Source code for PAMI.highUtilityPattern.basic.HMiner

#  High Utility itemSet Mining (HMinER) is an important algorithm to miner High utility items from the database.
#
# **Importing this algorithm into a python program**
# --------------------------------------------------------
#
#
#             from PAMI.highUtilityPattern.basic import HMiner as alg
#
#             obj = alg.HMiner("input.txt", 35)
#
#             obj.mine()
#
#             Patterns = obj.getPatterns()
#
#             print("Total number of high utility Patterns:", len(Patterns))
#
#             obj.save("output")
#
#             memUSS = obj.getMemoryUSS()
#
#             print("Total Memory in USS:", memUSS)
#
#             memRSS = obj.getMemoryRSS()
#
#             print("Total Memory in RSS", memRSS)
#
#             run = obj.getRuntime()
#
#             print("Total ExecutionTime in seconds:", run)
#





__copyright__ = """
Copyright (C)  2021 Rage Uday Kiran

     This program is free software: you can redistribute it and/or modify
     it under the terms of the GNU General Public License as published by
     the Free Software Foundation, either version 3 of the License, or
     (at your option) any later version.

     This program is distributed in the hope that it will be useful,
     but WITHOUT ANY WARRANTY; without even the implied warranty of
     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
     GNU General Public License for more details.

     You should have received a copy of the GNU General Public License
     along with this program.  If not, see <https://www.gnu.org/licenses/>.
     Copyright (C)  2021 Rage Uday Kiran

"""

from PAMI.highUtilityPattern.basic import abstract as _ab
from deprecated import deprecated


class _Element:
    """
    A class represents an Element of a utility list.

    :Attributes :

        ts : int
            keep tact of transaction id
        nu : int
            non-closed itemSet utility
        nru : int
             non-closed remaining utility
        pu : int
            prefix utility
        ppos: int
            position of previous item in the list
    """

    def __init__(self, tid, nu, nru, pu, ppos):
        self.tid = tid
        self.nu = nu
        self.nru = nru
        self.pu = pu
        self.ppos = ppos


class _CUList:
    """
    A class represents a UtilityList

    :Attributes :

        item: int
            item 
        sumNu: long
            the sum of item utilities
        sumNru: long
            the sum of remaining utilities
        sumCu : long
            the sum of closed utilities
        sumCru: long
            the sum of closed remaining utilities
        sumCpu: long
            the sum of closed prefix utilities
        elements: list
            the list of elements 
    :Methods :

        addElement(element)
            Method to add an element to this utility list and update the sums at the same time.
    """

    def __init__(self, item):
        self.item = item
        self.sumnu = 0
        self.sumnru = 0
        self.sumCu = 0
        self.sumCru = 0
        self.sumCpu = 0
        self.elements = []

    def addElements(self, element):
        """
        A method to add new element to CUList
        :param element: element to be added to CUList
        :type element: Element
        """
        self.sumnu += element.nu
        self.sumnru += element.nru
        self.elements.append(element)


class _Pair:
    """
    A class represent an item and its utility in a transaction
    """

    def __init__(self):
        self.item = 0
        self.utility = 0


[docs] class HMiner(_ab._utilityPatterns): """ :Description: High Utility itemSet Mining (HMIER) is an importent algorithm to miner High utility items from the database. :Reference: :param iFile: str : Name of the Input file to mine complete set of High Utility patterns :param oFile: str : Name of the output file to store complete set of High Utility patterns :param minUtil: int : The user given minUtil value. :param minSup: int or float or str : The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count. Otherwise, it will be treated as float. :param maxPer: float : The user can specify maxPer in count or proportion of database size. If the program detects the data type of maxPer is integer, then it treats maxPer is expressed in count. :param sep: str : This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator. :Attributes: iFile : file Name of the input file to mine complete set of frequent patterns oFile : file Name of the output file to store complete set of frequent patterns memoryRSS : float To store the total amount of RSS memory consumed by the program startTime:float To record the start time of the mining process endTime:float To record the completion time of the mining process minUtil : int The user given minUtil mapFMAP: list EUCS map of the FHM algorithm candidates: int candidates genetated huiCnt: int huis created neighbors: map keep track of nighboues of elements :Methods: mine() Mining process will start from here getPatterns() Complete set of patterns will be retrieved with this function save(oFile) Complete set of frequent patterns will be loaded in to a output file getPatternsAsDataFrame() Complete set of frequent patterns will be loaded in to a dataframe getMemoryUSS() Total amount of USS memory consumed by the mining process will be retrieved from this function getMemoryRSS() Total amount of RSS memory consumed by the mining process will be retrieved from this function getRuntime() Total amount of runtime taken by the mining process will be retrieved from this function Explore_SearchTree(prefix, uList, minUtil) A method to find all high utility itemSets UpdateCLosed(x, culs, st, excul, newT, ex, ey_ts, length) A method to update closed values saveitemSet(prefix, prefixLen, item, utility) A method to save itemSets updateElement(z, culs, st, excul, newT, ex, duppos, ey_ts) A method to updates vales for duplicates construcCUL(x, culs, st, minUtil, length, exnighbors) A method to construct CUL's database **Executing the code on terminal:** -------------------------------------------- .. code-block:: console Format: (.venv) $ python3 HMiner.py <inputFile> <outputFile> <minUtil> Example Usage: (.venv) $ python3 HMiner.py sampleTDB.txt output.txt 35 .. note:: minSup will be considered in percentage of database transactions Sample run of importing the code: -------------------------------------- .. code-block:: python from PAMI.highUtilityPattern.basic import HMiner as alg obj = alg.HMiner("input.txt",35) obj.mine() Patterns = obj.getPatterns() print("Total number of high utility Patterns:", len(Patterns)) obj.save("output") memUSS = obj.getMemoryUSS() print("Total Memory in USS:", memUSS) memRSS = obj.getMemoryRSS() print("Total Memory in RSS", memRSS) run = obj.getRuntime() print("Total ExecutionTime in seconds:", run) **Credits:** ----------------------------- The complete program was written by B.Sai Chitra under the supervision of Professor Rage Uday Kiran. """ _startTime = float() _endTime = float() _minSup = str() _maxPer = float() _finalPatterns = {} _Database = {} _transactions = [] _utilities = [] _utilitySum = [] _iFile = " " _oFile = " " _minUtil = 0 _sep = "\t" _memoryUSS = float() _memoryRSS = float() def __init__(self, iFile1, minUtil, sep="\t"): super().__init__(iFile1, minUtil, sep) self.oFile = None self._huiCount = 0 self._candidates = 0 self._mapOfTWU = {} self._minutil = 0 self._mapFMAP = {} self._finalPatterns = {} def _HMiner(self, o1, o2) -> int: """ A Function that sort all FFI-list in ascending order of Support :param o1: First FFI-list :type o1: _FFList :param o2: Second FFI-list :type o1: _FFList :return: Comparision Value :rtype: int """ compare = self._mapOfTWU[o1.item] - self._mapOfTWU[o2.item] if compare == 0: return int(o1.item) - int(o2.item) else: return compare def _creteItemsets(self): """ Storing the complete transactions of the database/input file in a database variable """ self._transactions, self._utilities, self._utilitySum = [], [], [] if isinstance(self._iFile, _ab._pd.DataFrame): if self._iFile.empty: print("its empty..") i = self._iFile.columns.values.tolist() if 'Transactions' in i: self._transactions = self._iFile['Transactions'].tolist() if 'Utilities' in i: self._utilities = self._iFile['Utilities'].tolist() if 'UtilitySum' in i: self._utilitySum = self._iFile['UtilitySum'].tolist() if isinstance(self._iFile, str): if _ab._validators.url(self._iFile): #print("hey") data = _ab._urlopen(self._iFile) for line in data: line = line.decode("utf-8") line = line.split("\n")[0] parts = line.split(":") items = parts[0].split(self._sep) self._transactions.append([x for x in items if x]) utilities = parts[2].split(self._sep) self._utilities.append(utilities) self._utilitySum.append(int(parts[1])) else: try: with open(self._iFile, 'r', encoding='utf-8') as f: for line in f: line = line.split("\n")[0] parts = line.split(":") items = parts[0].split(self._sep) self._transactions.append([x for x in items if x]) utilities = parts[2].split(self._sep) self._utilities.append(utilities) self._utilitySum.append(int(parts[1])) except IOError: print("File Not Found") quit()
[docs] @deprecated("It is recommended to use 'mine()' instead of 'mine()' for mining process. Starting from January 2025, 'mine()' will be completely terminated.") def startMine(self): """ Main program to start the operation """ self.mine()
[docs] def mine(self): """ Main program to start the operation """ self._startTime = _ab._time.time() self._creteItemsets() self._finalPatterns = {} for line in range(len(self._transactions)): items_str = self._transactions[line] #utility_str = self._utilities[line] transUtility = self._utilitySum[line] for i in range(0, len(items_str)): item = items_str[i] twu = self._mapOfTWU.get(item) if twu is None: twu = transUtility else: twu += transUtility self._mapOfTWU[item] = twu listOfCUList = [] hashTable = {} mapItemsToCUList = {} minutil = self._minUtil for item in self._mapOfTWU.keys(): if self._mapOfTWU.get(item) >= self._minUtil: uList = _CUList(item) mapItemsToCUList[item] = uList listOfCUList.append(uList) listOfCUList.sort(key=_ab._functools.cmp_to_key(self._HMiner)) tid = 1 for line in range(len(self._transactions)): items = self._transactions[line] utilities = self._utilities[line] ru = 0 newTwu = 0 tx_key = [] revisedTrans = [] for i in range(0, len(items)): pair = _Pair() pair.item = items[i] pair.utility = int(utilities[i]) if self._mapOfTWU.get(pair.item) >= self._minUtil: revisedTrans.append(pair) tx_key.append(pair.item) newTwu += pair.utility revisedTrans.sort(key=_ab._functools.cmp_to_key(self._HMiner)) tx_key1 = tuple(tx_key) if len(revisedTrans) > 0: if tx_key1 not in hashTable.keys(): hashTable[tx_key1] = len(mapItemsToCUList[revisedTrans[len(revisedTrans) - 1].item].elements) for i in range(len(revisedTrans) - 1, -1, -1): pair = revisedTrans[i] cuListoFItems = mapItemsToCUList.get(pair.item) element = _Element(tid, pair.utility, ru, 0, 0) if i > 0: element.ppos = len(mapItemsToCUList[revisedTrans[i - 1].item].elements) else: element.ppos = - 1 cuListoFItems.addElements(element) ru += pair.utility else: pos = hashTable[tx_key1] ru = 0 for i in range(len(revisedTrans) - 1, -1, -1): cuListoFItems = mapItemsToCUList[revisedTrans[i].item] cuListoFItems.elements[pos].nu += revisedTrans[i].utility cuListoFItems.elements[pos].nru += ru cuListoFItems.sumnu += revisedTrans[i].utility cuListoFItems.sumnru += ru ru += revisedTrans[i].utility pos = cuListoFItems.elements[pos].ppos # EUCS for i in range(len(revisedTrans) - 1, -1, -1): pair = revisedTrans[i] mapFMAPItem = self._mapFMAP.get(pair.item) if mapFMAPItem is None: mapFMAPItem = {} self._mapFMAP[pair.item] = mapFMAPItem for j in range(i + 1, len(revisedTrans)): pairAfter = revisedTrans[j] twuSUm = mapFMAPItem.get(pairAfter.item) if twuSUm is None: mapFMAPItem[pairAfter.item] = newTwu else: mapFMAPItem[pairAfter.item] = twuSUm + newTwu tid += 1 self._ExploreSearchTree([], listOfCUList, minutil) 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 print("High Utility patterns were generated successfully using HMiner algorithm")
def _ExploreSearchTree(self, prefix, uList, minutil): """ A method to find all high utility itemSets :parm prefix:it represents all items in prefix :type prefix:list :parm uList:projected Utility list :type uList: lists :parm minutil:user minUtil :type minutil:int """ for i in range(0, len(uList)): x = uList[i] #soted_prefix = [0] * (len(prefix) + 1) soted_prefix = prefix[0:len(prefix) + 1] soted_prefix.append(x.item) if x.sumnu + x.sumCu >= minutil: self._saveitemSet(prefix, len(prefix), x.item, x.sumnu + x.sumCu) self._candidates += 1 if x.sumnu + x.sumCu + x.sumnru + x.sumCru >= minutil: exULs = self._construcCUL(x, uList, i, minutil, len(soted_prefix)) self._ExploreSearchTree(soted_prefix, exULs, minutil) def _construcCUL(self, x, culs, st, minutil, length): """ A method to construct CUL's database :parm x: Compact utility list :type x: Node :parm culs:list of Compact utility list :type culs:lists :parm st: starting pos of culs :type st:int :parm minutil: user minUtil :type minutil:int :parm length: length of x :type length:int :return: projectd database of list X :rtype: list """ excul = [] lau = [] cutil = [] ey_tid = [] for i in range(0, len(culs)): uList = _CUList(culs[i].item) excul.append(uList) lau.append(0) cutil.append(0) ey_tid.append(0) sz = len(culs) - (st + 1) exSZ = sz for j in range(st + 1, len(culs)): mapOfTWUF = self._mapFMAP[x.item] if mapOfTWUF is not None: twuf = mapOfTWUF.get(culs[j].item) if twuf is not None and twuf < minutil: excul[j] = None exSZ = sz - 1 else: uList = _CUList(culs[j].item) excul[j] = uList ey_tid[j] = 0 lau[j] = x.sumCu + x.sumCru + x.sumnu + x.sumnru cutil[j] = x.sumCu + x.sumCru hashTable = {} for ex in x.elements: newT = [] for j in range(st + 1, len(culs)): if excul[j] is None: continue eylist = culs[j].elements while ey_tid[j] < len(eylist) and eylist[ey_tid[j]].tid < ex.tid: ey_tid[j] = ey_tid[j] + 1 if ey_tid[j] < len(eylist) and eylist[ey_tid[j]].tid == ex.tid: newT.append(j) else: lau[j] = lau[j] - ex.nu - ex.nru if lau[j] < minutil: excul[j] = None exSZ = exSZ - 1 if len(newT) == exSZ: self._UpdateCLosed(x, culs, st, excul, newT, ex, ey_tid, length) else: if len(newT) == 0: continue ru = 0 newT1 = tuple(newT) if newT1 not in hashTable.keys(): hashTable[newT1] = len(excul[newT[len(newT) - 1]].elements) for i in range(len(newT) - 1, -1, -1): cuListoFItems = excul[newT[i]] y = culs[newT[i]].elements[ey_tid[newT[i]]] element = _Element(ex.tid, ex.nu + y.nu - ex.pu, ru, ex.nu, 0) if i > 0: element.ppos = len(excul[newT[i - 1]].elements) else: element.ppos = - 1 cuListoFItems.addElements(element) ru += y.nu - ex.pu else: dppos = hashTable[newT1] self._updateElement(x, culs, st, excul, newT, ex, dppos, ey_tid) for j in range(st + 1, len(culs)): cutil[j] = cutil[j] + ex.nu + ex.nru filter_culs = [] for j in range(st + 1, len(culs)): if cutil[j] < minutil or excul[j] is None: continue else: if length > 1: excul[j].sumCu += culs[j].sumCu + x.sumCu - x.sumCpu excul[j].sumCru += culs[j].sumCru excul[j].sumCpu += x.sumCu filter_culs.append(excul[j]) return filter_culs def _UpdateCLosed(self, x, culs, st, excul, newT, ex, ey_tid, length): """ A method to update closed values :parm x: Compact utility list :type x: lists :parm culs:list of Compact utility list :type culs:lists :parm st: starting pos of culs :type st:int :parm excul: list of culs :type excul: list :parm newT:transaction to be updated :type newT:list :parm ex: element ex :type ex:element :parm ey_tid:list of tss :type ey_tid:ts :parm length: length of x :type length:int """ nru = 0 for j in range(len(newT) - 1, -1, -1): ey = culs[newT[j]] eyy = ey.elements[ey_tid[newT[j]]] excul[newT[j]].sumCu += ex.nu + eyy.nu - ex.pu excul[newT[j]].sumCru += nru excul[newT[j]].sumCpu += ex.nu nru = nru + eyy.nu - ex.pu def _updateElement(self, z, culs, st, excul, newT, ex, duppos, ey_tid): """ A method to updates vales for duplicates :Attributes: :parm z: Compact utility list :type z: lists :parm culs:list of Compact utility list :type culs:lists :parm st: starting pos of culs :type st:int :parm excul:list of culs :type excul:list :parm newT:transaction to be updated :type newT:list :parm ex: element ex :type ex:element :parm duppos: position of z in excul :type duppos:int :parm ey_tid:list of tss :type ey_tid:ts """ nru = 0 pos = duppos for j in range(len(newT) - 1, -1, -1): ey = culs[newT[j]] eyy = ey.elements[ey_tid[newT[j]]] excul[newT[j]].elements[pos].nu += ex.nu + eyy.nu - ex.pu excul[newT[j]].sumnu += ex.nu + eyy.nu - ex.pu excul[newT[j]].elements[pos].nru += nru excul[newT[j]].sumnru += nru excul[newT[j]].elements[pos].pu += ex.nu nru = nru + eyy.nu - ex.pu pos = excul[newT[j]].elements[pos].ppos def _saveitemSet(self, prefix, prefixLen, item, utility): """ A method to save itemSets :parm prefix: it represents all items in prefix :type prefix :list :parm prefixLen: length of prefix :type prefixLen:int :parm item:item :type item: int :parm utility:utility of itemSet :type utility:int """ self._huiCount += 1 res = str() for i in range(0, prefixLen): res += str(prefix[i]) + "\t" res += str(item) self._finalPatterns[str(res)] = str(utility)
[docs] def getPatternsAsDataFrame(self): """ Storing final frequent patterns in a dataframe :return: returning frequent patterns in a dataframe :rtype: pd.DataFrame """ dataFrame = {} data = [] for a, b in self._finalPatterns.items(): data.append([a.replace('\t', ' '), b]) dataFrame = _ab._pd.DataFrame(data, columns=['Patterns', 'Utility']) return dataFrame
[docs] def getPatterns(self): """ Function to send the set of frequent patterns after completion of the mining process :return: returning frequent patterns :rtype: dict """ return self._finalPatterns
[docs] def save(self, outFile): """ Complete set of frequent patterns will be loaded in to an output file :param outFile: name of the output file :type outFile: csv file """ self.oFile = outFile writer = open(self.oFile, 'w+') for x, y in self._finalPatterns.items(): patternsAndSupport = x.strip() + ":" + str(y) writer.write("%s\n" % patternsAndSupport)
[docs] def getMemoryUSS(self): """ Total amount of USS memory consumed by the mining process will be retrieved from this function :return: returning USS memory consumed by the mining process :rtype: float """ return self._memoryUSS
[docs] def getMemoryRSS(self): """ Total amount of RSS memory consumed by the mining process will be retrieved from this function :return: returning RSS memory consumed by the mining process :rtype: float """ return self._memoryRSS
[docs] def getRuntime(self): """ Calculating the total amount of runtime taken by the mining process :return: returning total amount of runtime taken by the mining process :rtype: float """ return self._endTime - self._startTime
[docs] def printResults(self): """ This function is used to print the results """ print("Total number of High Utility Patterns:", len(self.getPatterns())) print("Total Memory in USS:", self.getMemoryUSS()) print("Total Memory in RSS", self.getMemoryRSS()) print("Total ExecutionTime in seconds:", self.getRuntime())
if __name__ == "__main__": _ap = str() if len(_ab._sys.argv) == 4 or len(_ab._sys.argv) == 5: if len(_ab._sys.argv) == 5: # includes separator _ap = HMiner(_ab._sys.argv[1], int(_ab._sys.argv[3]), _ab._sys.argv[4]) if len(_ab._sys.argv) == 4: # to consider "\t" as a separator _ap = HMiner(_ab._sys.argv[1], int(_ab._sys.argv[3])) _ap.mine() _ap.mine() print("Total number of huis:", len(_ap.getPatterns())) _ap.save(_ab._sys.argv[2]) print("Total Memory in USS:", _ap.getMemoryUSS()) print("Total Memory in RSS", _ap.getMemoryRSS()) print("Total ExecutionTime in ms:", _ap.getRuntime()) else: print("Error! The number of input parameters do not match the total number of parameters provided")