Changeset 31df0c9 in sasmodels for sasmodels/models/cylinder.py

Timestamp:

Aug 1, 2017 2:38:47 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:

1511c37c

Parents:

d49ca5c

Message:

tuned random model generation for more models

File:

• sasmodels/models/cylinder.py (modified) (3 diffs)

sasmodels/models/cylinder.py

@@ -63 +63 @@
 .. figure:: img/cylinder_angle_definition.png
 
-    Definition of the $\theta$ and $\phi$ orientation angles for a cylinder relative 
-    to the beam line coordinates, plus an indication of their orientation distributions 
-    which are described as rotations about each of the perpendicular axes $\delta_1$ and $\delta_2$ 
+    Definition of the $\theta$ and $\phi$ orientation angles for a cylinder relative
+    to the beam line coordinates, plus an indication of their orientation distributions
+    which are described as rotations about each of the perpendicular axes $\delta_1$ and $\delta_2$
     in the frame of the cylinder itself, which when $\theta = \phi = 0$ are parallel to the $Y$ and $X$ axes.
 
@@ -72 +72 @@
     Examples for oriented cylinders.
 
-The $\theta$ and $\phi$ parameters to orient the cylinder only appear in the model when fitting 2d data. 
+The $\theta$ and $\phi$ parameters to orient the cylinder only appear in the model when fitting 2d data.
 On introducing "Orientational Distribution" in the angles, "distribution of theta" and "distribution of phi" parameters will
-appear. These are actually rotations about the axes $\delta_1$ and $\delta_2$ of the cylinder, which when $\theta = \phi = 0$ are parallel 
+appear. These are actually rotations about the axes $\delta_1$ and $\delta_2$ of the cylinder, which when $\theta = \phi = 0$ are parallel
 to the $Y$ and $X$ axes of the instrument respectively. Some experimentation may be required to understand the 2d patterns fully.
-(Earlier implementations had numerical integration issues in some circumstances when orientation distributions passed through 90 degrees, such 
-situations, with very broad distributions, should still be approached with care.) 
+(Earlier implementations had numerical integration issues in some circumstances when orientation distributions passed through 90 degrees, such
+situations, with very broad distributions, should still be approached with care.)
 
 Validation
@@ -150 +150 @@
     return 0.5 * (ddd) ** (1. / 3.)
 
+def random():
+    import numpy as np
+    V = 10**np.random.uniform(5, 12)
+    length = 10**np.random.uniform(-2, 2)*V**0.333
+    radius = np.sqrt(V/length/np.pi)
+    pars = dict(
+        #scale=1,
+        #background=0,
+        length=length,
+        radius=radius,
+    )
+    return pars
+
+
 # parameters for demo
 demo = dict(scale=1, background=0,