# HighUtilityGeoreferencedFrequentPatternMining Class for Mining High Utility Georeferenced Frequent Patterns
#
# **Importing and Using the HighUtilityGeoreferencedFrequentPatternMining Class in a Python Program**
#
# from geoanalytics.patternMining import HighUtilityGeoreferencedFrequentPatternMining
#
# miner = HighUtilityGeoreferencedFrequentPatternMining("data/input.txt")
#
# miner.run(minSupport=3, minUtil=50, nFile="data/neighbor.txt")
#
__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.UtilityDatabase import UtilityDatabase
from PAMI.highUtilityGeoreferencedFrequentPattern.basic import SHUFIM
from .abstract import PatternMiner
[docs]
class HighUtilityGeoreferencedFrequentPatternMining(PatternMiner):
"""
**About this algorithm**
:**Description**:
This module implements the **SHUFIM algorithm** for mining **high utility georeferenced frequent patterns**
from utility transactional datasets enriched with spatial information. It extends high utility pattern mining
by integrating geospatial neighborhood data through a neighborhood file.
This approach is useful in spatial data mining applications where both utility and location influence pattern
discovery, such as in retail location analysis or geographic resource optimization.
:**Parameters**:
- `inputFile` (*str*): Path to the utility transactional database file.
- `nFile` (*str*): Path to the neighborhood file specifying spatial relationships.
:**Attributes**:
- **inputFile** (*str*): The utility transactional input file provided during object instantiation.
- **miner** (*SHUFIM*): Instance of the SHUFIM algorithm from the PAMI library.
**Execution methods**
**Calling from a Python program**
.. code-block:: python
from geoanalytics.patternMining import HighUtilityGeoreferencedFrequentPatternMining
miner = HighUtilityGeoreferencedFrequentPatternMining("data/input.txt")
miner.run(minSupport=3, minUtil=50, nFile="data/neighbor.txt")
**Credits**
Written by M. Charan Teja, under the guidance of Professor Rage Uday Kiran.
"""
def _create_database(self):
"""
Internal method to initialize the utility transactional database.
Returns:
UtilityDatabase: Utility transactional database object from the PAMI library.
"""
return UtilityDatabase(self.inputFile)
[docs]
def run(self, minSupport: int, minUtil: int, nFile: str):
"""
Executes the SHUFIM algorithm to mine high utility georeferenced frequent patterns.
Args:
minSupport (int): Minimum support threshold for frequent itemsets.
minUtil (int): Minimum utility threshold to identify high utility patterns.
nFile (str): Path to the neighborhood file containing spatial proximity information.
Output:
Prints the discovered high utility georeferenced frequent patterns to the console.
"""
self.miner = SHUFIM.SHUFIM(iFile=self.inputFile, minSup=minSupport, minUtil=minUtil, nFile=nFile)
self.miner.mine()
self.miner.printResults()