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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Abinit Post Process Application
author: Martin Alexandre
last edited: May 2013
"""
import sys,os,commands,time
import string, math
from numpy import array,sqrt,zeros,conjugate,arange,linspace,exp,log,sin,dot,degrees,arccos
from numpy.fft import rfft,fft, ifft
from numpy.linalg import inv
#Fortran Code
import fortran.math as math
import fortran.topology as topo
#----------------------------------------------------------------#
#--------------(AUTO)CORRELATION FUNCTION------------------------#
#----------------------------------------------------------------#
class Correlation:
#-------------Constructor--------------#
def __init__(self, serie1,serie2=None):
# This class aim is to calculate the (auto)correlation function
# the parameter is :
# - pSerie witch is the serie ([time,atom,[x,y,z]] )
self.nbtime = len(serie1) # Number of steps in the simulation
self.nbatom = len(serie1[0]) # Number of atoms in the simulation
self.CorrelationFunction = zeros(2*self.nbtime,complex) # (Auto)correlation function array
self.calculation(serie1,serie2)
#------------Methods-----------------------#
def calculation(self, pserie1, pserie2):
serie1 = pserie1
if pserie2 == None:
serie2 = pserie1
else:
serie2 = pserie2
for at in range(self.nbatom):
for j in range(3):
self.CorrelationFunction += ifft(conjugate(fft(serie1[:,at,j],2*self.nbtime,0))*fft(serie2[:,at,j],2*self.nbtime,0))
#Normalisation by the therm 1/ ((nbtime - t) * 3 * N). N is the number of atoms, nbtime the number of step and t the step.
self.CorrelationFunction = self.CorrelationFunction.real[:self.nbtime] / ((self.nbtime-arange(self.nbtime)) * 3 * self.nbatom)
def getCorrelationFunction(self,normalize = False):
if len(self.CorrelationFunction ) >= 0 :
if normalize:
return self.CorrelationFunction/self.CorrelationFunction[0]
else:
return self.CorrelationFunction
else:
return 0
#----------------------------------------------------------------#
#------------------DENSITY OF STATES (PHONONS)-------------------#
#----------------------------------------------------------------#
class DOS:
def __init__(self, pdata, pres, pdtion):
# This class aim is to calculate the density of phonon states (DOS),as being the Fourier transforms of the VACF
# the parameters are :
# - pdata witch is the array (1D) of the VACF
# - pres witch is the resolution
# - pdtion witch is ion time steps in atomic units of time
self.atu = 2.41884*10**-5 # one atomic time unit (in ps)
self.dtion = pdtion # ion time steps in atomic units of time
self.VACF = pdata # Velocity autocorelation Function (array 1D)
self.dt = self.dtion * self.atu # time step (in ps)
self.nbtime = len(pdata) # Number of steps
self.times = self.dt * arange(self.nbtime)# 1D array with the times of the simulation
self.fact = 0.6582054674822119 # conversion factor ps => 1/meV
#Calculation of sigma for the gaussian function
self.resolution = pres
self.sigma = 1.0/(1.5192669*self.resolution/(2.0*sqrt(2.0*log(2.0))))
def getDOS(self):
#Return array (1D) phonons density of states (1/mev)
DOS = self.windowGaussian(self.VACF, self.times, self.sigma)
return fft(DOS,len(DOS),0).real[:len(self.VACF)] * self.dt * self.fact
def getFrequencies(self):
#Return array (1D) with the frenquencies (mev)
frequencies = 4.1356 * arange(self.nbtime)/(2 * self.nbtime*self.dt)
return frequencies
def windowGaussian(self, inputSeries, x, s = 50, x0 = 0):
# Return the input serie multiplying by the gaussian function
# The size of the output array is double that the input serie,
# because the final array is periodized function
gauss= exp(-0.5*( (x - x0)**2 / (2*s**2)))
# Creation of the final array:
res = zeros(2*len(inputSeries))
# Multiplying the input serie by the gaussian:
win = gauss*inputSeries
# Periodic function is creating :
res[:len(inputSeries)] = win
res[len(inputSeries):] = win[-1:-len(inputSeries)-1:-1]
#old algorithm:
#res = zeros((2*len(inputSeries) - 2,))
#win = gauss*inputSeries
#res[:len(inputSeries)] = win
#res[len(inputSeries):] = win[-2:0:-1]
return res
def getSprectumDOS(self):
return rfft(self.VACF,2*len(self.VACF)-1,0).real * 2 * self.dt * self.fact
#----------------------------------------------------------------#
#-------------------Periodic table of the Element----------------#
#----------------------------------------------------------------#
class PeriodicTableElement :
# This class returns the atomic number of an element.
# Or the element corresponding to the atomic number.
def __init__(self):
self.table1 = { 'Ru' : 44, 'Re' : 75, 'Rf' : 104, 'Rg' : 111, 'Ra' : 88, 'Rb' : 37, 'Rn' : 86, 'Rh' : 45, 'Be' : 4, 'Ba' : 56,\
'Bh' : 107, 'Bi' : 83, 'Bk' : 97, 'Br' : 35, 'Ho' : 67, 'H' : 1, 'P' : 15, 'Os' : 76, 'Es' : 99, 'Hg' : 80,\
'Ge' : 32, 'Gd' : 64, 'Ga' : 31, 'He' : 2, 'Pr' : 59, 'Pt' : 78, 'Pu' : 94, 'Mg' : 12, 'Pb' : 82, 'Pa' : 91,\
'Pd' : 46, 'Xe' : 54, 'Po' : 84, 'Pm' : 61, 'Uut' : 113, 'Uuq' : 114, 'Uup' : 115, 'Uus' : 117, 'Uuo' : 118,\
'Uuh' : 116, 'Hf' : 72, 'K' : 19, 'Uub' : 112, 'Md' : 101, 'C' : 6, 'Mo' : 42, 'Mn' : 25, 'O' : 8, 'Mt' : 109,\
'S' : 16, 'W' : 74, 'Zn' : 30, 'Eu' : 63, 'Zr' : 40, 'Er' : 68, 'Ni' : 28, 'No' : 102, 'Na' : 11, 'Nb' : 41,\
'Nd' : 60, 'Ne' : 10, 'Np' : 93, 'Fr' : 87, 'Fe' : 26, 'Fm' : 100, 'B' : 5, 'F' : 9, 'Sr' : 38, 'N' : 7, 'Kr' : 36,\
'Si' : 14, 'Sn' : 50, 'Sm' : 62, 'V' : 23, 'Sc' : 21, 'Sb' : 51, 'Sg' : 106, 'Se' : 34, 'Co' : 27, 'Cm' : 96,\
'Cl' : 17, 'Ca' : 20, 'Cf' : 98, 'Ce' : 58, 'Cd' : 48, 'Lu' : 71, 'Cs' : 55, 'Cr' : 24, 'Cu' : 29, 'La' : 57,\
'Li' : 3, 'Tl' : 81, 'Tm' : 69, 'Lr' : 103, 'Th' : 90, 'Ti' : 22, 'Te' : 52, 'Tb' : 65, 'Tc' : 43, 'Ta' : 73,\
'Yb' : 70, 'Db' : 105, 'Dy' : 66, 'Ds' : 110, 'I' : 53, 'In' : 49, 'U' : 92, 'Y' : 39, 'Ac' : 89, 'Ag' : 47,\
'Ir' : 77, 'Am' : 95, 'Al' : 13, 'As' : 33, 'Ar' : 18, 'Au' : 79, 'At' : 85, 'Hs' : 108}
self.table2 = { 44 : 'Ru', 75 : 'Re', 104 : 'Rf', 111 : 'Rg', 88 : 'Ra', 37 : 'Rb', 86 : 'Rn', 45 : 'Rh', 4 : 'Be', 56 : 'Ba',\
107 : 'Bh', 83 : 'Bi', 97 : 'Bk', 35 : 'Br', 67 : 'Ho', 1 : 'H', 15 : 'P', 76 : 'Os', 99 : 'Es', 80 : 'Hg',\
32 : 'Ge', 64 : 'Gd', 31 : 'Ga', 2 : 'He', 59 : 'Pr', 78 : 'Pt', 94 : 'Pu', 12 : 'Mg', 82 : 'Pb', 91 : 'Pa',\
46 : 'Pd', 54 : 'Xe', 84 : 'Po', 61 : 'Pm', 113 : 'Uut', 114 : 'Uuq', 115 : 'Uup', 117 : 'Uus', 118 : 'Uuo',\
116 : 'Uuh', 72 : 'Hf', 19 : 'K', 112 : 'Uub', 101 : 'Md', 6 : 'C', 42 : 'Mo', 25 : 'Mn', 8 : 'O', 109 : 'Mt',\
16 : 'S', 74 : 'W', 30 : 'Zn', 63 : 'Eu', 40 : 'Zr', 68 : 'Er', 28 : 'Ni', 102 : 'No', 11 : 'Na', 41 : 'Nb',\
60 : 'Nd', 10 : 'Ne', 93 : 'Np', 87 : 'Fr', 26 : 'Fe', 100 : 'Fm', 5 : 'B', 9 : 'F', 38 : 'Sr', 7 : 'N',\
36 : 'Kr', 14 : 'Si', 50 : 'Sn', 62 : 'Sm', 23 : 'V', 21 : 'Sc', 51 : 'Sb', 106 : 'Sg', 34 : 'Se', 27 : 'Co',\
96 : 'Cm', 17 : 'Cl', 20 : 'Ca', 98 : 'Cf', 58 : 'Ce', 48 : 'Cd', 71 : 'Lu', 55 : 'Cs', 24 : 'Cr', 29 : 'Cu',\
57 : 'La', 3 : 'Li', 81 : 'Tl', 69 : 'Tm', 103 : 'Lr', 90 : 'Th', 22 : 'Ti', 52 : 'Te', 65 : 'Tb', 43 : 'Tc',\
73 : 'Ta', 70 : 'Yb', 105 : 'Db', 66 : 'Dy', 110 : 'Ds', 53 : 'I', 49 : 'In', 92 : 'U', 39 : 'Y', 89 : 'Ac',\
47 : 'Ag', 77 : 'Ir', 95 : 'Am', 13 : 'Al', 33 : 'As', 18 : 'Ar', 79 : 'Au', 85 : 'At', 108 : 'Hs'}
self.table3 = { 1: 1.007940, 2: 4.002602, 3: 6.941000, 4: 9.012182, 5: 10.811000, 6: 12.011000, 7: 14.006740,\
8: 15.999400, 9: 18.998404, 10: 20.179701, 11: 22.989767, 12: 24.305000, 13: 26.981539, 14: 28.085501,\
15: 30.973763, 16: 32.066002, 17: 35.452702, 18: 39.948002, 19: 39.098301, 20: 40.077999, 21: 44.955910,\
22: 47.880001, 23: 50.941502, 24: 51.996101, 25: 54.938049, 26: 55.847000, 27: 58.933201, 28: 58.689999, 29: 63.546001, 30: 65.389999,\
31: 69.723000, 32: 72.610001, 33: 74.921593, 34: 78.959999, 35: 79.903999, 36: 83.800003, 37: 85.467796, 38: 87.620003, 39: 88.905853,\
40: 91.223999, 41: 92.906380, 42: 95.940002, 43: 98.906197, 44: 101.070000, 45: 102.905502, 46: 106.419998, 47: 107.868202, 48: 112.411003,\
49: 114.820000, 50: 118.709999, 51: 121.752998, 52: 127.599998, 53: 126.904472, 54: 131.289993, 55: 132.905426, 56: 137.326996, 57: 138.905502,\
58: 140.115005, 59: 140.907654, 60: 144.240005, 61: 147.910004, 62: 150.360001, 63: 151.964996, 64: 157.250000, 65: 158.925339, 66: 162.500000, \
67: 164.930313, 68: 167.259995, 69: 168.934204, 70: 173.039993, 71: 174.966995, 72: 178.490005, 73: 180.947906, 74: 183.850006, 75: 186.207001, \
76: 190.199997, 77: 192.220001, 78: 195.080002, 79: 196.966537, 80: 200.589996, 81: 204.383301, 82: 207.199997, 83: 208.980377, 84: 209.000000, \
85: 210.000000, 86: 222.000000, 87: 223.000000, 88: 226.025406, 89: 230.000000, 90: 232.038101, 91: 231.035904, 92: 238.028900, 93: 237.048203, \
94: 242.000000, 95: 243.000000, 96: 247.000000, 97: 247.000000, 98: 249.000000, 99: 254.000000,100: 253.000000,101: 256.000000,102: 254.000000,\
103: 257.000000}
def getZnucl(self,name):
try :
return self.table1[name]
except:
return 0
def getName(self,znucl):
try :
return self.table2[znucl]
except:
return 'Unknown Element'
def getMass(self,znucl):
try :
return self.table3[znucl]
except:
return 'Unknown Element'
#----------------------------------------------------------------#
#-------------------RADIAL DISTRIBUTION FUNCTION-----------------#
#----------------------------------------------------------------#
class RDF:
def __init__(self, pfile, mode, atom1, atom2, box, pdr, pstep, No_Windows=False):
# This class aim is to calculate the Radial Distrubution Function
# the parameters are :
# - mode = 0 for normal RDF, 1 for its deconvolution
# - pfile is the output file (ascii/netcdf)
# - atom1/2 give the number of the atom in typat
# - box : give the number of box wide for the calculculation of g(r)
# - pdr : give the radial precision of the calculation
# - pstep : give the self.increment for the step loop
file = pfile
pos = file.getXCart() # position of atom (cartesian)
inc = pstep # incrementation
acell = file.getAcell() # acell
a = acell[:,0]
b = acell[:,1]
c = acell[:,2]
a_max = max(acell[:,0])
b_max = max(acell[:,1])
c_max = max(acell[:,2])
rprim = zeros((3,3)) # primitives vectors of the cell
rprim[0] = file.getRPrim()[0,0]
rprim[1] = file.getRPrim()[0,1]
rprim[2] = file.getRPrim()[0,2]
rho = 1/file.getVol() # density
if box >= 0:
f = (1/2.+box) # factor of maximum radius
else: # box < 0
f = 3**0.5/2.
rmax = f*min(a_max,b_max,c_max)
deltaR = pdr # delta r (Bohr)
maxbin = int((rmax/deltaR)) # number of iteration
typat = file.getTypat() # Type of particule
if atom1 == 0:
indexAtom1 = array([i for i,x in enumerate(typat) if x == 1 and 2],dtype=int) + 1
else:
indexAtom1 = array([i for i,x in enumerate(typat) if x == atom1],dtype=int) + 1 #get list of the index of typat1 (+1 for fortran)
if atom2 == 0:
indexAtom2 = array([i for i,x in enumerate(typat) if x == 1 and 2 ],dtype=int) + 1
else:
indexAtom2 = array([i for i,x in enumerate(typat) if x == atom2],dtype=int) + 1 #get list of the index of typat2 (+1 for fortran)
nbtime = len(pos) # final step
self.r = arange(maxbin)*deltaR
if mode == 0:
self.g = topo.pair_distribution(nbtime,pos,rprim,f,inc,a,b,c,deltaR,rho,indexAtom1,indexAtom2,self.r)
self.r += deltaR/2.
else: #mode == 1
nba = len(pos[0]) # number of atom
it = (int(nbtime/inc)+1)*nba*(nba-1)
self.m = topo.m_distribution(0,nbtime,pos,inc,it,a,b,c,indexAtom1,indexAtom2)
def getR(self):
return self.r
def getRDF(self):
return self.g[0]
def getINT(self):
return self.g[1]
def getDATA(self):
return self.m[2]
class DEC:
def __init__(self, pfile, n, atom1, atom2, data, box, pdr, step, No_Windows=False):
# This class aim is to calculate the Deconvolution of the RDF
# the parameters are :
# - pfile is the output file (ascii/netcdf)
# - n = is the neibhor number
# - atom1/2 give the number of the atom in typat
# - box : give the number of box wide for the calculculation of g(r)
# - pdr : give the radial precision of the calculation
# - pstep : give the self.increment for the step loop
file = pfile
pos = file.getXCart() # position of atom (cartesian)
nei = n
inc = step #incrementation
acell = file.getAcell() #acell
a_max = max(acell[:,0])
b_max = max(acell[:,1])
c_max = max(acell[:,2])
if box >= 0:
f = (1/2.+ box) # factor of maximum radius
else: # box < 0
f = 3**0.5/2.
rmax = f*min(a_max,b_max,c_max)
deltaR = pdr # delta r (Bohr)
maxbin = int((rmax/deltaR)) # number of iteration
typat = file.getTypat() # Type of particule
if atom1 == 0:
indexAtom1 = array([i for i,x in enumerate(typat) if x == 1 and 2],dtype=int) + 1
else:
indexAtom1 = array([i for i,x in enumerate(typat) if x == atom1],dtype=int) + 1 #get list of the index of typat1 (+1 for fortran)
if atom2 == 0:
indexAtom2 = array([i for i,x in enumerate(typat) if x == 1 and 2 ],dtype=int) + 1
else:
indexAtom2 = array([i for i,x in enumerate(typat) if x == atom2],dtype=int) + 1 #get list of the index of typat2 (+1 for fortran)
nbtime = len(pos) # final step
self.r = arange(maxbin)*deltaR
self.n = topo.n_distribution(nei,nbtime,data,inc,deltaR,indexAtom1,indexAtom2,0,self.r)
def getNEI(self):
return self.n
#-----------------------------------------------------------------#
#-------------------ANGULAR DISTRIBUTION FUNCTION-----------------#
#-----------------------------------------------------------------#
class ADF:
def __init__(self, nei, pfile, atom1, atom2, pdt, pstep, No_Windows=False):
# This class aim is to calculate the Angular Distrubution Function
# the parameters are :
# - nei gives the number of neibours we consider
# - pfile is the output file (ascii/netcdf)
# - atom1/2 give the number of the atom in typat
# - pdt : give the dtheta for the calculation
# - pstep : give the self.increment for the step loop
file = pfile
pos = file.getXCart() # position of atom (cartesian)
inc = pstep #incrementation
acell = file.getAcell() #acell
a = acell[:,0]
b = acell[:,1]
c = acell[:,2]
rprim = zeros((3,3)) # primitives vectors of the cell
rprim[0] = file.getRPrim()[0,0]
rprim[1] = file.getRPrim()[0,1]
rprim[2] = file.getRPrim()[0,2]
deltaTheta = pdt # delta Theta (degres)
maxbin = int((180./deltaTheta)) + 1 # number of iteration
typat = file.getTypat() # Type of particule
if atom1 == 0:
indexAtom1 = array([i for i,x in enumerate(typat) if x == 1 and 2],dtype=int) + 1
else:
indexAtom1 = array([i for i,x in enumerate(typat) if x == atom1],dtype=int) + 1 #get list of the index of typat1 (+1 for fortran)
if atom2 == 0:
indexAtom2 = array([i for i,x in enumerate(typat) if x == 1 and 2 ],dtype=int) + 1
else:
indexAtom2 = array([i for i,x in enumerate(typat) if x == atom2],dtype=int) + 1 #get list of the index of typat2 (+1 for fortran)
nbtime = len(pos) # final step
self.t = arange(maxbin)*deltaTheta
self.a = topo.angular_distribution(nei,nbtime,pos,rprim,inc,a,b,c,deltaTheta,indexAtom1,indexAtom2,self.t)
def getTheta(self):
return self.t
def getADF(self):
return self.a
#------------------------------------------------------------------#
#-------------------NEIGHBOR DISTRIBUTION FUNCTION-----------------#
#------------------------------------------------------------------#
class NDF:
def __init__(self, nei, pfile, atom1, atom2, pdr, pstep, No_Windows=False):
# This class aim is to calculate the Neighbor Distrubution Function
# the parameters are :
# - nei gives the neith neibours we consider.
# - pfile is the output file (ascii/netcdf)
# - atom1 give the number of the atom in typat
# - pdt : give the dtheta for the calculation
# - pstep : give the self.increment for the step loop
file = pfile
pos = file.getXCart() # position of atom (cartesian)
inc = pstep #incrementation
acell = file.getAcell() #acell
a = acell[:,0]
b = acell[:,1]
c = acell[:,2]
rprim = zeros((3,3)) # primitives vectors of the cell
rprim[0] = file.getRPrim()[0,0]
rprim[1] = file.getRPrim()[0,1]
rprim[2] = file.getRPrim()[0,2]
deltaR = pdr
typat = file.getTypat() # Type of particule
if atom1 == 0:
indexAtom1 = array([i for i,x in enumerate(typat) if x == 1 and 2],dtype=int) + 1
else:
indexAtom1 = array([i for i,x in enumerate(typat) if x == atom1],dtype=int) + 1 #get list of the index of typat1 (+1 for fortran)
if atom2 == 0:
indexAtom2 = array([i for i,x in enumerate(typat) if x == 1 and 2 ],dtype=int) + 1
else:
indexAtom2 = array([i for i,x in enumerate(typat) if x == atom2],dtype=int) + 1 #get list of the index of typat2 (+1 for fortran)
nbtime = len(pos) # final step
nba = len(pos[0]) # number of atom
it = (int(nbtime/inc)+1)*nba*(nba-1)
self.m = topo.m_distribution(nei,nbtime,pos,rprim,inc,it,a,b,c,indexAtom1,indexAtom2)
maxi = self.m[0]
mini = self.m[1]
data = self.m[2]
self.r = []
for i in range(int(mini*1000),int(maxi*1000+1),int(deltaR*1000)):
i = i/1000.
self.r.append(i)
self.n = topo.n_distribution(nei,nbtime,data,inc,deltaR,indexAtom1,indexAtom2,mini,self.r)
def getR(self):
return self.r
def getNDF(self):
return self.n
#--------------------------------------------------------#
#-------------------Probability function-----------------#
#--------------------------------------------------------#
class Proba:
def __init__(self, nei, pfile, atom1, No_Windows=False):
# This class aim is to calculate the Pobability that one neighbor stay in the same neighborhood of an atom between the first step and the last step considered
# the parameters are :
# - nei give the number of neighbors considered
# - pfile is the output file (ascii/netcdf)
# - atom1 give the number of the atom in typat
file = pfile
pos = file.getXCart() # position of atom (cartesian)
acell = file.getAcell() #acell
a = acell[:,0]
b = acell[:,1]
c = acell[:,2]
rprim = zeros((3,3)) # primitives vectors of the cell
rprim[0] = file.getRPrim()[0,0]
rprim[1] = file.getRPrim()[0,1]
rprim[2] = file.getRPrim()[0,2]
typat = file.getTypat() # Type of particule
if atom1 == 0:
indexAtom1 = array([i for i,x in enumerate(typat) if x == 1 and 2],dtype=int) + 1
else:
indexAtom1 = array([i for i,x in enumerate(typat) if x == atom1],dtype=int) + 1 #get list of the index of typat1 (+1 for fortran)
nbtime = len(pos) # final step
self.n = arange(1,nei+1)
self.p = topo.probability(nei,nbtime,pos,rprim,a,b,c,indexAtom1,indexAtom1)
def getN(self):
return self.n
def getProba(self):
return self.p
#-----------------------------------------------------------------#
#-------------------MEANS SQUARE DISPLACEMENT---------------------#
#-----------------------------------------------------------------#
class MSD:
def __init__(self, pfile, atom1):
# This class aim is to calculate the Mean square displacement
# the parameters are :
# - pfile is the output file (ascii/netcdf)
# - atom1 give the number of the atom in typat
file = pfile
pos = file.getXCart() # position of atom (cartesian)
typat = file.getTypat() # Type of particule
indexAtom1 = array([i for i,x in enumerate(typat) if x == atom1],dtype=int) + 1 #get list of the index of typat1 (+1 for fortran)
self.mds = math.mean_square_displacement(pos,indexAtom1)
self.x = arange(len(self.mds))
def getX(self):
return self.x
def getMSD(self):
return self.mds
#---------------------------------------------------#
#---------ELASTIC CALCULATION CLASS-----------------#
#---------------------------------------------------#
class elasticCalculation:
#-------------Constructor--------------#
def __init__(self,pfiles,pni,pWDData):
# This class aim is to calculate the Elastic constant
# the parameter is :
# -pfiles : witch is dictionnay array with the path of the files
self.files = pfiles #Dictionnary array
self.elastic = {} #Dictionnary array with the elastics constants
self.ni = pni #Departure of the step
self.datasetWD = pWDData #Dataset without deformation
self.struct = structure(self.files).getStructure()
self.deformation = deformation(self.files,self.ni,self.datasetWD).getDeformation()
if len(self.deformation) != 0 :
if (self.struct == 'cubic'):
self.elastic['C11'] = 0
self.elastic['C12'] = 0
self.elastic['C44'] = 0
self.M = 0 # M = C11 - C12 using in the tetragonal deformotation
self.T = 0 # T = C11 + 2C12 using in the isotropic deformotation
#print self.deformation
#for key in self.deformation:
#print key
sigma_0 = self.deformation['WD'][2]
for i in range(len(self.deformation)-1):
sigma_i = self.deformation[i][2]
delta = self.deformation[i][1]
if self.deformation[i][0] == 'single':
C11 = ( sigma_i[2] - sigma_0[2] ) / delta
C12 = ( sigma_i[1] - sigma_0[1] ) / delta
C44 = ( sigma_i[5] - sigma_0[5] ) / (2*delta)
self.elastic['C11'] += C11
self.elastic['C12'] += C12
self.elastic['C44'] += C44
if self.deformation[i][0] == 'orto':
C44 = ( sigma_i[5] - sigma_0[5] ) / (2*delta)
self.elastic['C44'] += C44
if self.deformation[i][0] == 'tetra':
self.M += ( sigma_i[1]- sigma_0[1] ) / delta
if self.deformation[i][0] == 'iso':
self.T += ( sigma_i[1] - sigma_0[1] ) / delta
#----------ADD OTHER DEFORMATION HERE--------#
#--------------------------------------------#
try:
self.M /= self.count(self.deformation,'tetra')
self.T /= self.count(self.deformation,'iso')
except:
pass
nbOfSingleDef = self.count(self.deformation,'single')
if (self.M == 0 and self.T != 0 or self.M != 0 and self.T == 0):
print 'Deformation error 1'
self.elastic = {}
return
elif (self.M != 0 and self.T != 0):
self.elastic['C11'] += ( 2 * self.M + self.T ) / 3
self.elastic['C12'] += -( self.M - self.T ) / 3
nbC11 = nbOfSingleDef +1
else :
nbC11 = nbOfSingleDef
if nbC11 != 0 :
self.elastic['C11'] /= nbC11
self.elastic['C12'] /= nbC11
self.elastic['C44'] /= (nbOfSingleDef + self.count(self.deformation,'orto') )
return
#----------ADD OTHER STRUCTURE HERE--------#
if (self.struct == 'hexagonal'):
return
#------------------------------------------#
else:
self.elastic = {}
print 'Deformation error 2'
return
#------------Methods--------------------#
def getElasticsConstants(self):
return self.elastic
def count(self,dic,pkey):
i = 0
for key in dic:
if dic[key][0] == pkey :
i += 1
return i
#---------------------------------------------------#
#---------------------------------------------------#
#----------------STRUCTURE CLASS--------------------#
#--------------------NOT YET IMPLEMENTED------------#
#---------------------------------------------------#
class structure:
#-------------Constructor--------------#
def __init__(self, pfiles):
# This class aim is to determinate the structure of the system
# the parameters are :
# -self.files
self.files = pfiles
def getStructure(self):
return "cubic"
#---------------------------------------------------#
#---------------------------------------------------#
#----------------DEFORMATION CLASS------------------#
#---------------------------------------------------#
#---------------------------------------------------#
class deformation:
#-------------Constructor--------------#
def __init__(self, pfiles,pni,pWDData):
# This class aim is to determinate the deformations used for the calculation of elastic constant
# the parameters are :
# -self.files
# -self.ni
self.files = pfiles
self.ni = pni
self.datasetWD = pWDData #Dataset without deformation
self.deformation = {}
self.goodDeformation = True
self.calculation()
#------------Methods--------------------#
def calculation(self):
self.rprim0 = []
self.sigma = {}
self.deformation = {}
if self.files['WD'].getIonMove()[0] in [1,6,7,8,9,12] :
self.files['WD'].setNi(self.ni)
sigma = self.files['WD'].getStress()
sigma = sum(sigma[:,:]) / len(sigma)
self.deformation['WD'] = ['WD', 0 ,sigma]
self.rprim_0 = self.files['WD'].getRPrim()[0,:,:]
for i in range(len(self.files)-1):
self.files[i].setNi(self.ni)
sigma = self.files[i].getStress()
sigma = sum(sigma[:,:]) / len(sigma)
rprim = self.files[i].getRPrim()[0,:,:]
d = dot(inv(self.rprim_0),rprim)
self.deform(i,d,sigma)
return
if self.files['WD'].getIonMove()[0] == 0 :
if 1 == 1:
sigma = self.files['WD'].getStress()[self.datasetWD]
self.deformation['WD'] = ['WD', 0 ,sigma]
self.rprim_0 = self.files['WD'].getRPrim()[self.datasetWD]
self.nbdataset = self.files['WD'].getNbDataset()
j = 0
for i in range(self.nbdataset) :
if i != self.datasetWD :
sigma = self.files['WD'].getStress()[i]
rprim = self.files['WD'].getRPrim()[i]
d = dot(inv(self.rprim_0),rprim)
self.deform(j,d,sigma)
j += 1
for i in range(len(self.files)-1):
self.nbdataset = self.files[i].getNbDataset()
for j in range(self.nbdataset) :
sigma = self.files[i].getStress()[j]
rprim = self.files[i].getRPrim()[j]
d = dot(inv(self.rprim_0),rprim)
self.deform(i,d,sigma)
return
else :
self.goodDeformation = False
def deform(self,i,d,sigma):
if( round(d[0][1],6) == round(d[1][0],6) and round(d[0][0],6) == round(d[1][1],6) and round(d[2][2],6) == (1 + round(d[0][1],6)) ):
self.deformation[i] = ['single',round(d[0][1],5),sigma]
return
if( round(d[0][0],6) == round(d[1][1],6) and round(d[2][2],4) == round( 1.0 / ( d[0][0]**2 ),4 ) ):\
if ( abs(d[0][1]) <= 1e-10 and abs(d[1][0]) <= 1e-10 and abs(d[2][0]) <= 1e-10 and d[2][1]<= 1e-10 and abs(d[1][0]) <= 1e-10 ):
self.deformation[i] = ['tetra',d[0][0]-1,sigma]
return
if( round(d[0][1],6) == round(d[1][0],6) and round(d[2][2],4) == round( 1.0 / (1 - d[0][1]**2 ),4 ) ):
if (d[0][0] == d[1][1] and abs(d[0][2]) <= 1e-10 and abs(d[1][2]) <= 1e-10):
self.deformation[i] = ['orto',round(d[0][1],4),sigma]
return
if( round(d[0][0],6) == round(d[1][1],6) and round(d[1][1],6) == round(d[2][2],6) and round(d[0][0],6) != 0 ):
if ( abs(d[0][1]) <= 1e-10 and abs(d[0][2]) <= 1e-10 and abs(d[0][1]) <= 1e-10 and abs(d[1][0]) <= 1e-10):
if (abs(d[1][0]) <= 1e-10 and abs(d[1][2])<= 1e-10 and abs(d[1][0]) <= 1e-10 ):
self.deformation[i] = ['iso',d[0][0]-1,sigma]
return
#----------ADD OTHER DEFORMATION HERE------#
#------------------------------------------#
self.goodDeformation = False
#--------Accessor-----------#
def getDeformation(self):
if (self.goodDeformation):
return self.deformation
else:
return []
#----------------------------------------------------------------#
#-------------------CALCULATION OF BULK MODULUS------------------#
#----------------------------------------------------------------#
class birch:
def __init__(self,data,number):
#This class uses FORTRAN code for the fit
self.value = {}
self.namefiles ="fit.inp"
self.workDir = os.getcwd()
self.homeDir = commands.getoutput('echo ~/')
path = os.path.dirname(__file__) + "/" # Get the path of the source Code
os.system('cp -r '+path + 'BIRCH '+ self.homeDir) # Copy the BIRCH DIR to the home DIR
os.chdir(self.homeDir + 'BIRCH') # Move to the BIRCH DIR
print os.getcwd()
file_out = open( self.namefiles ,"w") # Creation of the inputFIle for the FIT
file_out.write(' 2 ! Nb of columns\n')
file_out.write(' 1 ! Column of X-axis\n')
file_out.write(' 2 ! Column of Y-axis\n')
file_out.write(' 1 ! What is X: 1 for Volume, 2 for Acell\n')
file_out.write(' 1 ! 1 for V=a^3/4, 2 for V=a^3/2\n')
file_out.write(' 2 ! Unit for L: 1 for angstrom, 2 for u.a.\n')
file_out.write(' 3 ! Unit for E: 1 for Ryd, 2 for Ev, 3 for Ha, 4 for ?\n')
file_out.write(' 1 ! Mupliplier for V (V will be multiplied by this factor)\n')
file_out.write(' 1 ! Mupliplier for E (E will be divided by this factor)\n')
file_out.write(' '+str(number)+' ! Nb of input points\n')
file_out.write(data)
file_out.write(' 3 ! Order of v^(-2/3) polynomial\n')
file_out.write(' -2 ! ?\n')
file_out.write(' 0 ! ?\n')
file_out.write(' 0 ! ?\n')
file_out.write(' 0 ! ?\n')
file_out.close()
benf = commands.getoutput('./benf ') # execution of the FIT program
if benf == '':
print 'fit program computes successfully!'
else:
commands.getoutput('ifort -O -o benf benf.f')# compilation of the fit program
benf = commands.getoutput('./benf ')
if benf =='':
print 'fit program computes successfully!'
else:
print 'unable to launch the fit program'
## Get the value of the fit
self.value['E0'] = float( (commands.getoutput('grep -P \'Eo = .* Rydbergs\' fit.res').split())[2]) / 2.0
self.value['B0'] = float( (commands.getoutput('grep -P \'Ko = .* GPa\' fit.res').split())[2] )
self.value['dB0'] = float( (commands.getoutput('grep -P \"Ko\'=.*\" fit.res').split())[1] )
self.value['V0'] = float( (commands.getoutput('grep -P \'Vo =.* Bohr.*\' fit.res').split())[2])
self.value['RMS'] = float( (commands.getoutput('grep -P \"RMS.*Ry\" fit.res').split())[6]) / 2.0
os.chdir(self.homeDir) # Move to the HOME DIR
os.system('rm -r BIRCH') # Remove the BIRCH DIR
os.chdir(self.workDir) # Move to the original path
def getValue(self):
return self.value
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