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CasADi currently supports derivative calculation by propagating derivatives numerically through the algorithm (operator overloading approach) or symbolically (source code transformation approach).
Th…
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I'd like to propose using source code transformation instead of operator overloading. Operator overloading is slow in general and not really optimized in Julia; the compiler doesn't seem to optimize a…
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```
For the above expression, factor is working too hard (in polys8) to get the
answer (1+x)**200. This should barely take more time than to simply factor
the base. Perhaps this is because factor is v…
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```
chjofer2@CH-L-0073657 ~/acado_git/build
$ make test
Running tests...
Test project /home/chjofer2/acado_git/build
Start 1: basic_data_structures_curve_getting_started_test
1/108 Test …
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```
>>> import sympy
>>> x=sympy.var('x')
Zero is sometimes wrongly reported as a solution.
>>> sympy.solve(-(1 + x)/(2 + x)**2 + 1/(2 + x), x)
[0]
There is a corresponding "TODO" in the source cod…
wxgeo updated
10 years ago
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Hi all,
I have a symbolic function P(X) of the type 'MX'. I want to calculate the jacobian and only need the 4th element.
The problem is I need to reduce memory usage, and it seems that when you refe…
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I'm a little worried by the duplication of so many distributions in this codebase. Julia should have exactly one implementation of all distributions. If something's wrong with how Distributions.jl is …
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This is a question about a feature; excuse my lack of knowledge in case the feature exists and I am not aware of it (tried to google it first). Is it possible to perform symbolic computations in Julia…
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*Issue migrated from trac ticket # 1746*
**milestone:** HeuristicLab 3.3.x Backlog | **component:** Problems.DataAnalysis.Symbolic | **priority:** medium | **resolution:** obsolete
#### 2012-01-09 1…
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For those interested, these are the current timings for the likelihoods I've rewritten for numexpr.
The gist seems to be that at small sizes, numexpr is much slower. At larger sizes it is comparable …