Changeset 24b3821 in sasview for src/sas/sasgui/perspectives/fitting/model_thread.py
- Timestamp:
- Apr 11, 2017 7:02:04 AM (7 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-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload
- Children:
- 426df2e
- Parents:
- d26f025
- File:
-
- 1 edited
Legend:
- Unmodified
- Added
- Removed
-
src/sas/sasgui/perspectives/fitting/model_thread.py
r7432acb r24b3821 71 71 (self.data.qy_data * self.data.qy_data)) 72 72 73 # For theory, qmax is based on 1d qmax 73 # For theory, qmax is based on 1d qmax 74 74 # so that must be mulitified by sqrt(2) to get actual max for 2d 75 75 index_model = (self.qmin <= radius) & (radius <= self.qmax) … … 91 91 self.data.qy_data[index_model] 92 92 ]) 93 output = np.zeros(len(self.data.qx_data)) 93 # Initialize output to NaN so masked elements do not get plotted. 94 output = np.empty_like(self.data.qx_data) 94 95 # output default is None 95 96 # This method is to distinguish between masked 96 97 #point(nan) and data point = 0. 97 output = output / output98 output[:] = np.NaN 98 99 # set value for self.mask==True, else still None to Plottools 99 100 output[index_model] = value … … 198 199 output[index] = self.model.evalDistribution(self.data.x[index]) 199 200 201 x=self.data.x[index] 202 y=output[index] 200 203 sq_values = None 201 204 pq_values = None 202 s_model = None203 p_model = None204 205 if isinstance(self.model, MultiplicationModel): 205 206 s_model = self.model.s_model 206 207 p_model = self.model.p_model 207 elif hasattr(self.model, "get_composition_models"): 208 p_model, s_model = self.model.get_composition_models() 209 210 if p_model is not None and s_model is not None: 211 sq_values = np.zeros((len(self.data.x))) 212 pq_values = np.zeros((len(self.data.x))) 213 sq_values[index] = s_model.evalDistribution(self.data.x[index]) 214 pq_values[index] = p_model.evalDistribution(self.data.x[index]) 208 #sq_values = np.zeros((len(self.data.x))) 209 #pq_values = np.zeros((len(self.data.x))) 210 #sq_values[index] = s_model.evalDistribution(self.data.x[index]) 211 #pq_values[index] = p_model.evalDistribution(self.data.x[index]) 212 sq_values = s_model.evalDistribution(x) 213 pq_values = p_model.evalDistribution(x) 214 elif hasattr(self.model, "calc_composition_models"): 215 results = self.model.calc_composition_models(x) 216 if results is not None: 217 sq_values = results[0] 218 pq_values = results[1] 219 215 220 216 221 elapsed = time.time() - self.starttime 217 222 218 self.complete(x= self.data.x[index], y=output[index],223 self.complete(x=x, y=y, 219 224 page_id=self.page_id, 220 225 state=self.state,
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