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plotter.py
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plotter.py
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import os
import pandas as pd
import matplotlib.pyplot as plt
import scipy.constants as sp
import numpy as np
def plot_relation(variable_to_plot, folder_name):
"""
Plot pressure against another variable from the simulation data as exported from the simulate Tracker method
All data files must be in a single folder and end with 'Quantities.csv'
Also plots the theoretical pressure from the ideal gas law
variable_to_plot - str value that accepts: 'Temperature','Volume, 'Inverse Volume',
'Number of particles', 'Number of collisions
folder_name - str value of the folder name in the directory of this file containing the simulation data
"""
plt.rcParams.update({'font.size': 25})
if variable_to_plot == 'Inverse Volume':
variable = 'Volume'
else:
variable = variable_to_plot
# Read data files as DataFrames
directory = 'C:\\Users\\wardi\\Documents\\Uni\\OneDrive - Lancaster University\\Year 4\\Computer Modelling\\Kinetic Gas\\phys389-2021-project-Wardi0-1\\' + folder_name
simulation_quantities = []
for entry in os.scandir(directory):
if entry.path.endswith("Quantities.csv") and entry.is_file():
simulation_quantities.append(pd.read_csv(entry,index_col=0))
# Extract the pressure and relevant variable from the DataFrames
pressures = []
variables = []
for simulation in simulation_quantities:
pressures.append(simulation.loc['Pressure'][0])
variables.append(simulation.loc[variable][0])
# Plot the relations for the chosen variable
if variable_to_plot == 'Temperature':
volume = simulation_quantities[0].loc['Volume'][0]
number = simulation_quantities[0].loc['Number of particles'][0]
x = np.linspace(0,max(variables)*1.1,1000)
y = number * sp.Boltzmann * x / volume
plt.scatter(variables,pressures,color='k',label='Simulation Data',zorder=20)
plt.title('$N$='+str(int(number))+', $V$='+str(volume)+'$m^{3}$')
plt.xlabel('Temperature ($K$)')
plt.plot(x,y,color='r',label='Theoretical Values')
elif variable_to_plot == 'Number of particles':
volume = simulation_quantities[0].loc['Volume'][0]
temperature = simulation_quantities[0].loc['Temperature'][0]
x = np.linspace(0,max(variables)*1.1,1000)
y = temperature * sp.Boltzmann * x / volume
plt.scatter(variables,pressures,color='k',label='Simulation Data',zorder=20)
plt.title('$V$='+str(volume)+'$m^{3}$, $T$='+str(round(temperature,3))+'K')
plt.xlabel('Number of Particles')
plt.plot(x,y,color='r',label='Theoretical Values')
elif variable_to_plot == 'Inverse Volume':
# Linear in 1/V so change data
variables = np.array(variables)
x = np.linspace(0,max(1/variables)*1.1,1000)
number = simulation_quantities[0].loc['Number of particles'][0]
temperature = simulation_quantities[0].loc['Temperature'][0]
y = temperature * number * sp.Boltzmann * x
inverse_V = 1/np.array(variables)
plt.scatter(inverse_V, pressures,color='k',label='Simulation Data',zorder=20)
plt.title('$N$='+str(int(number))+', $T$='+str(round(temperature,3))+'K')
plt.xlabel('Volume$^{-1}$ ($m^{-3}$)')
plt.plot(x,y,color='r',label='Theoretical Values')
elif variable_to_plot == 'Volume':
number = simulation_quantities[0].loc['Number of particles'][0]
temperature = simulation_quantities[0].loc['Temperature'][0]
x = np.linspace(min(variables)*0.95,max(variables)*1.1,1000)
y = temperature * sp.Boltzmann * number / x
plt.scatter(variables,pressures,color='k',label='Simulation Data',zorder=20)
plt.xlim(0,max(variables)*1.15)
plt.title('$N$='+str(int(number))+', $T$='+str(round(temperature,3))+'K')
plt.xlabel('Volume ($m^{3}$)')
plt.plot(x,y,color='r',label='Theoretical Values')
elif variable_to_plot == 'Number of collisions':
volume = simulation_quantities[0].loc['Volume'][0]
number = simulation_quantities[0].loc['Number of particles'][0]
temperature = simulation_quantities[0].loc['Temperature'][0]
x = np.linspace(0,max(variables)*1.1,10)
y = np.array([temperature * sp.Boltzmann * number / volume]*10)
plt.plot(x,y,color='r',label='Theoretical Value')
plt.scatter(variables,pressures,color='k',label='Simulation Data',zorder=20)
plt.xlim(0,max(variables)*1.15)
plt.title('$N$='+str(int(number))+', $V$='+str(volume)+'$m^{3}$, $T$='+str(round(temperature,3))+'K')
plt.xlabel('Number of collisions')
plt.ylabel('Pressure ($Pa$)')
plt.legend()
plt.grid()
plt.show()