Changes in sasmodels/kernel.py [b297ba9:a34b811] in sasmodels
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sasmodels/kernel.py
rb297ba9 ra34b811 78 78 """ 79 79 _, F2, _, shell_volume, _ = self.Fq(call_details, values, cutoff, 80 magnetic, effective_radius_type=0)80 magnetic, radius_effective_mode=0) 81 81 combined_scale = values[0]/shell_volume 82 82 background = values[1] … … 85 85 86 86 def Fq(self, call_details, values, cutoff, magnetic, 87 effective_radius_type=0):87 radius_effective_mode=0): 88 88 # type: (CallDetails, np.ndarray, np.ndarray, float, bool, int) -> np.ndarray 89 89 r""" … … 143 143 volume fraction of the particles. The model can have several 144 144 different ways to compute effective radius, with the 145 * effective_radius_type* parameter used to select amongst them. The145 *radius_effective_mode* parameter used to select amongst them. The 146 146 volume fraction of particles should be determined from the total 147 147 volume fraction of the form, not just the shell volume fraction. … … 153 153 """ 154 154 self._call_kernel(call_details, values, cutoff, magnetic, 155 effective_radius_type)155 radius_effective_mode) 156 156 #print("returned",self.q_input.q, self.result) 157 157 nout = 2 if self.info.have_Fq and self.dim == '1d' else 1 … … 165 165 form_volume = self.result[nout*self.q_input.nq + 1]/total_weight 166 166 shell_volume = self.result[nout*self.q_input.nq + 2]/total_weight 167 effective_radius= self.result[nout*self.q_input.nq + 3]/total_weight167 radius_effective = self.result[nout*self.q_input.nq + 3]/total_weight 168 168 if shell_volume == 0.: 169 169 shell_volume = 1. … … 171 171 if nout == 2 else None) 172 172 F2 = self.result[0:nout*self.q_input.nq:nout]/total_weight 173 return F1, F2, effective_radius, shell_volume, form_volume/shell_volume173 return F1, F2, radius_effective, shell_volume, form_volume/shell_volume 174 174 175 175 def release(self): … … 181 181 182 182 def _call_kernel(self, call_details, values, cutoff, magnetic, 183 effective_radius_type):183 radius_effective_mode): 184 184 # type: (CallDetails, np.ndarray, np.ndarray, float, bool, int) -> np.ndarray 185 185 """
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