Changeset f734e7d in sasmodels for sasmodels/direct_model.py

Timestamp:

Feb 22, 2015 1:44:54 AM (9 years ago)

Author:

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:

6137124

Parents:

711d8e2

Message:

restructure c code generation for maintainability; extend test harness to allow opencl and ctypes tests

File:

• sasmodels/direct_model.py (modified) (1 diff)

sasmodels/direct_model.py

@@ -3 +3 @@
 import numpy as np
 
-from . import models
-from . import weights
-
-try:
-    from .kernelcl import load_model
-except ImportError,exc:
-    warnings.warn(str(exc))
-    warnings.warn("using ctypes instead")
-    from .kerneldll import load_model
-
-def load_model_definition(model_name):
-    __import__('sasmodels.models.'+model_name)
-    model_definition = getattr(models, model_name, None)
-    return model_definition
-
-# load_model is imported above.  It looks like the following
-#def load_model(model_definition, dtype='single):
-#    if kerneldll:
-#        if source is newer than compiled: compile
-#        load dll
-#        return kernel
-#    elif kernelcl:
-#        compile source on context
-#        return kernel
-
-
-def make_kernel(model, q_vectors):
-    """
-    Return a computation kernel from the model definition and the q input.
-    """
-    input = model.make_input(q_vectors)
-    return model(input)
-
-def get_weights(kernel, pars, name):
-    """
-    Generate the distribution for parameter *name* given the parameter values
-    in *pars*.
-
-    Searches for "name", "name_pd", "name_pd_type", "name_pd_n", "name_pd_sigma"
-    """
-    relative = name in kernel.info['partype']['pd-rel']
-    limits = kernel.info['limits']
-    disperser = pars.get(name+'_pd_type', 'gaussian')
-    value = pars.get(name, kernel.info['defaults'][name])
-    npts = pars.get(name+'_pd_n', 0)
-    width = pars.get(name+'_pd', 0.0)
-    nsigma = pars.get(name+'_pd_nsigma', 3.0)
-    v,w = weights.get_weights(
-        disperser, npts, width, nsigma,
-        value, limits[name], relative)
-    return v,w/np.sum(w)
-
-def call_kernel(kernel, pars):
-    fixed_pars = [pars.get(name, kernel.info['defaults'][name])
-                  for name in kernel.fixed_pars]
-    pd_pars = [get_weights(kernel, pars, name) for name in kernel.pd_pars]
-    return kernel(fixed_pars, pd_pars)
+from .core import load_model_definition, make_kernel, call_kernel
+from .core import load_model_cl as load_model
+if load_model is None:
+    warnings.warn("unable to load opencl; using ctypes instead")
+    from .core import load_model_dll as load_model
 
 class DirectModel: