Changeset a151caa in sasmodels for sasmodels/models/be_polyelectrolyte.py

Timestamp:

Jul 28, 2017 10:49:09 PM (7 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:

404ebbd

Parents:

0bdddc2

Message:

tuned random model generator for be_polyelectrolyte, barbell, core multishell, core-shell bicelle

File:

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

sasmodels/models/be_polyelectrolyte.py

@@ -17 +17 @@
     r_{0}^2 = \frac{1}{\alpha \sqrt{C_a} \left( b/\sqrt{48\pi L_b}\right)}
 
-where 
+where
 
 $K$ is the contrast factor for the polymer which is defined differently than in
@@ -28 +28 @@
 
     a = b_p - (v_p/v_s) b_s
-    
+
 where $b_p$ and $b_s$ are sum of the scattering lengths of the atoms
 constituting the monomer of the polymer and the sum of the scattering lengths
@@ -35 +35 @@
 
 $L_b$ is the Bjerrum length(|Ang|) - **Note:** This parameter needs to be
-kept constant for a given solvent and temperature! 
+kept constant for a given solvent and temperature!
 
 $h$ is the virial parameter (|Ang^3|/mol) - **Note:** See [#Borue]_ for the
@@ -67 +67 @@
 * **Author:** NIST IGOR/DANSE **Date:** pre 2010
 * **Last Modified by:** Paul Kienzle **Date:** July 24, 2016
-* **Last Reviewed by:** Paul Butler and Richard Heenan **Date:** 
+* **Last Reviewed by:** Paul Butler and Richard Heenan **Date:**
   October 07, 2016
 """
@@ -139 +139 @@
 Iq.vectorized = True  # Iq accepts an array of q values
 
+def random():
+    import numpy as np
+    pars = dict(
+        scale=10000, #background=0,
+        #polymer_concentration=0.7,
+        polymer_concentration=np.random.beta(5, 3), # around 70%
+        #salt_concentration=0.0,
+        # keep salt concentration extremely low
+        # and use explicit molar to match polymer concentration
+        salt_concentration=np.random.beta(1, 100)*6.022136e-4,
+        #contrast_factor=10.0,
+        contrast_fact=np.random.uniform(1, 100),
+        #bjerrum_length=7.1,
+        bjerrum_length=np.random.uniform(1, 10),
+        #virial_param=12.0,
+        virial_param=np.random.uniform(-1000, 30),
+        #monomer_length=10.0,
+        monomer_length=10.0**(4*np.random.beta(1.5, 3)),
+        #ionization_degree=0.05,
+        ionization_degree=np.random.beta(1.5, 4),
+    )
+    return pars
 
 demo = dict(scale=1, background=0.1,