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#2 updated CHARM.py documentation.
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vanithakattumuri committed Apr 30, 2024
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124 changes: 54 additions & 70 deletions PAMI/frequentPattern/closed/CHARM.py
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# CHARM is an algorithm to discover closed frequent patterns in a transactional database. Closed frequent patterns are patterns if there exists no superset that has the same support count as this original itemset . This algorithm employs depth-first search technique to find the complete set of closed frequent patterns in a
# CHARM is an algorithm to discover closed frequent patterns in a transactional database. Closed frequent patterns are patterns if there exists no superset that has the same support count as this original itemset . This algorithm employs depth-first search technique to find the complete set of closed frequent patterns in a transactional database.
#
# **Importing this algorithm into a python program**
# --------------------------------------------------------------
#
#
# from PAMI.frequentPattern.closed import CHARM as alg
#
# iFile = 'sampleDB.txt'
#
# minSup = 10 # can also be specified between 0 and 1
#
# obj = alg.CHARM(iFile, minSup)
#
# obj.mine()
Expand All @@ -32,8 +34,6 @@
#




__copyright__ = """
Copyright (C) 2021 Rage Uday Kiran
Expand All @@ -58,61 +58,33 @@

class CHARM(_ab._frequentPatterns):
"""
:Description: CHARM is an algorithm to discover closed frequent patterns in a transactional database. Closed frequent patterns are patterns if there exists no superset that has the same support count as this original itemset. This algorithm employs depth-first search technique to find the complete set of closed frequent patterns in a
:Reference: Mohammed J. Zaki and Ching-Jui Hsiao, CHARM: An Efficient Algorithm for Closed Itemset Mining,
Proceedings of the 2002 SIAM, SDM. 2002, 457-473, https://doi.org/10.1137/1.9781611972726.27
:param iFile: str :
Name of the Input file to mine complete set of frequent patterns
:param oFile: str :
Name of the output file to store complete set of frequent patterns
: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.
: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:
startTime : float
To record the start time of the mining process
:**Description**: CHARM is an algorithm to discover closed frequent patterns in a transactional database. Closed frequent patterns are patterns if there exists no superset that has the same support count as this original itemset. This algorithm employs depth-first search technique to find the complete set of closed frequent patterns in a transactional database.
endTime : float
To record the completion time of the mining process
:**Reference**: Mohammed J. Zaki and Ching-Jui Hsiao, CHARM: An Efficient Algorithm for Closed Itemset Mining,
Proceedings of the 2002 SIAM, SDM. 2002, 457-473, https://doi.org/10.1137/1.9781611972726.27
finalPatterns : dict
Storing the complete set of patterns in a dictionary variable
:**Parameters**: - **iFile** (*str or URL or dataFrame*) -- *Name of the Input file to mine complete set of frequent patterns.*
- **oFile** (*str*) -- *Name of the output file to store complete set of frequent patterns.*
- **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.*
- **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.*
memoryUSS : float
To store the total amount of USS memory consumed by the program
:**Attributes**: - **startTime** (*float*) -- *To record the start time of the mining process.*
- **endTime** (*float*) -- *To record the completion time of the mining process.*
- **finalPatterns** (*dict*) -- *Storing the complete set of patterns in a dictionary variable.*
- **memoryUSS** (*float*) -- *To store the total amount of USS memory consumed by the program.*
- **memoryRSS** (*float*) -- *To store the total amount of RSS memory consumed by the program.*
- **Database** (*list*) -- *To store the transactions of a database in list.*
- **mapSupport** (*Dictionary*) -- *To maintain the information of item and their frequency.*
- **tree** (*class*) -- *It represents the Tree class.*
- **itemSetCount** (*int*) -- *It represents the total no of patterns.*
- **tidList** (*dict*) -- *Stores the timestamps of an item.*
- **hashing** (*dict*) -- *Stores the patterns with their support to check for the closed property.*
memoryRSS : float
To store the total amount of RSS memory consumed by the program
Database : list
To store the transactions of a database in list
Execution methods
=================
mapSupport : Dictionary
To maintain the information of item and their frequency
lno : int
it represents the total no of transactions
tree : class
it represents the Tree class
itemSetCount : int
it represents the total no of patterns
finalPatterns : dict
it represents to store the patterns
tidList : dict
stores the timestamps of an item
hashing : dict
stores the patterns with their support to check for the closed property
**Methods to execute code on terminal**
--------------------------------------------------------------
**Terminal command**
.. code-block:: console
Expand All @@ -124,15 +96,19 @@ class CHARM(_ab._frequentPatterns):
(.venv) $ python3 CHARM.py sampleDB.txt patterns.txt 10.0
.. note:: minSup will be considered in percentage of database transactions
.. note:: minSup can be specified in support count or a value between 0 and 1.
**Calling from a python program**
**Importing this algorithm into a python program**
--------------------------------------------------------------
.. code-block:: python
from PAMI.frequentPattern.closed import CHARM as alg
iFile = 'sampleDB.txt'
minSup = 10 # can also be specified between 0 and 1
obj = alg.CHARM(iFile, minSup)
obj.mine()
Expand All @@ -158,10 +134,10 @@ class CHARM(_ab._frequentPatterns):
print("Total ExecutionTime in seconds:", run)
**Credits:**
-------------------------------
Credits:
=======
The complete program was written by P.Likhitha under the supervision of Professor Rage Uday Kiran.
The complete program was written by P.Likhitha and revised by Tarun Sreepada under the supervision of Professor Rage Uday Kiran.
"""

Expand Down Expand Up @@ -190,11 +166,8 @@ def _convert(self, value):
To convert the type of user specified minSup value
:param value: user specified minSup value
:type value: int or float or str
:return: converted type
"""
if type(value) is int:
value = int(value)
Expand Down Expand Up @@ -266,21 +239,22 @@ def _creatingItemsets(self):

def _calculate(self, tidSet):
"""
To calculate the hashcode of pattern
:param tidSet: the timestamps of a pattern
:type tidSet: list
:rtype: int
"""

return abs(sum(tidSet)) % self._tableSize

def _contains(self, itemSet, value, hashcode):
"""
Check for the closed property(patterns with same support) by checking the hashcode(sum of timestamps),
if hashcode key in hashing dict is none then returns a false, else returns with true.
:param itemSet: frequent pattern
:type itemSet: list
:param value: support of the pattern
Expand All @@ -298,19 +272,15 @@ def _contains(self, itemSet, value, hashcode):

def _save(self, prefix, suffix, tidSetx):
"""
Check for the closed property (patterns with same support), if found deletes the subsets and stores
supersets and also saves the patterns that satisfy the closed property
:param prefix: the prefix of a pattern
:type prefix: frequent item or pattern
:param suffix: the suffix of a patterns
:type suffix: list
:param tidSetx: the timestamp of a patterns
:type tidSetx: list
"""
if prefix is None:
Expand All @@ -335,7 +305,9 @@ def _save(self, prefix, suffix, tidSetx):

def _processEquivalenceClass(self, prefix, itemSets, tidSets):
"""
Equivalence class is followed and check for the patterns which satisfies frequent properties.
:param prefix: main equivalence prefix
:type prefix: frequent item or pattern
:param itemSets: patterns which are items combined with prefix and satisfying the minSup
Expand Down Expand Up @@ -458,7 +430,9 @@ def mine(self):

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
"""
Expand All @@ -467,7 +441,9 @@ def getMemoryUSS(self):

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
"""
Expand All @@ -476,7 +452,9 @@ def getMemoryRSS(self):

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
"""
Expand All @@ -485,7 +463,9 @@ def getRuntime(self):

def getPatternsAsDataFrame(self):
"""
Storing final frequent patterns in a dataframe
:return: returning frequent patterns in a dataframe
:rtype: pd.DataFrame
"""
Expand All @@ -499,7 +479,9 @@ def getPatternsAsDataFrame(self):

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: csvfile
"""
Expand All @@ -511,7 +493,9 @@ def save(self, outFile):

def getPatterns(self):
"""
Function to send the set of frequent patterns after completion of the mining process
:return: returning frequent patterns
:rtype: dict
"""
Expand Down

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