Changeset 0e04dd7 in sasmodels


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Timestamp:
Jul 19, 2018 11:44:48 AM (5 weeks ago)
Author:
GitHub <noreply@…>
Branches:
ticket-608-user-defined-weights
Children:
9ce5bcb
Parents:
36873d1
git-author:
Steve K <smk78@…> (07/19/18 11:44:48)
git-committer:
GitHub <noreply@…> (07/19/18 11:44:48)
Message:

Update polydispersity.rst

Minor tweaks.

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  • doc/guide/pd/polydispersity.rst

    r36873d1 r0e04dd7  
    5959*  *Schulz Distribution* 
    6060*  *Array Distribution* 
     61*  *User-defined Distributions* 
    6162 
    6263These are all implemented as *number-average* distributions. 
    6364 
    64 Additional distributions are under consideration. 
    6565 
    6666Suggested Applications 
     
    7777Lognormal) because angles can be negative! 
    7878 
    79 The array distribution allows a user-defined distribution to be applied. 
     79The array distribution provides a very simple means of implementing a user- 
     80defined distribution, but without any fittable parameters. Greater flexibility 
     81is conferred by the user-defined distribution.  
    8082 
    8183.. ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ 
     
    318320^^^^^^^^^^^^^^^^^^^^^^^^^^ 
    319321 
    320 You can define your own distribution by creating a python file defining a 
     322You can also define your own distribution by creating a python file defining a 
    321323*Distribution* object with a *_weights* method.  The *_weights* method takes 
    322324*center*, *sigma*, *lb* and *ub* as arguments, and can access *self.npts* 
     
    326328  if it is an angular dispersity.  This parameter may be fitted. 
    327329 
    328 * *sigma* the width of the distribution, with is the polydispersity parameter 
     330* *sigma* the width of the distribution, which is the polydispersity parameter 
    329331  times the center for size dispersity, or the polydispersity parameter alone 
    330332  for angular dispersity.  This parameter may be fitted. 
    331333 
    332 * *lb*, *ub* are the parameter limits given in the model definition file.  For 
    333   example, a radius parameter has *lb* equal to zero.  A volume fraction 
    334   parameter would have *lb* equal to zero and *ub* equal to one. 
     334* *lb*, *ub* are the parameter limits (lower & upper bounds) given in the model 
     335  definition file.  For example, a radius parameter has *lb* equal to zero.  A 
     336  volume fraction parameter would have *lb* equal to zero and *ub* equal to one. 
    335337 
    336338* *self.nsigmas* the distance to go into the tails when evaluating the 
     
    344346  parameter in a three parameter distribution. 
    345347 
    346 The code following wraps the Laplace distribution from scipy stats:: 
     348As an example, the code following wraps the Laplace distribution from scipy stats:: 
    347349 
    348350    import numpy as np 
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