Changeset 7d0c1a8 in sasview

Timestamp:

Oct 9, 2008 2:33:14 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:

385d464

Parents:

fb8d4050

Message:

introduced fitdata1D and fitdata2D class instead of Data class.

Location:

park_integration

Files:

• AbstractFitEngine.py (modified) (3 diffs)
• ParkFitting.py (modified) (3 diffs)
• ScipyFitting.py (modified) (1 diff)
• test/test_fit_line.py (modified) (5 diffs)

park_integration/AbstractFitEngine.py

@@ -167 +167 @@
         """
         return []
+class FitData1D(object):
+    """ Wrapper class  for SANS data """
+    def __init__(self,sans_data1d):
+        """
+            Data can be initital with a data (sans plottable)
+            or with vectors.
+        """
+        self.data=sans_data1d
+        self.x= sans_data1d.x
+        self.y= sans_data1d.y
+        self.dx= sans_data1d.dx
+        self.dy= sans_data1d.dy
+        self.qmin=None
+        self.qmax=None
+       
+       
+    def setFitRange(self,mini=None,maxi=None):
+        """ to set the fit range"""
+        self.qmin=mini
+        self.qmax=maxi
+        
+        
+    def getFitRange(self):
+        """
+            @return the range of data.x to fit
+        """
+        return self.qmin, self.qmax
+     
+     
+    def residuals(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=[]):
+        """ 
+            @return residuals derivatives .
+            @note: in this case just return empty array
+        """
+        return []
+    
+    
+class FitData2D(object):
+    """ Wrapper class  for SANS data """
+    def __init__(self,sans_data2d):
+        """
+            Data can be initital with a data (sans plottable)
+            or with vectors.
+        """
+        self.data=sans_data2d
+        self.image = sans_data2d.image
+        self.err_image = sans_data2d.err_image
+        self.x_bins= sans_data2d.x_bins
+        self.y_bins= sans_data2d.y_bins
+       
+        self.qmin= None
+        self.qmax= None
+       
+       
+    def setFitRange(self,mini=None,maxi=None):
+        """ to set the fit range"""
+        self.qmin= mini
+        self.qmax= maxi
+        
+        
+    def getFitRange(self):
+        """
+            @return the range of data.x to fit
+        """
+        return self.qmin, self.qmax
+     
+     
+    def residuals(self, fn):
+        """ @param fn: function that return model value
+            @return residuals
+        """
+        res=[]
+        if self.qmin==None and self.qmax==None: 
+            for i in range(len(self.x_bins)):
+                res.append( (self.image[i][i]- fn([self.x_bins[i],self.y_bins[i]]))\
+                            /self.err_image[i][i] )
+            return numpy.array(res)
+        else:
+            #idx = (x>=self.qmin) & (x <= self.qmax)
+            #fx = numpy.asarray([fn(item)for item in x[idx ]])
+            #return (y[idx] - fx)/dy[idx]
+            for i in range(len(self.x_bins)):
+                res.append( (self.image[i][i]- fn([self.x_bins[i],self.y_bins[i]]))\
+                            /self.err_image[i][i] )
+            return numpy.array(res)
+    def residuals_deriv(self, model, pars=[]):
+        """ 
+            @return residuals derivatives .
+            @note: in this case just return empty array
+        """
+        return []
     
 class sansAssembly:
@@ -229 +333 @@
             self.maxi=None
                
-            for data in listdata:
+            for item in listdata:
+                data=item.data
                 mini,maxi=data.getFitRange()
                 if self.mini==None and self.maxi==None:
@@ -370 +475 @@
     def get_data(self):
         """ @return:  list of data dList"""
-        return self.dList 
+        #return self.dList 
+        return self.dList[0] 
       
     def remove_data(self,data):

park_integration/ParkFitting.py

@@ -10 +10 @@
 from park import assembly
 from park.fitmc import FitSimplex, FitMC
-from sans.guitools.plottables import Data1D
+
 from Loader import Load
-from AbstractFitEngine import FitEngine,FitArrange,Model
+from AbstractFitEngine import FitEngine
 
 
@@ -75 +75 @@
             i+=1
             Ldata=item.get_data()
-            parkdata=self._concatenateData(Ldata)
-            
+            #parkdata=self._concatenateData(Ldata)
+            parkdata=Ldata
             fitness=(parkmodel,parkdata)
             mylist.append(fitness)
@@ -120 +120 @@
                          fitter=fitter,
                          handler= fitresult.ConsoleUpdate(improvement_delta=0.1))
+        #handler = fitresult.ConsoleUpdate(improvement_delta=0.1)
+        #models=self.problem
+        #service=None
+        #if models is None: raise RuntimeError('fit expected a list of models')
+        #from park.fit import LocalQueue,FitJob
+        #if service is None: service = LocalQueue()
+        #if fitter is None: fitter = fitmc.FitMC()
+        #if handler is None: handler = fitresult.FitHandler()
+    
+        #objective = assembly.Assembly(models) if isinstance(models,list) else models
+        #job = FitJob(self.problem,fitter,handler)
+        #service.start(job)
+        #import wx
+        #while not self.job.handler.done:
+        #    time.sleep(interval)
+        #    wx.Yield()
+        #result=service.job.handler.result
+        
         if result !=None:
             return result

park_integration/ScipyFitting.py

@@ -81 +81 @@
         listdata = fitproblem[0].get_data()
         # Concatenate dList set (contains one or more data)before fitting
-        data=self._concatenateData( listdata)
+        #data=self._concatenateData( listdata)
+        data=listdata
         #Assign a fit range is not boundaries were given
-        if qmin==None:
-            qmin= min(data.x)
-        if qmax==None:
-            qmax= max(data.x) 
+        if data.__class__.__name__=='Data1D':
+            if qmin==None:
+                qmin= min(data.x)
+            if qmax==None:
+                qmax= max(data.x) 
+        else:
+            if qmin==None:
+                qmin= numpy.min(data.image)
+            if qmax==None:
+                qmax= numpy.max(data.image) 
         functor= sansAssembly(self.paramList,model,data)
         out, cov_x, info, mesg, success = optimize.leastsq(functor,model.getParams(self.paramList), full_output=1, warning=True)

park_integration/test/test_fit_line.py

@@ -5 +5 @@
 from sans.guitools.plottables import Theory1D
 from sans.guitools.plottables import Data1D
-from sans.fit.AbstractFitEngine import Data, Model
+from sans.fit.AbstractFitEngine import Data, Model,FitData1D
 import math
 class testFitModule(unittest.TestCase):
@@ -21 +21 @@
         model1  = LineModel()
         model1.name = "M1"
-        data = Data(sans_data=data1 )
+        #data = Data(sans_data=data1 )
+        data = FitData1D(data1 )
         model = Model(model1)
         #fit with scipy test
@@ -85 +86 @@
         model22  = LineModel()
         model11.name= "M2"
-        data1 = Data(sans_data=data11 )
-        data2 = Data(sans_data=data22 )
+        #data1 = Data(sans_data=data11 )
+        #data2 = Data(sans_data=data22 )
+        data1 = FitData1D(data11 )
+        data2 = FitData1D(data22 )
+        
         model1 = Model(model11)
         model2 = Model(model22)
@@ -150 +154 @@
         # Constrain the constant value to be equal to parameter B (the real value is 2.5)
         
-        
-        data1 = Data(sans_data=data11 )
-        data2 = Data(sans_data=data22 )
+        #data1 = Data(sans_data=data11 )
+        #data2 = Data(sans_data=data22 )
+        
+        data1 = FitData1D(data11 )
+        data2 = FitData1D(data22 )
         model1 = Model(model11)
         model2 = Model(model22)
@@ -194 +200 @@
         model1.name= "M1"
       
-        data1 = Data(sans_data=data11 )
-        data2 = Data(sans_data=data22 )
+        #data1 = Data(sans_data=data11 )
+        #data2 = Data(sans_data=data22 )
+        data1 = FitData1D(data11 )
+        data2 = FitData1D(data22 )
         model = Model(model1)