Changes in sasmodels/models/triaxial_ellipsoid.py [0b56f38:15a90c1] in sasmodels

File:

• sasmodels/models/triaxial_ellipsoid.py (modified) (6 diffs)

sasmodels/models/triaxial_ellipsoid.py

@@ -65 +65 @@
 To provide easy access to the orientation of the triaxial ellipsoid,
 we define the axis of the cylinder using the angles $\theta$, $\phi$
-and $\psi$. These angles are defined on
-:numref:`triaxial-ellipsoid-angles` .
+and $\psi$. These angles are defined analogously to the elliptical_cylinder below
+
+.. figure:: img/elliptical_cylinder_angle_definition.png
+
+    Definition of angles for oriented triaxial ellipsoid, where radii shown here are $a < b << c$
+    and angle $\Psi$ is a rotation around the axis of the particle.
+
 The angle $\psi$ is the rotational angle around its own $c$ axis
 against the $q$ plane. For example, $\psi = 0$ when the
@@ -73 +78 @@
 .. _triaxial-ellipsoid-angles:
 
-.. figure:: img/triaxial_ellipsoid_angle_projection.jpg
+.. figure:: img/triaxial_ellipsoid_angle_projection.png
 
-    The angles for oriented ellipsoid.
+    Some example angles for oriented ellipsoid.
 
 The radius-of-gyration for this system is  $R_g^2 = (R_a R_b R_c)^2/5$.
@@ -81 +86 @@
 The contrast $\Delta\rho$ is defined as SLD(ellipsoid) - SLD(solvent).  In the
 parameters, $R_a$ is the minor equatorial radius, $R_b$ is the major
-equatorial radius, and $R_c$ is the polar radius of the ellipsoid.
+equatorial radius, and $R_c$ is the polar radius of the ellipsoid. 
 
 NB: The 2nd virial coefficient of the triaxial solid ellipsoid is
@@ -112 +117 @@
 """
 
-from numpy import inf, sin, cos, pi
+from numpy import inf
 
 name = "triaxial_ellipsoid"
@@ -147 +152 @@
 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 +176 @@
             phi_pd=15, phi_pd_n=1,
             psi_pd=15, psi_pd_n=1)
-q = 0.1
-# april 6 2017, rkh add unit tests, NOT compared with any other calc method, assume correct!
-# add 2d test after pull #890
-qx = q*cos(pi/6.0)
-qy = q*sin(pi/6.0)
-tests = [[{}, 0.05, 24.8839548033],
-#        [{'theta':80., 'phi':10.}, (qx, qy), 9999. ],
-        ]
-del qx, qy  # not necessary to delete, but cleaner
+
+# TODO: need some unit tests!