Changeset 4aaf89a in sasmodels

Timestamp:

Apr 6, 2017 6:11:41 AM (8 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, costrafo411, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

15a90c1

Parents:

b6e0636

Message:

triaxial ellipsoid/parallelepiped: choose the pair of lengths that are closest to each other as the equatorial plane when computing ER

Location:

sasmodels/models

Files:

• parallelepiped.py (modified) (1 diff)
• triaxial_ellipsoid.py (modified) (2 diffs)

sasmodels/models/parallelepiped.py

@@ -208 +208 @@
 def ER(length_a, length_b, length_c):
     """
-        Return effective radius (ER) for P(q)*S(q)
+    Return effective radius (ER) for P(q)*S(q)
     """
-
+    # now that axes can be in any size order, need to sort a,b,c where a~b and c is either much smaller 
+    # or much larger
+    abc = np.vstack((length_a, length_b, length_c))
+    abc = np.sort(abc, axis=0)
+    selector = (abc[1] - abc[0]) > (abc[2] - abc[1])
+    length = np.where(selector, abc[0], abc[2])
     # surface average radius (rough approximation)
-    surf_rad = sqrt(length_a * length_b / pi)
-
-    ddd = 0.75 * surf_rad * (2 * surf_rad * length_c + (length_c + surf_rad) * (length_c + pi * surf_rad))
+    radius = np.sqrt(np.where(~selector, abc[0]*abc[1], abc[1]*abc[2]) / pi)
+
+    ddd = 0.75 * radius * (2*radius*length + (length + radius)*(length + pi*radius))
     return 0.5 * (ddd) ** (1. / 3.)
 

sasmodels/models/triaxial_ellipsoid.py

@@ -147 +147 @@
 def ER(radius_equat_minor, radius_equat_major, radius_polar):
     """
-        Returns the effective radius used in the S*P calculation
+    Returns the effective radius used in the S*P calculation
     """
     import numpy as np
     from .ellipsoid import ER as ellipsoid_ER
-     # now that radii can be in any size order, radii need sorting a,b,c where a~b and c is either much smaller or much larger
-     # also need some unit tests!
-    
-    return ellipsoid_ER(radius_polar, np.sqrt(radius_equat_minor * radius_equat_major))
+
+    # now that radii can be in any size order, radii need sorting a,b,c where a~b and c is either much smaller 
+    # or much larger
+    radii = np.vstack((radius_equat_major, radius_equat_minor, radius_polar))
+    radii = np.sort(radii, axis=0)
+    selector = (radii[1] - radii[0]) > (radii[2] - radii[1])
+    polar = np.where(selector, radii[0], radii[2])
+    equatorial = np.sqrt(np.where(~selector, radii[0]*radii[1], radii[1]*radii[2]))
+    return ellipsoid_ER(polar, equatorial)
 
 demo = dict(scale=1, background=0,
@@ -166 +171 @@
             phi_pd=15, phi_pd_n=1,
             psi_pd=15, psi_pd_n=1)
+
+# TODO: need some unit tests!