pKaTool/pKa_system_file_menu.py
def uniqueness_scan(self):
        """Attempts to find critiria for when a unique solution can be found. Combinatorial scans are carried out on generated titration curves based on varius pKa values and interaction energies """
        self.display_loaded_curves.set(1)
#        pka_dists = range(0,10)
#        for i in range(len(pka_dists)):
#            pka_dists[i]=pka_dists[i]/1.0
        pka_dists = [0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0]

#        int_dists = range(0,10)
#        for i in range(len(int_dists)):
#            int_dists[i]=int_dists[i]/1.0
        int_dists = [0.0, 0.5, 1.0, 1.5, 2.0]
        out = 'pka_dist   int_dist   no_close  max_para_dist'
        print out
        for pka_dist in pka_dists:
            for int_dist in int_dists:
                #
                # move to new position
                #
                self.groups[0].intpka.set(4)
                self.groups[0].intpka.set(4+pka_dist)
                self.groups[1].intenes[0].set(int_dist)

                now = self.eval(silent=1)
                #
                # copy this conformation
                #
                self.titration_data = {}
                for group in now.curves.keys():
                    self.titration_data[group] = {}
                    for ph in now.curves[group].keys():
                        if not ph == 'pKa':
                            if not ph == 'pka':
                                self.titration_data[group][ph] = float('%4.1f'%now.curves[group][ph])################ one decimal point
                #file name
                fn = 'close_'+str(int(pka_dist*10))+'_'+str(int(int_dist*10))+'.txt'

                #max_diff = self.test_uniqueness(silent=1)
                no_close,max_para_dist = self.combinatorial_scan(silent=1,filename=fn)
                out = '%3.2f      %3.2f      %5d      %3.2f' %(pka_dist,int_dist,no_close,max_para_dist)
                print out

        return
Attempts to find critiria for when a unique solution can be found. Combinatorial scans are carried out on generated titration curves based on varius pKa values and interaction energies 
Attempts to find critiria for when a unique solution can be found. Combinatorial scans are carried out on generated titration curves based on varius pKa values and interaction energies
Attempts to find critiria for when a unique solution can be found . Combinatorial scans are carried out on generated titration curves based on varius pKa values and interaction energies
def uniqueness_scan(self):
        self.display_loaded_curves.set(1)
        pka_dists = [0.0, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0]
        int_dists = [0.0, 0.5, 1.0, 1.5, 2.0]
        out = 'pka_dist   int_dist   no_close  max_para_dist'
        print out
        for pka_dist in pka_dists:
            for int_dist in int_dists:
                 move to new position
                self.groups[0].intpka.set(4)
                self.groups[0].intpka.set(4+pka_dist)
                self.groups[1].intenes[0].set(int_dist)
                now = self.eval(silent=1)
                 copy this conformation
                self.titration_data = {}
                for group in now.curves.keys():
                    self.titration_data[group] = {}
                    for ph in now.curves[group].keys():
                        if not ph == 'pKa':
                            if not ph == 'pka':
                                self.titration_data[group][ph] = float('%4.1f'%now.curves[group][ph]) one decimal point
                file name
                fn = 'close_'+str(int(pka_dist*10))+'_'+str(int(int_dist*10))+'.txt'
                max_diff = self.test_uniqueness(silent=1)
                no_close,max_para_dist = self.combinatorial_scan(silent=1,filename=fn)
                out = '%3.2f      %3.2f      %5d      %3.2f' %(pka_dist,int_dist,no_close,max_para_dist)
                print out
        return
def uniqueness_scan ( self ) : self . display_loaded_curves . set ( 1 ) pka_dists = [ 0.0 , 0.5 , 1.0 , 1.5 , 2.0 , 2.5 , 3.0 ] int_dists = [ 0.0 , 0.5 , 1.0 , 1.5 , 2.0 ] out = 'pka_dist   int_dist   no_close  max_para_dist' print out for pka_dist in pka_dists : for int_dist in int_dists : self . groups [ 0 ] . intpka . set ( 4 ) self . groups [ 0 ] . intpka . set ( 4 + pka_dist ) self . groups [ 1 ] . intenes [ 0 ] . set ( int_dist ) now = self . eval ( silent = 1 ) self . titration_data = { } for group in now . curves . keys ( ) : self . titration_data [ group ] = { } for ph in now . curves [ group ] . keys ( ) : if not ph == 'pKa' : if not ph == 'pka' : self . titration_data [ group ] [ ph ] = float ( '%4.1f' % now . curves [ group ] [ ph ] ) fn = 'close_' + str ( int ( pka_dist * 10 ) ) + '_' + str ( int ( int_dist * 10 ) ) + '.txt' no_close , max_para_dist = self . combinatorial_scan ( silent = 1 , filename = fn ) out = '%3.2f      %3.2f      %5d      %3.2f' % ( pka_dist , int_dist , no_close , max_para_dist ) print out return
Attempts to find critiria for when a unique solution can be found.
Attempts to find critiria for when a unique solution can be found .
"""Attempts to find critiria for when a unique solution can be found. Combinatorial scans are carried out on generated titration curves based on varius pKa values and interaction energies """ #        pka_dists = range(0,10) #        for i in range(len(pka_dists)): #            pka_dists[i]=pka_dists[i]/1.0 #        int_dists = range(0,10) #        for i in range(len(int_dists)): #            int_dists[i]=int_dists[i]/1.0 # # move to new position # # # copy this conformation # ################ one decimal point #file name #max_diff = self.test_uniqueness(silent=1)
self