Index: fittingview/src/sans/perspectives/fitting/plugin_models/sum_p1_p2.py
===================================================================
--- fittingview/src/sans/perspectives/fitting/plugin_models/sum_p1_p2.py	(revision e9bd127913a8ceb9ec7480a739688e320a4a8239)
+++ 	(revision )
@@ -1,409 +1,0 @@
-# A sample of an experimental model function for Sum(Pmodel1,Pmodel2)
-import copy
-from sans.models.pluginmodel import Model1DPlugin
-
-"""
-## *****************************************************************************
-Please select the 'Compile' from the menubar after the modification and saving.
-Note that we recommend to save the file as a different file name.
-Otherwise, it could be removed in the future on re-installation of the SansView.
-## *****************************************************************************
-"""
-
-# Available model names for this sum model
-"""
-BCCrystalModel, BEPolyelectrolyte, BarBellModel, BinaryHSModel, BroadPeakModel,
-CSParallelepipedModel, CappedCylinderModel, CoreShellCylinderModel,
-CoreShellEllipsoidModel, CoreShellModel, CorrLengthModel, CylinderModel, 
-DABModel, DebyeModel, EllipsoidModel, EllipticalCylinderModel, FCCrystalModel,
-FlexCylEllipXModel, FlexibleCylinderModel, FractalCoreShellModel, FractalModel,
-FuzzySphereModel, GaussLorentzGelModel, GuinierModel, GuinierPorodModel,
-HardsphereStructure, HayterMSAStructure, HollowCylinderModel, LamellarFFHGModel,
-LamellarModel, LamellarPCrystalModel, LamellarPSHGModel, LamellarPSModel,
-LineModel, LorentzModel, MultiShellModel, ParallelepipedModel, PeakGaussModel,
-PeakLorentzModel, PearlNecklaceModel, Poly_GaussCoil, PolymerExclVolume,
-PorodModel, PowerLawAbsModel, SCCrystalModel, SphereModel, SquareWellStructure,
-StackedDisksModel, StickyHSStructure, TeubnerStreyModel, TriaxialEllipsoidModel,
-TwoLorentzianModel, TwoPowerLawModel, VesicleModel
-"""
-## This is same as the Easy Custom Sum(p1 + p2) 
-#
-#     Custom model = scale_factor * (P1 + P2)
-#
-## User can REPLACE model names below two arrowed lines (two names per line)
-from sans.models.CylinderModel import CylinderModel as P1          #<========
-from sans.models.PolymerExclVolume import PolymerExclVolume as P2  #<========
-
-#####DO NOT CHANGE ANYTHING BELOW THIS LINE 
-#####---------------------------------------------------------------------------
-class Model(Model1DPlugin):
-    """
-    Use for p1(Q)+p2(Q); 
-    Note: P(Q) refers to 'form factor' model.
-    """
-    name = ""
-    def __init__(self):
-        Model1DPlugin.__init__(self, name='')
-        """
-        :param p_model1: a form factor, P(Q)
-        :param p_model2: another form factor, P(Q)
-        """
-        p_model1 = P1()
-        p_model2 = P2()
-        ## Setting  model name model description
-        self.description=""
-        self.name = self._get_name(p_model1.name, p_model2.name)
-        self.description = p_model1.name+"\n"
-        self.description += p_model2.name+"\n"
-        self.fill_description(p_model1, p_model2)
-
-        ## Define parameters
-        self.params = {}
-
-        ## Parameter details [units, min, max]
-        self.details = {}
-        
-        # non-fittable parameters
-        self.non_fittable = p_model1.non_fittable  
-        self.non_fittable += p_model2.non_fittable  
-            
-        ##models 
-        self.p_model1= p_model1
-        self.p_model2= p_model2
-        
-       
-        ## dispersion
-        self._set_dispersion()
-        ## Define parameters
-        self._set_params()
-        ## New parameter:Scaling factor
-        self.params['scale_factor'] = 1
-        
-        ## Parameter details [units, min, max]
-        self._set_details()
-        self.details['scale_factor'] = ['',  None, None]
-
-        
-        #list of parameter that can be fitted
-        self._set_fixed_params()  
-        ## parameters with orientation
-        for item in self.p_model1.orientation_params:
-            new_item = "p1_" + item
-            if not new_item in self.orientation_params:
-                self.orientation_params.append(new_item)
-            
-        for item in self.p_model2.orientation_params:
-            new_item = "p2_" + item
-            if not new_item in self.orientation_params:
-                self.orientation_params.append(new_item)
-        # get multiplicity if model provide it, else 1.
-        try:
-            multiplicity1 = p_model1.multiplicity
-            try:
-                multiplicity2 = p_model2.multiplicity
-            except:
-                multiplicity2 = 1
-        except:
-            multiplicity1 = 1
-            multiplicity2 = 1
-        ## functional multiplicity of the model
-        self.multiplicity1 = multiplicity1  
-        self.multiplicity2 = multiplicity2    
-        self.multiplicity_info = []   
-        
-    def _clone(self, obj):
-        """
-            Internal utility function to copy the internal
-            data members to a fresh copy.
-        """
-        obj.params     = copy.deepcopy(self.params)
-        obj.description     = copy.deepcopy(self.description)
-        obj.details    = copy.deepcopy(self.details)
-        obj.dispersion = copy.deepcopy(self.dispersion)
-        obj.p_model1  = self.p_model1.clone()
-        obj.p_model2  = self.p_model2.clone()
-        #obj = copy.deepcopy(self)
-        return obj
-    
-    def _get_name(self, name1, name2):
-        """
-        Get combined name from two model names
-        """
-        name = self._get_upper_name(name1)
-        name += "+"
-        name += self._get_upper_name(name2)
-        return name
-    
-    def _get_upper_name(self, name=None):
-        """
-        Get uppercase string from model name
-        """
-        if name == None:
-            return ""
-        upper_name = ""
-        str_name = str(name)
-        for index in range(len(str_name)):
-            if str_name[index].isupper():
-                upper_name += str_name[index]
-        return upper_name
-        
-    def _set_dispersion(self):
-        """
-           combined the two models dispersions
-           Polydispersion should not be applied to s_model
-        """
-        ##set dispersion only from p_model 
-        for name , value in self.p_model1.dispersion.iteritems():
-            #if name.lower() not in self.p_model1.orientation_params:
-            new_name = "p1_" + name
-            self.dispersion[new_name]= value 
-        for name , value in self.p_model2.dispersion.iteritems():
-            #if name.lower() not in self.p_model2.orientation_params:
-            new_name = "p2_" + name
-            self.dispersion[new_name]= value 
-            
-    def function(self, x=0.0): 
-        """
-        """
-        return 0
-                               
-    def getProfile(self):
-        """
-        Get SLD profile of p_model if exists
-        
-        : return: (r, beta) where r is a list of radius of the transition points
-                beta is a list of the corresponding SLD values 
-        : Note: This works only for func_shell# = 2 (exp function)
-                and is not supporting for p2
-        """
-        try:
-            x,y = self.p_model1.getProfile()
-        except:
-            x = None
-            y = None
-            
-        return x, y
-    
-    def _set_params(self):
-        """
-            Concatenate the parameters of the two models to create
-            this model parameters 
-        """
-
-        for name , value in self.p_model1.params.iteritems():
-            # No 2D-supported
-            #if name not in self.p_model1.orientation_params:
-            new_name = "p1_" + name
-            self.params[new_name]= value
-            
-        for name , value in self.p_model2.params.iteritems():
-            # No 2D-supported
-            #if name not in self.p_model2.orientation_params:
-            new_name = "p2_" + name
-            self.params[new_name]= value
-                
-        # Set "scale" as initializing
-        self._set_scale_factor()
-      
-            
-    def _set_details(self):
-        """
-            Concatenate details of the two models to create
-            this model details 
-        """
-        for name ,detail in self.p_model1.details.iteritems():
-            new_name = "p1_" + name
-            #if new_name not in self.orientation_params:
-            self.details[new_name]= detail
-            
-        for name ,detail in self.p_model2.details.iteritems():
-            new_name = "p2_" + name
-            #if new_name not in self.orientation_params:
-            self.details[new_name]= detail
-    
-    def _set_scale_factor(self):
-        """
-        Not implemented
-        """
-        pass
-        
-                
-    def setParam(self, name, value):
-        """ 
-        Set the value of a model parameter
-    
-        :param name: name of the parameter
-        :param value: value of the parameter
-        """
-        # set param to p1+p2 model
-        self._setParamHelper(name, value)
-        
-        ## setParam to p model 
-        model_pre = name.split('_', 1)[0]
-        new_name = name.split('_', 1)[1]
-        if model_pre == "p1":
-            if new_name in self.p_model1.getParamList():
-                self.p_model1.setParam(new_name, value)
-        elif model_pre == "p2":
-             if new_name in self.p_model2.getParamList():
-                self.p_model2.setParam(new_name, value)
-        elif name.lower() == 'scale_factor':
-            self.params['scale_factor'] = value
-        else:
-            raise ValueError, "Model does not contain parameter %s" % name
-            
-    def getParam(self, name):
-        """ 
-        Set the value of a model parameter
-
-        :param name: name of the parameter
-        
-        """
-        # Look for dispersion parameters
-        toks = name.split('.')
-        if len(toks)==2:
-            for item in self.dispersion.keys():
-                # 2D not supported
-                if item.lower()==toks[0].lower():# and \
-                            #item.lower() not in self.orientation_params \
-                            #and toks[0].lower() not in self.orientation_params:
-                    for par in self.dispersion[item]:
-                        if par.lower() == toks[1].lower():
-                            return self.dispersion[item][par]
-        else:
-            # Look for standard parameter
-            for item in self.params.keys():
-                if item.lower()==name.lower():#and \
-                            #item.lower() not in self.orientation_params \
-                            #and toks[0].lower() not in self.orientation_params:
-                    return self.params[item]
-        return  
-        #raise ValueError, "Model does not contain parameter %s" % name
-       
-    def _setParamHelper(self, name, value):
-        """
-        Helper function to setparam
-        """
-        # Look for dispersion parameters
-        toks = name.split('.')
-        if len(toks)== 2:
-            for item in self.dispersion.keys():
-                if item.lower()== toks[0].lower():# and \
-                            #item.lower() not in self.orientation_params:
-                    for par in self.dispersion[item]:
-                        if par.lower() == toks[1].lower():#and \
-                                #item.lower() not in self.orientation_params:
-                            self.dispersion[item][par] = value
-                            return
-        else:
-            # Look for standard parameter
-            for item in self.params.keys():
-                if item.lower()== name.lower():#and \
-                            #item.lower() not in self.orientation_params:
-                    self.params[item] = value
-                    return
-            
-        raise ValueError, "Model does not contain parameter %s" % name
-             
-   
-    def _set_fixed_params(self):
-        """
-             fill the self.fixed list with the p_model fixed list
-        """
-        for item in self.p_model1.fixed:
-            new_item = "p1" + item
-            self.fixed.append(new_item)
-        for item in self.p_model2.fixed:
-            new_item = "p2" + item
-            self.fixed.append(new_item)
-
-        self.fixed.sort()
-                
-                    
-    def run(self, x = 0.0):
-        """ 
-        Evaluate the model
-        
-        :param x: input q-value (float or [float, float] as [r, theta])
-        :return: (scattering function value)
-        """
-        self._set_scale_factor()
-        return self.params['scale_factor'] * \
-                (self.p_model1.run(x) + self.p_model2.run(x))
-    
-    def runXY(self, x = 0.0):
-        """ 
-        Evaluate the model
-        
-        :param x: input q-value (float or [float, float] as [qx, qy])
-        :return: scattering function value
-        """  
-        self._set_scale_factor()
-        return self.params['scale_factor'] * \
-                (self.p_model1.runXY(x) + self.p_model2.runXY(x))
-    
-    ## Now (May27,10) directly uses the model eval function 
-    ## instead of the for-loop in Base Component.
-    def evalDistribution(self, x = []):
-        """ 
-        Evaluate the model in cartesian coordinates
-        
-        :param x: input q[], or [qx[], qy[]]
-        :return: scattering function P(q[])
-        """
-        self._set_scale_factor()
-        return self.params['scale_factor'] * \
-                    (self.p_model1.evalDistribution(x) + \
-                                 self.p_model2.evalDistribution(x))
-
-    def set_dispersion(self, parameter, dispersion):
-        """
-        Set the dispersion object for a model parameter
-        
-        :param parameter: name of the parameter [string]
-        :dispersion: dispersion object of type DispersionModel
-        """
-        value= None
-        new_pre = parameter.split("_", 1)[0]
-        new_parameter = parameter.split("_", 1)[1]
-        try:
-            if new_pre == 'p1' and \
-                            new_parameter in self.p_model1.dispersion.keys():
-                value= self.p_model1.set_dispersion(new_parameter, dispersion)
-            if new_pre == 'p2' and \
-                             new_parameter in self.p_model2.dispersion.keys():
-                value= self.p_model2.set_dispersion(new_parameter, dispersion)
-            self._set_dispersion()
-            return value
-        except:
-            raise 
-
-    def fill_description(self, p_model1, p_model2):
-        """
-        Fill the description for P(Q)+P(Q)
-        """
-        description = ""
-        description +="This model gives the summation of  %s and %s.\n"% \
-                                        ( p_model1.name, p_model2.name )
-        self.description += description
-        
-if __name__ == "__main__": 
-    m1= Model() 
-    #m1.setParam("p1_scale", 25)  
-    #m1.setParam("p1_length", 1000)
-    #m1.setParam("p2_scale", 100) 
-    #m1.setParam("p2_rg", 100) 
-    out1 = m1.runXY(0.01)
-
-    m2= Model()
-    #m2.p_model1.setParam("scale", 25) 
-    #m2.p_model1.setParam("length", 1000) 
-    #m2.p_model2.setParam("scale", 100)
-    #m2.p_model2.setParam("rg", 100)
-    out2 = m2.p_model1.runXY(0.01) + m2.p_model2.runXY(0.01)
-    print "Testing at Q = 0.01:"
-    print out1, " = ", out2
-    if out1 == out2:
-        print "===> Simple Test: Passed!"
-    else:
-        print "===> Simple Test: Failed!"
