Changeset 7e99f5c in sasview for sansmodels/src/sans

Timestamp:

Mar 12, 2010 1:04:16 PM (15 years ago)

Author:

Jae Cho <jhjcho@…>

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, release_4.0.1, ticket-1009, ticket-1094-headless, ticket-1242-2d-resolution, ticket-1243, ticket-1249, ticket885, unittest-saveload

Children:

3080527

Parents:

83195f7

Message:

updated data input

File:

• sansmodels/src/sans/models/test/utest_evaldist.py (modified) (6 diffs)

sansmodels/src/sans/models/test/utest_evaldist.py

@@ -56 +56 @@
         qx = numpy.asarray(qx_values)
         qy = numpy.asarray(qy_values)
-        
-        qx_prime = numpy.reshape(qx, [3,1])
-        qy_prime = numpy.reshape(qy, [1,3])
+                     
+        new_x = numpy.tile(qx, (len(qy),1))
+        new_y = numpy.tile(qy, (len(qx),1))
+        new_y = new_y.swapaxes(0,1)
+    
+        #iq is 1d array now (since 03-12-2010)
+        qx_prime = new_x.flatten()
+        qy_prime = new_y.flatten()
         
         iq = self.model.evalDistribution([qx_prime, qy_prime])
@@ -64 +69 @@
         for i in range(3):
             for j in range(3):
-                self.assertAlmostEquals(iq[i][j], expected[i][j])
+                k = i+len(qx)*j
+                self.assertAlmostEquals(iq[k], expected[i][j])
 
     def test_rectangle_methods(self):
@@ -92 +98 @@
         qx = numpy.asarray(qx_values)
         qy = numpy.asarray(qy_values)
-        
-        qx_prime = numpy.reshape(qx, [3,1])
-        qy_prime = numpy.reshape(qy, [1,2])
+                     
+        new_x = numpy.tile(qx, (len(qy),1))
+        new_y = numpy.tile(qy, (len(qx),1))
+        new_y = new_y.swapaxes(0,1)
+    
+        #iq is 1d array now (since 03-12-2010)
+        qx_prime = new_x.flatten()
+        qy_prime = new_y.flatten()
         
         iq = self.model.evalDistribution([qx_prime, qy_prime])
@@ -100 +111 @@
         for i in range(3):
             for j in range(2):
-                self.assertAlmostEquals(iq[i][j], expected[i][j])
+                k = i+len(qx)*j
+                self.assertAlmostEquals(iq[k], expected[i][j])
 
 
@@ -151 +163 @@
         qx = numpy.asarray(qx_values)
         qy = numpy.asarray(qy_values)
-        
-        qx_prime = numpy.reshape(qx, [3,1])
-        qy_prime = numpy.reshape(qy, [1,3])
+              
+        new_x = numpy.tile(qx, (len(qy),1))
+        new_y = numpy.tile(qy, (len(qx),1))
+        new_y = new_y.swapaxes(0,1)
+    
+        #iq is 1d array now (since 03-12-2010)
+        qx_prime = new_x.flatten()
+        qy_prime = new_y.flatten()
         
         iq = self.model.evalDistribution([qx_prime, qy_prime])
@@ -159 +176 @@
         for i in range(3):
             for j in range(3):
-                self.assertAlmostEquals(iq[i][j], expected[i][j])
+                # convert index into 1d array
+                k = i+len(qx)*j
+                self.assertAlmostEquals(iq[k], expected[i][j])