Changeset d2caa18 in sasview for sansview/perspectives
- Timestamp:
- Sep 9, 2009 6:56:54 PM (15 years ago)
- 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:
- 9ce41c6
- Parents:
- f1c79d2
- File:
-
- 1 edited
Legend:
- Unmodified
- Added
- Removed
-
sansview/perspectives/fitting/model_thread.py
rc8727c5 rd2caa18 26 26 self.qstep= qstep 27 27 # Reshape dimensions of x and y to call evalDistribution 28 self.x_array = numpy.reshape(x,[len(x),1]) 29 self.y_array = numpy.reshape(y,[1,len(y)]) 28 #self.x_array = numpy.reshape(x,[len(x),1]) 29 #self.y_array = numpy.reshape(y,[1,len(y)]) 30 self.x_array = numpy.reshape(x,[1,len(x)]) 31 self.y_array = numpy.reshape(y,[len(y),1]) 30 32 # Numpy array of dimensions 1 used for model.run method 31 33 self.x= numpy.array(x) … … 50 52 self.qmax=math.sqrt( newx + newy ) 51 53 # Define matrix where data will be plotted 52 radius= numpy.sqrt( self.x_array**2 + self.y_array**2)54 radius= numpy.sqrt( self.x_array**2 + self.y_array**2 ) 53 55 index_data= (self.qmin<= radius) 54 56 index_model = (self.qmin <= radius)&(radius<= self.qmax) 55 57 56 58 output = numpy.zeros((len(self.x),len(self.y))) 57 try: 58 ## receive only list of 2 numpy array 59 ## One must reshape to vertical and the other to horizontal 60 value = self.model.evalDistribution([self.x_array,self.y_array] ) 61 ## for data ignore the qmax 62 if self.data == None: 63 # Only qmin value will be consider for the detector 64 output = value *index_data 65 else: 66 # The user can define qmin and qmax for the detector 67 output = value*index_model 68 except: 69 raise 70 71 59 60 ## receive only list of 2 numpy array 61 ## One must reshape to vertical and the other to horizontal 62 value = self.model.evalDistribution([self.x_array,self.y_array] ) 63 ## for data ignore the qmax 64 if self.data == None: 65 # Only qmin value will be consider for the detector 66 output = value *index_data 67 else: 68 # The user can define qmin and qmax for the detector 69 output = index_model*value 70 72 71 elapsed = time.time()-self.starttime 73 72 self.complete( image = output,
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