Changeset 9e771a3 in sasmodels

Timestamp:

Oct 18, 2017 10:51:08 PM (7 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:

94f4543

Parents:

9b7b23f

Message:

sort out weights (seems to be correct this time)

Location:

sasmodels

Files:

• core.py (modified) (1 diff)
• details.py (modified) (2 diffs)
• direct_model.py (modified) (3 diffs)

sasmodels/core.py

@@ -272 +272 @@
     Possible types include 'half', 'single', 'double' and 'quad'.  If the
     type is 'fast', then this is equivalent to dtype 'single' but using
-    fast native functions rather than those with the precision level guaranteed
-    by the OpenCL standard.
+    fast native functions rather than those with the precision level
+    guaranteed by the OpenCL standard.  'default' will choose the appropriate
+    default for the model and platform.
 
     Platform preference can be specfied ("ocl" vs "dll"), with the default

sasmodels/details.py

@@ -234 +234 @@
     # skipping scale and background when building values and weights
     values, dispersity, weights = zip(*mesh[2:npars+2]) if npars else ((), (), ())
-    weights = correct_theta_weights(kernel.info.parameters, values, weights)
+    weights = correct_theta_weights(kernel.info.parameters, dispersity, weights)
     length = np.array([len(w) for w in weights])
     offset = np.cumsum(np.hstack((0, length)))
@@ -247 +247 @@
     return call_details, data, is_magnetic
 
-def correct_theta_weights(parameters, values, weights):
+def correct_theta_weights(parameters, dispersity, weights):
     # type: (ParameterTable, Sequence[np.ndarray], Sequence[np.ndarray]) -> Sequence[np.ndarray]
     """
     If there is a theta parameter, update the weights of that parameter so that
-    the cosine weighting required for polar integration is preserved.  Avoid
-    evaluation strictly at the pole, which would otherwise send the weight to
-    zero.
-
-    Note: values and weights do not include scale and background
-    """
-    # TODO: document code, explaining why scale and background are skipped
-    # given that we don't have scale and background in the list, we
-    # should be calling the variables something other than values and weights
+    the cosine weighting required for polar integration is preserved.
+
+    Avoid evaluation strictly at the pole, which would otherwise send the
+    weight to zero.  This is probably not a problem in practice (if dispersity
+    is +/- 90, then you probably should be using a 1-D model of the circular
+    average).
+
+    Note: scale and background parameters are not include in the tuples for
+    dispersity and weights, so index is parameters.theta_offset, not
+    parameters.theta_offset+2
+
+    Returns updated weights vectors
+    """
+    # TODO: explain in a comment why scale and background are missing
     # Apparently the parameters.theta_offset similarly skips scale and
-    # and background, so the indexing works out.
+    # and background, so the indexing works out, but they are still shipped
+    # to the kernel, so we need to add two there.
     if parameters.theta_offset >= 0:
         index = parameters.theta_offset
-        theta = values[index]
-        theta_weight = np.minimum(abs(cos(radians(theta))), 1e-6)
-        # copy the weights list so we can update it
-        weights = list(weights)
-        weights[index] = theta_weight*np.asarray(weights[index])
-        weights = tuple(weights)
+        theta = dispersity[index]
+        # TODO: modify the dispersity vector to avoid the theta=-90,90,270,...
+        theta_weight = abs(cos(radians(theta)))
+        weights = tuple(theta_weight*v if k == index else v
+                        for k, v in enumerate(weights))
     return weights
 

sasmodels/direct_model.py

@@ -56 +56 @@
     """
     mesh = get_mesh(calculator.info, pars, dim=calculator.dim, mono=mono)
+    #print("pars", list(zip(*mesh))[0])
     call_details, values, is_magnetic = make_kernel_args(calculator, mesh)
     #print("values:", values)
@@ -152 +153 @@
     width = values.get(parameter.name+'_pd', 0.0)
     relative = parameter.relative_pd
-    if npts == 0 or width == 0 or not active:
+    if npts == 0 or width == 0.0 or not active:
         # Note: orientation parameters have the viewing angle as the parameter
         # value and the jitter in the distribution, so be sure to set the
         # empty pd for orientation parameters to 0.
-        pd = [value if relative else 0.0], [1.0]
+        pd = [value if relative or not parameter.polydisperse else 0.0], [1.0]
     else:
         limits = parameter.limits
@@ -166 +167 @@
 
 
-def _vol_pars(model_info, pars):
+def _vol_pars(model_info, values):
     # type: (ModelInfo, ParameterSet) -> Tuple[np.ndarray, np.ndarray]
-    vol_pars = [get_weights(p, pars)
+    vol_pars = [_get_par_weights(p, values)
                 for p in model_info.parameters.call_parameters
                 if p.type == 'volume']
     #import pylab; pylab.plot(vol_pars[0][0],vol_pars[0][1]); pylab.show()
-    value, weight = dispersion_mesh(model_info, vol_pars)
-    return value, weight
+    dispersity, weight = dispersion_mesh(model_info, vol_pars)
+    return dispersity, weight