -> bool:
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168 for stmt in withBinding(lhs, binding):
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169 log.debug(f'lhs verify {stmt}')
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170 if stmt[1] in filterFuncs:
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171 if not mathTest(*stmt):
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172 return False
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173 elif stmt not in workingSet and stmt[1] not in inferredFuncs:
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174 log.debug(f' ver culls here')
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175 return False
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176 return True
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177
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178
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179 inferredFuncs = {
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180 ROOM['asFarenheit'],
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181 MATH['sum'],
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182 }
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183 filterFuncs = {
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184 MATH['greaterThan'],
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185 }
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186
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187
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188 def inferredFuncObject(subj, pred, graph, bindings):
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189 if pred == ROOM['asFarenheit']:
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190 return Literal(Decimal(subj.toPython()) * 9 / 5 + 32)
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191 elif pred == MATH['sum']:
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192 operands = Collection(graph, subj)
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193 # shouldn't be redoing this here
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194 operands = [bindings[o] if isinstance(o, Variable) else o for o in operands]
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195 log.debug(f' sum {list(operands)}')
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196 return Literal(sum(op.toPython() for op in operands))
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197
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198 else:
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199 raise NotImplementedError(pred)
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200
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201
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202 def mathTest(subj, pred, obj):
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203 x = subj.toPython()
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204 y = obj.toPython()
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205 if pred == MATH['greaterThan']:
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206 return x > y
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207 else:
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208 raise NotImplementedError(pred)
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209
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210
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211 def organize(candidateTermMatches: Dict[Variable, Set[Node]]) -> Tuple[List[Variable], List[List[Node]]]:
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212 items = list(candidateTermMatches.items())
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213 items.sort()
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214 orderedVars: List[Variable] = []
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215 orderedValueSets: List[List[Node]] = []
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216 for v, vals in items:
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217 orderedVars.append(v)
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218 orderedValues: List[Node] = list(vals)
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219 orderedValues.sort(key=str)
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220 orderedValueSets.append(orderedValues)
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221
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222 return orderedVars, orderedValueSets
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223
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224
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225 def someStaticStmtDoesntMatch(staticRuleStmts, workingSet):
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226 for ruleStmt in staticRuleStmts:
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227 if ruleStmt not in workingSet:
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228 return True
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229 return False