Changeset 17bbadd in sasmodels for sasmodels/kernelcl.py

Timestamp:

Mar 15, 2016 10:47:12 AM (8 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, costrafo411, magnetic_model, release_v0.94, release_v0.95, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

754e27b

Parents:

5ceb7d0

Message:

refactor so all model defintion queries use model_info; better documentation of model_info structure; initial implementation of product model (broken)

File:

• sasmodels/kernelcl.py (modified) (6 diffs)

sasmodels/kernelcl.py

@@ -289 +289 @@
     GPU wrapper for a single model.
 
-    *source* and *info* are the model source and interface as returned
-    from :func:`gen.make`.
+    *source* and *model_info* are the model source and interface as returned
+    from :func:`generate.make_source` and :func:`generate.make_model_info`.
 
     *dtype* is the desired model precision.  Any numpy dtype for single
@@ -300 +300 @@
     that the compiler is allowed to take shortcuts.
     """
-    def __init__(self, source, info, dtype=generate.F32):
-        self.info = info
+    def __init__(self, source, model_info, dtype=generate.F32):
+        self.info = model_info
         self.source = source
         self.dtype = generate.F32 if dtype == 'fast' else np.dtype(dtype)
@@ -356 +356 @@
     """
     def __init__(self, q_vectors, dtype=generate.F32):
+        # TODO: do we ever need double precision q?
         env = environment()
         self.nq = q_vectors[0].size
@@ -389 +390 @@
     *kernel* is the GpuKernel object to call
 
-    *info* is the module information
+    *model_info* is the module information
 
     *q_vectors* is the q vectors at which the kernel should be evaluated
@@ -403 +404 @@
     Call :meth:`release` when done with the kernel instance.
     """
-    def __init__(self, kernel, info, q_vectors, dtype):
+    def __init__(self, kernel, model_info, q_vectors, dtype):
         q_input = GpuInput(q_vectors, dtype)
         self.kernel = kernel
-        self.info = info
+        self.info = model_info
         self.res = np.empty(q_input.nq, q_input.dtype)
         dim = '2d' if q_input.is_2d else '1d'
-        self.fixed_pars = info['partype']['fixed-' + dim]
-        self.pd_pars = info['partype']['pd-' + dim]
+        self.fixed_pars = model_info['partype']['fixed-' + dim]
+        self.pd_pars = model_info['partype']['pd-' + dim]
 
         # Inputs and outputs for each kernel call
@@ -430 +431 @@
                 else np.float32)  # will never get here, so use np.float32
 
+        #print "pars", fixed_pars, pd_pars
         res_bi = self.res_b
         nq = np.uint32(self.q_input.nq)