PAMI.partialPeriodicPattern.topk package

Submodules

PAMI.partialPeriodicPattern.topk.abstract module

class PAMI.partialPeriodicPattern.topk.abstract.partialPeriodicPatterns(iFile, k, period, sep='\t')[source]

Bases: ABC

Description:

This abstract base class defines the variables and methods that every periodic-frequent pattern mining algorithm must employ in PAMI

Attributes:
iFilestr

Input file name or path of the input file

k: int or float or str

The user can specify minPS either in count or proportion of database size. If the program detects the data type of minPS is integer, then it treats minPS is expressed in count. Otherwise, it will be treated as float. Example: minPS=10 will be treated as integer, while minPS=10.0 will be treated as float

period: int or float or str

The user can specify period either in count or proportion of database size. If the program detects the data type of period is integer, then it treats period is expressed in count. Otherwise, it will be treated as float. Example: period=10 will be treated as integer, while period=10.0 will be treated as float

sepstr

This variable is used to distinguish items from one another in a transaction. The default seperator is tab space or . However, the users can override their default separator.

startTime:float

To record the start time of the algorithm

endTime:float

To record the completion time of the algorithm

finalPatterns: dict

Storing the complete set of patterns in a dictionary variable

oFilestr

Name of the output file to store complete set of periodic-frequent patterns

memoryUSSfloat

To store the total amount of USS memory consumed by the program

memoryRSSfloat

To store the total amount of RSS memory consumed by the program

Methods:
startMine()

Mining process will start from here

getPatterns()

Complete set of patterns will be retrieved with this function

save(oFile)

Complete set of periodic-frequent patterns will be loaded in to a output file

getPatternsAsDataFrame()

Complete set of periodic-frequent patterns will be loaded in to data frame

getMemoryUSS()

Total amount of USS memory consumed by the program will be retrieved from this function

getMemoryRSS()

Total amount of RSS memory consumed by the program will be retrieved from this function

getRuntime()

Total amount of runtime taken by the program will be retrieved from this function

abstract getMemoryRSS()[source]

Total amount of RSS memory consumed by the program will be retrieved from this function

abstract getMemoryUSS()[source]

Total amount of USS memory consumed by the program will be retrieved from this function

abstract getPatterns()[source]

Complete set of periodic-frequent patterns generated will be retrieved from this function

abstract getPatternsAsDataFrame()[source]

Complete set of periodic-frequent patterns will be loaded in to data frame from this function

abstract getRuntime()[source]

Total amount of runtime taken by the program will be retrieved from this function

abstract printResults()[source]

To print all the results of execution

abstract save(oFile)[source]

Complete set of periodic-frequent patterns will be saved in to an output file from this function

Parameters:

oFile (file) – Name of the output file

abstract startMine()[source]

Code for the mining process will start from this function

PAMI.partialPeriodicPattern.topk.k3PMiner module

Module contents