-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathplot_r2SCANx_bh76_mads.py
187 lines (153 loc) · 5.69 KB
/
plot_r2SCANx_bh76_mads.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
import yaml
import numpy as np
from os import path
from glob import glob
import matplotlib.pyplot as plt
from matplotlib.ticker import (MultipleLocator, AutoMinorLocator)
from analysis import BH76_analysis,rdir
sl_name = 'r2SCAN'
sl_tex_name = 'r$^2$SCAN'
abbr_name = 'R2'
hf_dir = './results_aug-cc-pvqz/'
hyb_dir = './{:}_hybrids/'.format(sl_name)
fl_l = glob('./{:}_hybrids/{:}*X'.format(sl_name,sl_name))
x_l = np.sort(np.asarray([float(adir[:-1].split(sl_name)[-1]) for adir in fl_l]))
Nx = len(x_l)
dfad = {'LSDA': 'LSDA', 'PBE': 'PBE', 'BLYP': 'BLYP' ,
'SCAN': 'SCAN', 'r2SCAN': 'r$^2$SCAN',
'B3LYP': 'B3LYP', 'LCwPBE': 'LC-$\\omega$PBE',
abbr_name: '{:}X-$x$'.format(abbr_name)
}
lbld = {'LSDA': [0,0.70,11],
'PBE': [0,0.60,6.4],
'BLYP': [1,0.50,.57],
'B3LYP': [0,0.41,4.1],
'LCwPBE': [1, 0.65, 1.38],
'R2': [0,0.80,6.1], 'r2SCAN': [0,0.25,5.4], 'SCAN': [1,0.60,.8]
}
cls = ['darkblue','darkorange','dodgerblue','tab:green','darkred','indigo','k','gray']
lsls = ['-','--','-.',':']
fig,ax = plt.subplots(2,1,figsize=(6,7))
ndfa = 1
for dfa in dfad:
ndfa += 1
ovals = np.zeros((Nx+2,ndfa))
for ix in range(Nx):
ovals[ix,0] = x_l[ix]/100.
scf_mads = {abbr_name: 0.0}
for dfa in dfad:
if dfa == abbr_name:
continue
tdir = hf_dir + '/' + dfa + '/' + dfa + '_BH76/'
tfl = tdir + 'BH76_total.yaml'
if not path.isfile(tfl):
BH76_analysis(cdir=tdir)
td = yaml.load(open(tfl,'r'),Loader=yaml.Loader)
scf_mads[dfa] = td['Stats']['MAD']
at_hf_mads = {abbr_name: 1.0}
for dfa in dfad:
if dfa == abbr_name:
continue
tdir = hf_dir + '/' + dfa + '/' + dfa + '@HF_BH76/'
tfl = tdir + 'BH76_total.yaml'
if not path.isfile(tfl):
BH76_analysis(cdir=tdir)
td = yaml.load(open(tfl,'r'),Loader=yaml.Loader)
at_hf_mads[dfa] = td['Stats']['MAD']
for idfa,dfa in enumerate(dfad):
tlist = [0.0 for ix in range(Nx)]
for ix,x in enumerate(x_l):
if dfa == abbr_name:
if x == 0:
tdir = hyb_dir + '/{:}00X/{:}_BH76/'.format(sl_name,sl_name)
elif x == 'HF':
tdir = hf_dir + '/HF_BH76/'
else:
tdir = hyb_dir + '/{:}{:}X/{:}_{:}_EXX_BH76/'.format(\
sl_name,int(x),sl_name,int(x))
else:
if x == 0:
if dfa == sl_name:
tdir = hyb_dir + '/{:}00X/{:}_BH76/'.format(sl_name,sl_name)
else:
tdir = hyb_dir + '/{:}00X/{:}@{:}00X_BH76/'.format(\
sl_name,dfa,sl_name)
elif x == 'HF':
tdir = hf_dir + '/' + dfa + '@HF_BH76/'
else:
tdir = hyb_dir + '/{:}{:}X/{:}@{:}{:}X_BH76/'.format(\
sl_name,int(x),dfa,sl_name,int(x))
tfl = tdir + 'BH76_total.yaml'
if not path.isfile(tfl):
BH76_analysis(cdir=tdir)
td = yaml.load(open(tfl,'r'),Loader=yaml.Loader)
tlist[ix] = td['Stats']['MAD']
ovals[ix,1+idfa] = td['Stats']['MAD']
ovals[-2,1+idfa] = scf_mads[dfa]
if dfa != abbr_name:
ovals[-1,1+idfa] = at_hf_mads[dfa]
ax[0].plot(x_l/100., tlist, color=cls[idfa], linestyle=lsls[idfa%len(lsls)],\
label=dfad[dfa])
if dfa != abbr_name:
ax[1].plot(x_l/100.,np.array(tlist)/scf_mads[dfa],color=cls[idfa],\
linestyle=lsls[idfa%len(lsls)],label=dfad[dfa])
if dfa in lbld:
ax[lbld[dfa][0]].annotate(dfad[dfa],(lbld[dfa][1],lbld[dfa][2]),\
color=cls[idfa], fontsize=12)
ax[1].set_xlabel('$x$',fontsize=12)
xticks = np.array([0,10,25,40,50,60,70,80,90,100])/100.
xtl = []
for x in xticks:
if x == 0.:
xtl.append(sl_tex_name)
elif x == 0.25:
xtl.append('0.25/{:}0'.format(sl_tex_name))
else:
xtl.append('{:}'.format(x))
for i in range(2):
ax[i].set_xlim(min(x_l)/100.,max(x_l)/100.)
ax[i].tick_params(axis='both',labelsize=10)
ax[i].set_xticks(xticks)
ax[i].set_xticklabels(xtl,rotation=0)
ax[0].set_ylabel('BH76 MAD \n(kcal/mol)',fontsize=12,rotation=45)
ax[0].yaxis.set_label_coords(-0.085,.65)
ax[1].set_ylabel('$\\frac{\\mathrm{MAD(DFA@'+abbr_name+'X)}}{\\mathrm{MAD(DFA@DFA)}}$',\
fontsize=12,rotation=45)
ax[1].yaxis.set_label_coords(-0.05,0.9)
#ax[1].legend(fontsize=12,ncol=2)
ax[1].hlines(1.0,*ax[1].get_xlim(),color='k',linewidth=1,linestyle=':')
ax[0].yaxis.set_minor_locator(MultipleLocator(1))
ax[0].yaxis.set_major_locator(MultipleLocator(5))
ax[1].yaxis.set_minor_locator(MultipleLocator(0.1))
ax[1].yaxis.set_major_locator(MultipleLocator(0.5))
ax[0].annotate('(a)',(0.01,12),fontsize=16)
ax[1].annotate('(b)',(0.01,1.5),fontsize=16)
#plt.show() ; exit()
plt.savefig('./{:}_hyb_mads.pdf'.format(sl_name),dpi=600,bbox_inches='tight')
tmpstr = 'x'
for dfa in dfad:
tmpstr += ', {:}'.format(dfa)
if dfa == abbr_name:
tmpstr += 'X-x'
tmpstr += '\n'
tmpstr += 'SCF' + (', {:}'*(ndfa-1)).format(*ovals[-2,1:]) + '\n'
for ix in range(Nx):
tmpstr += ('{:}, '*(ndfa-1) + '{:} \n').format(*ovals[ix])
tmpstr += '@HF' + (', {:}'*(ndfa-1)).format(*ovals[-1,1:]) + '\n'
with open('./DFA_at_{:}Xx.csv'.format(abbr_name),'w+') as tfl:
tfl.write(tmpstr)
tmpstr = '$x$'
for dfa in dfad:
tmpstr += ' & {:}'.format(dfa)
if dfa == abbr_name:
tmpstr += 'X-$x$'
tmpstr += ' \\\\ \n'
tmpstr += 'SCF' + (' & {:.2f}'*(ndfa-1)).format(*ovals[-2,1:]) + ' \\\\ \hline \n'
for ix in range(Nx):
lchar = ''
if ix == Nx-1:
lchar = '\hline'
tmpstr += ('{:.2f}' + ' & {:.2f}'*(ndfa-1) + ' \\\\ {:} \n').format(*ovals[ix],lchar)
tmpstr += '@HF' + (' & {:.2f}'*(ndfa-1)).format(*ovals[-1,1:]) + ' \\\\ \n'
with open('./DFA_at_{:}Xx.tex'.format(abbr_name),'w+') as tfl:
tfl.write(tmpstr)