Comments (9)
A simple grid is perfectly uniform. The purpose of Sobol sequences is to sample uniformly while lessening the curse of dimensionality. However, in HCubature we inevitably have the curse of dimensionality anyway, and we can only handle box subdomains.
(For a smooth function in low dimensions, HCubature should be much more efficient than any Monte–Carlo method.)
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OK, I can confirm that, at least for me, it works! Thanks a lot!!!
from hcubature.jl.
Any ideas on what I can do?
Do you need to use this package or other packages are fine?
from hcubature.jl.
anything that works will be fine!
from hcubature.jl.
The divonne
function in Cuba.jl has a peakfinder
option to increase sampling around the given points. This is really useful when you have a function that is non-zero in very small regions and you know the position of those regions.
Honestly I've never used this feature in the julia interface but did use in the past directly with the C library, in these cases it's incredibly useful. Probably I can help you to do this in Cuba.jl as well.
Edit: probably the xgiven option should be sufficient, which is definitely easier to use
from hcubature.jl.
Great! I'll give it a solid try after lunch :)
from hcubature.jl.
Hmmm, seg fault:
julia> result = divonne((x, f) -> f = getsignal(x), 2, 1, nextra = 100)
signal (11): Segmentation fault
in expression starting at no file:0
unknown function (ip: 0xffffffffffffffff)
Iterate at /home/yakir/.julia/packages/Cuba/6hxNB/deps/usr/lib/libcuba.so (unknown line)
Integrate at /home/yakir/.julia/packages/Cuba/6hxNB/deps/usr/lib/libcuba.so (unknown line)
llDivonne at /home/yakir/.julia/packages/Cuba/6hxNB/deps/usr/lib/libcuba.so (unknown line)
dointegrate! at /home/yakir/.julia/packages/Cuba/6hxNB/src/divonne.jl:52 [inlined]
dointegrate at /home/yakir/.julia/packages/Cuba/6hxNB/src/Cuba.jl:185 [inlined]
#divonne#2 at /home/yakir/.julia/packages/Cuba/6hxNB/src/divonne.jl:145
#divonne at ./none:0
unknown function (ip: 0x7f3051f69193)
jl_fptr_trampoline at /usr/bin/../lib/libjulia.so.1 (unknown line)
jl_apply_generic at /usr/bin/../lib/libjulia.so.1 (unknown line)
unknown function (ip: 0x7f3070e53ab7)
unknown function (ip: 0x7f3070e53860)
unknown function (ip: 0x7f3070e54828)
unknown function (ip: 0x7f3070e54f04)
unknown function (ip: 0xfffffffffffffffe)
unknown function (ip: 0x7f304a9c109f)
unknown function (ip: 0xb)
unknown function (ip: 0x7f3070e553cc)
unknown function (ip: 0x7f306f87206c)
jl_toplevel_eval_in at /usr/bin/../lib/libjulia.so.1 (unknown line)
unknown function (ip: 0x7f306691c161)
jl_apply_generic at /usr/bin/../lib/libjulia.so.1 (unknown line)
unknown function (ip: 0x7f3066a8d6ba)
unknown function (ip: 0x7f3066a8d92b)
jl_apply_generic at /usr/bin/../lib/libjulia.so.1 (unknown line)
unknown function (ip: 0x7f306f858d8d)
unknown function (ip: 0xffffffffffffffff)
Allocations: 45132449 (Pool: 45126241; Big: 6208); GC: 91
Segmentation fault (core dumped)
from hcubature.jl.
I added an initdiv
keyword option that should address this: it allows you to force the function to be sampled on a finer grid initially. e.g. try checking out the master branch and passing initdiv=10
.
from hcubature.jl.
Doing it now. Exciting! Thank you. Alternatively, you could use your Sobol to improve from a simple grid to a more uniform sampling.
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Related Issues (20)
- Check for NaN?
- Promotion of endpoints to a common type? HOT 4
- Internal error got on Julia1.2.0
- Error estimation HOT 2
- Bounds order while using hquadrature HOT 4
- Incorrect and variable results for smooth function depending on initdiv HOT 1
- Parallel integrand evaluation [Feature Req.] HOT 2
- Inconsistent results for Inf integrands HOT 3
- slow hcubature for large vector-valued integrands HOT 7
- TagBot trigger issue HOT 29
- Type instability when using a vector for the limits. HOT 1
- Mimic `Cubature.INDIVIDUAL` behavior [Feature Req.] HOT 6
- Question about 2D integral with a complex function f HOT 6
- A question regarding nodes and weights in hcubature HOT 1
- Any plans to add Symbolics.jl inside HCubature.jl? HOT 1
- Performance versus `quadgk` HOT 1
- hcubature not type stable HOT 2
- GPU support HOT 2
- Errors with BigFloat boundaries HOT 6
- Tagging is misconfigured?
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