# StablePeriodicPatternMining Class for Mining Stable Periodic Patterns
#
# **Importing and Using the StablePeriodicPatternMining Class in a Python Program**
#
# from geoanalytics.patternMining import StablePeriodicPatternMining
#
# miner = StablePeriodicPatternMining("data/input.txt")
#
# miner.run(minSupport=3, maxPer=10, maxLa=5)
#
__copyright__ = """
Copyright (C) 2022 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/>.
"""
import pandas as pd
from PAMI.extras.dbStats.TemporalDatabase import TemporalDatabase
from PAMI.stablePeriodicFrequentPattern.basic import SPPGrowth
from .abstract import PatternMiner
[docs]
class StablePeriodicPatternMining(PatternMiner):
"""
**About this algorithm**
:**Description**:
This module implements the **SPPGrowth algorithm** for mining **stable periodic frequent patterns**
from temporal databases. It discovers itemsets that appear frequently with stable periodicity
under given constraints on maximum period and maximum latency.
:**Parameters**:
- `inputFile` (*str*): Path to the temporal transactional database file.
:**Attributes**:
- **inputFile** (*str*): The temporal database file provided during object instantiation.
- **miner** (*SPPGrowth*): Instance of the SPPGrowth algorithm from the PAMI library.
**Execution methods**
**Calling from a Python program**
.. code-block:: python
from geoanalytics.patternMining import StablePeriodicPatternMining
miner = StablePeriodicPatternMining("data/input.txt")
miner.run(minSupport=3, maxPer=10, maxLa=5)
**Credits**
Written by M. Charan Teja, under the guidance of Professor Rage Uday Kiran.
"""
def _create_database(self):
"""
Internal method to initialize the temporal database.
Returns:
TemporalDatabase: Temporal database object from the PAMI library.
"""
return TemporalDatabase(self.inputFile)
[docs]
def run(self, minSupport: int, maxPer: int, maxLa: int):
"""
Runs the SPPGrowth algorithm to mine stable periodic patterns.
Args:
minSupport (int): Minimum support threshold for patterns.
maxPer (int): Maximum period allowed for the patterns.
maxLa (int): Maximum latency allowed for the patterns.
Output:
Prints the discovered stable periodic patterns to the console.
"""
self.miner = SPPGrowth.SPPGrowth(inputFile=self.inputFile, minSup=minSupport, maxPer=maxPer, maxLa=maxLa)
self.miner.mine()
self.miner.printResults()