Changeset eb69cce in sasmodels for sasmodels/models/spherepy.py

Timestamp:

Nov 30, 2015 9:18:41 PM (8 years ago)

Author:

Paul Kienzle <pkienzle@…>

Branches:

master, core_shell_microgels, costrafo411, magnetic_model, release_v0.94, release_v0.95, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests

Children:

d18f8a8

Parents:

d138d43

Message:

make model docs more consistent; build pdf docs

File:

• sasmodels/models/spherepy.py (modified) (5 diffs)

sasmodels/models/spherepy.py

@@ -11 +11 @@
 .. math::
 
-    I(Q) = \frac{\text{scale}}{V} \cdot \left[ \
-        3V(\Delta\rho) \cdot \frac{\sin(QR) - QR\cos(QR))}{(QR)^3} \
+    I(q) = \frac{\text{scale}}{V} \cdot \left[
+        3V(\Delta\rho) \cdot \frac{\sin(qr) - qr\cos(qr))}{(qr)^3}
         \right]^2 + \text{background}
 
 where *scale* is a volume fraction, $V$ is the volume of the scatterer,
-$R$ is the radius of the sphere, *background* is the background level and
+$r$ is the radius of the sphere, *background* is the background level and
 *sld* and *solvent_sld* are the scattering length densities (SLDs) of the
 scatterer and the solvent respectively.
@@ -27 +27 @@
 The 2D scattering intensity is the same as above, regardless of the
 orientation of $\vec q$.
-
-Our model uses the form factor calculations as defined in the IGOR
-package provided by the NIST Center for Neutron Research (Kline, 2006).
 
 Validation
@@ -49 +46 @@
 
 
-Reference
----------
+References
+----------
 
 A Guinier and G. Fournet, *Small-Angle Scattering of X-Rays*,
@@ -64 +61 @@
 title = "Spheres with uniform scattering length density"
 description = """\
-P(q)=(scale/V)*[3V(sld-solvent_sld)*(sin(qR)-qRcos(qR))
-                /(qR)^3]^2 + background
-    R: radius of sphere
+P(q)=(scale/V)*[3V(sld-solvent_sld)*(sin(qr)-qr cos(qr))
+                /(qr)^3]^2 + background
+    r: radius of sphere
     V: The volume of the scatter
     sld: the SLD of the sphere
@@ -101 +98 @@
     fq = bes * (sld - solvent_sld) * form_volume(radius)
     return 1.0e-4 * fq ** 2
-Iq.vectorized = True  # Iq accepts an array of Q values
+Iq.vectorized = True  # Iq accepts an array of q values
 
 def Iqxy(qx, qy, sld, solvent_sld, radius):
     return Iq(sqrt(qx ** 2 + qy ** 2), sld, solvent_sld, radius)
-Iqxy.vectorized = True  # Iqxy accepts arrays of Qx, Qy values
+Iqxy.vectorized = True  # Iqxy accepts arrays of qx, qy values
 
 def sesans(z, sld, solvent_sld, radius):