Changeset 7e7e806 in sasview
- Timestamp:
- Aug 26, 2011 10:22:08 AM (13 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:
- c647377
- Parents:
- 2dbffcc
- File:
-
- 1 edited
Legend:
- Unmodified
- Added
- Removed
-
fittingview/src/sans/perspectives/fitting/model_thread.py
r49c69de r7e7e806 2 2 3 3 import time 4 import sys 5 import numpy 6 import math 7 from sans.models.smearing_2d import Smearer2D 4 8 from data_util.calcthread import CalcThread 5 import sys6 import numpy,math7 from sans.models.smearing_2d import Smearer2D8 9 9 10 class Calc2D(CalcThread): … … 14 15 and I(qx, qy) = I(-qx, -qy) is assumed. 15 16 """ 16 def __init__(self, x, y, data,model,smearer,qmin, qmax,qstep, 17 page_id , 17 def __init__(self, data, model, smearer, qmin, qmax, page_id, 18 18 state=None, 19 19 toggle_mode_on=False, 20 completefn =None,21 updatefn =None,20 completefn=None, 21 updatefn=None, 22 22 update_chisqr=True, 23 yieldtime =0.04,24 worktime =0.0423 yieldtime=0.04, 24 worktime=0.04 25 25 ): 26 26 CalcThread.__init__(self,completefn, … … 28 28 yieldtime, 29 29 worktime) 30 self.qmin = qmin31 self.qmax = qmax32 self.qstep= qstep30 self.qmin = qmin 31 self.qmax = qmax 32 #self.qstep = qstep 33 33 self.toggle_mode_on = toggle_mode_on 34 self.x = x 35 self.y = y 36 self.data= data 34 self.data = data 37 35 self.page_id = page_id 38 36 self.state = None 39 37 # the model on to calculate 40 38 self.model = model 41 self.smearer = smearer #(data=self.data,model=self.model)39 self.smearer = smearer 42 40 self.starttime = 0 43 41 self.update_chisqr = update_chisqr … … 49 47 self.starttime = time.time() 50 48 # Determine appropriate q range 51 if self.qmin ==None:49 if self.qmin == None: 52 50 self.qmin = 0 53 if self.qmax== None: 54 if self.data !=None: 55 newx= math.pow(max(math.fabs(self.data.xmax),math.fabs(self.data.xmin)),2) 56 newy= math.pow(max(math.fabs(self.data.ymax),math.fabs(self.data.ymin)),2) 57 self.qmax=math.sqrt( newx + newy ) 58 59 if self.data != None: 60 self.I_data = self.data.data 61 self.qx_data = self.data.qx_data 62 self.qy_data = self.data.qy_data 63 self.dqx_data = self.data.dqx_data 64 self.dqy_data = self.data.dqy_data 65 self.mask = self.data.mask 66 else: 67 xbin = numpy.linspace(start= -1*self.qmax, 68 stop= self.qmax, 69 num= self.qstep, 70 endpoint=True ) 71 ybin = numpy.linspace(start= -1*self.qmax, 72 stop= self.qmax, 73 num= self.qstep, 74 endpoint=True ) 75 76 new_xbin = numpy.tile(xbin, (len(ybin),1)) 77 new_ybin = numpy.tile(ybin, (len(xbin),1)) 78 new_ybin = new_ybin.swapaxes(0,1) 79 new_xbin = new_xbin.flatten() 80 new_ybin = new_ybin.flatten() 81 self.qy_data = new_ybin 82 self.qx_data = new_xbin 83 # fake data 84 self.I_data = numpy.ones(len(self.qx_data)) 85 86 self.mask = numpy.ones(len(self.qx_data),dtype=bool) 87 88 # Define matrix where data will be plotted 89 radius= numpy.sqrt( self.qx_data*self.qx_data + self.qy_data*self.qy_data ) 90 index_data= (self.qmin<= radius)&(self.mask) 51 if self.qmax == None: 52 if self.data != None: 53 newx = math.pow(max(math.fabs(self.data.xmax), 54 math.fabs(self.data.xmin)), 2) 55 newy = math.pow(max(math.fabs(self.data.ymax), 56 math.fabs(self.data.ymin)), 2) 57 self.qmax = math.sqrt(newx + newy) 58 59 if self.data is None: 60 msg = "Compute Calc2D receive data = %s.\n" % str(self.data) 61 raise ValueError, msg 62 63 # Define matrix where data will be plotted 64 radius= numpy.sqrt((self.data.qx_data * self.data.qx_data) + \ 65 (self.data.qy_data * self.data.qy_data)) 66 index_data = (self.qmin <= radius) & self.data.mask 91 67 92 68 # For theory, qmax is based on 1d qmax 93 69 # so that must be mulitified by sqrt(2) to get actual max for 2d 94 index_model = ((self.qmin <= radius)&(radius<= self.qmax)) 95 index_model = (index_model)&(self.mask) 96 index_model = (index_model)&(numpy.isfinite(self.I_data)) 97 if self.data ==None: 98 # Only qmin value will be consider for the detector 99 index_model = index_data 100 101 if self.smearer != None: 70 index_model = (self.qmin <= radius) & (radius <= self.qmax) 71 index_model = index_model & self.data.mask 72 index_model = index_model & numpy.isfinite(self.data.data) 73 74 if self.smearer is not None: 102 75 # Set smearer w/ data, model and index. 103 76 fn = self.smearer … … 106 79 # Get necessary data from self.data and set the data for smearing 107 80 fn.get_data() 108 # Calculate smeared Intensity (by Gaussian averaging): DataLoader/smearing2d/Smearer2D() 81 # Calculate smeared Intensity 82 #(by Gaussian averaging): DataLoader/smearing2d/Smearer2D() 109 83 value = fn.get_value() 110 111 84 else: 112 85 # calculation w/o smearing 113 value = self.model.evalDistribution([self.qx_data[index_model],self.qy_data[index_model]]) 114 115 output = numpy.zeros(len(self.qx_data)) 116 86 value = self.model.evalDistribution([self.data.qx_data[index_model], 87 self.data.qy_data[index_model]]) 88 output = numpy.zeros(len(self.data.qx_data)) 117 89 # output default is None 118 # This method is to distinguish between masked point(nan) and data point = 0. 90 # This method is to distinguish between masked 91 #point(nan) and data point = 0. 119 92 output = output/output 120 93 # set value for self.mask==True, else still None to Plottools 121 94 output[index_model] = value 122 123 95 elapsed = time.time()-self.starttime 124 96 self.complete(image=output, … … 132 104 qmin=self.qmin, 133 105 qmax=self.qmax, 134 qstep=self.qstep,135 update_chisqr = self.update_chisqr 106 #qstep=self.qstep, 107 update_chisqr = self.update_chisqr) 136 108 137 109 … … 140 112 Compute 1D data 141 113 """ 142 def __init__(self, x,model,114 def __init__(self, model, 143 115 page_id, 144 data =None,116 data, 145 117 qmin=None, 146 118 qmax=None, … … 150 122 completefn = None, 151 123 update_chisqr=True, 152 updatefn =None,153 yieldtime =0.01,154 worktime =0.01124 updatefn=None, 125 yieldtime=0.01, 126 worktime=0.01 155 127 ): 156 128 """ … … 160 132 yieldtime, 161 133 worktime) 162 self.x = numpy.array(x)163 134 self.data = data 164 135 self.qmin = qmin … … 177 148 """ 178 149 self.starttime = time.time() 179 output = numpy.zeros((len(self. x)))180 index= (self.qmin <= self. x)& (self.x <= self.qmax)150 output = numpy.zeros((len(self.data.x))) 151 index= (self.qmin <= self.data.x)& (self.data.x <= self.qmax) 181 152 182 153 ##smearer the ouput of the plot 183 if self.smearer!=None: 184 first_bin, last_bin = self.smearer.get_bin_range(self.qmin, self.qmax) 185 output[first_bin:last_bin] = self.model.evalDistribution(self.x[first_bin:last_bin]) 154 if self.smearer is not None: 155 first_bin, last_bin = self.smearer.get_bin_range(self.qmin, 156 self.qmax) 157 mask = self.data.x[first_bin:last_bin] 158 output[first_bin:last_bin] = self.model.evalDistribution(mask) 186 159 output = self.smearer(output, first_bin, last_bin) 187 160 else: 188 output[index] = self.model.evalDistribution(self. x[index])161 output[index] = self.model.evalDistribution(self.data.x[index]) 189 162 190 163 elapsed = time.time() - self.starttime 191 164 192 self.complete(x=self. x[index], y=output[index],165 self.complete(x=self.data.x[index], y=output[index], 193 166 page_id=self.page_id, 194 167 state=self.state, … … 196 169 elapsed=elapsed,index=index, model=self.model, 197 170 data=self.data, 198 update_chisqr = self.update_chisqr 171 update_chisqr = self.update_chisqr) 199 172 200 173 def results(self):
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