Changeset 20d30e9 in sasview

Timestamp:

Mar 20, 2009 8:29:58 PM (16 years ago)

Author:

Gervaise Alina <gervyh@…>

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, release_4.0.1, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

858fabed

Parents:

c77d859

Message:

fit with qmin qmax value only

Location:

park_integration

Files:

• AbstractFitEngine.py (modified) (16 diffs)
• Fitting.py (modified) (5 diffs)
• test/test_park_scipy.py (added)

park_integration/AbstractFitEngine.py

@@ -46 +46 @@
             hi= numpy.inf
         return lo,hi
-        
     
     def _setrange(self,r):
@@ -157 +156 @@
             @return residuals
         """
-        
         x,y,dy = [numpy.asarray(v) for v in (self.x,self.y,self.dy)]
         if self.qmin==None and self.qmax==None: 
@@ -207 +205 @@
         
         ## Min Q-value
-        self.qmin=None
+        self.qmin= min (self.data.x)
         ## Max Q-value
-        self.qmax=None
-       
-       
-    def setFitRange(self,qmin=None,qmax=None,ymin=None,ymax=None,):
+        self.qmax= max (self.data.x)
+       
+       
+    def setFitRange(self,qmin=None,qmax=None):
         """ to set the fit range"""
-        self.qmin=qmin
-        self.qmax=qmax
+        self.qmin = qmin
+        self.qmax = qmax
         
         
@@ -238 +236 @@
            
         # Find entries to consider
-        if self.qmin==None and self.qmax==None:
-            idx = Ellipsis
-        else:
-            idx = (x>=self.qmin) & (x <= self.qmax)
-                        
+        if self.qmin==None:
+            self.qmin= min(self.data.x)
+        if  self.qmax==None:
+            self.qmin= max(self.data.x)
+        
+        idx = (x>=self.qmin) & (x <= self.qmax)
+  
         # Compute theory data f(x)
         fx = numpy.zeros(len(x))
@@ -250 +250 @@
         if self.smearer is not None:
             fx = self.smearer(fx)
+       
         # Sanity check
         if numpy.size(dy) < numpy.size(x):
@@ -256 +257 @@
         return (y[idx] - fx[idx])/dy[idx]
      
-    def residuals_old(self, fn):
-        """ @param fn: function that return model value
-            @return residuals
-        """
-        x,y,dy = [numpy.asarray(v) for v in (self.x,self.y,self.dy)]
-        if self.qmin==None and self.qmax==None: 
-            fx =numpy.asarray([fn(v) for v in x])
-            return (y - fx)/dy
-        else:
-            idx = (x>=self.qmin) & (x <= self.qmax)
-            fx = numpy.asarray([fn(item)for item in x[idx ]])
-            return (y[idx] - fx)/dy[idx]
+  
         
     def residuals_deriv(self, model, pars=[]):
@@ -290 +280 @@
         self.y_bins= sans_data2d.y_bins
        
-        self.xmin= self.data.xmin
-        self.xmax= self.data.xmax
-        self.ymin= self.data.ymin
-        self.ymax= self.data.ymax
-       
-       
-    def setFitRange(self,qmin=None,qmax=None,ymin=None,ymax=None):
+        x = max(self.data.xmin, self.data.xmax)
+        y = max(self.data.ymin, self.data.ymax)
+        
+        ## fitting range
+        self.qmin = 0
+        self.qmax = math.sqrt(x*x +y*y)
+       
+       
+       
+    def setFitRange(self,qmin=None,qmax=None):
         """ to set the fit range"""
-        self.xmin= qmin
-        self.xmax= qmax
-        self.ymin= ymin
-        self.ymax= ymax
+        self.qmin= qmin
+        self.qmax= qmax
+      
         
     def getFitRange(self):
@@ -307 +299 @@
             @return the range of data.x to fit
         """
-        return self.xmin, self.xmax,self.ymin, self.ymax
+        return self.qmin, self.qmax
      
      
@@ -315 +307 @@
         """
         res=[]
-        if self.xmin==None:        #Here we define that xmin = qmin >=0 and xmax=qmax>=qmain
-            self.xmin= 0 #self.data.xmin
-        if self.xmax==None:
-            self.xmax= self.data.xmax
-        if self.ymin==None:
-            self.ymin= self.data.ymin
-        if self.ymax==None:
-            self.ymax= self.data.ymax
+        #Here we define that  qmin >=0 and qmax>=qmain
+        x = max(self.data.xmin, self.data.xmax)
+        y = max(self.data.ymin, self.data.ymax)
+        
+        ## fitting range
+        if self.qmin == None:
+            self.qmin = 0
+        if self.qmax == None:
+            self.qmax = math.sqrt(x*x +y*y)
+        
+        
         for i in range(len(self.y_bins)):
-            #if self.y_bins[i]>= self.ymin and self.y_bins[i]<= self.ymax:
             for j in range(len(self.x_bins)):
-                 if math.pow(self.data.x_bins[i],2)+math.pow(self.data.y_bins[j],2)>=math.pow(self.xmin,2):
-                     if math.pow(self.data.x_bins[i],2)+math.pow(self.data.y_bins[j],2)<=math.pow(self.xmax,2):
-                         #if self.x_bins[j]>= self.xmin and self.x_bins[j]<= self.xmax:                
-                        res.append( (self.image[i][j]- fn([self.x_bins[i],self.y_bins[j]]))\
-                            /self.err_image[i][j] )
+                radius = math.pow(self.data.x_bins[i],2)+math.pow(self.data.y_bins[j],2)
+                if self.qmin <= radius and radius <= self.qmax:
+                    res.append( (self.image[j][i]- fn([self.x_bins[i],self.y_bins[j]]))\
+                            /self.err_image[j][i] )
         
         return numpy.array(res)
@@ -346 +339 @@
          Sans Assembly class a class wrapper to be call in optimizer.leastsq method
     """
-    
     def __init__(self,paramlist,Model=None , Data=None):
         """
@@ -365 +357 @@
         for item in self.res:
             sum += item*item
-        #print "length of data =",len(self.res)
+       
         return sum/ len(self.res)
+    
     def __call__(self,params):
         """
@@ -413 +406 @@
             ytemp=[]
             dytemp=[]
-            dxtemp=[]
             self.mini=None
             self.maxi=None
@@ -437 +429 @@
                     else:
                         raise RuntimeError, "Fit._concatenateData: y-errors missing"
-                    if data.dx is not None and len(data.dx)==len(data.x):   
-                        dxtemp.append(data.dx[i])
-                    else:
-                        raise RuntimeError, "Fit._concatenateData: dQ-errors missing"
-            data= Data(x=xtemp,y=ytemp,dy=dytemp, dx=dxtemp)
+            data= Data(x=xtemp,y=ytemp,dy=dytemp)
             data.setFitRange(self.mini, self.maxi)
             return data
@@ -476 +464 @@
             raise ValueError, "park_integration:missing parameters"
     
-    def set_data(self,data,Uid,smearer=None,qmin=None,qmax=None,ymin=None,ymax=None):
+    def set_data(self,data,Uid,smearer=None,qmin=None,qmax=None):
         """ Receives plottable, creates a list of data to fit,set data
             in a FitArrange object and adds that object in a dictionary 
@@ -487 +475 @@
         else:
             fitdata=FitData1D(data, smearer)
-        fitdata.setFitRange(qmin=qmin,qmax=qmax, ymin=ymin,ymax=ymax)
+       
+        fitdata.setFitRange(qmin=qmin,qmax=qmax)
         #A fitArrange is already created but contains model only at Uid
         if self.fitArrangeDict.has_key(Uid):
@@ -496 +485 @@
             fitproblem.add_data(fitdata)
             self.fitArrangeDict[Uid]=fitproblem    
-
+   
     def get_model(self,Uid):
         """ 

park_integration/Fitting.py

@@ -31 +31 @@
             self._engine will contain an instance of ScipyFit or ParkFit
         """
-        self._engine=None
+        self._engine = None
         self.set_engine(engine)
+          
           
     def set_engine(self,word):
@@ -48 +49 @@
             raise ValueError, "enter the keyword scipy or park"
         
-    def returnEngine(self):
-        """ @return self._engine""" 
-        return self._engine
+   
     
     def fit(self,handler=None):
@@ -57 +56 @@
         return self._engine.fit(handler)
     
+    
     def set_model(self,model,Uid,pars=[]):
-         self._engine.set_model(model,Uid,pars)
+        """
+        store a model model to fit at the position Uid of the fit engine
+        """
+        self._engine.set_model(model,Uid,pars)
    
-    def set_data(self,data,Uid,smearer=None,qmin=None, qmax=None,ymin=None, ymax=None):
-        self._engine.set_data(data,Uid,smearer,qmin,qmax,ymin,ymax)
+   
+    def set_data(self,data,Uid,smearer=None,qmin=None, qmax=None):
+        """
+            Store data to fit at the psotion Uid of the fit engine
+            @param data: data to fit
+            @param smearer: smearerobject to smear data
+            @param qmin: the minimum q range to fit 
+            @param qmax: the minimum q range to fit
+        """
+        self._engine.set_data(data,Uid,smearer,qmin, qmax)
+        
         
     def get_model(self,Uid):
@@ -67 +79 @@
         self._engine.get_model(Uid)
 
+
     def remove_Fit_Problem(self,Uid):
         """remove   fitarrange in Uid"""
         self._engine.remove_Fit_Problem(Uid)
+        
         
     def select_problem_for_fit(self,Uid,value):
@@ -79 +93 @@
         self._engine.select_problem_for_fit(Uid,value)
         
+        
     def get_problem_to_fit(self,Uid):
         """