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License: MIT License
The docs suggest you can use Dsp::SmoothedFilterDesign
instead of Dsp::FilterDesign
. It isn't clear if this work is on the master branch of the lib though.
This crash occurred after adding the "chilis" image to the overview patcher. Not sure if it is specific to 4-plane char bandstop in the cheby1 or not...
Thread 0 Crashed:: CrBrowserMain Dispatch queue: com.apple.main-thread
0 libsystem_kernel.dylib 0x00007fff9778fd42 __pthread_kill + 10
1 libsystem_pthread.dylib 0x00007fff9787d5bf pthread_kill + 90
2 libsystem_c.dylib 0x00007fff976f5420 abort + 129
3 libsystem_c.dylib 0x00007fff976bc893 __assert_rtn + 320
4 com.cycling74.jit-filter-chebyshev1 0x0000000118eaf0da Dsp::BandStopTransform::BandStopTransform(double, double, Dsp::LayoutBase&, Dsp::LayoutBase const&) + 2378 (PoleFilter.cpp:290)
5 com.cycling74.jit-filter-chebyshev1 0x0000000118eafde9 Dsp::BandStopTransform::BandStopTransform(double, double, Dsp::LayoutBase&, Dsp::LayoutBase const&) + 57 (PoleFilter.cpp:311)
6 com.cycling74.jit-filter-chebyshev1 0x0000000118ea1855 Dsp::ChebyshevI::BandStopBase::setup(int, double, double, double, double) + 117 (ChebyshevI.cpp:218)
7 com.cycling74.jit-filter-chebyshev1 0x0000000118ed587e Dsp::ChebyshevI::Design::TypeII<Dsp::ChebyshevI::BandStop<24> >::setParams(Dsp::Params const&) + 158 (ChebyshevI.h:267)
8 com.cycling74.jit-filter-chebyshev1 0x0000000118ed53bc Dsp::FilterDesignBase<Dsp::ChebyshevI::Design::BandStop<24> >::doSetParams(Dsp::Params const&) + 44 (Filter.h:186)
9 com.cycling74.jit-filter-chebyshev1 0x0000000118ed0b06 Dsp::Filter::setParams(Dsp::Params const&) + 70 (Filter.h:96)
10 com.cycling74.jit-filter-chebyshev1 0x0000000118ecd77f std::__1::enable_if<true, void>::type filter_mop<jit_chebyshev1, true, true>::do_update<true>() + 879 (filter.h:330)
11 com.cycling74.jit-filter-chebyshev1 0x0000000118ecd370 filter_mop<jit_chebyshev1, true, true>::'lambda'(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&)::operator()(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&) const + 48 (filter.h:199)
12 com.cycling74.jit-filter-chebyshev1 0x0000000118ecd334 std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > std::__1::__invoke_void_return_wrapper<std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > >::__call<filter_mop<jit_chebyshev1, true, true>::'lambda'(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&)&, std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&>(filter_mop<jit_chebyshev1, true, true>::'lambda'(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&)&&&, std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&&&) + 84 (__functional_base:437)
13 com.cycling74.jit-filter-chebyshev1 0x0000000118ecd1d0 std::__1::__function::__func<filter_mop<jit_chebyshev1, true, true>::'lambda'(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&), std::__1::allocator<filter_mop<jit_chebyshev1, true, true>::'lambda'(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&)>, std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > (std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&)>::operator()(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&) + 64 (functional:1437)
14 com.cycling74.jit-filter-chebyshev1 0x0000000118eb9af4 std::__1::function<std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > (std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&)>::operator()(std::__1::vector<c74::min::atom, std::__1::allocator<c74::min::atom> > const&) const + 180 (functional:1817)
15 com.cycling74.jit-filter-chebyshev1 0x0000000118eb41cc c74::min::queue::qfn() + 172 (c74_min_queue.h:92)
16 com.cycling74.jit-filter-chebyshev1 0x0000000118eb4115 queue_qfn_callback + 21 (c74_min_impl.h:55)
Coefficient caching/hashing a la memoization might be a cool thing to explore but probably wait for user complaints and profiling stats before putting too much effort into optimizations.
The concern is that in multichannel versions the amount of time to compute the coefficients for N channels will O(N) whereas it could be close to O(1) with some kind of memoization.
Currently we are doing forward (left-to-right) filtering of each vector (line) of the matrix. We can break this into two attributes:
1. Direction
2. Axis
To implement this for a cell operator I'm currently thinking that we add some infrastructure to Min that allow the matrix traversal to have the above options. Then this technology is available to all authors of objects using the Min API.
We could also offer a "direction" called "temporal" or something like that for these filter objects. Then the object would need a separate filter for each cell of the matrix. Sort of like a poly~ mode or something. That might get a bit unwieldy though? Certainly it can wait until the other stuff is handled.
especially for the order
parameter -- see Cycling74/min-api#29
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