#spectra=ccam.normalize(spectra,wvl,normtype=normtype)
#
#km=cluster.KMeans(n_clusters=k,n_init=100)
#km.fit(spectra)
#clusters=km.predict(spectra)
#
#

#calculate full model
ccam.pls_cal(dbfile,
             maskfile,
             outpath,
             which_elem,
             testfold,
             nc,
             normtype=normtype,
             mincomp=mincomp,
             maxcomp=maxcomp,
             plstype=plstype,
             keepfile=keepfile,
             removefile=removefile,
             cal_dir=cal_dir,
             masterlist_file=masterlist_file,
             compfile=dbfile,
             name_sub_file=name_sub_file,
             foldfile=foldfile,
             nfolds=nfolds)

#for i in range(k):
#    ccam.pls_cal(dbfile,maskfile,outpath,which_elem,testfold,nc,normtype=normtype,mincomp=mincomp,maxcomp=maxcomp,plstype=plstype,keepfile=keepfile,removefile=removefile,cal_dir=cal_dir,masterlist_file=masterlist_file,compfile=dbfile,name_sub_file=name_sub_file,foldfile=foldfile,nfolds=nfolds,clusters=(clusters==i))
Пример #2
0
#calculate full model
normtype = 3
removefile = 'C:\\Users\\rbanderson\\Documents\\MSL\\ChemCam\\DataProcessing\\Working\\Input\\removelist_Na2O_0-100.csv'

ccam.pls_cal(dbfile,
             maskfile,
             outpath,
             which_elem,
             testfold,
             nc,
             normtype=normtype,
             mincomp=mincomp,
             maxcomp=maxcomp,
             plstype=plstype,
             keepfile=keepfile,
             removefile=removefile,
             cal_dir=cal_dir,
             masterlist_file=masterlist_file,
             compfile=dbfile,
             name_sub_file=name_sub_file,
             foldfile=foldfile,
             nfolds=nfolds,
             seed=seed,
             n_bag=None,
             n_boost=None,
             skscale=False)

normtype = 1
ccam.pls_cal(dbfile,
             maskfile,
             outpath,
Пример #3
0
removefile = 'C:\\Users\\rbanderson\\Documents\\Projects\\MSL\\ChemCam\\DataProcessing\\Working\\Input\\removelist_SiO2_0-100.csv'

#set the range of compositions in the submodel
mincomp = 0
maxcomp = 100
#Set the normalization  for the submodel
normtype = 1
ccam.pls_cal(dbfile,
             maskfile,
             outpath,
             which_elem,
             nc,
             normtype=normtype,
             mincomp=mincomp,
             maxcomp=maxcomp,
             keepfile=keepfile,
             removefile=removefile,
             cal_dir=cal_dir,
             masterlist_file=masterlist_file,
             compfile=dbfile,
             name_sub_file=name_sub_file,
             testsetfile=testsetfile,
             nfolds=nfolds,
             seed=seed,
             skscale=False)

#Set the normalization  for the submodel
normtype = 3
ccam.pls_cal(dbfile,
             maskfile,
             outpath,
             which_elem,