UdayLab#114 updated documentation of temporal and transactional database

vanithakattumuri · Apr 19, 2024 · 1996946 · 1996946
1 parent 652f136
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diff --git a/PAMI/AssociationRules/basic/ARWithConfidence.py b/PAMI/AssociationRules/basic/ARWithConfidence.py
@@ -299,18 +299,7 @@ def startMine(self):
         """
         Association rule mining process will start from here
         """
-        self._startTime = _ab._time.time()
-        k = self._readPatterns()
-        a = _Confidence(self._frequentPatterns, k, self._minConf)
-        a.run()
-        self._finalPatterns = a._finalPatterns
-        self._endTime = _ab._time.time()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
-        print("Association rules successfully  generated from frequent patterns ")
+        self.mine()
 
 
 

diff --git a/PAMI/AssociationRules/basic/ARWithLeverage.py b/PAMI/AssociationRules/basic/ARWithLeverage.py
@@ -299,18 +299,7 @@ def startMine(self) -> None:
         """
         Association rule mining process will start from here
         """
-        self._startTime = _ab._time.time()
-        k = self._readPatterns()
-        a = _Leverage(self._frequentPatterns, k, self._minConf)
-        a.run()
-        self._finalPatterns = a._finalPatterns
-        self._endTime = _ab._time.time()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
-        print("Association rules successfully  generated from frequent patterns ")
+        self.mine()
 
     def mine(self) -> None:
         """

diff --git a/PAMI/AssociationRules/basic/ARWithLift.py b/PAMI/AssociationRules/basic/ARWithLift.py
@@ -294,18 +294,7 @@ def startMine(self) -> None:
         """
         Association rule mining process will start from here
         """
-        self._startTime = _ab._time.time()
-        k = self._readPatterns()
-        a = Lift(self._frequentPatterns, k, self._minConf)
-        a.run()
-        self._finalPatterns = a._finalPatterns
-        self._endTime = _ab._time.time()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
-        print("Association rules successfully  generated from frequent patterns ")
+        self.mine()
 
     def mine(self) -> None:
         """

diff --git a/PAMI/AssociationRules/basic/RuleMiner.py b/PAMI/AssociationRules/basic/RuleMiner.py
@@ -418,27 +418,7 @@ def startMine(self):
         """
         Association rule mining process will start from here
         """
-        self._startTime = _ab._time.time()
-        k = self._readPatterns()
-        if self._measure == 'confidence':
-            a = Confidence(self._frequentPatterns, k, self._threshold)
-            a.run()
-            self._finalPatterns = a._finalPatterns
-        if self._measure == 'lift':
-            a = Lift(self._frequentPatterns, k, self._threshold)
-            a.run()
-            self._finalPatterns = a._finalPatterns
-        if self._measure == 'leverage':
-            a = Leverage(self._frequentPatterns, k, self._threshold)
-            a.run()
-            self._finalPatterns = a._finalPatterns
-        self._endTime = _ab._time.time()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
-        print("Association rules successfully  generated from frequent patterns ")
+        self.mine()
 
 
     def mine(self):

diff --git a/PAMI/contiguousFrequentPattern/basic/PositionMining.py b/PAMI/contiguousFrequentPattern/basic/PositionMining.py
@@ -273,28 +273,7 @@ def startMine(self):
         Pattern mining process will start from here
         """
         # pass
-        self._startTime = _ab._time.time()
-        self.table={i:{} for i in range(1,6)}
-        self.readData()
-
-        self.getfreqs()
-        temp=self.symbol_freq
-        self.table.update({1:temp})
-        self.current_candidate=1
-        self.mineNext_candidates()
-        self.frequentPatterns={}
-        for length in self.table:
-            temp=self.table[length]
-            for pattern in temp:
-                self.frequentPatterns.update({pattern:len(temp[pattern])})
-
-
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._endTime = _ab._time.time()
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
+        self.mine()
 
     def mine(self):
         """

diff --git a/PAMI/correlatedPattern/basic/CoMine.py b/PAMI/correlatedPattern/basic/CoMine.py
@@ -567,34 +567,7 @@ def startMine(self) -> None:
         """
         main method to start
         """
-        self._startTime = _ab._time.time()
-        if self._iFile is None:
-            raise Exception("Please enter the file path or file name:")
-        self._creatingItemSets()
-        self._minSup = self._convert(self._minSup)
-        self._tree = _Tree()
-        self._finalPatterns = {}
-        self._correlatedOneItem()
-        self._mapSupport = {k: v for k, v in self._mapSupport.items() if v >= self._minSup}
-        _itemSetBuffer = [k for k, v in sorted(self._mapSupport.items(), key=lambda x: x[1], reverse=True)]
-        for i in self._Database:
-            _transaction = []
-            for j in i:
-                if j in _itemSetBuffer:
-                    _transaction.append(j)
-            _transaction.sort(key=lambda val: self._mapSupport[val], reverse=True)
-            self._tree.addTransaction(_transaction)
-        self._tree.createHeaderList(self._mapSupport, self._minSup)
-        if len(self._tree.headerList) > 0:
-            self._itemSetBuffer = []
-            self._correlatedPatternGrowthGenerate(self._tree, self._itemSetBuffer, 0, self._mapSupport)
-        print("Correlated patterns were generated successfully using CoMine algorithm")
-        self._endTime = _ab._time.time()
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
+        self.mine()
 
     def mine(self) -> None:
         """

diff --git a/PAMI/correlatedPattern/basic/CoMinePlus.py b/PAMI/correlatedPattern/basic/CoMinePlus.py
@@ -573,37 +573,7 @@ def startMine(self) -> None:
         """
         Main program to start the operation
         """
-
-        self._startTime = _ab._time.time()
-        if self._iFile is None:
-            raise Exception("Please enter the file path or file name:")
-        if self._minSup is None:
-            raise Exception("Please enter the Minimum Support")
-        self._creatingItemSets()
-        self._finalPatterns = {}
-        self._tree = _Tree()
-        self._minSup = self._convert(self._minSup)
-        self._correlatedOneItem()
-        self._mapSupport = {k: v for k, v in self._mapSupport.items() if v >= self._minSup}
-        _itemSetBuffer = [k for k, v in sorted(self._mapSupport.items(), key=lambda x: x[1], reverse=True)]
-        for i in self._Database:
-            _transaction = []
-            for j in i:
-                if j in _itemSetBuffer:
-                    _transaction.append(j)
-            _transaction.sort(key=lambda val: self._mapSupport[val], reverse=True)
-            self._tree.addTransaction(_transaction)
-        self._tree.createHeaderList(self._mapSupport, self._minSup)
-        if len(self._tree.headerList) > 0:
-            self._itemSetBuffer = []
-            self._correlatedPatternGrowthGenerate(self._tree, self._itemSetBuffer, 0, self._mapSupport, self._minAllConf)
-        print("Correlated Frequent patterns were generated successfully using CorrelatedPatternGrowth algorithm")
-        self._endTime = _ab._time.time()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryRSS = float()
-        self._memoryUSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
+        self.mine()
 
     def mine(self) -> None:
         """

diff --git a/PAMI/coveragePattern/basic/CMine.py b/PAMI/coveragePattern/basic/CMine.py
@@ -300,25 +300,7 @@ def generateAllPatterns(self,coverageItems: Dict[str, int]) -> None:
     def startMine(self) -> None:
         """ Main method to start """
 
-        self._startTime = _ab._time.time()
-        if self._iFile is None:
-            raise Exception("Please enter the file path or file name:")
-        self._creatingItemSets()
-        self._minCS = self._convert(self._minCS)
-        self._minRF =  self._convert(self._minRF)
-        self._maxOR = self._convert(self._maxOR)
-        coverageItems = self.creatingCoverageItems()
-        self._finalPatterns = {k: len(v) for k, v in coverageItems.items()}
-        coverageItemsBitset = self.tidToBitset(coverageItems)
-        self.generateAllPatterns(coverageItemsBitset)
-        self.save('output.txt')
-        self._endTime = _ab._time.time()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
-        print("Coverage patterns were generated successfully using CMine  algorithm")
+        self.mine()
 
     def mine(self) -> None:
         """ Main method to start """

diff --git a/PAMI/coveragePattern/basic/CPPG.py b/PAMI/coveragePattern/basic/CPPG.py
@@ -356,41 +356,7 @@ def _convert(self, value: Union[int, float, str]) -> Union[int, float]:
     def startMine(self) -> None:
         """ Mining process will start from this function
         """
-
-        #global _minSup, _maxPer, _lno
-        self._startTime = _ab._time.time()
-        if self._iFile is None:
-            raise Exception("Please enter the file path or file name:")
-        if self._minRF is None:
-            raise Exception("Please enter the Relative Frequency")
-        if self._maxOR is None:
-            raise Exception("Please enter the Overlap Ratio")
-        if self._minCS is None:
-            raise Exception("Please enter the Coverage Ratio")
-        self._creatingItemSets()
-        self._minRF = self._convert(self._minRF)
-        self._maxOR = self._convert(self._maxOR)
-        self._minCS = self._convert(self._minCS)
-        if self._minRF > len(self._Database) or self._minCS > len(self._Database) or self._maxOR > len(self._Database):
-            raise Exception("Please enter the constraints in range between 0 to 1")
-        generatedItems, pfList = self._coverageOneItem()
-        self._finalPatterns = {k: v for k, v in generatedItems.items()}
-        updatedDatabases = self._updateDatabases(pfList)
-        proData = self._buildProjectedDatabase(updatedDatabases, pfList)
-        for x, y in proData.items():
-            uniqueItems = [x]
-            for i in y:
-                for j in i:
-                    if j not in uniqueItems:
-                        uniqueItems.append(j)
-            self._generateFrequentPatterns(uniqueItems)
-        self._endTime = _ab._time.time()
-        process = _ab._psutil.Process(_ab._os.getpid())
-        self._memoryUSS = float()
-        self._memoryRSS = float()
-        self._memoryUSS = process.memory_full_info().uss
-        self._memoryRSS = process.memory_info().rss
-        print("Coverage patterns were generated successfully using CPPG algorithm ")
+        self.mine()
 
     def mine(self) -> None:
         """ Mining process will start from this function