Changeset 0e04dd7 in sasmodels

Timestamp:

Jul 19, 2018 9:44:48 AM (6 years ago)

Author:

GitHub <noreply@…>

Branches:

master

Children:

9ce5bcb

Parents:

36873d1

git-author:

Steve K <smk78@…> (07/19/18 09:44:48)

git-committer:

GitHub <noreply@…> (07/19/18 09:44:48)

Message:

Update polydispersity.rst

Minor tweaks.

File:

• doc/guide/pd/polydispersity.rst (modified) (5 diffs)

doc/guide/pd/polydispersity.rst

@@ -59 +59 @@
 *  *Schulz Distribution*
 *  *Array Distribution*
+*  *User-defined Distributions*
 
 These are all implemented as *number-average* distributions.
 
-Additional distributions are under consideration.
 
 Suggested Applications
@@ -77 +77 @@
 Lognormal) because angles can be negative!
 
-The array distribution allows a user-defined distribution to be applied.
+The array distribution provides a very simple means of implementing a user-
+defined distribution, but without any fittable parameters. Greater flexibility
+is conferred by the user-defined distribution. 
 
 .. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ
@@ -318 +320 @@
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-You can define your own distribution by creating a python file defining a
+You can also define your own distribution by creating a python file defining a
 *Distribution* object with a *_weights* method.  The *_weights* method takes
 *center*, *sigma*, *lb* and *ub* as arguments, and can access *self.npts*
@@ -326 +328 @@
   if it is an angular dispersity.  This parameter may be fitted.
 
-* *sigma* the width of the distribution, with is the polydispersity parameter
+* *sigma* the width of the distribution, which is the polydispersity parameter
   times the center for size dispersity, or the polydispersity parameter alone
   for angular dispersity.  This parameter may be fitted.
 
-* *lb*, *ub* are the parameter limits given in the model definition file.  For
-  example, a radius parameter has *lb* equal to zero.  A volume fraction
-  parameter would have *lb* equal to zero and *ub* equal to one.
+* *lb*, *ub* are the parameter limits (lower & upper bounds) given in the model
+  definition file.  For example, a radius parameter has *lb* equal to zero.  A
+  volume fraction parameter would have *lb* equal to zero and *ub* equal to one.
 
 * *self.nsigmas* the distance to go into the tails when evaluating the
@@ -344 +346 @@
   parameter in a three parameter distribution.
 
-The code following wraps the Laplace distribution from scipy stats::
+As an example, the code following wraps the Laplace distribution from scipy stats::
 
     import numpy as np