Changes in / [c9801b8:8632a35] in sasmodels

Files:

• example/sesansfit.py (modified) (4 diffs)
• sasmodels/bumps_model.py (modified) (1 diff)

example/sesansfit.py

@@ -4 +4 @@
 from sasmodels import bumps_model as sas
 kernel = sas.load_model('sphere', dtype='single')
+#kernel = sas.load_model('triaxial_ellipsoid', dtype='single')
 
 
@@ -11 +12 @@
     loader=Loader()
     data=loader.load('testsasview1.ses')
+    data.x /=10
     
 #    data = load_sesans('mydatfile.pz')
@@ -20 +22 @@
     err_data = np.ones_like(SElength)*0.03
 
+    class Sample:
+        zacceptance = 0.1 # [A^-1]
+        thickness = 0.2 # [cm]
+        
     class SESANSData1D:
         #q_zmax = 0.23 # [A^-1]
-        zacceptance = 0.1 # [A^-1]
-        lam = 2e-10 # [m]
-        thickness = 0.2 # [cm]
+        lam = 0.2 # [nm]
         x = SElength
         y = data
         dy = err_data
-    data = SesansData()
-print dir(data)
+        sample = Sample()
+    data = SESANSData1D()
 
 radius = 1000
 data.Rmax = 3*radius # [A]
 
+##  Sphere parameters
+
 phi = Parameter(0.1, name="phi")
 model = sas.BumpsModel(data, kernel,
     scale=phi*(1-phi), sld=7.0, solvent_sld=1.0, radius=radius)
-phi.pmp(10)
-model.radius.pmp(40)
-model.sld.pm(2)
-model.background.range(0,5)
-
+phi.range(0.001,0.90)
+#model.radius.pmp(40)
+model.radius.range(100,10000)
+#model.sld.pmp(5)
+#model.background
+#model.radius_pd=0
+#model.radius_pd_n=0
 
 if False: # have sans data
@@ -49 +57 @@
     problem = FitProblem(model)
 
+
+### Tri-Axial Ellipsoid
+#
+#phi = Parameter(0.1, name='phi')
+#model = sas.BumpsModel(data, kernel,
+#    scale=phi*(1-phi), sld=7.0, solvent_sld=1.0, radius=radius)
+#phi.range(0.001,0.90)
+##model.radius.pmp(40)
+#model.radius.range(100,10000)
+##model.sld.pmp(5)
+##model.background
+##model.radius_pd=0
+##model.radius_pd_n=0
+#
+#if False: # have sans data
+#    sansmodel = sas.BumpsModel(sans_data, kernel, **model.parameters())
+#    problem = FitProblem([model, sansmodel])
+#else:
+#    problem = FitProblem(model)

sasmodels/bumps_model.py

@@ -354 +354 @@
             #self._theory[:] = self._fn.eval(pars, pd_pars)
             if self.data_type == 'sesans':
-                P = sesans.hankel(self.data.x, self.data.lam,
+                P = sesans.hankel(self.data.x, self.data.lam*1e-9,
                                   self.data.sample.thickness/10, self._fn_inputs[0],
                                   self._theory)