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comparison test/test_diag_perm.m @ 8965:42aff15e059b

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Implement diag \ sparse and sparse / diag. Not pretty, but somewhat efficient and preserves sparsity.
author Jason Riedy <jason@acm.org>
date Mon, 09 Mar 2009 17:49:14 -0400
parents f4f4d65faaa0
children 1bba53c0a38d
comparison
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8964:f4f4d65faaa0 8965:42aff15e059b
155 %! A = rand (n); 155 %! A = rand (n);
156 %! A(n, n-2) = NaN; 156 %! A(n, n-2) = NaN;
157 %! A(4, 1) = Inf; 157 %! A(4, 1) = Inf;
158 %! assert (Dr * A * Dc, A .* kron (dr, dc), eps); 158 %! assert (Dr * A * Dc, A .* kron (dr, dc), eps);
159 159
160 ## sparse inverse row scaling with a zero factor
161 %!test
162 %! n = 8;
163 %! A = sprand (n, n, .5);
164 %! scalefact = rand (n, 1);
165 %! Dr = diag (scalefact);
166 %! scalefact(n-1) = Inf;
167 %! Dr(n-1, n-1) = 0;
168 %! assert (full (Dr \ A), full (A) ./ repmat (scalefact, 1, n));
169
170 ## narrow sparse inverse row scaling
171 %!test
172 %! n = 8;
173 %! A = sprand (n, n, .5);
174 %! scalefact = rand (n-2, 1);
175 %! Dr = diag (scalefact, n, n-2);
176 %! assert (full (Dr \ A), Dr \ full(A))
177
178 ## sparse inverse column scaling with a zero factor
179 %!test
180 %! n = 11;
181 %! A = sprand (n, n, .5);
182 %! scalefact = rand (1, n);
183 %! Dc = diag (scalefact);
184 %! scalefact(n-1) = Inf;
185 %! Dc(n-1, n-1) = 0;
186 %! assert (full (A / Dc), full(A) / Dc)
187
188 ## short sparse inverse column scaling
189 %!test
190 %! n = 7;
191 %! A = sprand (n, n, .5);
192 %! scalefact = rand (1, n-2) + I () * rand(1, n-2);
193 %! Dc = diag (scalefact, n-2, n);
194 %! assert (full (A / Dc), full(A) / Dc)