Changes in / [01c8d9e:502c7b8] in sasmodels

Files:

• doc/guide/pd/polydispersity.rst (modified) (3 diffs)
• explore/beta/HSS_SQ.m (added)
• explore/beta/data_files/testPolydisperseGaussianSphere.dat (added)
• explore/beta/data_files/testPolydisperseGaussianSphere2.dat (added)
• explore/beta/sasfit_compare.py (modified) (8 diffs)
• explore/beta/sphereFormFactor.m (added)
• explore/beta/testPolyDiseperseSphricalBeta.m (added)
• sasmodels/models/core_shell_sphere.py (modified) (1 diff)

doc/guide/pd/polydispersity.rst

@@ -20 +20 @@
   P(q) = \text{scale} \langle F^* F \rangle / V + \text{background}
 
-where $F$ is the scattering amplitude and $\langle\cdot\rangle$ denotes an
-average over the size distribution.
+where $F$ is the scattering amplitude and $\langle\cdot\rangle$ denotes an 
+average over the size distribution $f(x; \bar x, \sigma)$, giving
+
+.. math::
+
+  P(q) = \frac{\text{scale}}{V} \int_\mathbb{R} 
+  f(x; \bar x, \sigma) F^2(q, x)\, dx + \text{background}
 
 Each distribution is characterized by a center value $\bar x$ or
@@ -41 +46 @@
 with larger values of $N_\sigma$ required for heavier tailed distributions.
 The scattering in general falls rapidly with $qr$ so the usual assumption
-that $G(r - 3\sigma_r)$ is tiny and therefore $f(r - 3\sigma_r)G(r - 3\sigma_r)$
+that $f(r - 3\sigma_r)$ is tiny and therefore $f(r - 3\sigma_r)f(r - 3\sigma_r)$
 will not contribute much to the average may not hold when particles are large.
 This, too, will require increasing $N_\sigma$.
@@ -63 +68 @@
 
 Additional distributions are under consideration.
+
+.. note:: In 2009 IUPAC decided to introduce the new term 'dispersity' to replace 
+           the term 'polydispersity' (see `Pure Appl. Chem., (2009), 81(2), 
+           351-353 <http://media.iupac.org/publications/pac/2009/pdf/8102x0351.pdf>`_ 
+           in order to make the terminology describing distributions of properties 
+           unambiguous. Throughout the SasView documentation we continue to use the 
+           term polydispersity because one of the consequences of the IUPAC change is 
+           that orientational polydispersity would not meet their new criteria (which 
+           requires dispersity to be dimensionless).
 
 Suggested Applications

explore/beta/sasfit_compare.py

@@ -1 +1 @@
 from __future__ import division, print_function
 # Make sasmodels available on the path
-import sys,os
+import sys, os
 BETA_DIR = os.path.dirname(os.path.realpath(__file__))
 #SASMODELS_DIR = os.path.dirname(os.path.dirname(BETA_DIR))
 SASMODELS_DIR = r"C:\Source\sasmodels"
 sys.path.insert(0, SASMODELS_DIR)
-import os
+
 from collections import namedtuple
 
@@ -223 +223 @@
     if radius_effective is None:
         radius_effective = radius_eff/total_weight
-    print("this is the effective radius for pure python",radius_effective)
     if norm == 'sasfit':
         IQD = F2
@@ -232 +231 @@
         #     = F2/total_weight / total_volume/total_weight
         #     = F2/total_volume
-        
         IQD = F2/average_volume*1e-4*volfraction
         F1 *= 1e-2  # Yun is using sld in 1/A^2, not 1e-6/A^2
@@ -245 +243 @@
     IQSD = IQD*SQ
     IQBD = IQD*SQ_EFF
-    print("\n\n\n\n\n this is F1" + str(F1))
-
-    print("\n\n\n\n\n this is F2" + str(F2))
-    print("\n\n\n\n\n this is SQ" + str(SQ))   
     return Theory(Q=q, F1=F1, F2=F2, P=IQD, S=SQ, I=IQSD, Seff=SQ_EFF, Ibeta=IQBD)
 
@@ -340 +334 @@
             Ipars.setdefault(k.replace("_pd_type", "_pd_nsigma"), nsigmas)
 
-    
     #Ppars['scale'] = Spars.get('volfraction', 1)
     P = build_model(Pname, q)
@@ -417 +410 @@
     target = sasmodels_theory(q, model, beta_mode=1, **pars)
     actual = ellipsoid_pe(q, norm='sasview', **pars)
-    print(actual)
     title = " ".join(("sasmodels", model, pd_type))
     compare(title, target, actual)
@@ -460 +452 @@
     Q = data[0]
     F1 = data[1]
+    F2 = data[2]
     P = data[3]
     S = data[5]
@@ -471 +464 @@
     Q = data[0]
     F1 = data[1]
+    F2 = data[2]
     P = data[3]
     S = data[5]

sasmodels/models/core_shell_sphere.py

@@ -21 +21 @@
 .. math::
 
-    F^2(q) = \frac{3}{V_s}\left[
+    F(q) = \frac{3}{V_s}\left[
        V_c(\rho_c-\rho_s)\frac{\sin(qr_c)-qr_c\cos(qr_c)}{(qr_c)^3} +
        V_s(\rho_s-\rho_\text{solv})\frac{\sin(qr_s)-qr_s\cos(qr_s)}{(qr_s)^3}