'''
MIT License
Copyright (c) [2022] [Temitope Ajayi]
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
'''
import numpy as np
import os
import pandas as pd
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class Experiment(object):
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def __init__(self, filelocation, filetitle):
"""Initialization of Parameters
Parameters
-----------
file_location : string
Location of results file on system
file_title : string
Title or name of the file. Example is 'kddconc.tec' or 'OUTPUT.csv'
Returns
--------
"""
self.filelocation = filelocation
os.chdir(self.filelocation)
self.filetitle = filetitle
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def read_file(self):
""" Read file specified in file_location and file_title
Parameters
-----------
Returns
--------
data_table : pd.Dataframe
Dataframe with requested output
"""
os.chdir(self.filelocation)
data_table = pd.read_csv(self.filetitle)
return data_table
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def get_column_names(self):
""" Get column names from data table
Parameters
-----------
Returns
--------
column_names : list
column names in file
"""
df = self.read_file()
column_names = df.columns
return column_names
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def get_times(self):
""" Get times stored for duration of the simulation
Parameters
-----------
Returns
--------
unprocessed_time_data : list
Time data directly from file without processing.
"""
df = self.read_file()
unprocessed_time_data = df['Time']
unprocessed_time_data = list(unprocessed_time_data)
unprocessed_time_data = unprocessed_time_data[1:]
unprocessed_time_data = np.array(unprocessed_time_data, float)
return unprocessed_time_data
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def get_timeseries_data(self, param):
""" Get Time series data
Parameters
-----------
param: string
Parameter to be derived from data
Returns
--------
final_timeseries_data : list
Time series data for particular parameter.
"""
df = self.read_file()
final_timeseries_data = df[param]
final_timeseries_data = list(final_timeseries_data)
final_timeseries_data = final_timeseries_data[1:]
final_timeseries_data = np.array(final_timeseries_data, float)
return final_timeseries_data