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#2 updated the file plotLineGraphsFromDataFrame.py #555

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Dec 3, 2024
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#2 updated the file plotLineGraphsFromDataFrame.py #555

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156 changes: 94 additions & 62 deletions PAMI/extras/graph/plotLineGraphsFromDataFrame.py
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Original file line number Diff line number Diff line change
@@ -1,17 +1,29 @@
# plotLineGraphFromDataFrame is used to convert the given dataframe into plotLineGraph.
# plotLineGraphsFromDataFrame is used to convert the given dataframe into a Line Graph.
#
# **Importing this algorithm into a python program**
# --------------------------------------------------------
#
# from PAMI.extras.graph import plotLineGraphsFromDataFrame as plt
#
# obj = plt.plotLineGraphsFromDictionary(idf)
# dataFrame = pd.DataFrame(data)
#
# obj.save()
# obj = plt.plotLineGraphsFromDataFrame(dataFrame)
#
# obj.plot(result=dataFrame, xaxis='minSup', yaxis='patterns', label='algorithm')
#
# obj.plot(result=dataFrame, xaxis='minSup', yaxis='runtime', label='algorithm')
#
# obj.plot(result=dataFrame, xaxis='minSup', yaxis='memoryRSS', label='algorithm')
#
# obj.plot(result=dataFrame, xaxis='minSup', yaxis='memoryUSS', label='algorithm')
#
# obj.save(result=dataFrame, xaxis='minSup', yaxis='patterns', label='algorithm', oFile='patterns.png')
#
# obj.save(result=dataFrame, xaxis='minSup', yaxis='runtime', label='algorithm', oFile='runtime.png')
#
# obj.save(result=dataFrame, xaxis='minSup', yaxis='memoryRSS', label='algorithm', oFile='memoryRSS.png')
#
# obj.save(result=dataFrame, xaxis='minSup', yaxis='memoryUSS', label='algorithm', oFile='memoryUSS.png')
#





__copyright__ = """
Expand All @@ -32,69 +44,89 @@
"""

import matplotlib.pyplot as plt
import pandas as _pd
import sys
import pandas as pd


class plotGraphsFromDataFrame():
class plotLineGraphsFromDataFrame:
"""
plotLineGraphFromDataFrame is used to convert the given dataframe into plotLineGraph.
A class to generate and save line graphs from a given DataFrame.

:Attributes:

:param dataFrame : DataFrame
store input data as DataFrame
dataFrame (pd.DataFrame): Input DataFrame to generate graphs.

:Methods:

plotLineGraphFromDatFrame()
draw line graph of input data. input data's key is x and value is y.

**Importing this algorithm into a python program**
--------------------------------------------------------
.. code-block:: python

from PAMI.extras.graph import plotLineGraphsFromDataframe as plt

obj = plt.plotLineGraphsFromDataFrame(idf)

obj.save()
plot(result, xaxis, yaxis, label): Plots a line graph based on the specified axes.
save(result, xaxis, yaxis, label, oFile): Saves the line graph to the specified file.
"""

def __init__(self, dataFrame: _pd.DataFrame) -> None:

self._dataFrame = dataFrame

def plotGraphsFromDataFrame(self) -> None:
self._dataFrame.plot(x='minSup', y='patterns', kind='line')
def __init__(self, dataFrame: pd.DataFrame) -> None:
"""
Initialize the class with a DataFrame.

:param dataFrame: Input DataFrame
"""
self.dataFrame = dataFrame

def plot(self, result: pd.DataFrame, xaxis: str, yaxis: str, label: str) -> None:
"""
Plots a line graph.

:param result: Input DataFrame
:param xaxis: Column name for the x-axis
:param yaxis: Column name for the y-axis
:param label: Column name to use for legend labels
"""
plt.figure()
for key, grp in result.groupby(label):
plt.plot(grp[xaxis], grp[yaxis], label=f"{label}: {key}")
plt.xlabel(xaxis)
plt.ylabel(yaxis)
plt.title(f"{yaxis} vs {xaxis}")
plt.legend()
plt.show()
print('Graph for No Of Patterns is successfully generated!')
self._dataFrame.plot(x='minSup', y='runtime', kind='line')
plt.show()
print('Graph for Runtime taken is successfully generated!')
self._dataFrame.plot(x='minSup', y='memory', kind='line')
plt.show()
print('Graph for memory consumption is successfully generated!')




if __name__ == '__main__':
#data = {'algorithm': ['FPGrowth','FPGrowth', 'FPGrowth', 'FPGrowth', 'FPGrowth', 'ECLAT', 'ECLAT', 'ECLAT', 'ECLAT', 'ECLAT'],
# 'minSup': [0.01, 0.02, 0.03, 0.04, 0.05, 0.01, 0.02, 0.03, 0.04, 0.05],
# 'patterns': [386, 155, 60, 36, 10, 386, 155, 60, 26, 10],
# 'runtime': [7.351629, 4.658654 , 4.658654 , 1.946843, 1.909376, 4.574833, 2.514252, 1.834948, 1.889892, 1.809999],
# 'memory': [426545152, 309182464, 241397760, 225533952, 220950528, 233537536, 267165696, 252841984, 245690368,
# 295710720]
# }
print(f"Graph for {yaxis} vs {xaxis} is successfully generated!")

def save(self, result: pd.DataFrame, xaxis: str, yaxis: str, label: str, oFile: str) -> None:
"""
Saves the line graph to a file.

:param result: Input DataFrame
:param xaxis: Column name for the x-axis
:param yaxis: Column name for the y-axis
:param label: Column name to use for legend labels
:param oFile: Output file name to save the graph
"""
plt.figure()
for key, grp in result.groupby(label):
plt.plot(grp[xaxis], grp[yaxis], label=f"{label}: {key}")
plt.xlabel(xaxis)
plt.ylabel(yaxis)
plt.title(f"{yaxis} vs {xaxis}")
plt.legend()
plt.savefig(oFile)
plt.close()
print(f"Graph saved as {oFile}!")

if __name__ == "__main__":
# Example DataFrame
data = {
'algorithm': ['FPGrowth', 'FPGrowth', 'FPGrowth', 'FPGrowth', 'FPGrowth'],
'minSup': [0.01, 0.02, 0.03, 0.04, 0.05],
'patterns': [386, 155, 60, 36, 10],
'runtime': [7.351629, 4.658654, 4.658654, 1.946843, 1.909376],
'memory': [426545152, 309182464, 241397760, 225533952, 220950528]
}
dataFrame = _pd.DataFrame(data)
ab = plotGraphsFromDataFrame(dataFrame)
ab.plotGraphsFromDataFrame()
obj = plotGraphsFromDataFrame(sys.argv[1])
obj.plotGraphsFromDataFrame(sys.argv[2])
'minSup': [0.01, 0.02, 0.03, 0.01, 0.02],
'patterns': [386, 155, 60, 386, 155],
'runtime': [7.35, 4.66, 4.66, 4.57, 2.51],
'memoryRSS': [426545152, 309182464, 241397760, 233537536, 267165696],
'memoryUSS': [426545152, 309182464, 241397760, 233537536, 267165696]
}
dataFrame = pd.DataFrame(data)

obj = plotLineGraphsFromDataFrame(dataFrame)

obj.plot(result=dataFrame, xaxis='minSup', yaxis='patterns', label='algorithm')
obj.plot(result=dataFrame, xaxis='minSup', yaxis='runtime', label='algorithm')
obj.plot(result=dataFrame, xaxis='minSup', yaxis='memoryRSS', label='algorithm')
obj.plot(result=dataFrame, xaxis='minSup', yaxis='memoryUSS', label='algorithm')

obj.save(result=dataFrame, xaxis='minSup', yaxis='patterns', label='algorithm', oFile='patterns.png')
obj.save(result=dataFrame, xaxis='minSup', yaxis='runtime', label='algorithm', oFile='runtime.png')
obj.save(result=dataFrame, xaxis='minSup', yaxis='memoryRSS', label='algorithm', oFile='memoryRSS.png')
obj.save(result=dataFrame, xaxis='minSup', yaxis='memoryUSS', label='algorithm', oFile='memoryUSS.png')