Changes in sasmodels/details.py [ccd5f01:f39759c] in sasmodels

File:

• sasmodels/details.py (modified) (7 diffs)

sasmodels/details.py

@@ -15 +15 @@
 
 import numpy as np  # type: ignore
-from numpy import pi, cos, sin
+from numpy import pi, cos, sin, radians
 
 try:
@@ -29 +29 @@
 
 try:
-    from typing import List
+    from typing import List, Tuple, Sequence
 except ImportError:
     pass
 else:
     from .modelinfo import ModelInfo
+    from .modelinfo import ParameterTable
 
 
@@ -53 +54 @@
     coordinates, the total circumference decreases as latitude varies from
     pi r^2 at the equator to 0 at the pole, and the weight associated
-    with a range of phi values needs to be scaled by this circumference.
+    with a range of latitude values needs to be scaled by this circumference.
     This scale factor needs to be updated each time the theta value
     changes.  *theta_par* indicates which of the values in the parameter
@@ -231 +232 @@
     nvalues = kernel.info.parameters.nvalues
     scalars = [(v[0] if len(v) else np.NaN) for v, w in pairs]
-    values, weights = zip(*pairs[2:npars+2]) if npars else ((),())
+    # skipping scale and background when building values and weights
+    values, weights = zip(*pairs[2:npars+2]) if npars else ((), ())
+    weights = correct_theta_weights(kernel.info.parameters, values, weights)
     length = np.array([len(w) for w in weights])
     offset = np.cumsum(np.hstack((0, length)))
@@ -244 +247 @@
     return call_details, data, is_magnetic
 
+def correct_theta_weights(parameters, values, 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
+    # Apparently the parameters.theta_offset similarly skips scale and
+    # and background, so the indexing works out.
+    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)
+    return weights
+
 
 def convert_magnetism(parameters, values):
+    # type: (ParameterTable, Sequence[np.ndarray]) -> bool
     """
     Convert magnetism values from polar to rectangular coordinates.
@@ -255 +284 @@
     scale = mag[:,0]
     if np.any(scale):
-        theta, phi = mag[:, 1]*pi/180., mag[:, 2]*pi/180.
+        theta, phi = radians(mag[:, 1]), radians(mag[:, 2])
         cos_theta = cos(theta)
         mag[:, 0] = scale*cos_theta*cos(phi)  # mx
@@ -269 +298 @@
     """
     Create a mesh grid of dispersion parameters and weights.
+
+    pars is a list of pairs (values, weights), where the values are the
+    individual parameter values at which to evaluate the polydispersity
+    distribution and weights are the weights associated with each value.
+
+    Only the volume parameters should be included in this list.  Orientation
+    parameters do not affect the calculation of effective radius or volume
+    ratio.
 
     Returns [p1,p2,...],w where pj is a vector of values for parameter j