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change around convert to get memory and runtime
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suzuki-zudai committed Oct 11, 2024
1 parent f72a6d5 commit fbabe8e
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68 changes: 66 additions & 2 deletions PAMI/extras/convert/DF2DB.py
Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@
"""
import PAMI.extras.convert.denseDF2DB as dense
import PAMI.extras.convert.sparseDF2DB as sparse
import sys
import sys,psutil,os,time
from typing import Union

class DF2DB:
Expand All @@ -54,6 +54,14 @@ class DF2DB:
It is condition of all item
:param DFtype: str :
It is DataFrame type. It should be sparse or dense. Default DF is sparse.
:param memoryUSS : float
To store the total amount of USS memory consumed by the program
:param memoryRSS : float
To store the total amount of RSS memory consumed by the program
:param startTime : float
To record the start time of the mining process
endTime : float
To record the completion time of the mining process
**Importing this algorithm into a python program**
Expand Down Expand Up @@ -81,6 +89,11 @@ def __init__(self, inputDF, DFtype='dense') -> None:
self.DF2DB = dense.denseDF2DB(self.inputDF)
else:
raise Exception('DF type should be sparse or dense')
self._startTime = float()
self._endTime = float()
self._memoryUSS = float()
self._memoryRSS = float()

def convert2TransactionalDatabase(self, oFile: str, condition: str, thresholdValue: Union[int, float]) -> str:
"""
create transactional database and return oFileName
Expand All @@ -89,7 +102,12 @@ def convert2TransactionalDatabase(self, oFile: str, condition: str, thresholdVal
:return: oFile name
:rtype: str
"""
self._startTime = time.time()
self.DF2DB.convert2TransactionalDatabase(oFile,condition,thresholdValue)
process = psutil.Process(os.getpid())
self._memoryUSS = process.memory_full_info().uss
self._memoryRSS = process.memory_info().rss
self._endTime = time.time()
return self.DF2DB.getFileName()

def convert2TemporalDatabase(self, oFile: str, condition: str, thresholdValue: Union[int, float]) -> str:
Expand All @@ -100,7 +118,12 @@ def convert2TemporalDatabase(self, oFile: str, condition: str, thresholdValue: U
:return: oFile name
:rtype: str
"""
self._startTime = time.time()
self.DF2DB.convert2TemporalDatabase(oFile,condition,thresholdValue)
process = psutil.Process(os.getpid())
self._memoryUSS = process.memory_full_info().uss
self._memoryRSS = process.memory_info().rss
self._endTime = time.time()
return self.DF2DB.getFileName()

def convert2UtilityDatabase(self, oFile: str) -> str:
Expand All @@ -111,10 +134,51 @@ def convert2UtilityDatabase(self, oFile: str) -> str:
:return: outputFile name
:rtype: str
"""
self._startTime = time.time()
self.DF2DB.convert2UtilityDatabase(oFile)
process = psutil.Process(os.getpid())
self._memoryUSS = process.memory_full_info().uss
self._memoryRSS = process.memory_info().rss
self._endTime = time.time()
return self.DF2DB.getFileName()

def getMemoryUSS(self) -> float:
"""
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
"""

return self._memoryUSS

def getMemoryRSS(self) -> float:
"""
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
"""

return self._memoryRSS

def getRuntime(self) -> float:
"""
Calculating the total amount of runtime taken by the mining process
:return: returning total amount of runtime taken by the mining process
:rtype: float
"""

return self._endTime - self._startTime



if __name__ == '__main__':
obj = DF2DB(sys.argv[1])
obj.getTransactionalDatabase(sys.argv[2],sys.argv[3],sys.argv[4])
obj.getTransactionalDatabase(sys.argv[2],sys.argv[3],sys.argv[4])
print("Conversion is complete.")
print("Total Memory in USS:", obj.getMemoryUSS())
print("Total Memory in RSS", obj.getMemoryRSS())
print("Total ExecutionTime in ms:", obj.getRuntime())
120 changes: 120 additions & 0 deletions PAMI/extras/convert/_DF2DB.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,120 @@
# DF2DB in this code dataframe is converting databases into sparse or dense transactional, temporal, Utility.
#
#
# **Importing this algorithm into a python program**
# --------------------------------------------------------
#
# from PAMI.extras.DF2DB import DF2DB as db
#
# obj = db.DF2DB(idf, "sparse/dense")
#
# obj.convert2Transactional("outputFileName", ">=", 16) # To create transactional database
#
# obj.convert2Temporal("outputFileName", ">=", 16) # To create temporal database
#
# obj.convert2Utility("outputFileName") # To create utility database
#




__copyright__ = """
Copyright (C) 2021 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 PAMI.extras.convert.denseDF2DB as dense
import PAMI.extras.convert.sparseDF2DB as sparse
import sys
from typing import Union

class DF2DB:
"""
:Description: This class will create database for given DataFrame based on Threshold values and conditions are defined in the class.
Converts Dataframe into sparse or dense dataframes.
:Attributes:
:param inputDF: DataFrame :
It is sparse or dense DataFrame
:param thresholdValue: int or float :
It is threshold value of all item
:param condition: str :
It is condition of all item
:param DFtype: str :
It is DataFrame type. It should be sparse or dense. Default DF is sparse.
**Importing this algorithm into a python program**
--------------------------------------------------------
.. code-block:: python
from PAMI.extras.DF2DB import DF2DB as db
obj = db.DF2DB(idf, "sparse/dense")
obj.convert2Transactional("outputFileName",condition,threshold) # To create transactional database
obj.convert2Temporal("outputFileName",condition,threshold) # To create temporal database
obj.convert2Utility("outputFileName",condition,threshold) # To create utility database
""",


def __init__(self, inputDF, DFtype='dense') -> None:
self.inputDF = inputDF
self.DFtype = DFtype.lower()
if DFtype == 'sparse':
self.DF2DB = sparse.sparseDF2DB(self.inputDF)
elif DFtype == 'dense':
self.DF2DB = dense.denseDF2DB(self.inputDF)
else:
raise Exception('DF type should be sparse or dense')
def convert2TransactionalDatabase(self, oFile: str, condition: str, thresholdValue: Union[int, float]) -> str:
"""
create transactional database and return oFileName
:param oFile: file name or path to store database
:type oFile: str
:return: oFile name
:rtype: str
"""
self.DF2DB.convert2TransactionalDatabase(oFile,condition,thresholdValue)
return self.DF2DB.getFileName()

def convert2TemporalDatabase(self, oFile: str, condition: str, thresholdValue: Union[int, float]) -> str:
"""
create temporal database and return oFile name
:param oFile: file name or path to store database
:type oFile: str
:return: oFile name
:rtype: str
"""
self.DF2DB.convert2TemporalDatabase(oFile,condition,thresholdValue)
return self.DF2DB.getFileName()

def convert2UtilityDatabase(self, oFile: str) -> str:
"""
create utility database and return oFile name
:param oFile: file name or path to store database
:type oFile: str
:return: outputFile name
:rtype: str
"""
self.DF2DB.convert2UtilityDatabase(oFile)
return self.DF2DB.getFileName()


if __name__ == '__main__':
obj = DF2DB(sys.argv[1])
obj.getTransactionalDatabase(sys.argv[2],sys.argv[3],sys.argv[4])
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