Changeset 3080527 in sasview for sansmodels/src/sans/models/BaseComponent.py

Timestamp:

Mar 12, 2010 1:08:42 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:

e575db9

Parents:

7e99f5c

Message:

changed classtemplate for 2d evaluation from matrix form to 1d array form

File:

• sansmodels/src/sans/models/BaseComponent.py (modified) (3 diffs)

sansmodels/src/sans/models/BaseComponent.py

@@ -68 +68 @@
             
             
-            * For 2D, a list of numpy arrays are expected: [qx_prime,qy_prime].
-            
-            For the following matrix of q_values [qx,qy], we will have:
-                      +--------+--------+--------+
-            qy[2]     |        |        |        | 
-                      +--------+--------+--------+
-            qy[1]     |        |        |        |
-                      +--------+--------+--------+            
-            qy[0]     |        |        |        | 
-                      +--------+--------+--------+
-                        qx[0]    qx[1]    qx[2]
-
-
-            The q-values must be stored in numpy arrays.
-            The qxprime and qyprime are 2D arrays. From the two lists of q-values 
-            above, numpy arrays must be created the following way:
-
-            qx_prime = numpy.reshape(qx, [1,3])
-            qy_prime = numpy.reshape(qy, [3,1])
+            * For 2D, a list of numpy arrays are expected: [qx_prime,qy_prime],
+            where 1D arrays,
+            
+            qx_prime = [ qx[0], qx[1], qx[2], ....]
+            and
+            qy_prime = [ qy[0], qy[1], qy[2], ....] 
             
             The method is then called the following way:
@@ -92 +79 @@
             evalDistribution([qx_prime, qy_prime])
             
-            @param qdist: ndarray of scalar q-values or list [qx,qy] where qx,qy are 2D ndarrays 
+            @param qdist: ndarray of scalar q-values or list [qx,qy] where qx,qy are 1D ndarrays 
         """
         if qdist.__class__.__name__ == 'list':
@@ -106 +93 @@
             
             # Create output array
-            iq_array = numpy.zeros([qx.shape[1], qy.shape[0]])
-             
-            for j in range(qy.shape[0]):
-                for i in range(qx.shape[1]):
-                    iq_array[j][i] = self.runXY([qx[0][i],qy[j][0]])
+            iq_array = numpy.zeros((len(qx)))
+            
+            for i in range(len(qx)):
+                    iq_array[i] = self.runXY([qx[i],qy[i]])
             return iq_array