from __future__ import division, print_function
import matplotlib
matplotlib.use('Agg') # Use a non-GUI backend
import numpy as np, matplotlib.pyplot as plt

import CoolProp
CP = CoolProp.CoolProp

fluid = 'R1130(E)'

fig, ax = plt.subplots()
plt.ylim(10**-18, 10**2)

not_in_REFPROP = False
try:
    if CP.get_fluid_param_string(fluid, "REFPROP_name") == 'N/A':
        not_in_REFPROP = True
    else:
        RPfluid = 'REFPROP::'  + CP.get_fluid_param_string(fluid, "REFPROP_name")
        CAS = CP.get_fluid_param_string(RPfluid, "CAS")
except (RuntimeError,ValueError) as E:
    not_in_REFPROP = True

if not_in_REFPROP:
    ax.set_xlim(0,1)
    xlims = ax.get_xlim()
    ylims = ax.get_ylim()
    ax.plot([xlims[0],xlims[1]],[ylims[0],ylims[1]],lw = 3,c = 'r')
    ax.plot([xlims[0],xlims[1]],[ylims[1],ylims[0]],lw = 3,c = 'r')

    x = 0.5
    y = (ylims[0]*ylims[1])**0.5

    ax.text(x,y,'Not\nin\nREFPROP',ha='center',va ='center',bbox = dict(fc = 'white'))
else:
    RPfluid = 'REFPROP::'  + CP.get_fluid_param_string(fluid, "REFPROP_name")
    symbols = ["o", "v", "^", "<", ">","8", "s","p","*","h","H","+","x"]

    T = np.min([1.01*CP.PropsSI(fluid, 'Tcrit'),CP.PropsSI(fluid, 'Tmax')])
    rhoc = CP.PropsSI(fluid, 'rhomolar_critical')

    # Normal properties
    rho = np.linspace(1e-10, 2*rhoc)
    normalkeys = ['P','V','L','Cpmolar','Cvmolar']
    RPdata = CP.PropsSI(normalkeys, 'T', T, 'Dmolar', rho, RPfluid)
    CPdata = CP.PropsSI(normalkeys, 'T', T, 'Dmolar', rho, fluid)
    for i, key in enumerate(normalkeys):
        plt.plot(rho/rhoc, np.abs(RPdata[:,i]/CPdata[:,i]-1)*100, lw = 0, label = key, marker = symbols[i%len(symbols)])

    # Special properties
    rho = np.linspace(1e-10, 2*rhoc)
    keys = ['Hmolar','Smolar']
    for i, key in enumerate(keys):
        RPdata = CP.PropsSI(key, 'T', T, 'Dmolar', rho, RPfluid) - CP.PropsSI(key, 'T', T, 'Dmolar', 1, RPfluid)
        CPdata = CP.PropsSI(key, 'T', T, 'Dmolar', rho, fluid) - CP.PropsSI(key, 'T', T, 'Dmolar', 1, fluid)
        plt.plot(rho/rhoc, np.abs(RPdata/CPdata-1)*100, lw = 0, label = key, marker = symbols[(i+len(normalkeys))%len(symbols)])

    ax.legend(loc='best', ncol = 2)

plt.xlabel(r'Reduced density [$\rho/\rho_c$]')
plt.ylabel(r'Relative deviation $(y_{CP}/y_{RP}-1)\times 100$ [%]')

ax.set_yscale('log')
plt.title('Comparison between CoolProp and REFPROP(10.0) along T = 1.01*Tc')
plt.savefig(fluid+'.png', dpi = 100)
plt.savefig(fluid+'.pdf')
plt.close('all')