Changeset 51a4d78 in sasview for src/sas/sascalc/data_util

Timestamp:

Oct 8, 2016 3:33:04 PM (8 years ago)

Author:

jhbakker

Branches:

master, ESS_GUI, ESS_GUI_Docs, ESS_GUI_batch_fitting, ESS_GUI_bumps_abstraction, ESS_GUI_iss1116, ESS_GUI_iss879, ESS_GUI_iss959, ESS_GUI_opencl, ESS_GUI_ordering, ESS_GUI_sync_sascalc, costrafo411, magnetic_scatt, release-4.1.1, release-4.1.2, release-4.2.2, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

1fac6c0

Parents:

7988501 (diff), f7bc948 (diff)
Note: this is a merge changeset, the changes displayed below correspond to the merge itself.
Use the (diff) links above to see all the changes relative to each parent.

Message:

Merge branch 'ajj_sesans' into Jurrian1D

File:

• src/sas/sascalc/data_util/qsmearing.py (modified) (4 diffs)

src/sas/sascalc/data_util/qsmearing.py

@@ -5 +5 @@
 #This software was developed by the University of Tennessee as part of the
 #Distributed Data Analysis of Neutron Scattering Experiments (DANSE)
-#project funded by the US National Science Foundation. 
+#project funded by the US National Science Foundation.
 #See the license text in license.txt
 #copyright 2008, University of Tennessee
@@ -13 +13 @@
 import logging
 import sys
+import sasmodels.sesans
 
-from sasmodels.resolution import Slit1D, Pinhole1D
+from sasmodels.resolution import Slit1D, Pinhole1D, SESANS1D
 from sasmodels.resolution2d import Pinhole2D
 
@@ -48 +49 @@
 
     # Look for resolution smearing data
+    _found_sesans = False
+    if data.dx is not None and data.lam is not None:
+        if data.dx[0] > 0.0:
+            _found_sesans = True
+
+    if _found_sesans == True:
+        return sesans_smear(data, model)
+
     _found_resolution = False
     if data.dx is not None and len(data.dx) == len(data.x):
@@ -142 +151 @@
     width = data.dx if data.dx is not None else 0
     return PySmear(Pinhole1D(q, width), model)
+
+def sesans_smear(data, model=None):
+    #This should be calculated characteristic length scale
+    #Probably not a data prameter either
+    #Need function to calculate this based on model
+    #Here assume a number
+    Rmax = 50000
+    q_calc = sesans.make_q(data.sample.z, Rmax)
+    return PySmear(SESANS1D(data,q_calc),model)