julia> versioninfo()
Julia Version 0.6.2
Commit d386e40c17* (2017-12-13 18:08 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: AMD Ryzen 7 1800X Eight-Core Processor
WORD_SIZE: 64
BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Barcelona)
LAPACK: libopenblas64_
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A ratio greater than 1.0
denotes a possible regression (marked with ❌), while a ratio less
than 1.0
denotes a possible improvement (marked with ✅). Only significant results - results
that indicate possible regressions or improvements - are shown below (thus, an empty table means that all
benchmark results remained invariant between builds).
ID | time ratio | memory ratio |
---|---|---|
["inrange", "NearestNeighbors.KDTree 3 × 1000, ls = 1, input_size = 1000, r = 1.91e-01"] |
0.92 (5%) ✅ | 1.00 (1%) |
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#include <iostream> | |
#include <fcl/shape/geometric_shapes.h> | |
#include <fcl/collision.h> | |
#include <fcl/continuous_collision.h> | |
#include <fcl/ccd/motion.h> | |
using namespace std; | |
using namespace fcl; | |
int main(int argc, char** argv) |
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_ | |
_ _ _(_)_ | A fresh approach to technical computing | |
(_) | (_) (_) | Documentation: http://docs.julialang.org | |
_ _ _| |_ __ _ | Type "?help" for help. | |
| | | | | | |/ _` | | | |
| | |_| | | | (_| | | Version 0.4.6-pre+7 (2016-03-28 14:46 UTC) | |
_/ |\__'_|_|_|\__'_| | Commit 273b487* (0 days old release-0.4) | |
|__/ | x86_64-linux-gnu | |
julia> Pkg.build("Cxx") |
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With SecureCRT closed, edit your Global.ini which lives by default in %appdata%\VanDyke\Config\Global.ini, | |
find the three lines the start with B:"ANSI Color RGB" and replace it and the two lines of hex below it with: | |
B:"ANSI Color RGB"=00000040 | |
00 2b 38 00 dc 32 2f 00 85 99 00 00 b5 89 00 00 26 8b d2 00 d3 36 82 00 2a a1 98 00 ee e8 d5 00 | |
07 36 42 00 cb 4b 16 00 58 6e 75 00 65 7b 83 00 83 94 96 00 6c 71 c4 00 93 a1 a1 00 fd f6 e3 00 | |
(from https://web.archive.org/web/20140117045940/http://jessicalitwin.com/index.php/2013/02/solarized-for-securecrt/) |
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cummean(x) = cumsum(x) ./ [1:length(x)] | |
cumvar(x, m = cummean(x)) = cumsum((1 - 1 ./ [1:length(x)]).*(x - [0, m[1:end-1]]).^2) ./ [1:length(x)] | |
cumcov(x, y, mx = cummean(x), my = cummean(y)) = cumsum((1 - 1 ./ [1:length(x)]).*(x - [0, mx[1:end-1]]).*(y - [0, my[1:end-1]])) ./ [1:length(x)] |