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ferrolho/[SpanningTreeCoverage.jl] Notebooks

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[SpanningTreeCoverage.jl] Notebooks
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[SpanningTreeCoverage.jl] Notebooks
[SpanningTreeCoverage.jl] Notebooks
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benchmarks.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "dfbaa5c7-3961-48d4-b098-dbf57e9f4c14",
"metadata": {},
"outputs": [],
"source": [
"using BenchmarkTools\n",
"using SpanningTreeCoverage"
]
},
{
"cell_type": "markdown",
"id": "2ffb7b30-52f7-4ce8-b801-ea2ac2114e16",
"metadata": {},
"source": [
"Select _area_ to be used for the benchmark:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "dc0aea91-4c0f-4b24-9900-a2bc7488167b",
"metadata": {},
"outputs": [],
"source": [
"area = read_area(\"pillars\");"
]
},
{
"cell_type": "markdown",
"id": "1bf6d2dc-7b25-475f-841f-0bd8e8f4a28c",
"metadata": {},
"source": [
"Benchmark the method `solve`, which solves the whole the single-robot Coverage Path Planning (CPP) problem:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "ef5c008c-524e-42ae-98b2-4d493c801f2c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"BenchmarkTools.Trial: 945 samples with 1 evaluation.\n",
" Range \u001b[90m(\u001b[39m\u001b[36m\u001b[1mmin\u001b[22m\u001b[39m … \u001b[35mmax\u001b[39m\u001b[90m): \u001b[39m\u001b[36m\u001b[1m4.875 ms\u001b[22m\u001b[39m … \u001b[35m 7.032 ms\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmin … max\u001b[90m): \u001b[39m0.00% … 0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[34m\u001b[1mmedian\u001b[22m\u001b[39m\u001b[90m): \u001b[39m\u001b[34m\u001b[1m5.150 ms \u001b[22m\u001b[39m\u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmedian\u001b[90m): \u001b[39m0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[32m\u001b[1mmean\u001b[22m\u001b[39m ± \u001b[32mσ\u001b[39m\u001b[90m): \u001b[39m\u001b[32m\u001b[1m5.152 ms\u001b[22m\u001b[39m ± \u001b[32m154.687 μs\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmean ± σ\u001b[90m): \u001b[39m0.00% ± 0.00%\n",
"\n",
" \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m█\u001b[34m▅\u001b[39m\u001b[39m▃\u001b[39m▄\u001b[39m▅\u001b[39m▄\u001b[39m▃\u001b[39m▂\u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \n",
" \u001b[39m▂\u001b[39m▃\u001b[39m▃\u001b[39m▄\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▅\u001b[39m▅\u001b[39m▇\u001b[39m▆\u001b[39m▄\u001b[39m▆\u001b[39m▆\u001b[39m▇\u001b[39m▅\u001b[39m▆\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[34m█\u001b[39m\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m▇\u001b[39m▇\u001b[39m▆\u001b[39m█\u001b[39m▄\u001b[39m▄\u001b[39m▃\u001b[39m▃\u001b[39m▄\u001b[39m▃\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▃\u001b[39m▂\u001b[39m▂\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▂\u001b[39m▂\u001b[39m \u001b[39m▄\n",
" 4.87 ms\u001b[90m Histogram: frequency by time\u001b[39m 5.5 ms \u001b[0m\u001b[1m<\u001b[22m\n",
"\n",
" Memory estimate\u001b[90m: \u001b[39m\u001b[33m3.37 MiB\u001b[39m, allocs estimate\u001b[90m: \u001b[39m\u001b[33m9222\u001b[39m."
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"@benchmark solve($area)"
]
},
{
"cell_type": "markdown",
"id": "a3e79993-710d-4d9a-a358-bf6124f4b0ed",
"metadata": {},
"source": [
"---"
]
},
{
"cell_type": "markdown",
"id": "b81a43f7-d8c4-4c86-bf5e-1449aa373d11",
"metadata": {},
"source": [
"Benchmarks of the individual methods called by `solve` are shown below."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "4befa120-5310-47e9-b381-d38d487a5250",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"BenchmarkTools.Trial: 10000 samples with 1 evaluation.\n",
" Range \u001b[90m(\u001b[39m\u001b[36m\u001b[1mmin\u001b[22m\u001b[39m … \u001b[35mmax\u001b[39m\u001b[90m): \u001b[39m\u001b[36m\u001b[1m11.910 μs\u001b[22m\u001b[39m … \u001b[35m 1.547 ms\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmin … max\u001b[90m): \u001b[39m0.00% … 97.18%\n",
" Time \u001b[90m(\u001b[39m\u001b[34m\u001b[1mmedian\u001b[22m\u001b[39m\u001b[90m): \u001b[39m\u001b[34m\u001b[1m13.394 μs \u001b[22m\u001b[39m\u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmedian\u001b[90m): \u001b[39m0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[32m\u001b[1mmean\u001b[22m\u001b[39m ± \u001b[32mσ\u001b[39m\u001b[90m): \u001b[39m\u001b[32m\u001b[1m15.017 μs\u001b[22m\u001b[39m ± \u001b[32m42.296 μs\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmean ± σ\u001b[90m): \u001b[39m7.81% ± 2.75%\n",
"\n",
" \u001b[39m▂\u001b[39m▄\u001b[39m▅\u001b[39m▅\u001b[39m▇\u001b[39m█\u001b[34m█\u001b[39m\u001b[39m▇\u001b[39m▅\u001b[39m▃\u001b[39m▂\u001b[39m \u001b[32m \u001b[39m\u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m▂\n",
" \u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[34m█\u001b[39m\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[32m█\u001b[39m\u001b[39m▇\u001b[39m▆\u001b[39m▇\u001b[39m▆\u001b[39m▃\u001b[39m▄\u001b[39m▃\u001b[39m▅\u001b[39m▄\u001b[39m▃\u001b[39m▃\u001b[39m▄\u001b[39m▃\u001b[39m▁\u001b[39m▃\u001b[39m▃\u001b[39m▅\u001b[39m▅\u001b[39m▇\u001b[39m▇\u001b[39m█\u001b[39m▇\u001b[39m█\u001b[39m▇\u001b[39m▇\u001b[39m▇\u001b[39m▇\u001b[39m▆\u001b[39m▆\u001b[39m▆\u001b[39m▅\u001b[39m▁\u001b[39m▁\u001b[39m▃\u001b[39m▁\u001b[39m▃\u001b[39m▁\u001b[39m▄\u001b[39m▅\u001b[39m▄\u001b[39m▅\u001b[39m▅\u001b[39m▅\u001b[39m▆\u001b[39m▇\u001b[39m▇\u001b[39m \u001b[39m█\n",
" 11.9 μs\u001b[90m \u001b[39m\u001b[90mHistogram: \u001b[39m\u001b[90m\u001b[1mlog(\u001b[22m\u001b[39m\u001b[90mfrequency\u001b[39m\u001b[90m\u001b[1m)\u001b[22m\u001b[39m\u001b[90m by time\u001b[39m 26.6 μs \u001b[0m\u001b[1m<\u001b[22m\n",
"\n",
" Memory estimate\u001b[90m: \u001b[39m\u001b[33m38.66 KiB\u001b[39m, allocs estimate\u001b[90m: \u001b[39m\u001b[33m14\u001b[39m."
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"new_area = subdivide_area(area)\n",
"@benchmark subdivide_area($area)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c8bcceb9-ba59-4a7e-aeb5-94e7e29ae4dc",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"BenchmarkTools.Trial: 10000 samples with 8 evaluations.\n",
" Range \u001b[90m(\u001b[39m\u001b[36m\u001b[1mmin\u001b[22m\u001b[39m … \u001b[35mmax\u001b[39m\u001b[90m): \u001b[39m\u001b[36m\u001b[1m3.603 μs\u001b[22m\u001b[39m … \u001b[35m125.653 μs\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmin … max\u001b[90m): \u001b[39m0.00% … 92.73%\n",
" Time \u001b[90m(\u001b[39m\u001b[34m\u001b[1mmedian\u001b[22m\u001b[39m\u001b[90m): \u001b[39m\u001b[34m\u001b[1m3.968 μs \u001b[22m\u001b[39m\u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmedian\u001b[90m): \u001b[39m0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[32m\u001b[1mmean\u001b[22m\u001b[39m ± \u001b[32mσ\u001b[39m\u001b[90m): \u001b[39m\u001b[32m\u001b[1m4.383 μs\u001b[22m\u001b[39m ± \u001b[32m 5.570 μs\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmean ± σ\u001b[90m): \u001b[39m7.06% ± 5.38%\n",
"\n",
" \u001b[39m▁\u001b[39m▄\u001b[39m▆\u001b[39m█\u001b[34m█\u001b[39m\u001b[39m▄\u001b[39m▂\u001b[39m \u001b[32m \u001b[39m\u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m▂\n",
" \u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[34m█\u001b[39m\u001b[39m█\u001b[39m█\u001b[39m█\u001b[32m█\u001b[39m\u001b[39m▆\u001b[39m▃\u001b[39m▅\u001b[39m▁\u001b[39m▃\u001b[39m▃\u001b[39m▄\u001b[39m▁\u001b[39m▄\u001b[39m▆\u001b[39m▆\u001b[39m▇\u001b[39m█\u001b[39m█\u001b[39m▇\u001b[39m▆\u001b[39m▆\u001b[39m▆\u001b[39m▁\u001b[39m▁\u001b[39m▃\u001b[39m▄\u001b[39m▁\u001b[39m▄\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▄\u001b[39m▄\u001b[39m▄\u001b[39m▅\u001b[39m▅\u001b[39m▇\u001b[39m▅\u001b[39m▆\u001b[39m▅\u001b[39m▄\u001b[39m▃\u001b[39m▄\u001b[39m▃\u001b[39m▃\u001b[39m▄\u001b[39m▄\u001b[39m▄\u001b[39m▅\u001b[39m▄\u001b[39m▆\u001b[39m▆\u001b[39m \u001b[39m█\n",
" 3.6 μs\u001b[90m \u001b[39m\u001b[90mHistogram: \u001b[39m\u001b[90m\u001b[1mlog(\u001b[22m\u001b[39m\u001b[90mfrequency\u001b[39m\u001b[90m\u001b[1m)\u001b[22m\u001b[39m\u001b[90m by time\u001b[39m 9.15 μs \u001b[0m\u001b[1m<\u001b[22m\n",
"\n",
" Memory estimate\u001b[90m: \u001b[39m\u001b[33m21.77 KiB\u001b[39m, allocs estimate\u001b[90m: \u001b[39m\u001b[33m7\u001b[39m."
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"obstacle_nodes = calculate_obstacle_nodes(area)\n",
"@benchmark calculate_obstacle_nodes($area)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "c5d90f16-8ad3-4c09-88ce-b73e50df985e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"BenchmarkTools.Trial: 7033 samples with 1 evaluation.\n",
" Range \u001b[90m(\u001b[39m\u001b[36m\u001b[1mmin\u001b[22m\u001b[39m … \u001b[35mmax\u001b[39m\u001b[90m): \u001b[39m\u001b[36m\u001b[1m531.963 μs\u001b[22m\u001b[39m … \u001b[35m 6.043 ms\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmin … max\u001b[90m): \u001b[39m 0.00% … 83.91%\n",
" Time \u001b[90m(\u001b[39m\u001b[34m\u001b[1mmedian\u001b[22m\u001b[39m\u001b[90m): \u001b[39m\u001b[34m\u001b[1m599.780 μs \u001b[22m\u001b[39m\u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmedian\u001b[90m): \u001b[39m 0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[32m\u001b[1mmean\u001b[22m\u001b[39m ± \u001b[32mσ\u001b[39m\u001b[90m): \u001b[39m\u001b[32m\u001b[1m708.606 μs\u001b[22m\u001b[39m ± \u001b[32m564.115 μs\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmean ± σ\u001b[90m): \u001b[39m12.11% ± 12.86%\n",
"\n",
" \u001b[39m█\u001b[34m█\u001b[39m\u001b[39m▆\u001b[32m▄\u001b[39m\u001b[39m▂\u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m▁\n",
" \u001b[39m█\u001b[34m█\u001b[39m\u001b[39m█\u001b[32m█\u001b[39m\u001b[39m█\u001b[39m▆\u001b[39m▅\u001b[39m▄\u001b[39m▆\u001b[39m█\u001b[39m▅\u001b[39m▆\u001b[39m▃\u001b[39m▄\u001b[39m▁\u001b[39m▃\u001b[39m▃\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▄\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▆\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m \u001b[39m█\n",
" 532 μs\u001b[90m \u001b[39m\u001b[90mHistogram: \u001b[39m\u001b[90m\u001b[1mlog(\u001b[22m\u001b[39m\u001b[90mfrequency\u001b[39m\u001b[90m\u001b[1m)\u001b[22m\u001b[39m\u001b[90m by time\u001b[39m 4.27 ms \u001b[0m\u001b[1m<\u001b[22m\n",
"\n",
" Memory estimate\u001b[90m: \u001b[39m\u001b[33m1.15 MiB\u001b[39m, allocs estimate\u001b[90m: \u001b[39m\u001b[33m9143\u001b[39m."
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"mst = calculate_mst(size(area), obstacle_nodes)\n",
"@benchmark calculate_mst($size(area), $obstacle_nodes)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "4a640bd3-c1c7-4e69-90bc-02b0905358c7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"BenchmarkTools.Trial: 1477 samples with 1 evaluation.\n",
" Range \u001b[90m(\u001b[39m\u001b[36m\u001b[1mmin\u001b[22m\u001b[39m … \u001b[35mmax\u001b[39m\u001b[90m): \u001b[39m\u001b[36m\u001b[1m3.183 ms\u001b[22m\u001b[39m … \u001b[35m 5.797 ms\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmin … max\u001b[90m): \u001b[39m0.00% … 39.17%\n",
" Time \u001b[90m(\u001b[39m\u001b[34m\u001b[1mmedian\u001b[22m\u001b[39m\u001b[90m): \u001b[39m\u001b[34m\u001b[1m3.340 ms \u001b[22m\u001b[39m\u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmedian\u001b[90m): \u001b[39m0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[32m\u001b[1mmean\u001b[22m\u001b[39m ± \u001b[32mσ\u001b[39m\u001b[90m): \u001b[39m\u001b[32m\u001b[1m3.384 ms\u001b[22m\u001b[39m ± \u001b[32m210.870 μs\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmean ± σ\u001b[90m): \u001b[39m0.71% ± 3.35%\n",
"\n",
" \u001b[39m \u001b[39m \u001b[39m█\u001b[39m▅\u001b[39m▇\u001b[39m▃\u001b[39m▂\u001b[39m▃\u001b[39m▆\u001b[34m▆\u001b[39m\u001b[39m▆\u001b[32m▃\u001b[39m\u001b[39m▂\u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \n",
" \u001b[39m▃\u001b[39m▃\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[39m█\u001b[34m█\u001b[39m\u001b[39m█\u001b[32m█\u001b[39m\u001b[39m█\u001b[39m▇\u001b[39m▅\u001b[39m▅\u001b[39m▄\u001b[39m▃\u001b[39m▂\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▃\u001b[39m▂\u001b[39m▃\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▃\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▁\u001b[39m▂\u001b[39m▂\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▂\u001b[39m▂\u001b[39m▃\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m \u001b[39m▃\n",
" 3.18 ms\u001b[90m Histogram: frequency by time\u001b[39m 4.24 ms \u001b[0m\u001b[1m<\u001b[22m\n",
"\n",
" Memory estimate\u001b[90m: \u001b[39m\u001b[33m1.52 MiB\u001b[39m, allocs estimate\u001b[90m: \u001b[39m\u001b[33m46\u001b[39m."
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"guide = calculate_guide(size(area), obstacle_nodes, mst)\n",
"@benchmark calculate_guide($size(area), $obstacle_nodes, $mst)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "4c0871b6-5dfc-4787-ad94-d205b11fc5ae",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"BenchmarkTools.Trial: 4495 samples with 1 evaluation.\n",
" Range \u001b[90m(\u001b[39m\u001b[36m\u001b[1mmin\u001b[22m\u001b[39m … \u001b[35mmax\u001b[39m\u001b[90m): \u001b[39m\u001b[36m\u001b[1m1.008 ms\u001b[22m\u001b[39m … \u001b[35m 3.338 ms\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmin … max\u001b[90m): \u001b[39m0.00% … 0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[34m\u001b[1mmedian\u001b[22m\u001b[39m\u001b[90m): \u001b[39m\u001b[34m\u001b[1m1.087 ms \u001b[22m\u001b[39m\u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmedian\u001b[90m): \u001b[39m0.00%\n",
" Time \u001b[90m(\u001b[39m\u001b[32m\u001b[1mmean\u001b[22m\u001b[39m ± \u001b[32mσ\u001b[39m\u001b[90m): \u001b[39m\u001b[32m\u001b[1m1.110 ms\u001b[22m\u001b[39m ± \u001b[32m101.133 μs\u001b[39m \u001b[90m┊\u001b[39m GC \u001b[90m(\u001b[39mmean ± σ\u001b[90m): \u001b[39m0.76% ± 4.18%\n",
"\n",
" \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m▂\u001b[39m█\u001b[34m \u001b[39m\u001b[32m \u001b[39m\u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \u001b[39m \n",
" \u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▄\u001b[39m█\u001b[39m█\u001b[34m▇\u001b[39m\u001b[32m▆\u001b[39m\u001b[39m▅\u001b[39m▆\u001b[39m▄\u001b[39m▃\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▂\u001b[39m▁\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▂\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▁\u001b[39m▂\u001b[39m▂\u001b[39m▁\u001b[39m▂\u001b[39m▂\u001b[39m \u001b[39m▂\n",
" 1.01 ms\u001b[90m Histogram: frequency by time\u001b[39m 1.82 ms \u001b[0m\u001b[1m<\u001b[22m\n",
"\n",
" Memory estimate\u001b[90m: \u001b[39m\u001b[33m659.19 KiB\u001b[39m, allocs estimate\u001b[90m: \u001b[39m\u001b[33m15\u001b[39m."
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"path = calculate_circumnavigation_path(new_area, guide)\n",
"@benchmark calculate_circumnavigation_path($new_area, $guide)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Julia 1.7.0",
"language": "julia",
"name": "julia-1.7"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
"version": "1.7.0"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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