Added Range assumption to Kronecker Delta #17433
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Update The release notes on the wiki have been updated. |
| assert expr[i, j].diff(A[m, n]).doit() == ( | ||
| KDelta(i, m)*KDelta(j, n)*Trace(A) + | ||
| KDelta(m, n)*A[i, j] | ||
| ) |
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need to cross-check this result
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@asmeurer We have a new algorithm for matrix derivatives... and it was a lot easier to implement than the previous one. |
Codecov Report
@@ Coverage Diff @@
## master #17433 +/- ##
============================================
+ Coverage 60.18% 61.958% +1.778%
============================================
Files 631 631
Lines 163497 163526 +29
Branches 38362 38375 +13
============================================
+ Hits 98393 101319 +2926
+ Misses 59050 56466 -2584
+ Partials 6054 5741 -313 |
| @@ -137,26 +144,34 @@ def test_matrix_derivative_vectors_and_scalars(): | |||
| # Cookbook example 83: | |||
| expr = (X*b + c).T*D*(X*b + c) | |||
| assert expr.diff(X) == D*(X*b + c)*b.T + D.T*(X*b + c)*b.T | |||
| assert expr[0, 0].diff(X[m, n]).doit() | |||
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Is there something missing from this assert?
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Yes, there is a problem with the simplification of the Kronecker delta... the expression is not optimal. I will try to fix this.
Added Range assumption to Kronecker Delta
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