#!/usr/bin/env python3
import argparse
import os
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import BPoly, LSQUnivariateSpline, UnivariateSpline, interp1d
from scipy.optimize import fsolve, leastsq
kb = 1.3806488e-23 # J K^-1
kb_ev = 8.6173324e-05 # eV K^-1
h = 6.62606957e-34 # J.s
h_ev = 4.135667516e-15 # eV s
hb = 1.054571726e-34 # J.s
hb_ev = 6.58211928e-16 # eV s
mu = 1.660538921e-27 # kg
me = 9.1093821545e-31 # kg
NA = 6.02214129e23 # number per mol
eV2GPa = 1.602176565e2
eV2mol = 9.648455461e4 # eV/K --> J/mol/K
def __version__():
return "1.2.5"
[docs]
def get_eos_list_4p():
eos_list_4p = [
"murnaghan",
"birch",
"BM4",
"mBM4",
"mBM4poly",
"rBM4",
"rPT4",
"LOG4",
"vinet",
"Li4p",
"universal",
"morse",
"morse_AB",
"mie",
"mie_simple",
"SJX_v2",
]
return eos_list_4p
[docs]
def get_eos_list_5p():
eos_list_5p = ["BM5", "mBM5", "rBM5", "mBM5poly", "rPT5", "LOG5", "TEOS", "SJX_5p"]
return eos_list_5p
[docs]
def get_eos_list_6p():
eos_list_6p = ["morse_6p"]
return eos_list_6p
[docs]
def get_eos_list_3p():
eos_list_3p = ["morse_3p"]
return eos_list_3p
[docs]
def get_eos_list():
LIST_ALL = (
get_eos_list_3p() + get_eos_list_4p() + get_eos_list_5p() + get_eos_list_6p()
)
return LIST_ALL
# ----------------------------------------------------------------------------------------
[docs]
def res_murnaghan(pars, y, x):
return y - murnaghan(x, pars)
[docs]
def murnaghan(vol, pars):
"""Four-parameters murnaghan EOS.
From PRB 28,5480 (1983).
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
xx = (v0 / vol) ** bp
A = e0 - b0 * v0 / (bp - 1)
B = b0 * vol / bp
ee = A + B * (1 + xx / (bp - 1))
# ee = e0+b0*vol/bp*(((v0/vol)**bp)/(bp-1)+1) -b0*v0/(bp-1)
return ee
# ----------------------------------------------------------------------------------------
[docs]
def res_birch(pars, y, x):
return y - birch(x, pars)
[docs]
def birch(v, parameters):
"""From Intermetallic compounds: Principles and Practice, Vol. I: Princples
Chapter 9 pages 195-210 by M. Mehl. B. Klein, D. Papaconstantopoulos
paper downloaded from Web.
case where n=0
"""
e0 = parameters[0]
b0 = parameters[1]
bp = parameters[2]
v0 = parameters[3]
e = (
e0
+ 9.0 / 8.0 * b0 * v0 * ((v0 / v) ** (2.0 / 3.0) - 1.0) ** 2
+ 9.0 / 16.0 * b0 * v0 * (bp - 4.0) * ((v0 / v) ** (2.0 / 3.0) - 1.0) ** 3
)
return e
# ----------------------------------------------------------------------------------------
[docs]
def res_mBM4(pars, y, x):
return y - mBM4(x, pars)
[docs]
def calc_props_mBM4(pars):
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = (-74 + 45 * bp - 9 * bp * bp) / (9 * b0)
props = [e0, b0, bp, v0, bpp]
return props
[docs]
def mBM4(vol, pars):
"""Birch-Murnaghan 4 pars equation from PRB 70, 224107, 3-order BM."""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
a = e0 + 9 * b0 * v0 * (4 - bp) / 2.0
b = -9 * b0 * v0 ** (4.0 / 3) * (11 - 3 * bp) / 2.0
c = 9 * b0 * v0 ** (5.0 / 3) * (10 - 3 * bp) / 2.0
d = -9 * b0 * v0**2 * (3 - bp) / 2.0
n = 1 # 1 as mBM, 2 as BM
VV = np.power(vol, -n / 3)
ee = a + b * VV + c * VV**2 + d * VV**3
return ee
[docs]
def res_mBM5(pars, y, x):
return y - mBM5(x, pars)
[docs]
def mBM5(vol, pars):
"""Modified BM5 EOS, Shang SL comput mater sci, 2010: 1040-1048."""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
b2p = pars[4]
"""
# copy from ShunLi's matlab scripts.
a = (8 * e0 + 3 * b0 * (122 + 9 * b0 * b2p - 57 * bp + 9 * bp * bp) * v0) / 8
b = (-3 * b0 * (107 + 9 * b0 * b2p - 54 * bp + 9 * bp * bp) * v0 ** (4 / 3)) / 2
c = (9 * b0 * (94 + 9 * b0 * b2p - 51 * bp + 9 * bp * bp) * v0 ** (5 / 3)) / 4
d = (-3 * b0 * (83 + 9 * b0 * b2p - 48 * bp + 9 * bp * bp) * v0 ** 2) / 2
e = (3 * b0 * (74 + 9 * b0 * b2p - 45 * bp + 9 * bp * bp) * v0 ** (7 / 3)) / 8
"""
# retype according to formula in the article
a = e0 + 3 * b0 * v0 * (122 + 9 * b0 * b2p - 57 * bp + 9 * bp * bp) / 8
b = -3 * b0 * v0 ** (4 / 3) * (107 + 9 * b0 * b2p - 54 * bp + 9 * bp * bp) / 2
c = 9 * b0 * v0 ** (5 / 3) * (94 + 9 * b0 * b2p - 51 * bp + 9 * bp * bp) / 4
d = -3 * b0 * v0**2 * (83 + 9 * b0 * b2p - 48 * bp + 9 * bp * bp) / 2
e = 3 * b0 * v0 ** (7 / 3) * (74 + 9 * b0 * b2p - 45 * bp + 9 * bp * bp) / 8
VV = np.power(vol, -1 / 3)
ee = a + b * VV + c * VV**2 + d * VV**3 + e * VV**4
return ee
# ----------------------------------------------------------------------------------------
[docs]
def res_mBM4poly(pars, y, x):
return y - mBM4poly(x, pars)
[docs]
def mBM4poly(vol, parameters):
"""Modified BM5 EOS, Shang SL comput mater sci, 2010: 1040-1048, original expressions."""
a = parameters[0]
b = parameters[1]
c = parameters[2]
d = parameters[3]
e = 0
n = 1 # 1 as mBM, 2 as BM
VV = np.power(vol, -1 / 3)
E = a + b * VV + c * VV**2 + d * VV**3 + e * VV**4
return E
[docs]
def calc_v0_mBM4poly(x, pars):
a = pars[0]
b = pars[1]
c = pars[2]
d = pars[3]
e = 0
f = (
(4 * e) / (3 * x ** (7 / 3))
+ d / x**2
+ (2 * c) / (3 * x ** (5 / 3))
+ b / (3 * x ** (4 / 3))
) * eV2GPa
return f
[docs]
def calc_props_mBM4poly(pars):
a = pars[0]
b = pars[1]
c = pars[2]
d = pars[3]
e = 0
v0 = (
4 * c**3
- 9 * b * c * d
+ np.sqrt((c**2 - 3 * b * d) * (4 * c**2 - 3 * b * d) ** 2)
)
v0 = -v0 / b**3
b0 = (
(28 * e) / (9 * v0 ** (10 / 3))
+ (2 * d) / v0**3
+ (10 * c) / (9 * v0 ** (8 / 3))
+ (4 * b) / (9 * v0 ** (7 / 3))
) * v0
bp = (98 * e + 54 * d * v0 ** (1 / 3) + 25 * c * v0 ** (2 / 3) + 8 * b * v0) / (
42 * e + 27 * d * v0 ** (1 / 3) + 15 * c * v0 ** (2 / 3) + 6 * b * v0
)
b2p = (
v0 ** (8 / 3)
* (
9 * d * (14 * e + 5 * c * v0 ** (2 / 3) + 8 * b * v0)
+ 2
* v0 ** (1 / 3)
* (126 * b * e * v0 ** (1 / 3) + 5 * c * (28 * e + b * v0))
)
) / (2 * (14 * e + 9 * d * v0 ** (1 / 3) + 5 * c * v0 ** (2 / 3) + 2 * b * v0) ** 3)
e0 = mBM4poly(v0, pars)
props = [e0, b0, bp, v0, b2p]
return props
# ---------------------------------
[docs]
def res_mBM5poly(pars, y, x):
return y - mBM5poly(x, pars)
[docs]
def mBM5poly(vol, pars):
"""Modified BM5 EOS, Shang SL comput mater sci, 2010: 1040-1048, original expressions."""
a = pars[0]
b = pars[1]
c = pars[2]
d = pars[3]
e = pars[4]
n = 1 # 1 as mBM, 2 as BM
VV = np.power(vol, -1 / 3)
E = a + b * VV + c * VV**2 + d * VV**3 + e * VV**4
return E
[docs]
def calc_v0_mBM5poly(x, pars):
a = pars[0]
b = pars[1]
c = pars[2]
d = pars[3]
e = pars[4]
f = (
(4 * e) / (3 * x ** (7 / 3))
+ d / x**2
+ (2 * c) / (3 * x ** (5 / 3))
+ b / (3 * x ** (4 / 3))
) * eV2GPa
return f
[docs]
def calc_props_mBM5poly(pars):
a = pars[0]
b = pars[1]
c = pars[2]
d = pars[3]
e = pars[4]
n = 1
# guess v0
vtest = np.linspace(1, 100, 101)
etest = mBM5poly(vtest, pars)
vg = vtest[etest.argmin()]
# sol = root(calc_v0_mBM5poly, vg, args=pars)
# v0 = sol.x[0]
sol = fsolve(calc_v0_mBM5poly, vg, args=pars)
v0 = sol
b0 = (
(28 * e) / (9 * v0 ** (10 / 3))
+ (2 * d) / v0**3
+ (10 * c) / (9 * v0 ** (8 / 3))
+ (4 * b) / (9 * v0 ** (7 / 3))
) * v0
bp = (98 * e + 54 * d * v0 ** (1 / 3) + 25 * c * v0 ** (2 / 3) + 8 * b * v0) / (
42 * e + 27 * d * v0 ** (1 / 3) + 15 * c * v0 ** (2 / 3) + 6 * b * v0
)
b2p = (
v0 ** (8 / 3)
* (
9 * d * (14 * e + 5 * c * v0 ** (2 / 3) + 8 * b * v0)
+ 2
* v0 ** (1 / 3)
* (126 * b * e * v0 ** (1 / 3) + 5 * c * (28 * e + b * v0))
)
) / (2 * (14 * e + 9 * d * v0 ** (1 / 3) + 5 * c * v0 ** (2 / 3) + 2 * b * v0) ** 3)
"""
dEdV = -b / 3 * v0**(-4 / 3) - 2 / 3 * c * \
v0**(-5 / 3) - d * v0**(-2) - 4 / 3 * e * v0**(-7 / 3)
dEdV2 = 4 / 9 * b * v0**(-7 / 3) + 10 / 9 * c * \
v0**(-8 / 3) + 2 * d * v0**(-3) + 28 / 9 * e * v0**(-10 / 3)
dEdV3 = -28 / 27 * b * \
v0**(-10 / 3) - 80 / 27 * c * v0**(-11 / 3) - 6 * \
d * v0**(-4) - 280 / 27 * e * v0**(-13 / 3)
dEdV4 = 280 / 81 * b * v0**(-13 / 3) + 880 / 81 * c * \
v0**(-14 / 3) + 24 * d * v0**(-5) + 3640 / 81 * e * v0**(-16 / 3)
P = -v0 * dEdV
dBdV = dEdV2 + v0 * dEdV3
dPdV = -dEdV - v0 * dEdV2
dBdV2 = dEdV3 + dEdV3 + v0 * dEdV4
dPdV2 = -dEdV2 - dEdV2 - v0 * dEdV3
b0 = v0 * dEdV2
bp = dBdV / dPdV
b2p = (dBdV2 * dPdV - dPdV2 * dBdV) / dPdV**3
"""
e0 = mBM5poly(v0, pars)
props = [e0, b0, bp, v0, b2p]
return props
# ----------------------------------------------------------------------------------------
[docs]
def res_BM4(pars, y, x):
return y - BM4(x, pars)
[docs]
def calc_props_BM4(pars):
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = (-143 + 63 * bp - 9 * bp * bp) / (9 * b0)
props = [e0, b0, bp, v0, bpp]
return props
[docs]
def BM4(vol, pars):
"""Birch-Murnaghan 4 pars equation from PRB 70, 224107, 3-order."""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
eta = (v0 / vol) ** (1.0 / 3.0)
e = e0 + 9.0 * b0 * v0 / 16 * (eta**2 - 1) ** 2 * (
6 + bp * (eta**2 - 1.0) - 4.0 * eta**2
)
return e
# ----------------------------------------------------------------------------------------
[docs]
def res_BM5(pars, y, x):
return y - BM5(x, pars)
[docs]
def BM5(vol, pars):
"""Birch-Murnaghan 5 pars equation from PRB 70, 224107, 4-Order."""
e0 = pars[0]
b0 = pars[1]
b0p = pars[2]
v0 = pars[3]
b0pp = pars[4]
t1 = (v0 / vol) ** (1.0 / 3.0)
t2 = t1**2
t3 = t2 - 1.0
t4 = t3**2 / 4.0
t5 = b0p**2
ee = e0 + 3.0 / 8.0 * b0 * v0 * t4 * (
9.0 * t4 * b0 * b0pp
+ 9.0 * t4 * t5
- 63.0 * t4 * b0p
+ 143.0 * t4
+ 6.0 * b0p * t3
- 24.0 * t2
+ 36.0
)
return ee
[docs]
def rBM4(vol, pars):
"""Implementions as Alberto Otero-de-la-Roza, i.e. rBM4 is used here
Comput Physics Comm, 2011, 182: 1708-1720.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
x = v0 / vol
f = 0.5 * (x ** (2.0 / 3) - 1)
E = e0 + 4.5 * v0 * b0 * f**2 * (1 + (bp - 4) * f)
return E
[docs]
def res_rBM4(pars, y, x):
res = y - rBM4(x, pars)
return res
[docs]
def rBM4_pv(vol, pars):
"""Implementions as Alberto Otero-de-la-Roza, i.e. rBM4 is used here
Comput Physics Comm, 2011, 182: 1708-1720
Fit for V-P relations.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
x = v0 / vol
f = 0.5 * (x ** (2.0 / 3) - 1)
P = 1.5 * b0 * (2 * f + 1) ** (2.5) * (2 + 3 * (bp - 4) * f)
return P
[docs]
def res_rBM4_pv(pars, y, x):
res = y - rBM4_pv(x, pars)
return res
[docs]
def rBM5(vol, pars):
"""Implementions as Alberto Otero-de-la-Roza, i.e. rBM5 is used here
Comput Physics Comm, 2011, 182: 1708-1720.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = pars[4]
x = v0 / vol
f = 0.5 * (x ** (2.0 / 3) - 1)
H = b0 * bpp + b0 * b0
E = e0 + 3 / 8 * v0 * b0 * f**2 * (
(9 * H - 63 * bp + 143) * f**2 + 12 * (bp - 4) * f + 12
)
return E
[docs]
def res_rBM5(pars, y, x):
res = y - rBM5(x, pars)
return res
[docs]
def rBM5_pv(vol, pars):
"""Implementions as Alberto Otero-de-la-Roza, i.e. rBM5 is used here
Comput Physics Comm, 2011, 182: 1708-1720
Fit for V-P relations.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = pars[4]
x = v0 / vol
f = 0.5 * (x ** (2.0 / 3) - 1)
H = b0 * bpp + b0 * b0
P = (
0.5
* b0
* (2 * f + 1) ** (2.5)
* ((9 * H - 63 * bp + 143) * f**2 + 9 * (bp - 4) * f + 6)
)
return P
[docs]
def res_rBM5_pv(pars, y, x):
res = y - rBM5_pv(x, pars)
return res
# ----------------------------------------------------------------------------------------
[docs]
def res_universal(pars, y, x):
return y - universal(x, pars)
[docs]
def universal(vol, parameters):
"""Universal equation of state(Vinet P et al., J. Phys.: Condens. Matter 1, p1941 (1989))."""
e0 = parameters[0]
b0 = parameters[1]
bp = parameters[2]
v0 = parameters[3]
t1 = b0 * v0
t2 = bp - 1.0
t3 = (vol / v0) ** (1.0 / 3.0)
t4 = np.exp(-3.0 / 2.0 * t2 * (-1.0 + t3))
t5 = t2**2
t6 = 1.0 / t5
e = (
e0
- 2.0 * t1 * t4 * (3.0 * t3 * bp - 3.0 * t3 + 5.0 - 3.0 * bp) * t6
+ 4.0 * t1 * t6
)
return e
# ----------------------------------------------------------------------------------------
[docs]
def res_LOG4(pars, y, x):
return y - LOG4(x, pars)
[docs]
def LOG4(vol, pars):
"""Natrual strain (Poirier-Tarantola)EOS with 4 paramters
Seems only work in near-equillibrium range.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
t1 = b0 * v0
t2 = np.log(v0 / vol)
t3 = t2**2
t4 = t3 * t2
ee = e0 + t1 * t3 / 2.0 + t1 * t4 * bp / 6.0 - t1 * t4 / 3.0
"""
# write follows ShunLi's
xx = np.log(v0)
a = e0 + b0 * v0 * (3 * xx**2 + (bp - 2) * xx**3) / 6
b = -b0 * v0 * (2 * xx + (bp - 2) * xx**2) / 2
c = b0 * v0 * (1 + (bp - 2) * xx) / 2
d = -b0 * v0 * (bp - 2) / 6
VV = np.log(vol)
ee = a + b * VV + c * VV**2 + d * VV**3
"""
return ee
[docs]
def calc_props_LOG4(pars):
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = (-3 + 3 * bp - bp * bp) / b0
props = [e0, b0, bp, v0, bpp]
return props
# ----------------------------------------------------------------------------------------
[docs]
def rPT4(vol, pars):
"""Natrual strain EOS with 4 paramters
Seems only work in near-equillibrium range.
Implementions as Alberto Otero-de-la-Roza, i.e. rPT4 is used here
Comput Physics Comm, 2011, 182: 1708-1720,
in their article, labeled as PT3 (3-order), however, we mention it as
rPT4 for 4-parameters EOS.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
x = vol / v0
fn = 1 / 3 * np.log(x)
E = e0 + 4.5 * b0 * v0 * fn**2 * (-(bp - 2) * fn + 1)
return E
[docs]
def res_rPT4(pars, y, x):
res = y - rPT4(x, pars)
return res
[docs]
def rPT4_pv(vol, pars):
"""Natrual strain (Poirier-Tarantola)EOS with 4 paramters
Seems only work in near-equillibrium range.
Implementions as Alberto Otero-de-la-Roza, i.e. rPT4 is used here
Comput Physics Comm, 2011, 182: 1708-1720,
in their article, labeled as PT3 (3-order), however, we mention it as
rPT4 for 4-parameters EOS.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
x = vol / v0
fn = 1 / 3 * np.log(x)
P = -1.5 * b0 * fn * np.exp(-3 * fn) * (-3 * (bp - 2) * fn + 1)
return P
[docs]
def res_rPT4_pv(pars, y, x):
res = y - rPT4_pv(x, pars)
return res
# ----------------------------------------------------------------------------------------
[docs]
def res_LOG5(pars, y, x):
return y - LOG5(x, pars)
[docs]
def LOG5(vol, parameters):
"""Natrual strain (Poirier-Tarantola)EOS with 5 paramters."""
e0 = parameters[0]
b0 = parameters[1]
b0p = parameters[2]
v0 = parameters[3]
b0pp = parameters[4]
t1 = b0 * v0
t2 = np.log(v0 / vol)
t3 = t2**2
t4 = t3**2
t5 = b0**2
t6 = b0p**2
t7 = t3 * t2
e = (
e0
+ t1 * t4 / 8.0
+ t5 * v0 * t4 * b0pp / 24.0
- t1 * t4 * b0p / 8.0
+ t1 * t4 * t6 / 24.0
+ t1 * t7 * b0p / 6.0
- t1 * t7 / 3.0
+ t1 * t3 / 2.0
)
return e
[docs]
def rPT5(vol, pars):
"""Natrual strain EOS with 4 paramters
Seems only work in near-equillibrium range.
Implementions as Alberto Otero-de-la-Roza, i.e. rPT5 is used here
Comput Physics Comm, 2011, 182: 1708-1720,
in their article, labeled as PT3 (3-order), however, we mention it as
rPT5 for 4-parameters EOS.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = pars[4]
x = vol / v0
fn = 1 / 3 * np.log(x)
H = b0 * bpp + bp * bp
E = e0 + 9 / 8 * b0 * v0 * fn**2 * (
-3 * (H + 3 * bp - 3) * fn**2 - 4 * (bp - 2) * fn + 4
)
return E
[docs]
def res_rPT5(pars, y, x):
res = y - rPT5(x, pars)
return res
[docs]
def rPT5_pv(vol, pars):
"""Natrual strain (Poirier-Tarantola)EOS with 5 paramters
Implementions as Alberto Otero-de-la-Roza, i.e. rPT5 is used here
Comput Physics Comm, 2011, 182: 1708-1720,
in their article, labeled as PT3 (3-order), however, we mention it as
rPT5 for 4-parameters EOS.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = pars[4]
x = vol / v0
fn = 1 / 3 * np.log(x)
H = b0 * bpp + bp * bp
P = (
-1.5
* b0
* fn
* np.exp(-3 * fn)
* (-3 * (H + 3 * bp - 3) * fn**2 - 3 * (bp - 2) * fn + 2)
)
return P
[docs]
def res_rPT5_pv(pars, y, x):
res = y - rPT5_pv(x, pars)
return res
# ----------------------------------------------------------------------------------------
[docs]
def res_vinet(pars, y, x):
res = y - vinet(x, pars)
return res
[docs]
def calc_props_vinet(pars):
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = (19 - 18 * bp - 9 * bp * bp) / (36 * b0)
props = [e0, b0, bp, v0, bpp]
return props
[docs]
def vinet(vol, pars):
"""Vinet equation from PRB 70, 224107
Following, Shang Shunli et al., comput mater sci, 2010: 1040-1048, original expressions.
"""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
eta = (vol / v0) ** (1 / 3)
Y = 1.5 * (bp - 1) * (1 - eta)
Z = 4 * b0 * v0 / (bp - 1) ** 2
ee = e0 + Z - Z * (1 - Y) * np.exp(Y)
return ee
[docs]
def vinet_pv(vol, pars):
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
eta = (vol / v0) ** (1 / 3)
P = 3 * b0 * (1 - eta / eta**2) * np.exp(-1.5 * (bp - 1) * (eta - 1))
return P
[docs]
def res_vinet_pv(pars, y, x):
res = y - vinet(x, pars)
return res
# ----------------------------------------------------------------------------------------
[docs]
def Li4p(V, parameters):
"""Li JH, APL, 87, 194111 (2005)."""
E0 = parameters[0]
B0 = parameters[1]
BP = parameters[2]
V0 = parameters[3]
# In fact, it is just a small modified version of Rose or Vinet EOS.
x = (V / V0) ** (1.0 / 3.0)
eta = np.sqrt(-9 * B0 * V0 / E0)
astar = eta * (x - 1.0)
delta = (BP - 1.0) / (2 * eta) - 1.0 / 3.0
E = E0 * (1 + astar + delta * astar**3) * np.exp(-astar)
return E
[docs]
def res_Li4p(p, y, x):
return y - Li4p(x, p)
# ----------------------------------------------------------------------------------------
[docs]
def morse(v, pars):
"""Reproduce from ShunliShang's matlab script."""
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
# usually used in high pressure range, but maybe failed in large
# expansion( > 2*v0) range.
a = e0 + (9 * b0 * v0) / (2 * (-1 + bp) * (-1 + bp))
b = (-9 * b0 * np.exp(-1 + bp) * v0) / (-1 + bp) / (-1 + bp)
c = (9 * b0 * np.exp(-2 + 2 * bp) * v0) / (2 * (-1 + bp) * (-1 + bp))
d = (1 - bp) / (v0 ** (1.0 / 3))
ee = (
a
+ b * np.exp(d * np.power(v, 1.0 / 3))
+ c * np.exp(2 * d * np.power(v, 1.0 / 3))
)
return ee
[docs]
def calc_props_morse(pars):
e0 = pars[0]
b0 = pars[1]
bp = pars[2]
v0 = pars[3]
bpp = (5 - 5 * bp - 2 * bp * bp) / (9 * b0)
props = [e0, b0, bp, v0, bpp]
return props
[docs]
def res_morse(p, en, volume):
res = en - morse(volume, p)
return res
[docs]
def morse_AB(volume, p):
"""morse_AB EOS formula from Song's FVT souces."""
# p0 = [e0, b0, bp, v0, bpp]
E0 = p[0]
A = p[1]
B = p[2]
V0 = p[3]
xx = (volume / V0) ** (1 / 3)
E = (
1.5
* V0
* A
* (np.exp(B * (1.0 - 2.0 * xx)) - 2.0 * np.exp(-B * xx) + np.exp(-B))
+ E0
)
return E
[docs]
def res_morse_AB(p, en, volume):
res = en - morse_AB(volume, p)
return res
[docs]
def morse_3p(volume, p):
"""morse_AB EOS formula from Song's FVT souces
A= 0.5*B.
"""
# p0 = [e0, b0, bp, v0, bpp]
E0 = p[0]
A = p[1]
V0 = p[2]
B = 0.5 * A
xx = (volume / V0) ** (1 / 3)
E = (
1.5
* V0
* A
* (np.exp(B * (1.0 - 2.0 * xx)) - 2.0 * np.exp(-B * xx) + np.exp(-B))
+ E0
)
return E
[docs]
def res_morse_3p(p, en, volume):
res = en - morse_3p(volume, p)
return res
[docs]
def morse_6p(vol, par):
"""Generalized Morse EOS proposed by Qin, see:
Qin et al. Phys Rev B, 2008, 78, 214108.
Qin et al. Phys Rev B, 2008, 77, 220103(R).
"""
# p0 = [e0, b0, bp, v0, bpp]
e0 = par[0]
b0 = par[1]
p = abs(par[2])
v0 = par[3]
q = abs(par[4])
m = abs(par[5])
n = abs(par[6])
C = (p + m) * (q - n) * ((p + m) - (q - n)) + (p * n + q * m)
A = 9 * b0 * v0 * (q - n) / C
B = 9 * b0 * v0 * (p + m) / C
x = (vol / v0) ** (1 / 3)
ee = (
A * np.exp(-p * (x - 1)) / (x**m)
- B * (x**n) * np.exp(-q * (x - 1))
+ e0
- (A - B)
)
return ee
[docs]
def calc_props_morse_6p(par):
e0 = par[0]
b0 = par[1]
p = abs(par[2])
v0 = par[3]
q = abs(par[4])
m = abs(par[5])
n = abs(par[6])
bp = (p + q) / 3 + 1
bpp = ((7 - p * q) / 9 - bp) / b0
props = [e0, b0, bp, v0, bpp, m, n]
return props
[docs]
def res_morse_6p(p, en, volume):
res = en - morse_6p(volume, p)
return res
# ----------------------------------------------------------------------------------------
[docs]
def mie(v, p):
"""Mie model for song's FVT."""
# p0 = [e0, b0, bp, v0, bpp]
E0 = p[0]
m = p[1]
n = p[2]
V0 = p[3]
xx = (V0 / v) ** (1 / 3)
E = E0 / (n - m) * (n * (xx**m) - m * (xx**n))
return E
[docs]
def res_mie(p, e, v):
res = e - mie(v, p)
return res
[docs]
def mie_simple(v, p):
"""Mie_simple model for song's FVT."""
# p0 = [e0, b0, bp, v0, bpp]
E0 = p[0]
m = 4
n = p[2]
V0 = p[3]
xx = (V0 / v) ** (1 / 3)
E = E0 / (n - m) * (n * (xx**m) - m * (xx**n))
return E
[docs]
def res_mie_simple(p, e, v):
res = e - mie_simple(v, p)
return res
# ----------------------------------------------------------------------------------------
[docs]
def TEOS(v, par):
"""Holland, et al, Journal of Metamorphic Geology, 2011, 29(3): 333-383
Modified Tait equation of Huang & Chow.
"""
e0 = par[0]
b0 = par[1]
bp = par[2]
v0 = par[3]
bpp = par[4]
a = (1 + bp) / (1 + bp + b0 * bpp)
b = bp / b0 - bpp / (1 + bp)
c = (1 + bp + b0 * bpp) / (bp**2 + bp - b0 * bpp)
t1 = (v / v0) + a - 1
P = 1 / b * ((t1 / a) ** (-1 / c) - 1)
# ?? the following energy relation is nonsenses.
E = -P * np.log(v0) + e0
return E
[docs]
def res_TEOS(p, e, v):
res = e - TEOS(v, p)
return res
# ----------------------------------------------------------------------------------------
[docs]
def SJX_v2(vol, par):
"""Sun Jiuxun, et al. J phys Chem Solids, 2005, 66: 773-782.
They said it is satified for the limiting condition at high pressure.
"""
e0 = par[0]
b0 = par[1]
bp = par[2]
v0 = par[3]
Y = (v0 / vol) ** (1 / 3) - 1
alpha = 1 / 4 * (3 * bp - 1)
beta = 1 - 1 / alpha
a = alpha
b = beta
ee = e0 + 3 / 10 * a**4 * b0 * v0 * (
2 * (b**5 + 1 / a**5) * (1 - (Y + 1) ** (-3))
- 15 * b**4 * (1 - (Y + 1) ** (-2))
- 60 * b**3 * (1 - (Y + 1) ** (-1))
+ 60 * b**2 * np.log(Y + 1)
+ 3 * Y * (Y + 2)
- 30 * b * Y
)
return ee
[docs]
def res_SJX_v2(p, e, v):
res = e - SJX_v2(v, p)
return res
[docs]
def SJX_5p(vol, par):
"""SJX_5p's five parameters EOS, Physica B: Condens Mater, 2011, 406: 1276-1282."""
e0 = par[0]
a = par[1]
b = par[2]
v0 = par[3]
n = par[4]
X = (vol / v0) ** (1 / 3)
C1 = n * b * np.exp(a * (1 - X) + b * (1 - X**n))
C2 = (-n * b - a) * np.exp(b * (1 - X**n))
ee = e0 / a * (C1 + C2)
return ee
[docs]
def res_SJX_5p(p, e, v):
res = e - SJX_5p(v, p)
return res
[docs]
def calc_props_SJX_5p(par):
e0 = par[0]
a = par[1]
b = par[2]
v0 = par[3]
n = par[4]
b0 = n * b * e0 / (9 * v0) * (a + n * b + n - 1)
Q = (a + n * b) * (a + 2 * n * b) - (n - 1) * (n - 2)
bp = 1 + (Q / 3) / (a + n * b + n - 1)
props = [e0, b0, bp, v0, n]
return props
# ----------------------------------------------------------------------------------------
# some utility functions
[docs]
def read_ve(fin):
if not os.path.exists(fin):
print("Could not find input file: [%s]" % fin)
os.sys.exit(-1)
lines = open(fin).readlines()
nline = len(lines)
vol = []
en = []
for i in range(nline):
tmp = lines[i].split()
if len(tmp) >= 2:
# now, we can read ve.dat & vec.dat
# read the first two numbers.
v = float(tmp[0])
e = float(tmp[1])
vol.append(v)
en.append(e)
else:
pass
return [vol, en]
[docs]
def read_vlp(fin, fstart, fend):
if not os.path.exists(fin):
print(">> Could not find input file: [%s]" % fin)
os.sys.exit(-1)
lines = open(fin).readlines()
nline = len(lines)
print("\n** Totally, there are %d data points reading..." % nline)
vol = []
cella = []
cellb = []
cellc = []
cellba = []
cellca = []
for i in range(nline):
tmp = lines[i].split()
if len(tmp) >= 2:
# read the DATA information
v = float(tmp[0])
if len(tmp) == 6:
# for vlp.dat
a = float(tmp[1])
b = float(tmp[2])
c = float(tmp[3])
ba = float(tmp[4])
ca = float(tmp[5])
elif len(tmp) == 7:
# for velp.dat
e = float(tmp[1])
a = float(tmp[2])
b = float(tmp[3])
c = float(tmp[4])
ba = float(tmp[5])
ca = float(tmp[6])
vol.append(v)
cella.append(a)
cellb.append(b)
cellc.append(c)
cellba.append(ba)
cellca.append(ca)
print(f"\n** Vmin = {min(vol):f}, Vmax = {max(vol):f}")
# some special conditions
if fstart <= 0:
print("\n** Data range input parameters must be positive values!")
os.sys.exit(-1)
if fstart > fend:
if fend != -1:
tmp = fstart
fstart = fend
fend = tmp
if fend > nline:
print(
"\n** EoSfit fit range exceed available data numbers, Reset it to be %d now."
% nline
)
fend = nline
if fstart > nline:
print(
"EoSfit fit range exceed available data numbers, Reset it to be 1: %d now."
% nline
)
fstart = 1
fend = -1
fstart = fstart - 1
# get data in the predefined range.
fstart = fstart - 1
if fend != -1:
vol = vol[fstart:fend]
cella = cella[fstart:fend]
cellb = cellb[fstart:fend]
cellc = cellc[fstart:fend]
cellba = cellba[fstart:fend]
cellca = cellca[fstart:fend]
else:
vol = vol[fstart:]
cella = cella[fstart:]
cellb = cellb[fstart:]
cellc = cellc[fstart:]
cellba = cellba[fstart:]
cellca = cellca[fstart:]
return [vol, cella, cellb, cellc, cellba, cellca]
[docs]
def read_velp(fin, fstart, fend):
if not os.path.exists(fin):
print(">> Could not find input file: [%s]" % fin)
os.sys.exit(-1)
lines = open(fin).readlines()
nline = len(lines)
print("\n** Totally, there are %d data points reading..." % nline)
vol = []
eng = []
cella = []
cellb = []
cellc = []
cellba = []
cellca = []
for i in range(nline):
tmp = lines[i].split()
if len(tmp) >= 2:
# read the DATA information
v = float(tmp[0])
if len(tmp) == 7:
# for velp.dat
e = float(tmp[1])
a = float(tmp[2])
b = float(tmp[3])
c = float(tmp[4])
ba = float(tmp[5])
ca = float(tmp[6])
vol.append(v)
eng.append(e)
cella.append(a)
cellb.append(b)
cellc.append(c)
cellba.append(ba)
cellca.append(ca)
print(f"\n** Vmin = {min(vol):f}, Vmax = {max(vol):f}")
# some special conditions
if fstart <= 0:
print("\n** Data range input parameters must be positive values!")
os.sys.exit(-1)
if fstart > fend:
if fend != -1:
tmp = fstart
fstart = fend
fend = tmp
if fend > nline:
print(
"\n** EoSfit fit range exceed available data numbers, Reset it to be %d now."
% nline
)
fend = -1
if fstart > nline:
print(
"EoSfit fit range exceed available data numbers, Reset it to be 1: %d now."
% nline
)
fstart = 1
fend = -1
# get data in the predefined range.
fstart = fstart - 1
if fend != -1:
vol = vol[fstart:fend]
eng = eng[fstart:fend]
cella = cella[fstart:fend]
cellb = cellb[fstart:fend]
cellc = cellc[fstart:fend]
cellba = cellba[fstart:fend]
cellca = cellca[fstart:fend]
else:
vol = vol[fstart:]
eng = eng[fstart:]
cella = cella[fstart:]
cellb = cellb[fstart:]
cellc = cellc[fstart:]
cellba = cellba[fstart:]
cellca = cellca[fstart:]
return [vol, eng, cella, cellb, cellc, cellba, cellca]
[docs]
def init_guess(fin):
v, e = read_ve(fin)
a, b, c = np.polyfit(v, e, 2) # this comes from pylab
# initial guesses.
v0 = np.abs(-b / (2 * a))
e0 = a * v0**2 + b * v0 + c
b0 = 2 * a * v0
bp = 3.0
bpp = 1 * eV2GPa
x0 = [e0, b0, bp, v0, bpp]
return x0
[docs]
def repro_ve(func, vol_i, p):
ndata = len(vol_i)
eni = np.zeros(ndata)
for i in range(ndata):
eni[i] = eval(func)(vol_i[i], p)
return eni
[docs]
def repro_vp(func, vol_i, pars):
dv = 1e-5
efunc = eval(func)
ndata = len(vol_i)
Press = np.zeros(ndata)
for i in range(ndata):
v = vol_i[i]
P = (efunc(v + 0.5 * dv, pars) - efunc(v - 0.5 * dv, pars)) / dv
Press[i] = -P * eV2GPa
return Press
[docs]
def ext_vec(
func, fin, p0, fs, fe, vols=None, vole=None, ndata=101, refit=0, show_fig=False
):
"""Extrapolate the data points for E-V based on the fitted parameters in small or
very large volume range.
"""
# read fitted-parameters
# pars = np.loadtxt(fin, dtype=float)
fout = "EoSfit.out"
pars = lsqfit_eos(func, fin, p0, fs, fe, fout, refit=refit)
vol, eng, cella, cellb, cellc, cellba, cellca = read_velp(fin, fs, fe)
sca = ext_splint(vol, cellca)
# define extrapolate range
print("\n** Vext_start = %f, Vext_end = %f, N_ext = %d" % (vols, vole, ndata))
vol_ext = np.linspace(vols, vole, ndata)
en_ext = eval(func)(vol_ext, pars)
# en_ext = np.zeros(ndata)
fout = "ext_ve_" + func + ".dat"
fw = open(fout, "w+")
fw.write("%d\n" % ndata)
for i in range(ndata):
vx = vol_ext[i]
ex = en_ext[i]
if vx <= min(vol):
cax = cellca[0]
elif vx >= max(vol):
cax = cellca[-1]
else:
cax = sca(vx)
fw.write(f"{vx:f}\t{ex:f}\t{cax:f}\n")
fw.flush()
fw.close()
# plot the results
vol, en = read_ve(fin)
plt.plot(vol, en, "o-", vol_ext, en_ext, "rd")
plt.legend(["dft_calc", func + "_ext"], loc="best")
plt.savefig("ext_ve_" + func + ".png")
if show_fig:
plt.show()
plt.close()
print("\n>> Storing the extrapolate results in %s\n" % fout)
print("\n>> DONE!")
return
[docs]
def ext_splint(xp, yp, order=3, method="unispl"):
if method == "interp1d":
# old-implement of 1-D interpolation
# could not used in extrapolate
SPLINT = interp1d
return SPLINT(xp, yp, order, bounds_error=False)
elif method == "piecepoly":
SPLINT = BPoly.from_derivatives
return SPLINT(xp, yp, order)
else:
if method == "unispl":
# 1-D smoothing spline fit to a given set of data
SPLINT = UnivariateSpline
else:
SPLINT = LSQUnivariateSpline
return SPLINT(xp, yp, k=order)
[docs]
def ext_velp(
fin,
fstart,
fend,
vols,
vole,
ndata,
order=3,
method="unispl",
fout="ext_velp.dat",
show_fig=False,
):
"""Extrapolate the lattice parameters based on input data."""
# read file
vol, eng, cella, cellb, cellc, cellba, cellca = read_velp(fin, fstart, fend)
# define extrapolate range
print("\n** Vext_start = %f, Vext_end = %f, N_ext = %d" % (vols, vole, ndata))
vv = np.linspace(vols, vole, ndata)
# spline order = 3 by default
se = ext_splint(vol, eng, order, method)
ee = se(vv)
sa = ext_splint(vol, cella, order, method)
cellaa = sa(vv)
sb = ext_splint(vol, cellb, order, method)
cellbb = sb(vv)
sc = ext_splint(vol, cellc, order, method)
cellcc = sc(vv)
sba = ext_splint(vol, cellba, order, method)
cellbaba = sba(vv)
sca = ext_splint(vol, cellca, order, method)
cellcaca = sca(vv)
cellca_cal = cellcc / cellaa
# plot the extrapolate results
nfigure = 6
lp_ext = [ee, cellaa, cellbb, cellcc, cellbaba, cellcaca, cellca_cal]
lp_ori = [
eng,
cella,
cellb,
cellc,
cellba,
cellca,
np.array(cellc) / np.array(cella),
]
lp_ylabel = ["E(eV)", "a(A)", "b(A)", "c(A)", "b/a", "c/a", "c_ext/a_ext"]
for i in range(nfigure):
plt.subplot(nfigure, 1, i + 1)
plt.ylabel(lp_ylabel[i])
plt.plot(vol, lp_ori[i], "o-", vv, lp_ext[i], "rd")
if i == 0:
plt.legend(["ori", "ext"], loc="best")
plt.xlabel("Volume (A**3)")
plt.savefig("ext_velp.png")
if show_fig:
plt.show()
plt.close()
# save the fit data
# get vba.dat
fw = open(fout, "w+")
fw.write(
"#%12s\t%12s\t%12s\t%12s\t%12s\t%12s\t%12s\t%12s\n"
% ("volume", "eng", "cella", "cellb", "cellc", "b/a", "c/a", "cext/aext")
)
for i in range(ndata):
fw.write(
f"{vv[i]:12.6f}\t{ee[i]:12.6f}\t{cellaa[i]:12.6f}\t{cellbb[i]:12.6f}\t{cellcc[i]:12.6f}\t{cellbaba[i]:12.6f}\t{cellcaca[i]:12.6f}\t{cellca_cal[i]:12.6f}\n"
)
fw.flush()
fw.close()
print("\n>> Storing the extrapolate results in %s\n" % fout)
print("\n>> DONE!")
return
[docs]
def lsqfit_eos(
func, fin, par, fstart, fend, show_fig=False, fout="EoSfit.out", refit=-1
):
# make the screen output better.
print("\n")
print("\t>> We are using [ %s ] to fit the V-E relationship << \t" % func)
print("\n")
fs = fstart
fe = fend
p = par
if fs < 0:
print("start fitting range index must be a positive integer!")
os.sys.exit(-1)
# p0 = [e0, b0, bp, v0, bpp]
if refit == -1:
if (func == "morse_AB") or (func == "morse_3p"):
A = 6
B = 0.5 * A
if func == "morse_AB":
p0 = [p[0], A, B, p[3]]
else:
p0 = [p[0], A, p[3]]
elif func in ["mie", "mie_simple"]:
p0 = [p[0], 4, 6, p[3]]
elif func == "morse_6p":
P = 1
Q = 2
m = 1
n = 1
p0 = [p[0], p[1], P, p[3], Q, m, n]
elif func == "SJX_5p":
alpha = 1
beta = 1
n = 1
p0 = [p[0], alpha, beta, p[3], n]
else:
p0 = p
print(
">> use initial guess of fitted-paramters by polynomial fitting results:\n"
)
else:
p0 = np.loadtxt(fout)
print(">> use initial guess of fitted-paramters by last fitting results:\n")
print(p0)
vol, en = read_ve(fin)
ndata = len(vol)
# To determine the data points included in the fitting
if fe > ndata:
fe = ndata
print(
"\n[WARNING]: f_end exceed available data numbers, Reset it to be %d now."
% ndata
)
if fs > ndata:
print(
"\n[WARNING]: f_start exceed available data numbers, Reset it to be 1: %d now."
% ndata
)
print("and Reset f_end to be %d now." % ndata)
fs = 1
fe = ndata
if fe == -1:
print("\n[ATTENTIONS]: fend = -1")
num = ndata - fs + 1
else:
num = fe - fs + 1
vol = vol[fs - 1 : fe]
en = en[fs - 1 : fe]
print("\n%d/%d data was used in the fitting ...\n" % (num, ndata))
# *************************************************************************
# fit it: step 1.
popt, pcov, infodict, mesg, ier = leastsq(
eval("res_" + func),
p0,
args=(en, vol),
full_output=1,
maxfev=(len(p0) + 1) * 400,
)
nfev = infodict["nfev"]
fvec = infodict["fvec"]
"""
psi_i = sum(fvec**2)
psi_min = min(fvec)
pfactor = np.zeros(num)
wi = (4 + 1) / num * psi_i / psi_min
pfi = np.exp(-wi * wi)
"""
if ier not in [1, 2, 3, 4]:
raise RuntimeError("Optimal parameters not found: " + mesg)
# *************************************************************************
print("*" * 80)
print(">> fitted parameters (with %d iterations):" % nfev)
# p0 = [e0, b0, bp, v0, bpp]
if func == "morse_AB":
e0, A, B, v0 = popt
print("%12s\t%12s\t%12s\t%12s" % ("V0(A**3)", "A", "B", "E0(eV)"))
print(f"{v0:12f}\t{A:12f}\t{B:12f}\t{e0:12f}\n")
elif func == "morse_3p":
e0, A, v0 = popt
B = 0.5 * A
print("%12s\t%12s\t%12s\t%12s" % ("V0(A**3)", "A", "B", "E0(eV)"))
print(f"{v0:12f}\t{A:12f}\t{B:12f}\t{e0:12f}\n")
elif func in ["mie", "mie_simple"]:
e0, m, n, v0 = popt
print("%12s\t%12s\t%12s\t%12s" % ("V0(A**3)", "m", "n", "E0(eV)"))
print(f"{v0:12f}\t{m:12f}\t{n:12f}\t{e0:12f}\n")
elif func == "morse_6p":
e0, b0, bp, v0, bpp, m, n = calc_props_morse_6p(popt)
b0 = eV2GPa * b0
bpp = bpp / eV2GPa
print(
"%12s\t%12s\t%12s\t%12s\t%12s\t%12s\t%12s"
% ("V0(A**3)", "B0(GPa)", "Bp", "E0(eV)", "Bpp(1/GPa)", "m", "n")
)
print(f"{v0:12f}\t{b0:12f}\t{bp:12f}\t{e0:12f}\t{bpp:12f}\t{m:12f}\t{n:12f}\n")
elif func == "SJX_5p":
e0, b0, bp, v0, n = calc_props_SJX_5p(popt)
b0 = eV2GPa * b0
print(
"%12s\t%12s\t%12s\t%12s\t%12s"
% ("V0(A**3)", "B0(GPa)", "Bp", "E0(eV)", "n")
)
print(f"{v0:12f}\t{b0:12f}\t{bp:12f}\t{e0:12f}\t{n:12f}\n")
elif func in ["mBM4poly", "mBM5poly", "mBM4", "LOG4", "vinet", "morse", "BM4"]:
prop_func = eval("calc_props_" + func)
e0, b0, bp, v0, bpp = prop_func(popt)
b0 = eV2GPa * b0
bpp = bpp / eV2GPa
print(
"%12s\t%12s\t%12s\t%12s\t%12s"
% ("V0(A**3)", "B0(GPa)", "Bp", "E0(eV)", "Bpp(1/GPa)")
)
print(f"{v0:12f}\t{b0:12f}\t{bp:12f}\t{e0:12f}\t{bpp:12f}\n")
else:
e0, b0, bp, v0, bpp = popt
b0 = eV2GPa * b0
bpp = bpp / eV2GPa
print(
"%12s\t%12s\t%12s\t%12s\t%12s"
% ("V0(A**3)", "B0(GPa)", "Bp", "E0(eV)", "Bpp(1/GPa)")
)
print(f"{v0:12f}\t{b0:12f}\t{bp:12f}\t{e0:12f}\t{bpp:12f}\n")
# write the fitted results in fit.out
fw = open(fout, "w+")
for i in range(len(popt)):
fw.write("%f\n" % popt[i])
fw.flush()
fw.close()
# data evaluate by fitted parameters --to be used in the plot
vol_i = np.linspace(min(vol) * 0.95, max(vol) * 1.05, len(vol) * 2)
en_i = repro_ve(func, vol_i, popt)
print("*" * 80)
# calculate fitted residuals and square errors
res_opt = np.zeros(len(vol))
for i in range(len(vol)):
res_opt[i] = (fvec[i]) ** 2
fit_res = sum(res_opt)
fit_var = np.var(fvec)
fit_std = np.std(fvec)
print("\nfitted residuals\t= %16e\n" % fit_res)
print("fitted variations\t= %16e\n" % fit_var)
print("standard deviations\t= %16e\n" % fit_std)
# if fit_res > 1e-4:
# print("\n>> Residuals seems too large, please refit it by swithing argument --refit 1!\n")
# show = 'F' # reset show tag, not to show the figure.
plt.plot(vol, en, "o", vol_i, en_i)
plt.title("EoS fitted by: %s model" % str(func))
plt.legend(["calc", func + "-fit"], loc="best")
plt.xlabel("Volume (A**3)")
plt.ylabel("Energy (eV)")
plt.savefig("EoSfit_" + func + ".png")
if show_fig:
plt.show()
print("*" * 80)
plt.close()
# reproduce data by the popt and write it into files.
repro_en = repro_ve(func, vol, popt)
repro_press = repro_vp(func, vol, popt)
fve = open(func + "_ve_fit.dat", "w+")
fvp = open(func + "_vp_fit.dat", "w+")
fve.write(
"#%20s\t%20s\t%20s\t%20s\n"
% ("volume(A**3)", "energy(fit)", "energy(cal)", "dE(%)")
)
fvp.write(
"#%20s\t%20s\t%20s\t%20s\n"
% ("volume(A**3)", "pressure(GPa)", "pressure(Mbar)", "pressure(kbar)")
)
for i in range(len(vol)):
fve.write(
f"{vol[i]:20f}\t{repro_en[i]:20f}\t{en[i]:20f}\t{100 * np.abs((en[i] - repro_en[i]) / en[i]):20f}\n"
)
fve.flush()
p_tmp = repro_press[i]
fvp.write(f"{vol[i]:20f}\t{p_tmp:20f}\t{p_tmp / 100:20f}\t{p_tmp * 10:20f}\n")
fvp.flush()
fve.close()
fvp.close()
return popt
[docs]
def parse_argument():
parser = argparse.ArgumentParser(
description=" Script to fit EOS in MTP calculations"
)
parser.add_argument("choice", help="to run mfp, ext_vec, ext_velp?")
parser.add_argument("infile", help="input ve.dat, vec.dat, velp.dat, or vlp.dat")
parser.add_argument(
"-eos",
"--eos",
default="morse_AB",
help="Please choose one of the EOS name in: " + str(get_eos_list()),
)
parser.add_argument(
"--show", default="T", help="to show the fitted results[T] or not[F]?"
)
parser.add_argument(
"-vr",
"--vrange",
type=float,
nargs=3,
default=[30, 50, 101],
help="extend range used for ext, e.g. [vols, vole, ndata]: 1 10 31",
)
parser.add_argument(
"-fr",
"--frange",
type=int,
nargs=2,
default=[1, 1000],
help="data range to be fitted, e.g. [ns, ne]",
)
parser.add_argument(
"--refit",
type=int,
default=-1,
help="fit the data with last fitted parameters as initial guess",
)
parser.add_argument(
"-eord",
"--extorder",
type=int,
default=3,
help="spline order used in extrapolate",
)
parser.add_argument(
"-enum",
"--extnum",
type=int,
default=20,
help="number of data to be extrapolate",
)
parser.add_argument(
"-v", "--version", action="version", version="%(prog)s " + __version__()
)
args = parser.parse_args()
return args
# main
if __name__ == "__main__":
args = parse_argument()
cho = args.choice
fin = args.infile
func = args.eos
SHOW = args.show
REFIT = args.refit
eos_list = get_eos_list()
if func not in eos_list:
print("Choose one of the following eos name:")
print(eos_list)
os.sys.exit(-1)
else:
pass
# p0 = [e0, b0, bp, v0, bpp]
# used in mfp choice
fs = args.frange[0]
fe = args.frange[1]
if fs < 0:
print("ERROR, start range index must be a positive integer!")
os.sys.exit(-1)
if cho == "mfp":
p0 = init_guess(fin)
lsqfit_eos(func, fin, p0, fs, fe, SHOW, refit=REFIT)
elif cho == "ext_vec":
# used in ext choice
ExtVS = args.vrange[0]
ExtVE = args.vrange[1]
ExtNum = int(args.vrange[2])
if ExtVS < 0 or ExtVE < 0 or ExtNum < 0:
print("ERROR, range setting must be a positive value!")
exit(1)
# if ExtNum % 2 == 0:
# print("[WARNING]: ndata = %d, reset it to be %d" %
# (ExtNum, ExtNum + 1))
# ExtNum = ExtNum + 1
p0 = init_guess(fin)
ext_vec(func, fin, p0, fs, fe, ExtVS, ExtVE, ExtNum, refit=REFIT)
elif cho == "ext_velp":
EORDER = args.extorder
ExtVS = args.vrange[0]
ExtVE = args.vrange[1]
ExtNum = int(args.vrange[2])
if ExtVS < 0 or ExtVE < 0 or ExtNum < 0:
print("ERROR, range setting must be a positive value!")
exit(1)
if ExtNum % 2 == 0:
print("[WARNING]: ndata = %d, reset it to be %d" % (ExtNum, ExtNum + 1))
ExtNum = ExtNum + 1
ext_velp(fin, fs, fe, ExtVS, ExtVE, ExtNum, order=EORDER, method="unispl")
else:
print("Unkown Choice, abort now ... ...")
os.sys.exit(-1)