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qp_plugins_scemama/devel/svdwf/buildpsi_diagSVDit.py
Abdallah Ammar 2fd2fcac5d svd save
2021-07-28 17:19:18 +02:00

615 lines
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Python
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import sys, os
QMCCHEM_PATH=os.environ["QMCCHEM_PATH"]
sys.path.insert(0,QMCCHEM_PATH+"/EZFIO/Python/")
from ezfio import ezfio
from datetime import datetime
import time
import numpy as np
import subprocess
from scipy.linalg import eig, eigh
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_energy():
buffer = subprocess.check_output( ['qmcchem', 'result', '-e', 'e_loc', filename]
, encoding='UTF-8' )
if buffer.strip() != "":
buffer = buffer.splitlines()[-1]
_, energy, error = [float(x) for x in buffer.split()]
return energy, error
else:
return None, None
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def run_qmc():
return subprocess.check_output(['qmcchem', 'run', filename])
def stop_qmc():
subprocess.check_output(['qmcchem', 'stop', filename])
def set_vmc_params():
#subprocess.check_output(['qmcchem', 'edit', '-c', '-j', 'Simple',
# '-m', 'VMC',
# '-l', str(20),
# '--time-step=0.3',
# '--stop-time=36000',
# '--norm=1.e-5',
# '-w', '10',
# filename])
subprocess.check_output(['qmcchem', 'edit', '-c'
, '-j', 'None'
, '-l', str(block_time)
, '-t', str(total_time)
, filename])
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_Aref():
Aref = np.zeros( (n_alpha, n_beta) )
for k in range(n_det):
i = A_rows[k] - 1
j = A_cols[k] - 1
Aref[i,j] = A_vals[0][k]
return( Aref )
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def check_svd_error( A, U, S, V ):
# || A - U x S x transpose(V) ||
# to normalize
norm_A = np.linalg.norm(A, ord='fro')
# vector S ==> matrix S
_, na = U.shape
_, nb = V.shape
S_mat = np.zeros( (na,nb) )
for i in range( min(na,nb) ):
S_mat[i,i] = S[i]
#A_SVD = np.linalg.multi_dot([ U, np.diag(S), Vt ])
A_SVD = np.linalg.multi_dot([ U, S_mat, V.T ])
err_SVD = 100. * np.linalg.norm( A - A_SVD, ord="fro") / norm_A
print(' error between A_SVD and Aref = {} %\n'.format(err_SVD) )
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def FSVD_save_EZFIO():
U_toEZFIO = np.zeros( ( 1, U_FSVD.shape[1], U_FSVD.shape[0] ) )
V_toEZFIO = np.zeros( ( 1, V_FSVD.shape[1], V_FSVD.shape[0] ) )
U_toEZFIO[0,:,:] = U_FSVD.T
V_toEZFIO[0,:,:] = V_FSVD.T
ezfio.set_spindeterminants_psi_svd_alpha_unique( U_toEZFIO )
ezfio.set_spindeterminants_psi_svd_beta_unique ( V_toEZFIO )
ezfio.set_spindeterminants_psi_svd_coefs_unique( S_FSVD )
print(' Full SVD unique vectors & coeff are saved to EZFIO ')
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def numerote_selected_vectors():
numalpha_selected = []
numbeta_selected = []
for i in range(n_TSVD):
for j in range(n_TSVD):
numalpha_selected.append(j+1)
numbeta_selected.append(i+1)
if( (len(numalpha_selected)!=n_selected) or (len(numbeta_selected)!=n_selected) ) :
print(' error in numerating selectod vectors')
print(' {} != {} != {}'.format(n_selected,len(numalpha_selected),len(numbeta_selected)) )
else:
ezfio.set_spindeterminants_psi_svd_alpha_numselected(numalpha_selected)
ezfio.set_spindeterminants_psi_svd_beta_numselected (numbeta_selected)
print(' selected vectors are numeroted in EZFIO')
return( numalpha_selected,numbeta_selected )
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def numerote_toselect_vectors( choix ):
numalpha_toselect = []
numbeta_toselect = []
if( choix == 3 ):
# nondiagonal blocs
for i in range(n_TSVD):
for j in range(n_TSVD,n_beta):
numalpha_toselect.append(i+1)
numbeta_toselect.append(j+1)
for i in range(n_TSVD,n_alpha):
for j in range(n_TSVD):
numalpha_toselect.append(i+1)
numbeta_toselect.append(j+1)
# diagonal bloc
for i in range(n_TSVD,n_alpha):
for j in range(n_TSVD,n_beta):
numalpha_toselect.append(i+1)
numbeta_toselect.append(j+1)
elif( choix == 2 ):
# nondiagonal blocs
for i in range(n_TSVD):
for j in range(n_TSVD,n_beta):
numalpha_toselect.append(i+1)
numbeta_toselect.append(j+1)
for i in range(n_TSVD,n_alpha):
for j in range(n_TSVD):
numalpha_toselect.append(i+1)
numbeta_toselect.append(j+1)
else:
print(' choix = 2 ou 3' )
exit()
if( (len(numalpha_toselect)!=n_toselect) or (len(numbeta_toselect)!=n_toselect) ) :
print(' error in numerating vectors to select')
print(' {} != {} != {}'.format(n_toselect,len(numalpha_toselect),len(numbeta_toselect)) )
else:
ezfio.set_spindeterminants_psi_svd_alpha_numtoselect(numalpha_toselect)
ezfio.set_spindeterminants_psi_svd_beta_numtoselect (numbeta_toselect)
print(' vectors to select are numeroted in EZFIO')
return( numalpha_toselect,numbeta_toselect )
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def normalize_S_TSVD():
global S_TSVD
norm_S_TSVD = np.linalg.norm(S_TSVD, ord='fro')
S_TSVD = S_TSVD / norm_S_TSVD
return()
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_h_selected_matrix():
h_selected_matrix = np.zeros( (n_selected,n_selected) )
h_selected_stater = np.zeros( (n_selected,n_selected) )
beg_h_selected_matrix = results.find('h_selected_matrix : [ ') + len('h_selected_matrix : [ ')
end_h_selected_matrix = len(results)
h_selected_matrix_buf = results[beg_h_selected_matrix:end_h_selected_matrix]
h_selected_matrix_buf = h_selected_matrix_buf.split( '\n' )
for i in range(1,n_selected+1):
ii0 = (i-1) * n_selected
for j in range(1,n_selected+1):
iline = ii0 + j
line = h_selected_matrix_buf[iline].split()
indc = int ( line[0] )
if( indc != iline ):
print('Error in get_h_selected_matrix')
exit()
else:
h_selected_matrix[i-1][j-1] = float( line[2] )
h_selected_stater[i-1][j-1] = float( line[4] )
return(h_selected_matrix,h_selected_stater)
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_o_selected_matrix():
o_selected_matrix = np.zeros( (n_selected,n_selected) )
o_selected_stater = np.zeros( (n_selected,n_selected) )
beg_o_selected_matrix = results.find('overlop_selected_matrix : [ ') + len('overlop_selected_matrix : [ ')
end_o_selected_matrix = len(results)
o_selected_matrix_buf = results[beg_o_selected_matrix:end_o_selected_matrix]
o_selected_matrix_buf = o_selected_matrix_buf.split( '\n' )
for i in range(1,n_selected+1):
ii0 = (i-1) * n_selected
for j in range(1,n_selected+1):
iline = ii0 + j
line = o_selected_matrix_buf[iline].split()
indc = int ( line[0] )
if( indc != iline ):
print('Error in get_o_selected_matrix')
exit()
else:
o_selected_matrix[i-1][j-1] = float( line[2] )
o_selected_stater[i-1][j-1] = float( line[4] )
return(o_selected_matrix,o_selected_stater)
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_Epostsvd():
# symmetrise and diagonalise
aa = h_selected_matrix
aa = 0.5*( aa + aa.T )
bb = o_selected_matrix
eigvals_postsvd, vr = eig(aa, bb, left=False, right=True, overwrite_a=True, overwrite_b=True,
check_finite=True, homogeneous_eigvals=False)
d_postsvd = np.diagflat(S_TSVD)
d_postsvd = d_postsvd.reshape( (1,n_selected*n_selected) )
recouvre_postsvd = np.abs(d_postsvd @ vr)
ind_gspostsvd = np.argmax(recouvre_postsvd)
E_postsvd = eigvals_postsvd[ind_gspostsvd]
return( E_postsvd, vr[:,ind_gspostsvd] )
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def Hqmc_svd_diag():
# read CI_SVD matrices
Ci_h_matrix_svd = get_Ci_h_matrix_svd()
Ci_overlap_matrix_svd = get_Ci_overlap_matrix_svd()
# symmetrise
aa = Ci_h_matrix_svd
aa = 0.5*( aa + aa.T )
bb = Ci_overlap_matrix_svd
# diagonalise
eigvals_svd, vr = eig( aa, bb, left=False, right=True
, overwrite_a=True, overwrite_b=True
, check_finite=True, homogeneous_eigvals=False)
recouvre_svd = np.abs( np.dot( S_FSVD, vr) )
ind_gssvd = np.argmax(recouvre_svd)
E_svd = eigvals_svd[ind_gssvd] + nuc_energy
return( E_svd, vr[:,ind_gssvd] )
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def SVD_postsvd():
# reshape sigma_postsvd
sigma_postsvd_mat = np.zeros( (n_selected,n_selected) )
for i in range(n_TSVD):
ii = i*n_TSVD
for j in range(n_TSVD):
jj = i*n_TSVD + j
sigma_postsvd_mat[i][j] = sigma_postsvd[jj]
# construct the new matrix Y & perform a new SVD
Y = np.dot( U_TSVD , np.dot(sigma_postsvd_mat , Vt_TSVD) )
U, S, Vt = np.linalg.svd(Y, full_matrices=True)
return(U, S, Vt)
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_hij_fm():
hij_fm = np.zeros( (n_toselect) )
hij_fm_stater = np.zeros( (n_toselect) )
beg_hij = results.find('hij_fm : [ ') + len('hij_fm : [ ')
end_hij = len(results)
hij_buf = results[beg_hij:end_hij]
hij_buf = hij_buf.split( '\n' )
for iline in range(1,n_toselect+1):
line = hij_buf[iline].split()
indc = int( line[0] )
if( indc != iline ):
print('Error in get_hij_fm')
exit()
else:
hij_fm [iline-1] = float( line[2] )
hij_fm_stater[iline-1] = float( line[4] )
return(hij_fm, hij_fm_stater)
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_hij_sm():
hij_sm = np.zeros( (n_toselect) )
hij_sm_stater = np.zeros( (n_toselect) )
beg_hij = results.find('hij_sm : [ ') + len('hij_sm : [ ')
end_hij = len(results)
hij_buf = results[beg_hij:end_hij]
hij_buf = hij_buf.split( '\n' )
for iline in range(1,n_toselect+1):
line = hij_buf[iline].split()
indc = int( line[0] )
if( indc != iline ):
print('Error in get_hij_sm')
exit()
else:
hij_sm [iline-1] = float( line[2] )
hij_sm_stater[iline-1] = float( line[4] )
return(hij_sm, hij_sm_stater)
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
def get_xij_diag():
xij_diag = np.zeros( (n_toselect) )
xij_diag_stater = np.zeros( (n_toselect) )
beg_xij = results.find('xij_diag : [ ') + len('xij_diag : [ ')
end_xij = len(results)
xij_buf = results[beg_xij:end_xij]
xij_buf = xij_buf.split( '\n' )
for iline in range(1,n_toselect+1):
line = xij_buf[iline].split()
indc = int( line[0] )
if( indc != iline ):
print('Error in get_xij_diag')
exit()
else:
xij_diag [iline-1] = float( line[2] )
xij_diag_stater[iline-1] = float( line[4] )
return(xij_diag, xij_diag_stater)
# ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ ! ~ !
if __name__ == '__main__':
t0 = time.time()
print("Today's date:", datetime.now() )
# EZFIO file
filename = "/home/aammar/qp2/src/svdwf/2h2_work/2h2_cisd"
ezfio.set_file(filename)
print("filename = {}".format(filename))
# parameters
energ_nuc = 1.711353545183182 # for 2h2
# get spindeterminant data from EZFIO
n_alpha = ezfio.get_spindeterminants_n_det_alpha()
n_beta = ezfio.get_spindeterminants_n_det_beta()
A_rows = np.array(ezfio.get_spindeterminants_psi_coef_matrix_rows() )
A_cols = np.array(ezfio.get_spindeterminants_psi_coef_matrix_columns())
A_vals = np.array(ezfio.get_spindeterminants_psi_coef_matrix_values() )
n_det = A_rows.shape[0]
print('~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~')
print(' matrix: {} x {}'.format(n_alpha,n_beta))
print(' n_det = {}'.format(n_det))
print('~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~')
# construct intial dense matrix
Aref = get_Aref()
# perform initial Full SVD
print('')
print(' ----- Performing Full SVD ----- ')
U_FSVD, S_FSVD, Vt_FSVD = np.linalg.svd(Aref, full_matrices=True)
V_FSVD = Vt_FSVD.T
# check Full SVD error
check_svd_error( Aref, U_FSVD, S_FSVD, V_FSVD )
# save SVD vectors & coefficients in EZFIO
ezfio.set_spindeterminants_n_svd_coefs_unique(min(n_alpha,n_beta))
FSVD_save_EZFIO()
# truncated SVD
n_TSVD = 15
ezfio.set_spindeterminants_n_svd_coefs(n_TSVD)
U_TSVD = U_FSVD[:,:n_TSVD]
V_TSVD = V_FSVD[:,:n_TSVD]
S_TSVD = S_FSVD[:n_TSVD]
# check truncataed SVD error
check_svd_error( Aref, U_TSVD, S_TSVD, V_TSVD )
# numerote selected vectors & save to EZFIO
n_selected = n_TSVD * n_TSVD
print(' n_selected = {}'.format(n_selected))
ezfio.set_spindeterminants_n_svd_selected(n_selected)
numalpha_selected,numbeta_selected = numerote_selected_vectors()
# numerote vectors to select & save to EZFIO
n_toselect = n_alpha * n_beta - n_selected
print(' n_toselect = {}'.format(n_toselect))
ezfio.set_spindeterminants_n_svd_toselect(n_toselect)
numalpha_toselect,numbeta_toselect = numerote_toselect_vectors(choix=3)
#_________________________________________________________________________________________
#
# loop over SVD iterations
#_________________________________________________________________________________________
it_svd = 0
it_svd_max = 1
while( it_svd < it_svd_max ):
it_svd = it_svd + 1
# normalize sigular values in the truncated space
#normalize_S_TSVD()
# run QMC to get H_postsvd
block_time = 300 # in sec
total_time = 1800 # in sec
set_vmc_params()
ezfio.set_properties_hij_fm(False)
ezfio.set_properties_hij_sm(False)
ezfio.set_properties_xij_diag(False)
ezfio.set_properties_h_selected_matrix(True)
ezfio.set_properties_overlop_selected_matrix(True)
run_qmc()
# read QMC=CHEM results
t_read = time.time()
print(' getting QMCCHEM results from {}'.format(EZFIO_file) )
results = subprocess.check_output(['qmcchem', 'result', EZFIO_file, '>> results.dat'], encoding='UTF-8')
print(' getting results after {} minutes \n'.format( (time.time()-t_read)/60. ))
# < E_loc >
Eloc, ErrEloc = get_energy()
print(' Eloc = {} +/- {}'.format(Eloc, ErrEloc))
# get H and overlop from QMC=CHEM
h_selected_matrix, h_selected_stater = get_h_selected_matrix()
o_selected_matrix, o_selected_stater = get_o_selected_matrix()
# ground state from H S = E S
E_postsvd, sigma_postsvd = get_Epostsvd()
print(' post svd energy = {}'.format(E_postsvd+energ_nuc) )
# perform new SVD: U x sigma_postsvd x Vt --> U' x S' x Vt'
U_FSVD, S_FSVD, Vt_FSVD = SVD_postsvd()
V_FSVD = Vt_FSVD.T
# save in EZFIO
FSVD_save_EZFIO()
# run QMC to get hij, e and xij_diag from QMC=CHEM
block_time = 300 # in sec
total_time = 1800 # in sec
set_vmc_params()
ezfio.set_properties_h_selected_matrix(False)
ezfio.set_properties_overlop_selected_matrix(False)
ezfio.set_properties_hij_fm(True)
ezfio.set_properties_hij_sm(True)
ezfio.set_properties_xij_diag(True)
run_qmc()
# read QMC=CHEM results
t_read = time.time()
print(' getting QMCCHEM results from {}'.format(EZFIO_file) )
results = subprocess.check_output(['qmcchem', 'result', EZFIO_file, '>> results.dat'], encoding='UTF-8')
print(' getting results after {} minutes \n'.format( (time.time()-t_read)/60. ))
# < E_loc >
Eloc, ErrEloc = get_energy()
print(' Eloc = {} +/- {}'.format(Eloc, ErrEloc))
# hij = < psi_svd J | H | J l l' > / < psi_svd J | psi_svd J >
# = < H (J l l')/(psi_svd J) > ( first method: fm )
# = < E_loc (l l') / psi_svd > ( second method: sm )
hij_fm, hif_fm_stater = get_hij_fm()
hij_sm, hif_sm_stater = get_hij_sm()
# get xij_diag
xij_diag, xij_diag_stater = get_xij_diag()
# first method
dij_fm = np.zeros( (n_toselect) )
dij_fm_stater = np.zeros( (n_toselect) )
for i in range(n_toselect):
dij_fm[i] = hij_fm[i] / ( Eloc - xij_diag[i] )
# statistic error
a = ( hij_fm_stater[i]*hij_fm_stater[i] ) / ( hij_fm[i]*hij_fm[i] )
b = ( ErrEloc*ErrEloc + xij_diag_stater[i]*xij_diag_stater[i] ) / ( (Eloc-xij_diag[i])*(Eloc-xij_diag[i]) )
dij_fm_stater[i] = abs(dij_fm[i]) * np.sqrt( a + b )
cc = np.concatenate((dij_fm,dij_fm_stater),axis=1)
np.savetxt('dij_fm.txt',cc)
# second method
dij_sm = np.zeros( (n_toselect) )
dij_sm_stater = np.zeros( (n_toselect) )
for i in range(n_toselect):
dij_sm[i] = hij_sm[i] / ( Eloc - xij_diag[i] )
# statistic error
a = ( hij_fm_stater[i]*hij_fm_stater[i] ) / ( hij_sm[i]*hij_sm[i] )
b = ( ErrEloc*ErrEloc + xij_diag_stater[i]*xij_diag_stater[i] ) / ( (Eloc-xij_diag[i])*(Eloc-xij_diag[i]) )
dij_sm_stater[i] = abs(dij_sm[i]) * np.sqrt( a + b )
cc = np.concatenate((dij_sm,dij_sm_stater),axis=1)
np.savetxt('dij_sm.txt',cc)
# TODO
# choose fm or sm & perform a new SVD
#_________________________________________________________________________________________
print("end after {:.3f} minutes".format((time.time()-t0)/60.) )
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