*** empty log message ***

[ginac.git] / ginac / tensor.cpp

diff --git a/ginac/tensor.cpp b/ginac/tensor.cpp
index af085ece2ccb1bdef1c1361d7f058839c83f1d4c..48393665ad5fc0555add8a19bba463af14abf288 100644 (file)
--- a/ginac/tensor.cpp
+++ b/ginac/tensor.cpp
@@ -3,7 +3,7 @@
  *  Implementation of GiNaC's special tensors. */
 
 /*
- *  GiNaC Copyright (C) 1999-2002 Johannes Gutenberg University Mainz, Germany
+ *  GiNaC Copyright (C) 1999-2003 Johannes Gutenberg University Mainz, Germany
  *
  *  This program is free software; you can redistribute it and/or modify
  *  it under the terms of the GNU General Public License as published by
@@ -179,6 +179,13 @@ ex tensdelta::eval_indexed(const basic & i) const
        const idx & i1 = ex_to<idx>(i.op(1));
        const idx & i2 = ex_to<idx>(i.op(2));
 
+       // The dimension of the indices must be equal, otherwise we use the minimal
+       // dimension
+       if (!i1.get_dim().is_equal(i2.get_dim())) {
+               ex min_dim = i1.minimal_dim(i2);
+               return i.subs(lst(i1 == i1.replace_dim(min_dim), i2 == i2.replace_dim(min_dim)));
+       }
+
        // Trace of delta tensor is the (effective) dimension of the space
        if (is_dummy_pair(i1, i2)) {
                try {
@@ -492,11 +499,10 @@ bool tensepsilon::contract_with(exvector::iterator self, exvector::iterator othe
        if (is_ex_exactly_of_type(other->op(0), tensepsilon) && num+1 == other->nops()) {
 
                // Contraction of two epsilon tensors is a determinant
-               ex dim = ex_to<idx>(self->op(1)).get_dim();
                bool variance = is_a<varidx>(self->op(1));
                matrix M(num, num);
-               for (int i=0; i<num; i++) {
-                       for (int j=0; j<num; j++) {
+               for (unsigned i=0; i<num; i++) {
+                       for (unsigned j=0; j<num; j++) {
                                if (minkowski)
                                        M(i, j) = lorentz_g(self->op(i+1), other->op(j+1), pos_sig);
                                else if (variance)