Changeset 5399809 in sasmodels for sasmodels/kernelcl.py

Timestamp:

Aug 21, 2018 1:32:40 PM (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:

2a12351b

Parents:

c57ee9e

Message:

fix R_eff support infrastructure so more tests pass

File:

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

sasmodels/kernelcl.py

@@ -481 +481 @@
         # at this point, so instead using 32, which is good on the set of
         # architectures tested so far.
+        extra_q = 3  # total weight, weighted volume and weighted radius
         if self.is_2d:
-            # Note: 16 rather than 15 because result is 1 longer than input.
-            width = ((self.nq+16)//16)*16
+            width = ((self.nq+15+extra_q)//16)*16
             self.q = np.empty((width, 2), dtype=dtype)
             self.q[:self.nq, 0] = q_vectors[0]
             self.q[:self.nq, 1] = q_vectors[1]
         else:
-            # Note: 32 rather than 31 because result is 1 longer than input.
-            width = ((self.nq+32)//32)*32
+            width = ((self.nq+31+extra_q)//32)*32
             self.q = np.empty(width, dtype=dtype)
             self.q[:self.nq] = q_vectors[0]
@@ -539 +538 @@
         self.dim = '2d' if q_input.is_2d else '1d'
         # 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, plus another for R_eff
-        self.result = np.empty((q_input.nq+2)*num_returns, dtype)
+        nout = 2 if self.info.have_Fq and self.dim == '1d' else 1
+        # plus 3 weight, volume, radius
+        self.result = np.empty(q_input.nq*nout + 3, self.dtype)
 
         # Inputs and outputs for each kernel call
@@ -549 +548 @@
 
         self.result_b = cl.Buffer(self.queue.context, mf.READ_WRITE,
-                                  q_input.global_size[0] * num_returns * dtype.itemsize)
+                                  q_input.global_size[0] * nout * dtype.itemsize)
         self.q_input = q_input # allocated by GpuInput above