r24192 - /branches/disp_spin_speed/lib/linear_algebra/matrix_exponential.py -- June 20, 2014 - 09:38

Author: tlinnet
Date: Fri Jun 20 09:38:33 2014
New Revision: 24192

URL: http://svn.gna.org/viewcvs/relax?rev=24192&view=rev
Log:
Made the function matrix_exponential_rankN also find the exponential if the 
experiments indices are missing.

Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion 
models for Clustered analysis.

Modified:
    branches/disp_spin_speed/lib/linear_algebra/matrix_exponential.py

Modified: branches/disp_spin_speed/lib/linear_algebra/matrix_exponential.py
URL: 
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/linear_algebra/matrix_exponential.py?rev=24192&r1=24191&r2=24192&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/linear_algebra/matrix_exponential.py   
(original)
+++ branches/disp_spin_speed/lib/linear_algebra/matrix_exponential.py   Fri 
Jun 20 09:38:33 2014
@@ -68,7 +68,13 @@
     @rtype:     numpy float array of rank [NE][NS][NM][NO][ND][X][X]
     """
 
-    NE, NS, NM, NO, ND, Row, Col = A.shape
+    # Set initial to None.
+    NE, NS, NM, NO, ND, Row, Col = None, None, None, None, None, None, None
+
+    if len(A.shape) == 7:
+        NE, NS, NM, NO, ND, Row, Col = A.shape
+    elif len(A.shape) == 6:
+        NS, NM, NO, ND, Row, Col = A.shape
 
     # Is the original matrix real?
     complex_flag = any(iscomplex(A))
@@ -84,10 +90,16 @@
 
     # Calculate the exponential of all elements in the input array. Shape 
[NE][NS][NM][NO][ND][X]
     # Add one axis, to allow for broadcasting multiplication.
-    W_exp = exp(W).reshape(NE, NS, NM, NO, ND, Row, 1)
+    if NE == None:
+        W_exp = exp(W).reshape(NS, NM, NO, ND, Row, 1)
+    else:
+        W_exp = exp(W).reshape(NE, NS, NM, NO, ND, Row, 1)
 
     # Make a eye matrix, with Shape [NE][NS][NM][NO][ND][X][X]
-    eye_mat = tile(eye(Row)[newaxis, newaxis, newaxis, newaxis, newaxis, 
...], (NE, NS, NM, NO, ND, 1, 1) )
+    if NE == None:
+        eye_mat = tile(eye(Row)[newaxis, newaxis, newaxis, newaxis, newaxis, 
...], (NS, NM, NO, ND, 1, 1) )
+    else:
+        eye_mat = tile(eye(Row)[newaxis, newaxis, newaxis, newaxis, newaxis, 
...], (NE, NS, NM, NO, ND, 1, 1) )
 
     # Transform it to a diagonal matrix, with elements from vector down the 
diagonal.
     W_exp_diag = multiply(W_exp, eye_mat )