PAMI.extras.dbStats package

Submodules

PAMI.extras.dbStats.FuzzyDatabase module

class PAMI.extras.dbStats.FuzzyDatabase.FuzzyDatabase(inputFile: str, sep: str = '\t')[source]

Bases: object

Description:

FuzzyDatabase is class to get stats of fuzzyDatabase.

Attributes:

inputFilefile: input file path
sepstr: separator in file. Default is tab space.

Methods:

run(): execute readDatabase function
readDatabase(): read database from input file
getDatabaseSize(): get the size of database
getMinimumTransactionLength(): get the minimum transaction length
getAverageTransactionLength(): get the average transaction length. It is sum of all transaction length divided by database length.
getMaximumTransactionLength(): get the maximum transaction length
getStandardDeviationTransactionLength(): get the standard deviation of transaction length
getSortedListOfItemFrequencies(): get sorted list of item frequencies
getSortedListOfTransactionLength(): get sorted list of transaction length
save(data, outputFile): store data into outputFile
getMinimumUtility(): get the minimum utility
getAverageUtility(): get the average utility
getMaximumUtility(): get the maximum utility
getSortedUtilityValuesOfItem(): get sorted utility values each item

from PAMI.extras.dbStats import FuzzyDatabaseStats as db

obj = db.FuzzyDatabase(iFile, "     ")

obj.run()

obj.printStats()

obj.save(oFile)

creatingItemSets() → None[source]: Storing the complete transactions of the database/input file in a database variable

getAverageTransactionLength() → float[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length :rtype: float

getAverageUtility() → float[source]: get the average utility :return: average utility :rtype: float

getDatabaseSize() → int[source]: get the size of database :return: dataset size :rtype: int

getFrequenciesInRange() → dict[source]

getMaximumTransactionLength() → int[source]: get the maximum transaction length :return: maximum transaction length :rtype: int

getMaximumUtility() → int[source]: get the maximum utility :return: max utility :rtype: int

getMinimumTransactionLength() → int[source]: get the minimum transaction length :return: minimum transaction length :rtype: int

getMinimumUtility() → int[source]: get the minimum utility :return: min utility :rtype: int

getNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getSortedListOfItemFrequencies() → dict[source]: get sorted list of item frequencies :return: item frequencies :rtype: dict

getSortedUtilityValuesOfItem() → dict[source]: get sorted utility value each item. key is item and value is utility of item :return: sorted dictionary utility value of item :rtype: dict

getSparsity() → float[source]: get the sparsity of database :return: dataset sparsity :rtype: float

getStandardDeviationTransactionLength() → float[source]: get the standard deviation transaction length :return: standard deviation transaction length :rtype: float

getTotalNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getTotalUtility() → int[source]: get sum of utility :return: total utility :rtype: int

getTransanctionalLengthDistribution() → dict[source]: get transaction length :return: transactional length :rtype: dict

getVarianceTransactionLength() → float[source]: get the variance transaction length :return: variance transaction length :rtype: float

plotGraphs() → None[source]

printStats() → None[source]

readDatabase() → None[source]: read database from input file and store into database and size of each transaction.

run() → None[source]

save(data_: dict, outputFile: str) → None[source]: store data into outputFile :param data_: input data :type data_: dict :param outputFile: output file name or path to store :type outputFile: str :return: None

PAMI.extras.dbStats.MultipleTimeSeriesFuzzyDatabaseStats module

class PAMI.extras.dbStats.MultipleTimeSeriesFuzzyDatabaseStats.MultipleTimeSeriesFuzzyDatabaseStats(inputFile: str, sep: str = '\t')[source]

Bases: object

Description:

MultipleTimeSeriesDatabaseStats is class to get stats of multiple time series fuzzy database.

Attributes:

param inputFile:: file : input file path
param sep:: str separator in file. Default is tab space.

Methods:

run(): execute readDatabase function
readDatabase(): read database from input file
getDatabaseSize(): get the size of database
getTotalNumberOfItems(): get the total number of items in a database
getMinimumTransactionLength(): get the minimum transaction length
getAverageTransactionLength(): get the average transaction length. It is sum of all transaction length divided by database length.
getMaximumTransactionLength(): get the maximum transaction length
getStandardDeviationTransactionLength(): get the standard deviation of transaction length
convertDataIntoMatrix(): Convert the database into matrix form to calculate the sparsity and density of a database
getSparsity(): get sparsity value of database
getDensity(): get density value of database
getSortedListOfItemFrequencies(): get sorted list of item frequencies
getSortedListOfTransactionLength(): get sorted list of transaction length
save(data, outputFile): store data into outputFile
printStats(): To print all the stats of the database
plotGraphs(): To plot all the graphs of frequency disctribution of items and transaction length distribution in database

Importing this algorithm into a python program

from PAMI.extras.dbStats import MultipleTimeSeriesFuzzyDatabaseStats as db

obj = db.MultipleTimeSeriesFuzzyDatabaseStats(iFile, "      ")

obj.run()

obj.save(oFile)

obj.printStats()

convertDataIntoMatrix() → ndarray[source]

getAverageTransactionLength() → float[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length :rtype: float

getDatabaseSize() → int[source]: get the size of database :return: dataset size :rtype: int

getDensity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getFrequenciesInRange() → dict[source]

getMaximumTransactionLength() → int[source]: get the maximum transaction length :return: maximum transaction length :rtype: int

getMinimumTransactionLength() → int[source]: get the minimum transaction length :return: minimum transaction length :rtype: int

getNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getSortedListOfItemFrequencies() → dict[source]: get sorted list of item frequencies :return: item frequencies :rtype: dict

getSparsity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getStandardDeviationTransactionLength() → float[source]: get the standard deviation transaction length :return: standard deviation transaction length :rtype: float

getTotalNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getTransanctionalLengthDistribution() → dict[source]: get transaction length :return: transactional length :rtype: dict

getVarianceTransactionLength() → float[source]: get the variance transaction length :return: variance transaction length :rtype: float

plotGraphs() → None[source]

printStats() → None[source]

readDatabase() → None[source]: read database from input file and store into database and size of each transaction.

run() → None[source]

save(data: dict, outputFile: str) → None[source]: store data into outputFile :param data: input data :type data: dict :param outputFile: output file name or path to store :type outputFile: str :return: None

PAMI.extras.dbStats.SequentialDatabase module

class PAMI.extras.dbStats.SequentialDatabase.SequentialDatabase(inputFile, sep='\t', seqSep='-1')[source]

Bases: object

sequentialDatabaseStats is class to get stats of database.

inputFilefile: input file path
databasedict: store time stamp and its transaction
lengthListlist: store length of all transaction
sepstr: separator in file. Default is tab space.

seqSep: str - Separator for each item set Methods: ——- run()

execute readDatabase function

readDatabase(): read database from input file
getDatabaseSize(): get the size of database
getMinimumTransactionLength(): get the minimum transaction length
getAverageTransactionLength(): get the average transaction length. It is sum of all transaction length divided by database length.
getMaximumTransactionLength(): get the maximum transaction length
getStandardDeviationTransactionLength(): get the standard deviation of transaction length
getVarianceTransactionLength(): get the variance of transaction length
getSparsity(): get the sparsity of database
getSortedListOfItemFrequencies(): get sorted list of item frequencies
getSortedListOfTransactionLength(): get sorted list of transaction length
save(data, outputFile): store data into outputFile

convertDataIntoMatrix()[source]

getAverageItemsInSequenceLength()[source]: get the average Sequence length. It is sum of all transaction length divided by database length. :return: average Sequence length

getAverageSequenceLength()[source]: get the average Sequence length. It is sum of all Sequence length divided by database length. :return: average Sequence length

getAverageTransactionLength()[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length

getDatabaseSize()[source]: get the size of database :return: data base size

getDensity()[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity

getFrequenciesInRange()[source]

getMaximumSequenceLength()[source]: get the maximum Sequence length :return: maximum Sequence length

getMaximumTransactionLength()[source]: get the maximum transaction length :return: maximum transaction length

getMinimumSequenceLength()[source]: get the minimum Sequence length :return: minimum Sequence length

getMinimumTransactionLength()[source]: get the minimum transaction length :return: minimum transaction length

getNumberOfItems()[source]: get the number of items in database. :return: number of items

getSequentialLengthDistribution()[source]: get transaction length :return: transaction length

getSortedListOfItemFrequencies()[source]: get sorted list of item frequencies :return: item frequencies

getSparsity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getStandardDeviationSequenceLength()[source]: get the standard deviation Sequence length :return: standard deviation Sequence length

getStandardDeviationTransactionLength()[source]: get the standard deviation transaction length :return: standard deviation transaction length

getTotalNumberOfISeq()[source]: get the number of items in database. :return: number of items

getTotalNumberOfItems()[source]: get the number of items in database. :return: number of items

getVarianceSequenceLength()[source]: get the variance Sequence length :return: variance Sequence length

getVarianceTransactionLength()[source]: get the variance transaction length :return: variance transaction length

plotGraphs()[source]

printStats()[source]

readDatabase()[source]: read database from input file and store into database and size of each transaction.

run()[source]

save(data_, outputFile)[source]: store data into outputFile :param data_: input data :type data_: dict :param outputFile: output file name or path to store :type outputFile: str

PAMI.extras.dbStats.TemporalDatabase module

class PAMI.extras.dbStats.TemporalDatabase.TemporalDatabase(inputFile: str | DataFrame, sep: str = '\t')[source]

Bases: object

Description:

TemporalDatabase is class to get stats of database.

Attributes:

:param inputFilefile: input file path
:param sepstr: separator in file. Default is tab space.

Methods:

run(): execute readDatabase function
readDatabase(): read database from input file
getDatabaseSize(): get the size of database
getMinimumTransactionLength(): get the minimum transaction length
getAverageTransactionLength(): get the average transaction length. It is sum of all transaction length divided by database length.
getMaximumTransactionLength(): get the maximum transaction length
getStandardDeviationTransactionLength(): get the standard deviation of transaction length
getSortedListOfItemFrequencies(): get sorted list of item frequencies
getSortedListOfTransactionLength(): get sorted list of transaction length
save(data, outputFile): store data into outputFile
getMinimumPeriod(): get the minimum period
getAveragePeriod(): get the average period
getMaximumPeriod(): get the maximum period
getStandardDeviationPeriod(): get the standard deviation period
getNumberOfTransactionsPerTimestamp(): get number of transactions per time stamp. This time stamp range is 1 to max period.

Importing this algorithm into a python program

from PAMI.extras.dbStats import TemporalDatabase as db

obj = db.TemporalDatabase(iFile, "  ")

obj.save(oFile)

obj.run()

obj.printStats()

convertDataIntoMatrix() → ndarray[source]

getAverageInterArrivalPeriod() → float[source]: get the average inter arrival period. It is sum of all period divided by number of period. :return: average inter arrival period :rtype: float

getAveragePeriodOfItem() → float[source]: get the average period of the item :return: average period :rtype: float

getAverageTransactionLength() → float[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length :rtype: float

getDatabaseSize() → int[source]: get the size of database :return: dataset size :rtype: int

getDensity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getFrequenciesInRange() → Dict[int, int][source]

getMaximumInterArrivalPeriod() → int[source]: get the maximum inter arrival period :return: maximum inter arrival period :rtype: int

getMaximumPeriodOfItem() → int[source]: get the maximum period of the item :return: maximum period :rtype: int

getMaximumTransactionLength() → int[source]: get the maximum transaction length :return: maximum transaction length :rtype: int

getMinimumInterArrivalPeriod() → int[source]: get the minimum inter arrival period :return: minimum inter arrival period :rtype: int

getMinimumPeriodOfItem() → int[source]: get the minimum period of the item :return: minimum period :rtype: int

getMinimumTransactionLength() → int[source]: get the minimum transaction length :return: minimum transaction length :rtype: int

getNumberOfTransactionsPerTimestamp() → Dict[int, int][source]: get number of transactions per time stamp :return: number of transactions per time stamp as dict :rtype: dict

getPeriodsInRange() → Dict[int, int][source]

getSortedListOfItemFrequencies() → Dict[str, int][source]: get sorted list of item frequencies :return: item frequencies :rtype: dict

getSparsity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getStandardDeviationPeriod() → float[source]: get the standard deviation period :return: standard deviation period :rtype: float

getStandardDeviationTransactionLength() → float[source]: get the standard deviation transaction length :return: standard deviation transaction length :rtype: float

getTotalNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getTransanctionalLengthDistribution() → Dict[int, int][source]: get transaction length :return: transactional length :rtype: dict

getVarianceTransactionLength() → float[source]: get the variance transaction length :return: variance transaction length :rtype: float

plotGraphs() → None[source]

printStats() → None[source]

readDatabase() → None[source]: read database from input file and store into database and size of each transaction. And store the period between transactions as list

run() → None[source]

save(data_: dict, outputFile: str) → None[source]: store data into outputFile :param data_: input data :type data_: dict :param outputFile: output file name or path to store :type outputFile: str :return: None

PAMI.extras.dbStats.TransactionalDatabase module

class PAMI.extras.dbStats.TransactionalDatabase.TransactionalDatabase(inputFile: str | DataFrame, sep: str = '\t')[source]

Bases: object

Description:

TransactionalDatabase is class to get stats of database.

Attributes:

param inputFile:: file : input file path
param sep:: str separator in file. Default is tab space.

Methods:

run(): execute readDatabase function
readDatabase(): read database from input file
getDatabaseSize(): get the size of database
getMinimumTransactionLength(): get the minimum transaction length
getAverageTransactionLength(): get the average transaction length. It is sum of all transaction length divided by database length.
getMaximumTransactionLength(): get the maximum transaction length
getStandardDeviationTransactionLength(): get the standard deviation of transaction length
getSortedListOfItemFrequencies(): get sorted list of item frequencies
getSortedListOfTransactionLength(): get sorted list of transaction length
save(data, outputFile): store data into outputFile
getMinimumPeriod(): get the minimum period
getAveragePeriod(): get the average period
getMaximumPeriod(): get the maximum period
getStandardDeviationPeriod(): get the standard deviation period
getNumberOfTransactionsPerTimestamp(): get number of transactions per time stamp. This time stamp range is 1 to max period.

Importing this algorithm into a python program

from PAMI.extras.dbStats import TransactionalDatabase as db

obj = db.TransactionalDatabase(iFile, "     ")

obj.save(oFile)

obj.run()

obj.printStats()

convertDataIntoMatrix() → ndarray[source]

getAverageTransactionLength() → float[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length :rtype: float

getDatabaseSize() → int[source]: get the size of database :return: dataset size :rtype: int

getDensity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getFrequenciesInRange() → dict[source]

getMaximumTransactionLength() → int[source]: get the maximum transaction length :return: maximum transaction length :rtype: int

getMinimumTransactionLength() → int[source]: get the minimum transaction length :return: minimum transaction length :rtype: int

getNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getSortedListOfItemFrequencies() → dict[source]: get sorted list of item frequencies :return: item frequencies :rtype: dict

getSparsity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getStandardDeviationTransactionLength() → float[source]: get the standard deviation transaction length :return: standard deviation transaction length :rtype: float

getTotalNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getTransanctionalLengthDistribution() → dict[source]: Get transaction length :return: a dictionary with transaction length as keys and their total length as values :rtype: dict

getVarianceTransactionLength() → float[source]: get the variance transaction length :return: variance transaction length :rtype: float

plotGraphs(allTicks: bool = False) → None[source]

printStats() → None[source]

readDatabase() → None[source]: read database from input file and store into database and size of each transaction.

run() → None[source]

save(data_: dict, outputFile: str) → None[source]: store data into outputFile :param data_: input data :type data_: dict :param outputFile: output file name or path to store :type outputFile: str :return: None

PAMI.extras.dbStats.UncertainTemporalDatabase module

class PAMI.extras.dbStats.UncertainTemporalDatabase.UncertainTemporalDatabase(inputFile: str, sep: str = '\t')[source]

Bases: object

Description:

UncertainTemporalDatabaseStats is class to get stats of database.

Attributes:

:param inputFilefile: input file path
:param sepstr: separator in file. Default is tab space.

Methods:

run(): execute readDatabase function
readDatabase(): read database from input file
getDatabaseSize(): get the size of database
getMinimumTransactionLength(): get the minimum transaction length
getAverageTransactionLength(): get the average transaction length. It is sum of all transaction length divided by database length.
getMaximumTransactionLength(): get the maximum transaction length
getStandardDeviationTransactionLength(): get the standard deviation of transaction length
getSortedListOfItemFrequencies(): get sorted list of item frequencies
getSortedListOfTransactionLength(): get sorted list of transaction length
save(data, outputFile): store data into outputFile
getMinimumPeriod(): get the minimum period
getAveragePeriod(): get the average period
getMaximumPeriod(): get the maximum period
getStandardDeviationPeriod(): get the standard deviation period
getNumberOfTransactionsPerTimestamp(): get number of transactions per time stamp. This time stamp range is 1 to max period.

Importing this algorithm into a python program

from PAMI.extras.dbStats import UncertainTemporalDatabase as db

obj = db.UncertainTemporalDatabase(iFile, " ")

obj.save(oFile)

obj.run()

obj.printStats()

convertDataIntoMatrix() → ndarray[source]

getAveragePeriod() → float[source]: get the average period. It is sum of all period divided by number of period. :return: average period :rtype: float

getAverageTransactionLength() → float[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length :rtype: float

getDatabaseSize() → int[source]: get the size of database :return: dataset size :rtype: int

getDensity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getFrequenciesInRange() → dict[source]

getMaximumPeriod() → int[source]: get the maximum period :return: maximum period :rtype: int

getMaximumTransactionLength() → int[source]: get the maximum transaction length :return: maximum transaction length :rtype: int

getMinimumPeriod() → int[source]: get the minimum period :return: minimum period :rtype: int

getMinimumTransactionLength() → int[source]: get the minimum transaction length :return: minimum transaction length :rtype: int

getNumberOfTransactionsPerTimestamp() → dict[source]: get number of transactions per time stamp :return: number of transactions per time stamp as dict :rtype: float

getSortedListOfItemFrequencies() → dict[source]: get sorted list of item frequencies :return: item frequencies :rtype: dict

getSparsity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getStandardDeviationPeriod() → float[source]: get the standard deviation period :return: standard deviation period :rtype: float

getStandardDeviationTransactionLength() → float[source]: get the standard deviation transaction length :return: standard deviation transaction length :rtype: float

getTotalNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getTransanctionalLengthDistribution() → dict[source]: get transaction length :return: transactional length :rtype: dict

getVarianceTransactionLength() → float[source]: get the variance transaction length :return: variance transaction length :rtype: float

plotGraphs() → None[source]

printStats() → None[source]

readDatabase() → None[source]: read database from input file and store into database and size of each transaction. And store the period between transactions as list

run() → None[source]

save(data_: dict, outputFile: str) → None[source]: store data into outputFile :param data_: input data :type data_: dict :param outputFile: output file name or path to store :type outputFile: str :return: None

PAMI.extras.dbStats.UncertainTransactionalDatabase module

class PAMI.extras.dbStats.UncertainTransactionalDatabase.UncertainTransactionalDatabase(inputFile: str, sep: str = '\t')[source]

Bases: object

Description:

UncertainTransactionalDatabase is class to get stats of database.

Attributes:

inputFilefile: input file path
sepstr: separator in file. Default is tab space.

Methods:

run(): execute readDatabase function
readDatabase(): read database from input file
getDatabaseSize(): get the size of database
getMinimumTransactionLength(): get the minimum transaction length
getAverageTransactionLength(): get the average transaction length. It is sum of all transaction length divided by database length.
getMaximumTransactionLength(): get the maximum transaction length
getStandardDeviationTransactionLength(): get the standard deviation of transaction length
getVarianceTransactionLength(): get the variance of transaction length
getSparsity(): get the sparsity of database
getSortedListOfItemFrequencies(): get sorted list of item frequencies
getSortedListOfTransactionLength(): get sorted list of transaction length
save(data, outputFile): store data into outputFile

Importing this algorithm into a python program

from PAMI.extras.dbStats import UncertainTransactionalDatabase as db

obj = db.UncertainTransactionalDatabase(iFile, "    ")

obj.save(oFile)

obj.run()

obj.printStats()

convertDataIntoMatrix() → ndarray[source]

getAverageTransactionLength() → float[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length :rtype: float

getDatabaseSize() → int[source]: get the size of database :return: dataset size :rtype: int

getDensity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getFrequenciesInRange() → dict[source]

getMaximumTransactionLength() → int[source]: get the maximum transaction length :return: maximum transaction length :rtype: int

getMinimumTransactionLength() → int[source]: get the minimum transaction length :return: minimum transaction length :rtype: int

getNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getSortedListOfItemFrequencies() → dict[source]: get sorted list of item frequencies :return: item frequencies :rtype: dict

getSparsity() → float[source]: get the sparsity of database. sparsity is percentage of 0 of database. :return: database sparsity :rtype: float

getStandardDeviationTransactionLength() → float[source]: get the standard deviation transaction length :return: standard deviation transaction length :rtype: float

getTotalNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getTransanctionalLengthDistribution() → dict[source]: get transaction length :return: transactional length :rtype: dict

getVarianceTransactionLength() → float[source]: get the variance transaction length :return: variance transaction length :rtype: float

plotGraphs() → None[source]

printStats() → None[source]

readDatabase() → None[source]: read database from input file and store into database and size of each transaction.

run() → None[source]

save(data: dict, outputFile: str) → None[source]: store data into outputFile :param data: input data :type data: dict :param outputFile: output file name or path to store :type outputFile: str :return: None

PAMI.extras.dbStats.UtilityDatabase module

class PAMI.extras.dbStats.UtilityDatabase.UtilityDatabase(inputFile: str | DataFrame, sep: str = '\t')[source]

Bases: object

Description:

UtilityDatabase is class to get stats of database.

Attributes:

param inputFile:: file : input file path
param sep:: str separator in file. Default is tab space.

Importing this algorithm into a python program

from PAMI.extras.dbStats import UtilityDatabase as db

obj = db.UtilityDatabase(iFile, "   " )

obj.save(oFile)

obj.run()

obj.printStats()

creatingItemSets() → None[source]: Storing the complete transactions of the database/input file in a database variable

getAverageTransactionLength() → float[source]: get the average transaction length. It is sum of all transaction length divided by database length. :return: average transaction length :rtype: float

getAverageUtility() → float[source]: get the average utility :return: average utility :rtype: float

getDatabaseSize() → int[source]: get the size of database :return: size of database :rtype: int

getFrequenciesInRange() → dict[source]: This function is used to get the Frequencies in range :return: Frequencies In Range :rtype: dict

getMaximumTransactionLength() → int[source]: get the maximum transaction length :return: maximum transaction length :rtype: int

getMaximumUtility() → int[source]: get the maximum utility :return: integer value of maximum utility :rtype: int

getMinimumTransactionLength() → int[source]: get the minimum transaction length :return: minimum transaction length :rtype: int

getMinimumUtility() → int[source]: get the minimum utility :return: integer value of minimum utility :rtype: int

getNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getSortedListOfItemFrequencies() → dict[source]: get sorted list of item frequencies :return: item frequencies :rtype: dict

getSortedUtilityValuesOfItem() → dict[source]: get sorted utility value each item. key is item and value is utility of item :return: sorted dictionary utility value of item :rtype: dict

getSparsity() → float[source]: get the sparsity of database :return: sparsity of database in floating values :rtype: float

getStandardDeviationTransactionLength() → float[source]: get the standard deviation transaction length :return: standard deviation transaction length :rtype: float

getTotalNumberOfItems() → int[source]: get the number of items in database. :return: number of items :rtype: int

getTotalUtility() → int[source]: get sum of utility :return: total utility :rtype: int

getTransanctionalLengthDistribution() → dict[source]: get transaction length :return: a dictionary of Transaction Length Distribution :rtype: dict

getVarianceTransactionLength() → float[source]: get the variance transaction length :return: variance transaction length :rtype: float

plotGraphs() → None[source]

printStats() → None[source]: This function is used to print the results

readDatabase() → None[source]: read database from input file and store into database and size of each transaction.

run() → None[source]

save(data, outputFile) → None[source]: store data into outputFile :param data: input data :type data: dict :param outputFile: output file name or path to store :type outputFile: str :return: None

PAMI.extras.dbStats package

Submodules

PAMI.extras.dbStats.FuzzyDatabase module

PAMI.extras.dbStats.MultipleTimeSeriesFuzzyDatabaseStats module

Importing this algorithm into a python program

PAMI.extras.dbStats.SequentialDatabase module

PAMI.extras.dbStats.TemporalDatabase module

Importing this algorithm into a python program

PAMI.extras.dbStats.TransactionalDatabase module

Importing this algorithm into a python program

PAMI.extras.dbStats.UncertainTemporalDatabase module

Importing this algorithm into a python program

PAMI.extras.dbStats.UncertainTransactionalDatabase module

Importing this algorithm into a python program

PAMI.extras.dbStats.UtilityDatabase module

Importing this algorithm into a python program

Module contents