Changeset 6e7ba14 in sasmodels for sasmodels/kernelcl.py

Timestamp:

Aug 20, 2018 8:52:21 AM (6 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

aa44a6a

Parents:

bad3093

Message:

allow for different forms of effective_radius

File:

• sasmodels/kernelcl.py (modified) (3 diffs)

sasmodels/kernelcl.py

@@ -540 +540 @@
         # leave room for f1/f2 results in case we need to compute beta for 1d models
         num_returns = 1 if self.dim == '2d' else 2  #
-        # plus 1 for the normalization value
-        self.result = np.empty((q_input.nq+1)*num_returns, dtype)
+        # plus 1 for the normalization value, plus another for R_eff
+        self.result = np.empty((q_input.nq+2)*num_returns, dtype)
 
         # Inputs and outputs for each kernel call
@@ -558 +558 @@
                      else np.float32)  # will never get here, so use np.float32
 
-    def Iq(self, call_details, values, cutoff, magnetic):
-        # type: (CallDetails, np.ndarray, np.ndarray, float, bool) -> np.ndarray
-        self._call_kernel(call_details, values, cutoff, magnetic)
-        #print("returned",self.q_input.q, self.result)
-        pd_norm = self.result[self.q_input.nq]
-        scale = values[0]/(pd_norm if pd_norm != 0.0 else 1.0)
-        background = values[1]
-        #print("scale",scale,background)
-        return scale*self.result[:self.q_input.nq] + background
-    __call__ = Iq
-
-    def beta(self, call_details, values, cutoff, magnetic):
-        # type: (CallDetails, np.ndarray, np.ndarray, float, bool) -> np.ndarray
-        if self.dim == '2d':
-            raise NotImplementedError("beta not yet supported for 2D")
-        self._call_kernel(call_details, values, cutoff, magnetic)
-        w_norm = self.result[2*self.q_input.nq + 1]
-        pd_norm = self.result[self.q_input.nq]
-        if w_norm == 0.:
-            w_norm = 1.
-        F2 = self.result[:self.q_input.nq]/w_norm
-        F1 = self.result[self.q_input.nq+1:2*self.q_input.nq+1]/w_norm
-        volume_avg = pd_norm/w_norm
-        return F1, F2, volume_avg
-
-    def _call_kernel(self, call_details, values, cutoff, magnetic):
+    def _call_kernel(self, call_details, values, cutoff, magnetic, effective_radius_type):
         # type: (CallDetails, np.ndarray, np.ndarray, float, bool) -> np.ndarray
         context = self.queue.context
@@ -597 +572 @@
             details_b, values_b, self.q_input.q_b, self.result_b,
             self.real(cutoff),
+            np.uint32(effective_radius_type),
         ]
         #print("Calling OpenCL")