notebook.community



In [1]:

    
%cat 0Source_Citation.txt









    



Source and citation

- This notebook is a part of the `pytheos` package.
- Website: http://github.com/SHDShim/pytheos.
- How to cite: S.-H. Shim (2017) Pytheos - a python tool set for equations of state. DOI: 10.5281/zenodo.802392



In [2]:

    
%matplotlib inline
# %matplotlib notebook # for interactive

For high dpi displays.



In [3]:

    
%config InlineBackend.figure_format = 'retina'

0. General note

This example compares pressure calculated from pytheos and original publication for the MgO scale by Jamieson 1983.

1. Global setup



In [4]:

    
import matplotlib.pyplot as plt
import numpy as np
from uncertainties import unumpy as unp
import pytheos as eos

3. Compare



In [5]:

    
eta = np.linspace(0., 0.26, 53)
print(eta)









    



[0.    0.005 0.01  0.015 0.02  0.025 0.03  0.035 0.04  0.045 0.05  0.055
 0.06  0.065 0.07  0.075 0.08  0.085 0.09  0.095 0.1   0.105 0.11  0.115
 0.12  0.125 0.13  0.135 0.14  0.145 0.15  0.155 0.16  0.165 0.17  0.175
 0.18  0.185 0.19  0.195 0.2   0.205 0.21  0.215 0.22  0.225 0.23  0.235
 0.24  0.245 0.25  0.255 0.26 ]



In [6]:

    
jamieson_mgo = eos.periclase.Jamieson1982()



In [7]:

    
jamieson_mgo.print_equations()









    



P_static: Jamieson
P_thermal: Constq
P_anharmonic: None
P_electronic: None



In [8]:

    
jamieson_mgo.print_parameters()









    



Static:  OrderedDict([('rho0', 3.585+/-0), ('c0', 6.597+/-0), ('s', 1.369+/-0)])
Thermal:  OrderedDict([('v0', 74.67451012663052+/-0.001), ('gamma0', 1.32+/-0), ('q', 1.0+/-0), ('theta0', 760.0+/-0)])
Anharmonic: None
Electronic: None



In [9]:

    
v0 = 74.67451012663052



In [10]:

    
jamieson_mgo.three_r









    Out[10]:





24.939153588000003



In [11]:

    
v = v0 * (1.-eta) 
temp = 1500.



In [12]:

    
p = jamieson_mgo.cal_p(v, temp * np.ones_like(v))



In [13]:

    
print('for T = ', temp)
for eta_i, p_i in zip(eta, p):
    print("{0: .3f} {1: .2f}".format(eta_i, p_i))









    



for T =  1500.0
 0.000  6.61+/-0.00
 0.005  7.39+/-0.00
 0.010  8.19+/-0.00
 0.015  9.01+/-0.00
 0.020  9.86+/-0.00
 0.025  10.73+/-0.00
 0.030  11.62+/-0.00
 0.035  12.54+/-0.00
 0.040  13.48+/-0.00
 0.045  14.45+/-0.00
 0.050  15.45+/-0.00
 0.055  16.48+/-0.00
 0.060  17.53+/-0.00
 0.065  18.62+/-0.00
 0.070  19.73+/-0.00
 0.075  20.88+/-0.00
 0.080  22.06+/-0.00
 0.085  23.28+/-0.00
 0.090  24.53+/-0.00
 0.095  25.81+/-0.00
 0.100  27.14+/-0.00
 0.105  28.50+/-0.00
 0.110  29.90+/-0.00
 0.115  31.34+/-0.00
 0.120  32.82+/-0.00
 0.125  34.35+/-0.00
 0.130  35.92+/-0.00
 0.135  37.53+/-0.00
 0.140  39.20+/-0.00
 0.145  40.91+/-0.00
 0.150  42.68+/-0.00
 0.155  44.49+/-0.00
 0.160  46.37+/-0.00
 0.165  48.29+/-0.00
 0.170  50.28+/-0.00
 0.175  52.33+/-0.00
 0.180  54.44+/-0.00
 0.185  56.61+/-0.00
 0.190  58.85+/-0.00
 0.195  61.16+/-0.00
 0.200  63.55+/-0.00
 0.205  66.00+/-0.00
 0.210  68.54+/-0.00
 0.215  71.15+/-0.00
 0.220  73.85+/-0.00
 0.225  76.64+/-0.00
 0.230  79.51+/-0.00
 0.235  82.48+/-0.00
 0.240  85.55+/-0.00
 0.245  88.71+/-0.00
 0.250  91.98+/-0.00
 0.255  95.36+/-0.00
 0.260  98.86+/-0.00



In [14]:

    
v = jamieson_mgo.cal_v(p, temp * np.ones_like(p))
print(1.-(v/v0))









    



[0.    0.005 0.01  0.015 0.02  0.025 0.03  0.035 0.04  0.045 0.05  0.055
 0.06  0.065 0.07  0.075 0.08  0.085 0.09  0.095 0.1   0.105 0.11  0.115
 0.12  0.125 0.13  0.135 0.14  0.145 0.15  0.155 0.16  0.165 0.17  0.175
 0.18  0.185 0.19  0.195 0.2   0.205 0.21  0.215 0.22  0.225 0.23  0.235
 0.24  0.245 0.25  0.255 0.26 ]