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                """  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                Calculations of concordance between annotations.  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    3
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                """  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    4
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                import abc  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    5
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                import math  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                from collections import defaultdict  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                from typing import Collection, Sequence  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                import numpy as np  | 
            
                            
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                from mandos.analysis import AnalysisUtils as Au  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                from mandos.analysis import SimilarityDf  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                from mandos.model.hits import AbstractHit  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                # note that most of these math functions are much faster than their numpy counterparts  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                # if we're not broadcasting, it's almost always better to use them  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                # some are more accurate, too  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                # e.g. we're using fsum rather than sum  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                class MatrixCalculator(metaclass=abc.ABCMeta):  | 
            
                            
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                    def calc(self, hits: Sequence[AbstractHit]) -> SimilarityDf:  | 
            
                            
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                        raise NotImplemented()  | 
            
                            
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                class JPrimeMatrixCalculator(MatrixCalculator):  | 
            
                            
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                    def calc(self, hits: Sequence[AbstractHit]) -> SimilarityDf:  | 
            
            
                                                                        
                            
            
                                    
            
            
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                        inchikey_to_hits = Au.hit_multidict(hits, "origin_inchikey")  | 
            
            
                                                                        
                            
            
                                    
            
            
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                        data = defaultdict(dict)  | 
            
            
                                                                        
                            
            
                                    
            
            
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                        for (c1, hits1), (c2, hits2) in zip(inchikey_to_hits.items(), inchikey_to_hits.items()):  | 
            
                            
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                            data[c1][c2] = self._j_prime(hits1, hits2)  | 
            
            
                                                                        
                            
            
                                    
            
            
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                        return SimilarityDf.from_dict(data)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def _j_prime(self, hits1: Collection[AbstractHit], hits2: Collection[AbstractHit]) -> float:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        sources = {h.data_source for h in hits1}.intersection({h.data_source for h in hits2}) | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        if len(sources) == 0:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            return np.nan  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        values = [  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            self._jx(  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                [h for h in hits1 if h.data_source == source],  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                                [h for h in hits1 if h.data_source == source],  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            )  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                            for source in sources  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        ]  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        return float(math.fsum(values) / len(values))  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def _jx(self, hits1: Collection[AbstractHit], hits2: Collection[AbstractHit]) -> float:  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        pair_to_weights = Au.weights_of_pairs(hits1, hits2)  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        values = [self._wedge(ca, cb) / self._vee(ca, cb) for ca, cb in pair_to_weights.values()]  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                        return float(math.fsum(values) / len(values))  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def _wedge(self, ca: float, cb: float) -> float:  | 
            
                            
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                        return math.sqrt(Au.elle(ca) * Au.elle(cb))  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    def _vee(self, ca: float, cb: float) -> float:  | 
            
                            
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                        return Au.elle(ca) + Au.elle(cb) - math.sqrt(Au.elle(ca) * Au.elle(cb))  | 
            
            
                                                                                                            
                            
            
                                    
            
            
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                    59
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                __all__ = ["MatrixCalculator", "JPrimeMatrixCalculator"]  | 
            
            
                                                        
            
                                    
            
            
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