PEATDB/Ekin/Titration.py
def makeCombined(cls, ekindata1, ekindata2, names=None):
        """Make combined chem shft and fit,then compare to originals"""

        proteins = ekindata1.keys()
        ekindatac = {}
        E1 = EkinProject(ekindata1)
        E2 = EkinProject(ekindata2)
        for prot in proteins:
            print
            if cls.protnames != None:
                name = cls.protnames[prot]
                print 'processing protein', name
            print '-------------------------'
            if names != None and name not in names:
                continue
            if not ekindata2.has_key(prot):
                print 'this protein is not in the 2nd ekindata'
                continue
            edata1 = ekindata1[prot]; E1 = EkinProject(data=edata1)
            edata2 = ekindata2[prot]; E2 = EkinProject(data=edata2)
            Ec = EkinProject()
            for d in E1.datasets:
                if d in cls.excluded or not d in E2.datasets:
                    continue
                d1 = E1.getDataset(d)
                d2 = E2.getDataset(d)
                print name
                dc = cls.combineCurves(d1, d2)
                Ec.insertDataset(dc, d)
            Ec.saveProject(name[:5]+'_combined')
            for d in Ec.datasets:
                f, p = Ec.findBestModel(d, models=cls.models, strictchecking=True, alpha=0.05)
            Ec.saveProject(name[:5]+'_combined')
            ekindatac[prot] = Ec.prepare_data()
        return
Make combined chem shft and fit,then compare to originals
Make combined chem shft and fit,then compare to originals
Make combined chem shft and fit then compare to originals
def makeCombined(cls, ekindata1, ekindata2, names=None):
        proteins = ekindata1.keys()
        ekindatac = {}
        E1 = EkinProject(ekindata1)
        E2 = EkinProject(ekindata2)
        for prot in proteins:
            print
            if cls.protnames != None:
                name = cls.protnames[prot]
                print 'processing protein', name
            print '-------------------------'
            if names != None and name not in names:
                continue
            if not ekindata2.has_key(prot):
                print 'this protein is not in the 2nd ekindata'
                continue
            edata1 = ekindata1[prot]; E1 = EkinProject(data=edata1)
            edata2 = ekindata2[prot]; E2 = EkinProject(data=edata2)
            Ec = EkinProject()
            for d in E1.datasets:
                if d in cls.excluded or not d in E2.datasets:
                    continue
                d1 = E1.getDataset(d)
                d2 = E2.getDataset(d)
                print name
                dc = cls.combineCurves(d1, d2)
                Ec.insertDataset(dc, d)
            Ec.saveProject(name[:5]+'_combined')
            for d in Ec.datasets:
                f, p = Ec.findBestModel(d, models=cls.models, strictchecking=True, alpha=0.05)
            Ec.saveProject(name[:5]+'_combined')
            ekindatac[prot] = Ec.prepare_data()
        return
def makeCombined ( cls , ekindata1 , ekindata2 , names = None ) : proteins = ekindata1 . keys ( ) ekindatac = { } E1 = EkinProject ( ekindata1 ) E2 = EkinProject ( ekindata2 ) for prot in proteins : print if cls . protnames != None : name = cls . protnames [ prot ] print 'processing protein' , name print '-------------------------' if names != None and name not in names : continue if not ekindata2 . has_key ( prot ) : print 'this protein is not in the 2nd ekindata' continue edata1 = ekindata1 [ prot ] ; E1 = EkinProject ( data = edata1 ) edata2 = ekindata2 [ prot ] ; E2 = EkinProject ( data = edata2 ) Ec = EkinProject ( ) for d in E1 . datasets : if d in cls . excluded or not d in E2 . datasets : continue d1 = E1 . getDataset ( d ) d2 = E2 . getDataset ( d ) print name dc = cls . combineCurves ( d1 , d2 ) Ec . insertDataset ( dc , d ) Ec . saveProject ( name [ : 5 ] + '_combined' ) for d in Ec . datasets : f , p = Ec . findBestModel ( d , models = cls . models , strictchecking = True , alpha = 0.05 ) Ec . saveProject ( name [ : 5 ] + '_combined' ) ekindatac [ prot ] = Ec . prepare_data ( ) return
Make combined chem shft and fit,then compare to originals
Make combined chem shft and fit then compare to originals
"""Make combined chem shft and fit,then compare to originals"""
cls
ekindata1
ekindata2
names