def Sim(data):
##<Extract pars>##
layered_water_pars=vars(rgh_dlw)
layered_sorbate_pars=vars(rgh_dls)
raxs_vars=vars(rgh_raxs)
##<update sorbates>##
domain_creator.update_sorbate(domain=Domain1,anchored_atoms=[],func=domain_creator_sorbate.OS_sqr_antiprism_oligomer,info_lib=INFO_LIB,domain_tag='_D1',rgh=rgh_domain1,index_offset=[0,1],height_offset=HEIGHT_OFFSET)#domain1
domain_creator.update_sorbate(domain=Domain2,anchored_atoms=[],func=domain_creator_sorbate.OS_sqr_antiprism_oligomer,info_lib=INFO_LIB,domain_tag='_D2',rgh=rgh_domain2,index_offset=[0,1],height_offset=HEIGHT_OFFSET)#domain2
#You can add more domains
##<link groups if any>##
[eval(each_command) for each_command in domain_creator.link_atom_group(gp_info=atom_group_info,gp_scheme=GROUP_SCHEME)]
##<format domains>##
domain={'domains':[Domain1,Domain2],'layered_water_pars':layered_water_pars,'layered_sorbate_pars':layered_sorbate_pars,\
'global_vars':rgh,'raxs_vars':raxs_vars,'F1F2':F1F2,'E0':E0,'el':RAXR_EL}
sample = model.Sample(inst, bulk, domain, unitcell,coherence=COHERENCE,surface_parms={'delta1':0.,'delta2':0.})
##<calculate structure factor for each dataset>##
F,fom_scaler=[],[]
i=0
for data_set in data:
f=np.array([])
h = data_set.extra_data['h']
k = data_set.extra_data['k']
x = data_set.x
y = data_set.extra_data['Y']
LB = data_set.extra_data['LB']
dL = data_set.extra_data['dL']
if x[0]>100:
i+=1
rough = (1-rgh.beta)/((1-rgh.beta)**2 + 4*rgh.beta*np.sin(np.pi*(y-LB)/dL)**2)**0.5
else:
rough = (1-rgh.beta)/((1-rgh.beta)**2 + 4*rgh.beta*np.sin(np.pi*(x-LB)/dL)**2)**0.5
f=abs(sample.calculate_structure_factor(h,k,x,y,index=i,fit_mode=RAXR_FIT_MODE,height_offset=HEIGHT_OFFSET*BASIS[2]))
F.append(rough*f*f)
fom_scaler.append(1)
if COUNT_TIME:
t_2=datetime.now()
##<print structure/plotting files>##
if not RUN:
domain_creator.print_structure_files_muscovite(domain_list=[Domain1,Domain2],z_shift=0.8+HEIGHT_OFFSET,matrix_info=INFO_LIB,save_file='D://')
create_plots.generate_plot_files(output_file_path=OUTPUT_FILE_PATH,sample=sample,rgh=rgh,data=data,fit_mode=RAXR_FIT_MODE,z_min=0,z_max=50,RAXR_HKL=[0,0,20],height_offset=HEIGHT_OFFSET*BASIS[2])
#then do this command inside shell to extract the errors for A and P: model.script_module.create_plots.append_errors_for_A_P(par_instance=model.parameters,dump_file='D://temp_plot_raxr_A_P_Q',raxs_rgh='rgh_raxs')
if COUNT_TIME:
t_3=datetime.now()
print "It took "+str(t_1-t_0)+" seconds to setup"
print "It took "+str(t_2-t_1)+" seconds to do calculation for one generation"
print "It took "+str(t_3-t_2)+" seconds to generate output files"
return F,1,fom_scaler
##******************************<program ends here>****************************************************##
def Sim(data,VARS=VARS):
##<update the basis info>##
INFO_LIB['basis']=np.array([unitcell.a, unitcell.b, unitcell.c])
##<Extract pars>##
layered_water_pars=vars(rgh_dlw)
layered_sorbate_pars=vars(rgh_dls)
raxs_vars=vars(rgh_raxs)
##<update sorbates>##
[domain_creator.update_sorbate_new(domain=Domain1,anchored_atoms=[],func=domain_creator_sorbate.OS_cubic_oligomer,info_lib=INFO_LIB,domain_tag='_D1',rgh=VARS['rgh_domain1_set'+str(i+1)],index_offset=[i*2*NUMBER_EL_MOTIF,NUMBER_EL_MOTIF+i*2*NUMBER_EL_MOTIF],xy_offset=XY_OFFSET,height_offset=HEIGHT_OFFSET,level=LEVEL,symmetry_couple=SYMMETRY,cap=CAP,attach_sorbate_number=EXTRA_SORBATE,first_or_second=SWITCH_EXTRA_SORBATE,mirror=MIRROR_EXTRA_SORBATE,build_grid=BUILD_GRID) for i in range(NUMBER_SORBATE_LAYER)]#domain1
##<update gaussian peaks>##
if NUMBER_GAUSSIAN_PEAK>0:
domain_creator.update_gaussian(domain=Domain1,rgh=rgh_gaussian,groups=Gaussian_groups,el=EL_GAUSSIAN_PEAK,number=NUMBER_GAUSSIAN_PEAK,height_offset=HEIGHT_OFFSET,c=unitcell.c,domain_tag='_D1',shape=GAUSSIAN_SHAPE,print_items=False,use_cumsum=True)
if NUMBER_GAUSSIAN_PEAK_FREEZE>0:
domain_creator.update_gaussian(domain=Domain1,rgh=rgh_gaussian_freeze,groups=Gaussian_groups_freeze,el=EL_GAUSSIAN_PEAK_FREEZE,number=NUMBER_GAUSSIAN_PEAK_FREEZE,height_offset=HEIGHT_OFFSET,c=unitcell.c,domain_tag='_D1',shape=GAUSSIAN_SHAPE_FREEZE,print_items=False,use_cumsum=True,freeze_tag=True)
##<link groups>##
#[eval(each_command) for each_command in domain_creator.link_atom_group(gp_info=atom_group_info,gp_scheme=GROUP_SCHEME)]
domain_creator.setup_atom_group_2(VARS)
##<format domains>##
domain={'domains':[Domain1,Domain2],'layered_water_pars':layered_water_pars,'layered_sorbate_pars':layered_sorbate_pars,\
'global_vars':rgh,'raxs_vars':raxs_vars,'F1F2':F1F2,'E0':E0,'el':RAXR_EL,'freeze':FREEZE,'exp_factors':[exp_const,rgh.mu,re,auc,rgh.ra_conc],'sig_eff':sig_eff}
sample = model.Sample(inst, bulk, domain, unitcell,coherence=COHERENCE,surface_parms={'delta1':0.,'delta2':0.})
##<calculate structure factor>##
F,fom_scaler=[],[]
i=0
for data_set in data:
f=np.array([])
h = data_set.extra_data['h']
k = data_set.extra_data['k']
x = data_set.x
y = data_set.extra_data['Y']
LB = data_set.extra_data['LB']
dL = data_set.extra_data['dL']
if data_set.use:
if x[0]>100:
i+=1
q=np.pi*2*unitcell.abs_hkl(h,k,y)
rough = (1-rgh.beta)**2/(1+rgh.beta**2 - 2*rgh.beta*np.cos(q*unitcell.c*np.sin(np.pi-unitcell.beta)/2))
pre_factor=np.exp(-exp_const*rgh.mu/q)*(4*np.pi*re/auc)**2/q**2
else:
q=np.pi*2*unitcell.abs_hkl(h,k,x)
rough = (1-rgh.beta)**2/(1+rgh.beta**2 - 2*rgh.beta*np.cos(q*unitcell.c*np.sin(np.pi-unitcell.beta)/2))
pre_factor=np.exp(-exp_const*rgh.mu/q)*(4*np.pi*re/auc)**2/q**2
f=abs(sample.calculate_structure_factor(h,k,x,y,index=i,fit_mode=RAXR_FIT_MODE,height_offset=HEIGHT_OFFSET*unitcell.c,version=VERSION))
F.append(3e6*pre_factor*rough*f*f)
fom_scaler.append(1)
else:
if x[0]>100:
i+=1
f=np.zeros(len(y))
F.append(f)
fom_scaler.append(1)
if COUNT_TIME:
t_2=datetime.now()
##<print structure/plotting files>##
if not RUN:
domain_creator.print_structure_files_muscovite_new(domain_list=[Domain1,Domain2],z_shift=0.8+HEIGHT_OFFSET,number_gaussian=NUMBER_GAUSSIAN_PEAK,el=RAXR_EL,matrix_info=INFO_LIB,save_file=OUTPUT_FILE_PATH)
create_plots.generate_plot_files(output_file_path=OUTPUT_FILE_PATH,sample=sample,rgh=rgh,data=data,fit_mode=RAXR_FIT_MODE,z_min=-5,z_max=50,RAXR_HKL=[0,0,20],height_offset=HEIGHT_OFFSET*BASIS[2],version=VERSION,freeze=FREEZE)
#make sure the tab_file is saved in the dumped files directory before running this function
#domain_creator.print_data_for_publication_B3_muscovite(N_sorbate=NUMBER_GAUSSIAN_PEAK+len(U_RAXS_LIST)+NUMBER_GAUSSIAN_PEAK_FREEZE,domain=Domain1,z_shift=0.8+HEIGHT_OFFSET+0.8666,save_file=os.path.join(OUTPUT_FILE_PATH,'temp_publication_data_muscovite.xyz'),tab_file=os.path.join(OUTPUT_FILE_PATH,'best_fit_pars.tab'))
#then do this command inside shell to extract the errors for A and P: model.script_module.create_plots.append_errors_for_A_P(par_instance=model.parameters,dump_file=os.path.join(model.script_module.OUTPUT_FILE_PATH,'temp_plot_raxr_A_P_Q'),raxs_rgh='rgh_raxs')
make_dummy_data,combine_data_sets=False,False
if make_dummy_data:
domain_creator.make_dummy_data(file=os.path.join(OUTPUT_FILE_PATH,'temp_dummy_data.dat'),data=data,I=F)
if combine_data_sets:
domain_creator.combine_all_datasets(file=os.path.join(OUTPUT_FILE_PATH,'temp_full_dataset.dat'),data=data)
atm_number={'Zr':40}
convert_files.convert_best_pars_to_matlab_input_file(file_name=os.path.join(OUTPUT_FILE_PATH,'temp_matlab_param.dat'),domain=Domain1,layered_water=rgh_dlw,c=unitcell.c,rgh=rgh,scale=inst.get_inten(),vars=VARS,freeze=FREEZE,z_raxr=atm_number[RAXR_EL])
if COUNT_TIME:
t_3=datetime.now()
print "It took "+str(t_1-t_0)+" seconds to setup"
print "It took "+str(t_2-t_1)+" seconds to do calculation for one generation"
print "It took "+str(t_3-t_2)+" seconds to generate output files"
return F,1,fom_scaler
def Sim(data,VARS=VARS):
##<Extract pars>##
layered_water_pars=vars(rgh_dlw)
layered_sorbate_pars=vars(rgh_dls)
raxs_vars=vars(rgh_raxs)
##<update sorbates>##
[domain_creator.update_sorbate_new(domain=Domain1,anchored_atoms=[],func=domain_creator_sorbate.OS_cubic_oligomer,info_lib=INFO_LIB,domain_tag='_D1',rgh=VARS['rgh_domain1_set'+str(i+1)],index_offset=[i*2*NUMBER_EL_MOTIF,NUMBER_EL_MOTIF+i*2*NUMBER_EL_MOTIF],xy_offset=XY_OFFSET,height_offset=HEIGHT_OFFSET,level=LEVEL,symmetry_couple=SYMMETRY,cap=CAP,attach_sorbate_number=EXTRA_SORBATE,first_or_second=SWITCH_EXTRA_SORBATE,mirror=MIRROR_EXTRA_SORBATE,build_grid=BUILD_GRID) for i in range(NUMBER_SORBATE_LAYER)]#domain1
##<update gaussian peaks>##
if NUMBER_GAUSSIAN_PEAK>0:
domain_creator.update_gaussian(domain=Domain1,rgh=rgh_gaussian,groups=Gaussian_groups,el=EL_GAUSSIAN_PEAK,number=NUMBER_GAUSSIAN_PEAK,height_offset=HEIGHT_OFFSET,c=unitcell.c,domain_tag='_D1',shape=GAUSSIAN_SHAPE,print_items=False,use_cumsum=True)
##<link groups>##
[eval(each_command) for each_command in domain_creator.link_atom_group(gp_info=atom_group_info,gp_scheme=GROUP_SCHEME)]
##<format domains>##
domain={'domains':[Domain1,Domain2],'layered_water_pars':layered_water_pars,'layered_sorbate_pars':layered_sorbate_pars,\
'global_vars':rgh,'raxs_vars':raxs_vars,'F1F2':F1F2,'E0':E0,'el':RAXR_EL}
sample = model.Sample(inst, bulk, domain, unitcell,coherence=COHERENCE,surface_parms={'delta1':0.,'delta2':0.})
##<calculate structure factor>##
F,fom_scaler=[],[]
i=0
for data_set in data:
f=np.array([])
h = data_set.extra_data['h']
k = data_set.extra_data['k']
x = data_set.x
y = data_set.extra_data['Y']
LB = data_set.extra_data['LB']
dL = data_set.extra_data['dL']
if x[0]>100:
i+=1
rough = (1-rgh.beta)/((1-rgh.beta)**2 + 4*rgh.beta*np.sin(np.pi*(y-LB)/dL)**2)**0.5
else:
rough = (1-rgh.beta)/((1-rgh.beta)**2 + 4*rgh.beta*np.sin(np.pi*(x-LB)/dL)**2)**0.5
f=rough*abs(sample.calculate_structure_factor(h,k,x,y,index=i,fit_mode=RAXR_FIT_MODE,height_offset=HEIGHT_OFFSET*BASIS[2]))
F.append(f*f)
fom_scaler.append(1)
if COUNT_TIME:
t_2=datetime.now()
##<print structure/plotting files>##
if not RUN:
domain_creator.print_structure_files_muscovite_new(domain_list=[Domain1,Domain2],z_shift=0.8+HEIGHT_OFFSET,number_gaussian=NUMBER_GAUSSIAN_PEAK,el=RAXR_EL,matrix_info=INFO_LIB,save_file=OUTPUT_FILE_PATH)
create_plots.generate_plot_files(output_file_path=OUTPUT_FILE_PATH,sample=sample,rgh=rgh,data=data,fit_mode=RAXR_FIT_MODE,z_min=0,z_max=50,RAXR_HKL=[0,0,20],height_offset=HEIGHT_OFFSET*BASIS[2])
#then do this command inside shell to extract the errors for A and P: model.script_module.create_plots.append_errors_for_A_P(par_instance=model.parameters,dump_file=os.path.join(model.script_module.OUTPUT_FILE_PATH,'temp_plot_raxr_A_P_Q'),raxs_rgh='rgh_raxs')
make_dummy_data,combine_data_sets=False,False
if make_dummy_data:
domain_creator.make_dummy_data(file=os.path.join(OUTPUT_FILE_PATH,'temp_dummy_data.dat'),data=data,I=F)
if combine_data_sets:
domain_creator.combine_all_datasets(file=os.path.join(OUTPUT_FILE_PATH,'temp_full_dataset.dat'),data=data)
if COUNT_TIME:
t_3=datetime.now()
print "It took "+str(t_1-t_0)+" seconds to setup"
print "It took "+str(t_2-t_1)+" seconds to do calculation for one generation"
print "It took "+str(t_3-t_2)+" seconds to generate output files"
return F,1,fom_scaler
##========================================<program ends here>========================================================##
