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class99_last_drawmulinfo.py
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class99_last_drawmulinfo.py
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import sys
import os
import numpy as np
import matplotlib.pyplot as plt
#from pymatgen import Structure
sys.path.append(os.environ['SCRIPT'])
path = os.environ['PWD'] + '/'
from class0_functions1 import find_files, savedata, read_incar
from class1_read import read_file_values
from class0_functions3 import reorder_x_y_data
class drawmulinfo:
def __init__(self, x_str, y_str, header, middle='', lattice_structure=None, xlim=None, ylim=None, materialcomment=''):
# fixed info for all... the format of infodict(information dictionary) is 'keyword': ('xlabel', 'unit')
self.xfile_infodict = {'ENCUT': 'INCAR', 'SIGMA':'INCAR', 'AEXX': 'INCAR', 'HFSCREEN': 'INCAR','NELECT': 'INCAR', 'SCALING':'CONTCAR','bond_length':'POSCAR', 'grid':'KPOINTS'}
self.xlabel_infodict = {'ENCUT':("cutoff energy", 'eV'), 'SIGMA':('sigma','Gaussian smearing width'), 'energy':('energy', 'eV'), 'AEXX':('AEXX',''), 'HFSCREEN': ('HFSCREEN', ''), 'NELECT':('number of elections',''), 'SCALING':('volume',r'$\AA^3$'),'bond_length':('bond length',r'$\AA$'), 'grid':('kgrid','n*n*n')}
self.ylabel_infodict = {'equil_energy':('Final Energy', 'eV'),'bandgap':('bandgap', 'eV'),'wurtzite_u':('wurtzite u parameter',''), 'lattice_para':('lattice parameter',''), 'koopmans':('$E(N-1)-E(N)+E_{corr}+\epsilon_{ho}(N)$', 'eV'), 'hoenergy':('highest occ energy','eV'), 'bond_length':('bond length',r'$\AA$')}
# plot info provided
self.lattice_structure = lattice_structure
self.scalingvolume = True # use volume for scaling or use lattice parameter for scaling
self.header = header
self.middle=middle
self.x_str = x_str
self.y_str = y_str
# plot info generated
self.x_file_open = self.xfile_infodict[x_str]
self.xlabel = '%s (%s)' % self.xlabel_infodict[x_str]
self.ylabel = '%s (%s)' % self.ylabel_infodict[y_str]
self.title = '%s: %s vs %s' % (materialcomment, self.ylabel_infodict[y_str][0], self.xlabel_infodict[x_str][0])
self.xlim=xlim
self.ylim=ylim
# plot data initial
self.xx=np.array([])
self.data=[] #np.array([])
# read data
self.read()
if not os.path.isdir(os.environ['PWD']+'/savedDATA'):
os.system('mkdir savedDATA')
savedata(os.environ['PWD']+'/', self.xx, self.data, self.x_str, self.y_str, self.header)
def read(self):
'''
read variables in each subfolder:
1- go to subfolder
2- read x
3- read y
4- extra data manipulations
'''
exist_folders = find_files('.', self.header, self.x_str,middle=self.middle, remove=False)
print('folders:',exist_folders)
for di in exist_folders:
# 1- go to the subfolder
subfolder=path+di
os.chdir(subfolder)
print('pwd:',os.getcwd())
read_var = read_file_values(subfolder)
# 2- read x
if self.x_file_open == 'INCAR':
x=read_var.incar([self.x_str], float)[0] # format of a list
elif self.x_file_open == 'POSCAR' or self.x_file_open == 'CONTCAR':
if self.x_str == 'SCALING':
if self.scalingvolume:
x=read_var.poscar('volume')
else:
x=read_var.poscar('abc')
self.xlabel='%s (%s)'%('box length',r'$\AA$')
elif self.x_str == 'bond_length':
x=read_var.poscar('bond_length')
else:
print('Error! The variable to read for POSCAR is not prepared')
sys.exit()
elif self.x_file_open == 'KPOINTS':
if self.x_str == 'grid':
x=read_var.kpoints()
else:
print('Error! The x file you want to read is not prepared')
sys.exit()
self.xx=np.append(self.xx, x) # add x to self.xx
# 3- read y
if self.y_str=='equil_energy':
y = read_var.oszicar()
elif self.y_str == 'bandgap':
y = read_var.bandgap()
elif self.y_str == 'wurtzite_u':
y,_ = read_var.get_u()
elif self.y_str == 'lattice_para':
y, self.lattice_labels = read_var.lattice_para(self.lattice_structure)
elif self.y_str == 'koopmans':
# E(N-1)-E(N)+Eho+Ecorr
# read each item for a single folder. Not getting lists, but single numbers
positive_folder=subfolder.replace('0e_','1e_')
z1 = read_var.oszicar(folder=positive_folder) # E(N-1)
z2 = read_var.oszicar() # E(N)
z3 = read_var.eigenval_ho_lo()[0] # read Eho in neutral state; return (energy, band)
z4 = float(read_incar(positive_folder, incar='FREYCORR')['FREYCORR']) # Ecorr freysoldt correction
y = z1-z2+z3+z4 # not a list
elif self.y_str == 'hoenergy':
y = read_var.read_single_eigenE(eigenvaltype='ho',spinpolarized=False)
elif self.y_str == 'bond_length':
y = read_var.poscar('bond_length')
else:
print('Error! The y file you want to read is not prepared')
#self.data=np.append(self.data, y)
self.data.append(y)
self.data=np.array(self.data)
os.chdir(path)
# 4- extra data manipulations
if self.y_str == 'lattice_para':
self.data =np.transpose(self.data) # transpose to make data.shape = (3, N), so data[0] gives lattice parameter a(x_str)
elif self.y_str == 'equil_energy': # energy needs to reset reference
self.data = self.data-self.data[-1]
elif self.x_str == 'AEXX' and self.y_str == 'bandgap': # print fitting AEXX to bandgap
bandgap_selected_value=0.726 #11.3 for BeO
aexxvalue_selected = np.interp(bandgap_selected_value, self.data, self.xx)
print('\nAEXX=%.4f corresponds to experimental bandgap=%.5feV\n' % (aexxvalue_selected, bandgap_selected_value) )
with open( path+'%s_AEXX_bandgap=%.3feV' % (self.header,bandgap_selected_value), 'w') as f:
f.write( 'AEXX=%.4f # bandgap=%.5feV\n' % (aexxvalue_selected, bandgap_selected_value) )
## print data
self.xx=np.round(self.xx,6)
self.data=np.round(self.data,6)
print('xx='+', '.join(self.xx.astype(str)))
if len(self.data.shape) > 1:
for i in range(self.data.shape[0]):
print('yy='+', '.join(self.data[i].astype(str)))
else:
print('yy='+', '.join(self.data.astype(str)))
def plot(self):
plt.figure()
SMALL_SIZE = 12
MEDIUM_SIZE = 14
BIGGER_SIZE = 16
plt.rc('font', size=BIGGER_SIZE) # controls default text sizes
plt.rc('axes', titlesize=BIGGER_SIZE) # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE) # fontsize of the x and y labels
plt.rc('xtick', labelsize=SMALL_SIZE) # fontsize of the tick labels
plt.rc('ytick', labelsize=SMALL_SIZE) # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE) # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE) # fontsize of the figure title
# plot or scatter
if self.y_str == 'lattice_para':
#plt.subplots(nrows=len(data), ncols=1)
num_plots = len(self.data)
for i in range(num_plots):
#sub_num = num_plots * 100 + 10 + i
plt.subplot(num_plots, 1, i+1)
plt.plot(self.xx, self.data[i],'-')
#plt.scatter(self.xx, self.data[i],'-')
if i == 0:
plt.title('%s' % (self.title))
plt.ylabel(self.lattice_labels[i])
elif self.y_str == 'koopmans':
# Plot reference
plt.plot(self.xx,np.zeros(len(self.xx)), label='$E(N-1)-E(N)+\epsilon_{ho}+E_{corr}=0$')
# fit koopmans=0
if self.x_str == 'HFSCREEN':
numberofdata=5
fity1=self.data[:numberofdata]
fitx1=self.xx[:numberofdata]
else:
fity1=self.data
fitx1=self.xx
print('Fit this array to 0',fity1)
poly=np.polyfit(fity1,fitx1,1)# fitting function
po=np.poly1d(poly) # poly function
var_fit=np.round(po(0),3)
print('Fit %s=%s'%(self.x_str,var_fit))
# change title to contain the fixed initial parameters
relax_fix_var=['HFSCREEN', 'AEXX']
relax_fix_var.remove(self.x_str)
relax_fix_var = relax_fix_var[0]
read_fil=read_file_values(path)
relax_fix_para= self.header[-4:]#read_fil.incar([relax_fix_var])
self.title = '$\mathit{V}_\mathrm{O}$ %s=%s fit=%s' % ( relax_fix_var, relax_fix_para, var_fit)
# plot data
legend='$E(N-1)-E(N)+\epsilon_{ho}+E_{corr}$'
plt.plot(self.xx, self.data, 'o', label=legend)
plt.legend()
else:
plt.plot(self.xx, self.data,'o')
# plot setting
plt.xlabel(self.xlabel) # x label
if self.xlim:plt.xlim(self.xlim) # set limits
if self.ylim:plt.ylim(self.ylim)
if self.y_str=='lattice_para':
pass # done previously
else:
plt.title(self.title) # add title
plt.ylabel(self.ylabel) # y label, from y_str
# save
plt.tight_layout()
figname="%s-%s_%s.pdf" % (self.header,self.y_str, self.x_str)
print('save figure:%s/%s'% (os.environ['PWD'],figname))
plt.savefig(path+figname,dpi=600)
plt.close()
class drawmulinfo3D:
def __init__(self, x_str, y_str, z_str, header, middle='', lattice_structure=None, xlim=None, ylim=None, zlim=None):
# fixed info for all... the format of infodict(information dictionary) is 'keyword': ('xlabel', 'unit')
self.xfile_infodict = {'ENCUT': 'INCAR', 'AEXX': 'INCAR', 'HFSCREEN': 'INCAR'}
self.yfile_infodict = self.xfile_infodict
self.xlabel_infodict = {'ENCUT':("Cutoff energy", 'eV'), 'energy':('energy', 'eV'), 'AEXX':('AEXX',''), 'HFSCREEN':('HSCREEN', '')}
self.ylabel_infodict = self.xlabel_infodict
self.zlabel_infodict = {'equil_energy':('equil_energy', 'eV'),'bandgap':('bandgap', 'eV'),'wurtzite_u':('wurtzite u parameter',''), 'koopmans':('$E(N-1)-E(N)+E_{corr}+\epsilon_{ho}(N)$', 'eV'), 'eps':('electronic dielectric constant','')}
# 'lattice_para':('lattice parameter','')
# plot info provided
self.lattice_structure = lattice_structure
self.header = header
self.middle = middle
self.x_str = x_str
self.y_str = y_str
self.z_str = z_str
# plot info generated
self.x_file_open = self.xfile_infodict[x_str]
self.y_file_open = self.yfile_infodict[y_str]
self.xlabel = '%s %s' % self.xlabel_infodict[x_str]
self.ylabel = '%s %s' % self.ylabel_infodict[y_str]
self.zlabel = '%s %s' % self.zlabel_infodict[z_str]
self.title = '%s(%s,%s)' % (z_str, x_str, y_str)
self.xlim=xlim
self.ylim=ylim
self.zlim=zlim
# plot data initial
self.xx=np.array([])
self.yy=np.array([])
self.data=[]#np.array([])
# read data
self.read() # arguments are already saved self.arguments
savedata(os.environ['PWD']+'/', np.stack((self.xx, self.yy)), self.data, self.x_str+'_'+self.y_str, self.z_str, self.header)
def read(self):
'''
read variables in each subfolder:
1- go to subfolder
2- read x
3- read y
4- read data
5- extra data manipulations
'''
exist_folders = find_files('.', self.header, self.x_str, middle=self.middle, remove=False)
print('folders:',exist_folders)
for di in exist_folders:
# 1- go to the subfolder
subfolder=path+di
os.chdir(subfolder)
print('pwd:',os.getcwd())
read_var = read_file_values(subfolder)
# 2- read x
if self.x_file_open == 'INCAR':
x,y=read_var.incar([self.x_str,self.y_str], float) # format of a list
else:
print('Error! The x file you want to read is not prepared')
self.xx=np.append(self.xx, np.round(x,4)) # add x to self.xx
self.yy=np.append(self.yy, np.round(y,4)) # add y to self.yy
# 3- read y
if self.z_str=='equil_energy':
z = read_var.oszicar()
elif self.z_str == 'bandgap':
z = read_var.bandgap()
elif self.z_str == 'eps':
z = read_var.outcar_dielec_const()
elif self.z_str == 'wurtzite_u':
z,_ = read_var.get_u()
elif self.z_str == 'koopmans':
# E(N-1)-E(N)+Eho+Ecorr
# read each item for a single folder. Not getting lists, but single numbers
positive_folder=path+di.replace('0e_','1e_')
z1 = read_var.oszicar(folder=positive_folder) # E(N-1)
z2 = read_var.oszicar() # E(N)
z3 = read_var.eigenval_ho_lo()[0] # read Eho in neutral state; return (energy, band)
z4 = float(read_incar(positive_folder, incar='DEFECT')['FREYCORRELEC']) # Ecorr freysoldt correction
z = z1-z2+z3+z4 # not a list
elif self.z_str == 'lattice_para':
z, self.lattice_labels = read_var.lattice_para(self.lattice_structure)
else:
print('Error! The z file you want to read is not prepared')
#self.data=np.append(self.data, y)
self.data.append(np.round(z,4)) # self.data is a list
# reshape the data format
# the data should be meshgrid
#orderxx=np.unique(self.xx)
#orderyy=np.unique(self.yy)
#self.data=np.reshape(self.data,(len(self.yy), len(self.xx))) # data changes with x first, so shape=(yy,xx)
## put the change along x in the last axis
#self.xx,self.yy=np.meshgrid(self.xx,self.yy) # meshgrid makes x change along the last axis, so is consistent with data
self.xx,self.yy,self.data=reorder_x_y_data(self.xx,self.yy,self.data) # return ordered meshgrid data
os.chdir(path)
# 4- extra data manipulations
if self.z_str == 'lattice_para':
#self.data =np.transpose(self.data) # transpose to make data.shape = (3, N), so data[0] gives lattice parameter a(x_str)
print('The current data format is not working for multi data variables')
elif self.z_str == 'equil_energy': # energy needs to reset reference
self.data = self.data-self.data[-1]
elif (self.x_str == 'AEXX' ) and self.z_str == 'bandgap':
bandgap_selected_value=0.67 #11.3
aexxvalue_selected = np.interp(bandgap_selected_value, self.data, self.xx)
print('AEXX=%f corresponds to selected bandgap=%feV' % (aexxvalue_selected, bandgap_selected_value) )
#with open( path+'%s_AEXX_bandgap=%.2feV' % (self.header,bandgap_selected_value), 'w') as f:
# f.write( 'AEXX=%f # BeO bandgap=%feV\n' % (aexxvalue_selected, bandgap_selected_value) )
#with open( path+'%s_AEXX_bandgap=%.2feV' % (self.header,bandgap_selected_value), 'w') as f:
# f.write( 'AEXX=%f # BeO bandgap=%feV\n' % (aexxvalue_selected, bandgap_selected_value) )
# print data
#self.xx=np.round(self.xx,6)
#self.yy=np.round(self.yy,6)
#self.data=np.round(self.data,6)
# print data
print('xx='+', '.join(np.unique(self.xx).astype(str)))
print('yy='+', '.join(np.unique(self.yy).astype(str)))
if len(self.data.shape) > 1:
for i in range(self.data.shape[0]):
print('zz='+', '.join(self.data[i].astype(str)))
else:
print('zz='+', '.join(self.data.astype(str)))
def plot(self):
plt.figure()
SMALL_SIZE = 12
MEDIUM_SIZE = 14
BIGGER_SIZE = 16
plt.rc('font', size=BIGGER_SIZE) # controls default text sizes
plt.rc('axes', titlesize=BIGGER_SIZE) # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE) # fontsize of the x and y labels
plt.rc('xtick', labelsize=SMALL_SIZE) # fontsize of the tick labels
plt.rc('ytick', labelsize=SMALL_SIZE) # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE) # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE) # fontsize of the figure title
# plot or scatter
if self.z_str == 'lattice_para':
#plt.subplots(nrows=len(data), ncols=1)
num_plots = len(self.data)
for i in range(num_plots):
#sub_num = num_plots * 100 + 10 + i
plt.subplot(num_plots, 1, i+1)
plt.plot(self.xx, self.data[i],'-')
if i == 0:
plt.title('%s' % (self.title))
plt.ylabel(self.lattice_labels[i])
else:
#plt.scatter(self.xx, self.data)
#plt.contour(self.xx, self.yy, self.data)
fig, ax = plt.subplots()
if self.z_str == 'bandgap':
levels=np.linspace(10.1,12.1,6)
CS = ax.contour(self.xx, self.yy, self.data, levels=levels)
ax.clabel(CS, inline=True, fontsize=16)
elif self.z_str == 'koopmans':
levels=[-0.2,-0.1,0.,0.1,0.2]
CS = ax.contourf(self.xx, self.yy, self.data, levels=levels)
plt.colorbar(CS)
else:
print('Error! Coutour plot method not specified')
#ax.set_title('Simplest default with labels')
# plot setting
plt.xlabel(self.xlabel) # x label
#plt.ylabel(self.ylabel) # ylabel
if self.xlim:plt.xlim(self.xlim) # if need to set xlim or ylim: set limits
if self.ylim:plt.ylim(self.ylim) # set limits
if self.y_str=='lattice_para':
pass # done previously
else:
plt.title(self.title) # add title
plt.ylabel(self.ylabel) # y label, from y_str
# save
plt.tight_layout()
figname="%scontour-%s_%s_%s.pdf" % (self.header,self.z_str, self.x_str, self.y_str)
print('save figure:%s/%s'% (os.environ['PWD'],figname))
plt.savefig(path+figname,dpi=600)
#plt.close()