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<!DOCTYPE html>
<html lang="en-us">
<head>
<title>2021/day01.nim</title>
<link rel="icon" href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2280%22>🐳</text></svg>">
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<div class="nb-box">
<span><a href="..">🏡</a></span>
<span><code>2021/day01.nim</code></span>
<span><a href="https://github.com/pietroppeter/adventofnim"><svg aria-hidden="true" width="1.2em" height="1.2em" style="vertical-align: middle; fill: #fff" preserveAspectRatio="xMidYMid meet" viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27.68 0 1.36.09 2 .27 1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.013 8.013 0 0016 8c0-4.42-3.58-8-8-8z"></path></svg></a></span>
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<h2>2021, day 1: <a href="https://adventofcode.com/2021/day/1">Sonar Sweep</a> ⛴️🔈</h2>
<p>Another year of <a href="https://forum.nim-lang.org/t/8657">Advent of Nim</a> 🎄👑!</p>
<p><em>This year I would like to try and use cool nim libraries
for visualization</em> and similar stuff.
I will most likely be able to keep up only for a few days, but let's see.</p>
<p>But let's get to the first problem.
As usual we have a sequence of integers as input.</p>
<p>What is new this year is that,
<a href="https://nim-lang.org/blog/2021/10/19/version-160-released.html">thanks to 1.6</a>
we can use <code>toSeq</code> with method call syntax!</p>
<pre><code class="nim hljs"><span class="hljs-keyword">let</span> input: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>] = <span class="hljs-string">"2021/input01.txt"</span>.lines.toSeq.map(parseInt)
<span class="hljs-keyword">echo</span> input.len
<span class="hljs-keyword">echo</span> input[<span class="hljs-number">0</span> .. <span class="hljs-number">10</span>]
<span class="hljs-keyword">echo</span> input[^<span class="hljs-number">10</span> .. ^<span class="hljs-number">1</span>]</code></pre>
<pre><samp>2000
@[104, 105, 109, 120, 124, 113, 120, 121, 122, 123, 134]
@[7678, 7680, 7692, 7712, 7724, 7730, 7736, 7737, 7746, 7759]
</samp></pre>
<h3>Part 1</h3>
<blockquote>
<p>As the submarine drops below the surface of the ocean, it automatically performs a sonar sweep of the nearby sea floor. On a small screen, the sonar sweep report (your puzzle input) appears: each line is a measurement of the sea floor depth as the sweep looks further and further away from the submarine.</p>
<p>For example, suppose you had the following report:</p>
</blockquote>
<pre><code class="nim hljs"><span class="hljs-keyword">let</span> report = <span class="hljs-string">"""
199
200
208
210
200
207
240
269
260
263"""</span></code></pre>
<blockquote>
<p>This report indicates that, scanning outward from the submarine, the sonar sweep found depths of 199, 200, 208, 210, and so on.</p>
<p>The first order of business is to figure out how quickly the depth increases, ...</p>
<p>To do this, count the <em>number of times a depth measurement increases</em> from the previous measurement</p>
<p>... In this example, there are 7 measurements that are larger than the previous measurement.</p>
</blockquote>
<p>The solution for part1 (as expected) is pretty straightforward.
Just make sure you start from index 1:</p>
<pre><code class="nim hljs"><span class="hljs-keyword">func</span> countIncrease(s: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>]): <span class="hljs-built_in">int</span> =
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">1</span> .. s.<span class="hljs-keyword">high</span>:
<span class="hljs-keyword">if</span> s[i] > s[i - <span class="hljs-number">1</span>]:
inc <span class="hljs-literal">result</span>
<span class="hljs-keyword">let</span> testInput = report.splitLines.toSeq.map(parseInt)
doAssert testInput.countIncrease == <span class="hljs-number">7</span>
<span class="hljs-keyword">echo</span> countIncrease(input)</code></pre>
<pre><samp>1557
</samp></pre>
<p>That's the right answer! You are <em class="star">one gold star</em> closer to saving your vacation.</p>
<h3>Part 2</h3>
<blockquote>
<p>Considering every single measurement isn't as useful as you expected: there's just too much noise in the data.</p>
<p>Instead, consider <em>sums of a three-measurement sliding window</em>.</p>
<p>... Your goal now is to count <em>the number of times the sum of measurements in this sliding window increases</em> from the previous sum.</p>
<p>... In [test] example, there are 5 sums that are larger than the previous sum.</p>
</blockquote>
<p>let's create a function that copmutes the window function of a sequence,
then we will apply previous function to the result.</p>
<pre><code class="nim hljs"><span class="hljs-keyword">func</span> window(s: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>], size=<span class="hljs-number">3</span>): <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>] =
<span class="hljs-keyword">assert</span> s.len >= size
<span class="hljs-keyword">var</span> sum = s[<span class="hljs-number">0</span> ..< size].sum
<span class="hljs-literal">result</span>.add sum
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> size .. s.<span class="hljs-keyword">high</span>:
sum = sum - s[i - size] + s[i]
<span class="hljs-literal">result</span>.add sum
<span class="hljs-keyword">echo</span> input[<span class="hljs-number">0</span> ..< <span class="hljs-number">10</span>]
<span class="hljs-keyword">echo</span> input[<span class="hljs-number">0</span> ..< <span class="hljs-number">10</span>].window</code></pre>
<pre><samp>@[104, 105, 109, 120, 124, 113, 120, 121, 122, 123]
@[318, 334, 353, 357, 357, 354, 363, 366]
</samp></pre>
<pre><code class="nim hljs">doAssert testInput.window.countIncrease == <span class="hljs-number">5</span>
<span class="hljs-keyword">echo</span> input.window.countIncrease</code></pre>
<pre><samp>1608
</samp></pre>
<p>That's the right answer! You are <em class="star">one gold star</em> closer to saving your vacation.</p>
<h3>Optimizing part 2</h3>
<p>As hinted by <a href="https://github.com/narimiran">narimiran</a> in our nim-aoc discord chat,
there is a simpler way to compute part 2 that also reveals that <em>the "window" approach
does not really denoise the signal</em>. Since two successive windows of 3 depths have 2 overlapping
depth, to check if there is an increase we only need to check first and last depth:</p>
<pre><code class="nim hljs"><span class="hljs-keyword">func</span> countIncrease2(s: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>], window=<span class="hljs-number">3</span>): <span class="hljs-built_in">int</span> =
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">0</span> ..< (s.len - window):
<span class="hljs-keyword">if</span> s[i + window] > s[i]:
inc <span class="hljs-literal">result</span>
<span class="hljs-keyword">echo</span> input.countIncrease2</code></pre>
<pre><samp>1608
</samp></pre>
<h3>Visualization</h3>
<p>I will use the excellent <a href="https://github.com/Vindaar/ggplotnim">ggplotnim</a>
to plot the depth profile and the dataframe library <a href="https://github.com/SciNim/Datamancer">datamancer</a>
(implictly imported through ggplotnim) to manage the data.
Thanks to <a href="https://github.com/Vindaar">Vindaar</a> for help in this section</p>
<pre><code class="nim hljs"><span class="hljs-keyword">import</span> ggplotnim
<span class="hljs-keyword">var</span> df = seqsToDf({<span class="hljs-string">"depth"</span>: input}) <span class="hljs-comment"># toDf(input): new column will be named input</span>
df[<span class="hljs-string">"x"</span>] = collect:
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">1</span> .. input.len:
i
<span class="hljs-keyword">echo</span> df
<span class="hljs-keyword">let</span>
dark = parseHex(<span class="hljs-string">"202b38"</span>)
gold = parseHex(<span class="hljs-string">"ffff66"</span>)
ggplot(df, aes(x=<span class="hljs-string">"x"</span>, y=<span class="hljs-string">"depth"</span>)) + scale_y_reverse() +
geom_line(color=some(gold)) + theme_void(color=dark) +
ggsave(<span class="hljs-string">"2021/01_depths.png"</span>)</code></pre>
<pre><samp>Dataframe with 2 columns and 2000 rows:
Idx depth x
dtype: int int
0 104 1
1 105 2
2 109 3
3 120 4
4 124 5
5 113 6
6 120 7
7 121 8
8 122 9
9 123 10
10 134 11
11 133 12
12 134 13
13 150 14
14 160 15
15 165 16
16 179 17
17 178 18
18 180 19
19 178 20
INFO: The integer column `x` has been automatically determined to be continuous. To overwrite this behavior add a `+ scale_x/y_discrete()` call to the plotting chain. Choose `x` or `y` depending on which axis this column refers to. Or apply a `factor` to the column name in the `aes` call, i.e. `aes(..., factor("x"), ...)`.
StatusSuccess output of write_to_png
</samp></pre>
<figure>
<img src="../2021/01_depths.png" alt="">
<figcaption></figcaption>
</figure>
<p>Note:</p>
<ul>
<li>we use <code>seqsToDf</code> and a table constructor in order to give a new name to input</li>
<li>we built (using sugar's collect) a dummy x axis in order to use it in the plots</li>
<li>we reverse y scale to give the idea of increasing depth of sea bottom</li>
<li>we use a gold line and same background as that of the page, removing all axis</li>
<li>colors come from <a href="https://github.com/treeform/chroma">chroma</a></li>
</ul>
<p>Interesting also to plot the depth differences
(and its average, which we can expect to be close to 4):</p>
<pre><code class="nim hljs">df[<span class="hljs-string">"diff_depth"</span>] = collect:
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">0</span> .. input.<span class="hljs-keyword">high</span>:
<span class="hljs-keyword">if</span> i == <span class="hljs-number">0</span>:
<span class="hljs-number">0</span>
<span class="hljs-keyword">else</span>:
input[i] - input[i-<span class="hljs-number">1</span>]
<span class="hljs-keyword">let</span> mean_diff_depth = mean(df[<span class="hljs-string">"diff_depth"</span>].toTensor(<span class="hljs-built_in">float</span>))
dump mean_diff_depth
<span class="hljs-keyword">echo</span> df
<span class="hljs-keyword">let</span>
green = parseHex(<span class="hljs-string">"009900"</span>)
red = parseHtmlName(<span class="hljs-string">"red"</span>)
<span class="hljs-keyword">let</span>
font_aoc = <span class="hljs-type">Font</span>(
family: <span class="hljs-string">"sans-serif"</span>,
size: <span class="hljs-number">12.0</span>,
bold: <span class="hljs-literal">false</span>,
slant: fsNormal,
color: green, <span class="hljs-comment"># only change with respect to default</span>
alignKind: taCenter
)
theme_aoc = <span class="hljs-type">Theme</span>(
canvasColor: some(dark),
plotBackgroundColor: some(dark),
gridLineColor: some(green),
labelFont: some(font_aoc),
tickLabelFont: some(font_aoc),
<span class="hljs-comment"># hideTicks: some(true) # with this line:</span>
<span class="hljs-comment"># fatal.nim(53Error: unhandled exception: index out of bounds, the container is empty [IndexDefect]</span>
)
ggplot(df, aes(x=<span class="hljs-string">"x"</span>, y=<span class="hljs-string">"diff_depth"</span>)) +
geom_line(color=some(gold)) + theme_aoc +
geom_linerange(aes = aes(y = mean_diff_depth, xMin = <span class="hljs-number">0</span>, xMax = <span class="hljs-number">2000</span>), color=some(red)) +
ggsave(<span class="hljs-string">"2021/01_relative_depth.png"</span>)</code></pre>
<pre><samp>mean_diff_depth = 3.8275
Dataframe with 3 columns and 2000 rows:
Idx depth x diff_depth
dtype: int int int
0 104 1 0
1 105 2 1
2 109 3 4
3 120 4 11
4 124 5 4
5 113 6 -11
6 120 7 7
7 121 8 1
8 122 9 1
9 123 10 1
10 134 11 11
11 133 12 -1
12 134 13 1
13 150 14 16
14 160 15 10
15 165 16 5
16 179 17 14
17 178 18 -1
18 180 19 2
19 178 20 -2
INFO: The integer column `x` has been automatically determined to be continuous. To overwrite this behavior add a `+ scale_x/y_discrete()` call to the plotting chain. Choose `x` or `y` depending on which axis this column refers to. Or apply a `factor` to the column name in the `aes` call, i.e. `aes(..., factor("x"), ...)`.
StatusSuccess output of write_to_png
</samp></pre>
<figure>
<img src="../2021/01_relative_depth.png" alt="">
<figcaption></figcaption>
</figure>
<p>Note:</p>
<ul>
<li>to compute the mean we use <code>toTensor</code> and we convert to float (otherwise the result will be an <code>int</code>)</li>
<li>we create a custom "aoc" theme setting appropriately colors</li>
<li>we are using <code>geom_linerange</code> to plot the horizontal line since <code>geom_hline</code> is not (yet) implemented</li>
</ul>
<h3>highlights from subreddit</h3>
<p>Among the different stuff that is published in advent of code
<a href="https://www.reddit.com/r/adventofcode/">subreddit</a>
I found interesting:</p>
<ul>
<li>a site that allows to <a href="https://aocweb.yulrizka.com/?year=2021&day=1&language=Nim">search all solutions</a>
posted in the solution megathread by programming language (<a href="https://www.reddit.com/r/adventofcode/comments/r6cmn1/aocweb_a_website_that_collects_solutions_from_the/">announcement</a>)</li>
<li>a <a href="https://www.reddit.com/r/adventofcode/comments/r6asn2/2021_day_1_part_1well_its_a_game_turing_complete/">visualization</a> of a solution built with
<a href="https://store.steampowered.com/app/1444480/Turing_Complete/">Turing Complete</a>,
a game coded in Nim</li>
</ul>
</main>
<footer>
<hr>
<div class="nb-box">
<span><span class="nb-small">made with <a href="https://pietroppeter.github.io/nimib/">nimib 🐳</a></span></span>
<span></span>
<span><button class="nb-small" id="show" onclick="toggleSourceDisplay()">Show Source</button></span>
</div>
</footer>
<section id="source">
<pre><code class="nim hljs"><span class="hljs-keyword">import</span> nimib, animu, nimoji
nbInit(theme=useAdventOfNim)
nbText: <span class="hljs-string">"""## 2021, day 1: [Sonar Sweep](https://adventofcode.com/2021/day/1) ⛴️🔈
Another year of [Advent of Nim](https://forum.nim-lang.org/t/8657) :christmas_tree::crown:!
_This year I would like to try and use cool nim libraries
for visualization_ and similar stuff.
I will most likely be able to keep up only for a few days, but let's see.
But let's get to the first problem.
As usual we have a sequence of integers as input.
What is new this year is that,
[thanks to 1.6](https://nim-lang.org/blog/2021/10/19/version-160-released.html)
we can use `toSeq` with method call syntax!
"""</span>.emojize
nbCode:
<span class="hljs-keyword">let</span> input: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>] = <span class="hljs-string">"2021/input01.txt"</span>.lines.toSeq.map(parseInt)
<span class="hljs-keyword">echo</span> input.len
<span class="hljs-keyword">echo</span> input[<span class="hljs-number">0</span> .. <span class="hljs-number">10</span>]
<span class="hljs-keyword">echo</span> input[^<span class="hljs-number">10</span> .. ^<span class="hljs-number">1</span>]
nbText: <span class="hljs-string">"""### Part 1
> As the submarine drops below the surface of the ocean, it automatically performs a sonar sweep of the nearby sea floor. On a small screen, the sonar sweep report (your puzzle input) appears: each line is a measurement of the sea floor depth as the sweep looks further and further away from the submarine.
>
> For example, suppose you had the following report:
"""</span>
nbCode:
<span class="hljs-keyword">let</span> report = <span class="hljs-string">"""
199
200
208
210
200
207
240
269
260
263"""</span>
nbText: <span class="hljs-string">"""
> This report indicates that, scanning outward from the submarine, the sonar sweep found depths of 199, 200, 208, 210, and so on.
>
> The first order of business is to figure out how quickly the depth increases, ...
>
> To do this, count the _number of times a depth measurement increases_ from the previous measurement
>
> ... In this example, there are 7 measurements that are larger than the previous measurement.
The solution for part1 (as expected) is pretty straightforward.
Just make sure you start from index 1:
"""</span>
nbCode:
<span class="hljs-keyword">func</span> countIncrease(s: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>]): <span class="hljs-built_in">int</span> =
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">1</span> .. s.<span class="hljs-keyword">high</span>:
<span class="hljs-keyword">if</span> s[i] > s[i - <span class="hljs-number">1</span>]:
inc <span class="hljs-literal">result</span>
<span class="hljs-keyword">let</span> testInput = report.splitLines.toSeq.map(parseInt)
doAssert testInput.countIncrease == <span class="hljs-number">7</span>
<span class="hljs-keyword">echo</span> countIncrease(input)
doAssert countIncrease(input) == <span class="hljs-number">1557</span>
gotTheStar
nbText: <span class="hljs-string">"""### Part 2
> Considering every single measurement isn't as useful as you expected: there's just too much noise in the data.
>
> Instead, consider _sums of a three-measurement sliding window_.
>
> ... Your goal now is to count _the number of times the sum of measurements in this sliding window increases_ from the previous sum.
>
> ... In [test] example, there are 5 sums that are larger than the previous sum.
let's create a function that copmutes the window function of a sequence,
then we will apply previous function to the result.
"""</span>
nbCode:
<span class="hljs-keyword">func</span> window(s: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>], size=<span class="hljs-number">3</span>): <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>] =
<span class="hljs-keyword">assert</span> s.len >= size
<span class="hljs-keyword">var</span> sum = s[<span class="hljs-number">0</span> ..< size].sum
<span class="hljs-literal">result</span>.add sum
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> size .. s.<span class="hljs-keyword">high</span>:
sum = sum - s[i - size] + s[i]
<span class="hljs-literal">result</span>.add sum
<span class="hljs-keyword">echo</span> input[<span class="hljs-number">0</span> ..< <span class="hljs-number">10</span>]
<span class="hljs-keyword">echo</span> input[<span class="hljs-number">0</span> ..< <span class="hljs-number">10</span>].window
nbCode:
doAssert testInput.window.countIncrease == <span class="hljs-number">5</span>
<span class="hljs-keyword">echo</span> input.window.countIncrease
gotTheStar
doAssert input.window.countIncrease == <span class="hljs-number">1608</span>
nbText: <span class="hljs-string">"""### Optimizing part 2
As hinted by [narimiran](https://github.com/narimiran) in our nim-aoc discord chat,
there is a simpler way to compute part 2 that also reveals that _the "window" approach
does not really denoise the signal_. Since two successive windows of 3 depths have 2 overlapping
depth, to check if there is an increase we only need to check first and last depth:
"""</span>
nbCode:
<span class="hljs-keyword">func</span> countIncrease2(s: <span class="hljs-built_in">seq</span>[<span class="hljs-built_in">int</span>], window=<span class="hljs-number">3</span>): <span class="hljs-built_in">int</span> =
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">0</span> ..< (s.len - window):
<span class="hljs-keyword">if</span> s[i + window] > s[i]:
inc <span class="hljs-literal">result</span>
<span class="hljs-keyword">echo</span> input.countIncrease2
doAssert input.countIncrease2 == <span class="hljs-number">1608</span>
<span class="hljs-comment"># note that countIncrease2 is equivalent to countIncrease(..., window=1)</span>
nbText: <span class="hljs-string">"""### Visualization
I will use the excellent [ggplotnim](https://github.com/Vindaar/ggplotnim)
to plot the depth profile and the dataframe library [datamancer](https://github.com/SciNim/Datamancer)
(implictly imported through ggplotnim) to manage the data.
Thanks to [Vindaar](https://github.com/Vindaar) for help in this section
"""</span>
nbCode:
<span class="hljs-keyword">import</span> ggplotnim
<span class="hljs-keyword">var</span> df = seqsToDf({<span class="hljs-string">"depth"</span>: input}) <span class="hljs-comment"># toDf(input): new column will be named input</span>
df[<span class="hljs-string">"x"</span>] = collect:
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">1</span> .. input.len:
i
<span class="hljs-keyword">echo</span> df
<span class="hljs-keyword">let</span>
dark = parseHex(<span class="hljs-string">"202b38"</span>)
gold = parseHex(<span class="hljs-string">"ffff66"</span>)
ggplot(df, aes(x=<span class="hljs-string">"x"</span>, y=<span class="hljs-string">"depth"</span>)) + scale_y_reverse() +
geom_line(color=some(gold)) + theme_void(color=dark) +
ggsave(<span class="hljs-string">"2021/01_depths.png"</span>)
nbImage(<span class="hljs-string">"2021/01_depths.png"</span>)
nbText: <span class="hljs-string">"""
Note:
- we use `seqsToDf` and a table constructor in order to give a new name to input
- we built (using sugar's collect) a dummy x axis in order to use it in the plots
- we reverse y scale to give the idea of increasing depth of sea bottom
- we use a gold line and same background as that of the page, removing all axis
- colors come from [chroma](https://github.com/treeform/chroma)
Interesting also to plot the depth differences
(and its average, which we can expect to be close to 4):
"""</span>
nbCode:
df[<span class="hljs-string">"diff_depth"</span>] = collect:
<span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-number">0</span> .. input.<span class="hljs-keyword">high</span>:
<span class="hljs-keyword">if</span> i == <span class="hljs-number">0</span>:
<span class="hljs-number">0</span>
<span class="hljs-keyword">else</span>:
input[i] - input[i-<span class="hljs-number">1</span>]
<span class="hljs-keyword">let</span> mean_diff_depth = mean(df[<span class="hljs-string">"diff_depth"</span>].toTensor(<span class="hljs-built_in">float</span>))
dump mean_diff_depth
<span class="hljs-keyword">echo</span> df
<span class="hljs-keyword">let</span>
green = parseHex(<span class="hljs-string">"009900"</span>)
red = parseHtmlName(<span class="hljs-string">"red"</span>)
<span class="hljs-keyword">let</span>
font_aoc = <span class="hljs-type">Font</span>(
family: <span class="hljs-string">"sans-serif"</span>,
size: <span class="hljs-number">12.0</span>,
bold: <span class="hljs-literal">false</span>,
slant: fsNormal,
color: green, <span class="hljs-comment"># only change with respect to default</span>
alignKind: taCenter
)
theme_aoc = <span class="hljs-type">Theme</span>(
canvasColor: some(dark),
plotBackgroundColor: some(dark),
gridLineColor: some(green),
labelFont: some(font_aoc),
tickLabelFont: some(font_aoc),
<span class="hljs-comment"># hideTicks: some(true) # with this line:</span>
<span class="hljs-comment"># fatal.nim(53Error: unhandled exception: index out of bounds, the container is empty [IndexDefect]</span>
)
ggplot(df, aes(x=<span class="hljs-string">"x"</span>, y=<span class="hljs-string">"diff_depth"</span>)) +
geom_line(color=some(gold)) + theme_aoc +
geom_linerange(aes = aes(y = mean_diff_depth, xMin = <span class="hljs-number">0</span>, xMax = <span class="hljs-number">2000</span>), color=some(red)) +
ggsave(<span class="hljs-string">"2021/01_relative_depth.png"</span>)
nbImage(<span class="hljs-string">"2021/01_relative_depth.png"</span>)
nbText: <span class="hljs-string">"""
Note:
* to compute the mean we use `toTensor` and we convert to float (otherwise the result will be an `int`)
* we create a custom "aoc" theme setting appropriately colors
* we are using `geom_linerange` to plot the horizontal line since `geom_hline` is not (yet) implemented
### highlights from subreddit
Among the different stuff that is published in advent of code
[subreddit](https://www.reddit.com/r/adventofcode/)
I found interesting:
- a site that allows to [search all solutions](https://aocweb.yulrizka.com/?year=2021&day=1&language=Nim)
posted in the solution megathread by programming language ([announcement](https://www.reddit.com/r/adventofcode/comments/r6cmn1/aocweb_a_website_that_collects_solutions_from_the/))
- a [visualization](https://www.reddit.com/r/adventofcode/comments/r6asn2/2021_day_1_part_1well_its_a_game_turing_complete/) of a solution built with
[Turing Complete](https://store.steampowered.com/app/1444480/Turing_Complete/),
a game coded in Nim
"""</span>
<span class="hljs-comment">#[
add section of highlights from subreddit
- new theme: adventure time
- site with all solutions
- turing complete solution
- deep water visualization
- ...
]#</span>
nbSave</code></pre>
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