import numpy as np

import matplotlib.pyplot as plt

# Constants for R$134-$a

w$1=-7\mathrm{.}59884$

w$2=1\mathrm{.}48886$

w$3=-3\mathrm{.}79873$

w$4=1\mathrm{.}81379$

# Critical point values

Pc $=40\mathrm{.}6*1$e$5$ # Convert bar to Pa

Tc $=374\mathrm{.}2$ # Celsius

# Reduced temperature range

Tr$\_$range $=$ np$.$linspace$(0\mathrm{.}5,1\mathrm{.}5,100)$

# Calculate reduced pressure using Wagner's correlation

Pr$\_$predicted $=$ np$.$exp$(($w$1(1-$ Tr$\_$range$)+$ w$2(1-$ Tr$\_$range$)**1\mathrm{.}5+$ w$3(1-$ Tr$\_$range$)*3+$ w$4(1-$ Tr$\_$range$)*6)/$ Tr$\_$range$)$

# Hypothetical data points from Appendix B $($replace with actual data$)$

T$\_$data $=[300,320,340,360,380]$

P$\_$data $=[100000,80000,60000,40000,20000]$

# Plotting

plt$.$figure$($figsize$=(10,6))$

plt$.$plot$($Tc Tr$\_$range, Pc Pr$\_$predicted, label$=$"Wagner's Correlation"$)$

plt$.$scatter$($T$\_$data, P$\_$data, marker$=\text{'}$o$\text{'},$ color$=$'red', label$=$'Data from Table'$)$

# Set labels and title

plt$.$xlabel$(\text{'}$Temperature $($K$)\text{'})$

plt$.$ylabel$(\text{'}$Pressure $($Pa$)\text{'})$

plt$.$title$(\text{'}$Comparison of Wagner$\backslash \text{'}$s Correlation with Data from Table for R$134-$a$\text{'})$

plt$.$legend$()$

# Choose the scale that gives the best depiction of the information

plt$.$xscale$(\text{'}$log$\text{'})$ # Log scale for temperature

plt$.$grid$($True$)$

plt$.$show$()$