diff --git a/ipynb/Advent-2022.ipynb b/ipynb/Advent-2022.ipynb
index c0a38b0..3bba6cf 100644
--- a/ipynb/Advent-2022.ipynb
+++ b/ipynb/Advent-2022.ipynb
@@ -8,13 +8,7 @@
"\n",
"# Advent of Code 2022\n",
"\n",
- "I'm doing Advent of Code (AoC) again this year.\n",
- "\n",
- "Happily for us all, [@GaryJGrady](https://twitter.com/GaryJGrady/) is drawing his cartoons again too! Below, Gary's elf makes preparations on the eve of AoC:\n",
- "\n",
- "\n",
- "\n",
- "I prepared by loading up my [**AdventUtils.ipynb**](AdventUtils.ipynb) notebook from last year:"
+ "I'm doing Advent of Code (AoC) again this year. On AoC eve, I prepared by loading up my [**AdventUtils.ipynb**](AdventUtils.ipynb) notebook:"
]
},
{
@@ -30,23 +24,34 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "You might want to [take a look](AdventUtils.ipynb) to see how the `parse` and `answer` functions work, since they will be used for each day's puzzles. You'll really have to read [each day's puzzle description](https://adventofcode.com/2022/day/1). Each solution will have three parts:\n",
+ "You might want to [take a look](AdventUtils.ipynb) to see how the `parse` and `answer` functions work. Each day's solution will use them as follows:\n",
"- **Reading the Input**, e.g. for Day 1, `in1 = parse(1, ints, sep=paragraph)`. The function `parse` splits the input file for day 1 into records (by default each line is a record, but the `sep` keyword argument can be used to split by paragraph or other separators), and then applies a function (here `ints`, which returns a tuple of all integers in a string) to each record. `parse` prints the first few lines of the input file and the first few records of the parsed result.\n",
- "- **Solving Part One**, e.g. `answer(1.1, ..., lambda: ...)`. The function `answer` takes three arguments:\n",
+ "- **Solving Part One**, After I've found the solution, I'll call, e.g., `answer(1.1, ..., lambda: ...)` to record how I got it. `answer` takes three arguments:\n",
" 1. The puzzle we are answering, in the form *day*.*part*\n",
- " 2. The correct answer as verified by AoC (recorded here so that if I modify and re-run the notebook, I can verify that it still works), \n",
- " 3. A function to call to compute the answer. (It is passed as a function so we can time how long it takes to run.)\n",
- "- **Solving Part Two**, e.g. `answer(1.2, ..., lambda: ...)`.\n",
+ " 2. The correct answer as verified by AoC \n",
+ " 3. A function to call to compute the answer (passed as a function so we can time how long it takes to run)\n",
+ "- **Solving Part Two**, e.g. `answer(1.2, ..., lambda: ...)`\n",
+ "\n",
+ "To understand each day's puzzle, you'll really have to read the day's puzzle description, which is linked in the header for each day, e.g. [**Day 1**](https://adventofcode.com/2022/day/1).\n",
"\n"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Happily for us all, [@GaryJGrady](https://twitter.com/GaryJGrady/) is drawing his cartoons again too! Below, Gary's elf makes his preparations:\n",
+ "\n",
+ ""
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# [Day 1](https://adventofcode.com/2022/day/1): Calorie Counting\n",
"\n",
- "There is a complex backstory involving food for the elves and calories, but computationally all we have to know is that the input is a sequence of paragraphs, where each paragraph contains some integers. My `parse` function knows how to handle that:"
+ "There is a complex backstory involving food for the elves and calories, but computationally all we have to know is that the input is a sequence of paragraphs, where each paragraph contains some integers. My `parse` function handles this easily:"
]
},
{
@@ -141,12 +146,14 @@
"cell_type": "markdown",
"metadata": {},
"source": [
+ "#### Recap\n",
+ "\n",
"To be clear, here is exactly what I did to solve the day's puzzle:\n",
"\n",
"1. Typed and executed `in1 = parse(1, ints, paragraphs)` in a Jupyter Notebook cell, and examined the output. Looked good to me.\n",
"2. Solved Part 1: typed and executed `max(sum(elf) for elf in in1)` in a cell, and saw the output, `70116`.\n",
- "3. Copy/pasted `70116` into the [AoC Day 1](https://adventofcode.com/2022/day/1) input box and submitted it.\n",
- "4. Verified that AoC agreed the answer was correct. (On some other days, the first such submission was not correct.)\n",
+ "3. Copy/pasted `70116` into the [AoC Day 1](https://adventofcode.com/2022/day/1) answer box and submitted it.\n",
+ "4. Verified that AoC agreed the answer was correct. (Sometimes the first submission is wrong, and I need to repeat steps 2–4.)\n",
"5. Typed and executed `answer(1.1, 70116, lambda: max(sum(elf) for elf in in1))` in a cell, for when I re-run the notebook.\n",
"6. Repeated steps 2–5 for Part 2."
]
@@ -164,7 +171,7 @@
"source": [
"# [Day 2](https://adventofcode.com/2022/day/2): Rock Paper Scissors \n",
"\n",
- "The input is two one-letter strings per line indicating the two player's plays:"
+ "The input is two one-letter strings per line indicating the two player's plays in a round of rock-paper-scissors:"
]
},
{
@@ -209,7 +216,7 @@
"source": [
"#### Part 1: What would your total score be if everything goes exactly according to your strategy guide?\n",
"\n",
- "One confusing aspect: there are multiple encodings. Rock/Paper/Scissors corresponds to A/B/C, and X/Y/Z, and scores of 1/2/3. I decided the least confusing approach would be to translate everything to 1/2/3:"
+ "One confusing aspect: there are three different encodings. Rock/Paper/Scissors corresponds to A/B/C, and to X/Y/Z, and to scores of 1/2/3. I decided the least confusing approach would be to translate everything to 1/2/3:"
]
},
{
@@ -230,7 +237,7 @@
"rps_winner = {Rock: Paper, Paper: Scissors, Scissors: Rock}\n",
"\n",
"def rps_score(you: int, me: int) -> int:\n",
- " \"\"\"My score for a round is my play plus 3 for draw and 6 for win.\"\"\"\n",
+ " \"\"\"My score for a round is 1/2/3 for my play plus 3 for draw and 6 for win.\"\"\"\n",
" return me + (6 if rps_winner[you] == me else 3 if me == you else 0)\n",
" \n",
"answer(2.1, 13268, lambda: sum(rps_score('.ABC'.index(a), '.XYZ'.index(x)) for a, x in in2))"
@@ -261,9 +268,9 @@
"source": [
"rps_loser = {rps_winner[x]: x for x in RPS} # Invert the dict\n",
"\n",
- "def rps_score2(you: int, x: Char) -> int:\n",
+ "def rps_score2(you: int, xyz: Char) -> int:\n",
" \"\"\"First letter means A=Rock/B=Paper/C=Scissors; second means X=lose/Y=draw/Z=win.\"\"\"\n",
- " me = rps_loser[you] if x == 'X' else you if x == 'Y' else rps_winner[you]\n",
+ " me = rps_loser[you] if xyz == 'X' else you if xyz == 'Y' else rps_winner[you]\n",
" return rps_score(you, me)\n",
"\n",
"answer(2.2, 15508, lambda: sum(rps_score2('.ABC'.index(a), x) for a, x in in2))"
@@ -310,7 +317,7 @@
"source": [
"#### Part 1: Find the item type that appears in both compartments of each rucksack. What is the sum of the priorities of those item types?\n",
"\n",
- "The two \"compartments\" are the two halves of the string. Find the common item by set intersection. The function `the` makes sure there is exactly one letter in the interesection:"
+ "The two \"compartments\" are the two halves of the string. Find the common item by set intersection. My utility function `split_at` divides a string into two parts at an index, and `the` makes sure there is exactly one letter in the interesection:"
]
},
{
@@ -322,15 +329,15 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "0.001 seconds for correct answer: 8,401\n"
+ "0.000 seconds for correct answer: 8,401\n"
]
}
],
"source": [
"def common_item(rucksack: str) -> Char:\n",
" \"\"\"The one letter that appears in both left and right halves of the input string.\"\"\"\n",
- " left, right = split_at(rucksack, len(rucksack) // 2)\n",
- " return the(set(left) & set(right))\n",
+ " compartments = split_at(rucksack, len(rucksack) // 2)\n",
+ " return the(intersection(compartments))\n",
"\n",
"priority = {c: i + 1 for i, c in enumerate(string.ascii_letters)}\n",
"\n",
@@ -376,7 +383,7 @@
"source": [
"# [Day 4](https://adventofcode.com/2022/day/4): Camp Cleanup\n",
"\n",
- "Each input line corresponds to two ranges of integers, which I'll represent with a 4-tuple of endpoints:"
+ "Each input line represents a pair of ranges of ID numbers for sections of camp that a given elf is assigned to clean up. I'll parse each line into a 4-tuple of endpoints:"
]
},
{
@@ -421,7 +428,7 @@
"source": [
"#### Part 1: In how many assignment pairs does one range fully contain the other?\n",
"\n",
- "I could have turned each range into a set of integers and compared the sets, but I was concerned that a huge range would mean a huge set, so instead I directly compare the endpoints of the ranges:"
+ "I could have turned each range into a set of integers and compared the sets, but a huge range would mean a huge set, so instead I directly compare the endpoints of the ranges:"
]
},
{
@@ -442,7 +449,7 @@
" \"\"\"Is the range `lo-hi` fully contained in `LO-HI`, or vice-veresa?\"\"\"\n",
" return (lo <= LO <= HI <= hi) or (LO <= lo <= hi <= HI)\n",
"\n",
- "answer(4.1, 477, lambda: quantify(fully_contained(*line) for line in in4))"
+ "answer(4.1, 477, lambda: quantify(fully_contained(*ranges) for ranges in in4))"
]
},
{
@@ -470,7 +477,7 @@
" \"\"\"Do the two ranges have any overlap?\"\"\"\n",
" return (lo <= LO <= hi) or (LO <= lo <= HI)\n",
"\n",
- "answer(4.2, 830, lambda: quantify(overlaps(*line) for line in in4))"
+ "answer(4.2, 830, lambda: quantify(overlaps(*ranges) for ranges in in4))"
]
},
{
@@ -479,9 +486,9 @@
"source": [
"# [Day 5](https://adventofcode.com/2022/day/5): Supply Stacks\n",
"\n",
- "My `parse` function is primarily intended for the case where every record is parsed the same way. In today's puzzle, the input has two sections (in two paragraphs), each of which should be parsed differently. The function `parse_sections` is designed to handle this case. It takes as input a list of parsers (in this case two of them), which will be applied in order to parse the corresponding section:\n",
- "- The first section is a **diagram**, which is parsed by picking out the characters in each stack; that is, in columns 1 and every 4th column after. \n",
- "- The second section is a list of **moves**, which can be parsed with `ints` to get a 3-tuple of numbers. \n"
+ "My `parse` function is primarily intended for the case where every record is parsed the same way. In today's puzzle, the input has two **sections**, each of which should be parsed differently. The function `parse_sections` is designed to handle this case. It takes as input a list of parsers (in this case two of them), which will be applied to parse each corresponding section:\n",
+ "- The first section is a **diagram**, which is parsed by picking out the characters in each stack; that is, in column 1 and every 4th column after: `line[1::4]`.\n",
+ "- The second section is a list of **moves**, which can be parsed with `ints` to get a 3-tuple of (number-of-crates, start-stack, end-stack). \n"
]
},
{
@@ -508,6 +515,7 @@
"\n",
"move 8 from 7 to 1\n",
"move 9 from 1 to 9\n",
+ "move 4 from 5 to 4\n",
"...\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────\n",
"Parsed representation ➜ 2 tuples:\n",
@@ -518,7 +526,9 @@
}
],
"source": [
- "in5 = parse(5, parse_sections([lambda line: line[1::4], ints]), sep=paragraphs, show=12)"
+ "parser5 = parse_sections([(lambda line: line[1::4]), ints])\n",
+ "\n",
+ "in5 = parse(5, parser5, paragraphs, show=13)"
]
},
{
@@ -527,7 +537,7 @@
"source": [
"#### Part 1: After the rearrangement procedure completes, what crate ends up on top of each stack?\n",
"\n",
- "Rearranging means repeatedly popping a crate from one stack and putting it on top of another stack, according to the move commands:"
+ "Rearranging means repeatedly popping a crate from one stack and putting it on top of another stack, according to the move commands. I'll define `rearrange` to manipulate and return a dict of {column: [crate, ...]}. You never know what Part 2 will want, so `rearrange` will return the whole dict, and `tops` will pull out the top crate from each stack."
]
},
{
@@ -544,16 +554,18 @@
}
],
"source": [
- "def rearrange(diagram, moves) -> str:\n",
+ "def rearrange(diagram, moves) -> Dict[int, List[Char]]:\n",
" \"\"\"Given a diagram of crates in stacks, apply move commands.\n",
" Then return a string of the crates that are on top of each stack.\"\"\"\n",
- " stacks = {int(row[-1]): [L for L in reversed(row[:-1]) if L != ' '] for row in T(diagram)}\n",
+ " stacks = {int(col[-1]): [L for L in reversed(col[:-1]) if L != ' '] for col in T(diagram)}\n",
" for (n, source, dest) in moves:\n",
" for _ in range(n):\n",
" stacks[dest].append(stacks[source].pop())\n",
- " return cat(stacks[i].pop() for i in stacks)\n",
+ " return stacks\n",
+ " \n",
+ "def tops(stacks) -> str: return cat(stacks[col][-1] for col in stacks)\n",
"\n",
- "answer(5.1, 'SHQWSRBDL', lambda: rearrange(*in5))"
+ "answer(5.1, 'SHQWSRBDL', lambda: tops(rearrange(*in5)))"
]
},
{
@@ -580,16 +592,16 @@
}
],
"source": [
- "def rearrange(diagram, moves, model=9000) -> str:\n",
- " stacks = {int(row[-1]): [L for L in row[-1::-1] if L != ' '] for row in T(diagram)}\n",
+ "def rearrange(diagram, moves, model=9000) -> dict:\n",
+ " stacks = {int(col[-1]): [L for L in reversed(col[:-1]) if L != ' '] for col in T(diagram)}\n",
" for (n, source, dest) in moves:\n",
" stacks[source], crates = split_at(stacks[source], -n)\n",
" if model == 9000: crates = crates[::-1]\n",
" stacks[dest].extend(crates)\n",
- " return cat(stacks[i].pop() for i in stacks)\n",
+ " return stacks\n",
"\n",
- "answer(5.1, 'SHQWSRBDL', lambda: rearrange(*in5))\n",
- "answer(5.2, 'CDTQZHBRS', lambda: rearrange(*in5, model=9001))"
+ "answer(5.1, 'SHQWSRBDL', lambda: tops(rearrange(*in5)))\n",
+ "answer(5.2, 'CDTQZHBRS', lambda: tops(rearrange(*in5, model=9001)))"
]
},
{
@@ -598,7 +610,7 @@
"source": [
"# [Day 6](https://adventofcode.com/2022/day/6): Tuning Trouble\n",
"\n",
- "The input is a single line of characters:"
+ "The input is a single line of characters, representing signals from a handheld device:"
]
},
{
@@ -627,7 +639,7 @@
"source": [
"#### Part 1: How many characters need to be processed before the first start-of-packet marker is detected?\n",
"\n",
- "A start-of-packet marker is when there are *n* distinct characters in a row. I initially made a mistake: I read the instructions hastily and assumed they were asking for the *start* of the start-of-packet marker, not the *end* of it. When AoC told me I had the wrong answer, I went back and figured it out."
+ "A start-of-packet marker is when there are *n* distinct characters in a row. I initially made a mistake: I read the instructions hastily and assumed they were asking for the *start* of the start-of-packet marker, not the *end* of it. When AoC told me I had the wrong answer, I read the instructions more carefully and figured it out."
]
},
{
@@ -657,7 +669,7 @@
"source": [
"#### Part 2: How many characters need to be processed before the first start-of-message marker is detected?\n",
"\n",
- "Now we're looking for 14 distinct characters, not just 4."
+ "A start-of-message marker is just like a start-of-packet marker, except it consists of 14 distinct characters rather than 4."
]
},
{
@@ -690,7 +702,7 @@
"source": [
"# [Day 7](https://adventofcode.com/2022/day/7): No Space Left On Device \n",
"\n",
- "The input is a sequence of shell commands; I'll make `parse` split each line into words:"
+ "The input is a transcript of shell commands and output; I'll make `parse` split each line into space-separated tokens:"
]
},
{
@@ -735,7 +747,7 @@
"source": [
"#### Part 1: Find all of the directories with a total size of at most 100000. What is the sum of the total sizes of those directories?\n",
"\n",
- "I'll keep track of a stack of directories (as Unix/Linux does with the `pushd`, `popd`, and `dirs` commands). All I need to track is `cd` commands (which change the `dirs` stack) and file size listings. I can ignore `ls` command lines and \"`dir` *name*\" output. The `browse` command examines the lines of the transcript and returns a Counter of `{directory_name: total_size}`. From that Counter I can sum the directory sizes that are under 100,000. "
+ "I'll keep track of a stack of directories (as Unix/Linux does with the [dirs/pushd/popd](https://www.gnu.org/software/bash/manual/html_node/Directory-Stack-Builtins.html) commands). All I need to pay attention to is `cd` commands (which change the `dirs` stack) and file size listings. I can ignore `ls` command lines and \"`dir` *name*\" output. My `browse` function examines the lines of the transcript and returns a Counter of `{directory_name: total_size}`. From that Counter I can sum the directory sizes that are under 100,000. "
]
},
{
@@ -753,7 +765,7 @@
],
"source": [
"def browse(transcript) -> Counter:\n",
- " \"\"\"Return a Counter of {directory_name: total_size}, as revealed by the transcript of commands and output.\"\"\"\n",
+ " \"\"\"Return a Counter of {directory_name: total_size}, as revealed by the transcript.\"\"\"\n",
" dirs = ['/'] # A stack of directories\n",
" sizes = Counter() # Mapping of directory name to total size\n",
" for tokens in transcript:\n",
@@ -809,7 +821,7 @@
"source": [
"# [Day 8](https://adventofcode.com/2022/day/8): Treetop Tree House\n",
"\n",
- "The input is a grid of heights of trees; my `Grid` class handles this well:"
+ "The input is a grid of single-digit heights of trees; my `Grid` class handles this well:"
]
},
{
@@ -866,7 +878,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "0.048 seconds for correct answer: 1,829\n"
+ "0.049 seconds for correct answer: 1,829\n"
]
}
],
@@ -896,7 +908,7 @@
"source": [
"#### Part 2: Consider each tree on your map. What is the highest scenic score possible for any tree?\n",
"\n",
- "If I had chosen better abstraction for Part 1, perhaps I could re-use some \"visible\" function. As it is, I can only re-use `go_in_direction`:"
+ "If I had chosen better abstractions for Part 1, perhaps I could re-use more. As it is, I can only re-use `go_in_direction`; I'll need two new functions to solve Part 2:"
]
},
{
@@ -917,8 +929,8 @@
" \"\"\"The product of the number of trees you can see in each of the 4 directions.\"\"\"\n",
" return prod(viewing_distance(loc, direction, grid) for direction in directions4)\n",
"\n",
- "def viewing_distance(loc, direction, grid):\n",
- " \"\"\"How many trees can you see from this location in this direction?\"\"\"\n",
+ "def viewing_distance(loc, direction, grid) -> int:\n",
+ " \"\"\"The number of trees you can see from this location in this direction.\"\"\"\n",
" seen = 0\n",
" for seen, p in enumerate(go_in_direction(loc, direction, grid), 1):\n",
" if grid[p] >= grid[loc]:\n",
@@ -939,9 +951,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "*Note*: Up to now, I haven't worried about the efficiency of the code, since every day's code ran in about a millisecond. But today took 50 times longer, so I'm starting to get nervous. Maybe in the coming days I will need to be more aware of efficiency issues.\n",
- "\n",
- "I can plot the trees. Darker green means taller, and the red dot is the most scenic spot. We see that the taller growth is towards the center of the forest:"
+ "I can plot the forest. Darker green means taller trees, and the red dot is the most scenic spot. We see that the taller growth is towards the center of the forest:"
]
},
{
@@ -974,7 +984,7 @@
"source": [
"# [Day 9](https://adventofcode.com/2022/day/9): Rope Bridge\n",
"\n",
- "The input consists of command lines, which we can parse as one tuple of two atoms (a command name and an integer) per line:"
+ "The input consists of command lines, each of which we can parse as a tuple of two atoms, a command name and an integer:"
]
},
{
@@ -1021,7 +1031,7 @@
"\n",
"#### Part 1: Simulate your complete hypothetical series of motions. How many positions does the tail of the rope visit at least once?\n",
"\n",
- "The rules for how the tail moves are a bit tricky, but otherwise the control flow is easy. I'll return the set of visited squares, in case I need it in part 2, but for this part I just need the size of the set. I provide for an optional starting position; this is arbitrary, but it makes it eeasier to follow the example in the puzzle description if I start at the same place they start at."
+ "The rules for how the tail moves are a bit tricky, but otherwise the control flow is easy. I'll return the set of visited squares (not just their count), in case I need it in part 2. I provide for an optional starting position; this is arbitrary, but it makes it easier to follow the example in the puzzle description if I start at the same place they start at."
]
},
{
@@ -1033,7 +1043,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "0.021 seconds for correct answer: 6,236\n"
+ "0.019 seconds for correct answer: 6,236\n"
]
}
],
@@ -1060,7 +1070,7 @@
" T = add(T, (0, sign(dy)))\n",
" return T\n",
" \n",
- "answer(9.1, 6236, lambda: len(move_rope(in9, (0, 4))))"
+ "answer(9.1, 6236, lambda: len(move_rope(in9)))"
]
},
{
@@ -1069,7 +1079,7 @@
"source": [
"#### Part 2: Simulate your complete series of motions on a larger rope with ten knots. How many positions does the tail of the rope visit at least once?\n",
"\n",
- "I'll re-write `move_rope` to take an optional argument giving the number of knots in the rope. Then instead of just one `move_tail` per loop, I'll move all the non-head knots in the rope, each one to follow the one immediately in front of it. I'll show that the re-write is backwards compatible by repeating the two-knot solution."
+ "I'll re-write `move_rope` to take an optional argument giving the number of knots in the rope. Then instead of just one `move_tail` per loop, I'll move all the non-head knots in the rope, each one to follow the one immediately in front of it. I'll show that the re-write is backwards compatible by repeating the two-knot solution from Part 1 and adding the ten-knot solution from Part 2:"
]
},
{
@@ -1082,14 +1092,15 @@
"output_type": "stream",
"text": [
"0.025 seconds for correct answer: 6,236\n",
- "0.111 seconds for correct answer: 2,449\n"
+ "0.109 seconds for correct answer: 2,449\n"
]
}
],
"source": [
"def move_rope(motions, start=(0, 4), knots=2) -> Set[Point]:\n",
+ " \"\"\"Move multi-`knots` rope according to `motions`; return set of points visited by tail.\"\"\"\n",
" deltas = dict(R=East, L=West, U=North, D=South)\n",
- " rope = [start] * knots\n",
+ " rope = [start] * knots # Positions of each knot in the rope\n",
" visited = {start}\n",
" for (op, n) in motions:\n",
" for _ in range(n):\n",
@@ -1099,8 +1110,8 @@
" visited.add(rope[-1])\n",
" return visited\n",
"\n",
- "answer(9.1, 6236, lambda: len(move_rope(in9, (0, 4))))\n",
- "answer(9.2, 2449, lambda: len(move_rope(in9, (0, 4), knots=10)))"
+ "answer(9.1, 6236, lambda: len(move_rope(in9)))\n",
+ "answer(9.2, 2449, lambda: len(move_rope(in9, knots=10)))"
]
},
{
@@ -1109,7 +1120,7 @@
"source": [
"#### Part 3: Exploration\n",
"\n",
- "Because I chose to return the set of visited points, I can plot the tail of the rope (for various size ropes):"
+ "I can plot the tail of the rope (for various size ropes). One interesting thing is that as the rope gets longer, the tail moves less. I guess the reason is that if any knot in the rope does not end up two spaces away from the one in front of it, then it does not move, and neither do any of the following knots. For a twisty-shaped rope this is bound to happen pretty frequently, so the tailmost knots move less often."
]
},
{
@@ -1178,6 +1189,28 @@
"square_plot(move_rope(in9, knots=20), '.');"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 33,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": "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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "square_plot(move_rope(in9, knots=100), '.');"
+ ]
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -1196,7 +1229,7 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 34,
"metadata": {},
"outputs": [
{
@@ -1234,12 +1267,14 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "We're never sure what we will need in Part 2, so I'll make the program interpreter output the cycle number and value of X for every cycle. For Part 1, we sum the product of these two for cycles in {20, 60, 100, ... 220}:"
+ "#### Part 1: Find the signal strength during the 20th, 60th, 100th, 140th, 180th, and 220th cycles. What is the sum of these six signal strengths?\n",
+ "\n",
+ "We're never sure what we will need in Part 2, so I'll make the program interpreter output the cycle number and value of X for every cycle. For Part 1, we sum the product of these two for cycles in {20, 60, ... 220}:"
]
},
{
"cell_type": "code",
- "execution_count": 34,
+ "execution_count": 35,
"metadata": {},
"outputs": [
{
@@ -1273,19 +1308,23 @@
"cell_type": "markdown",
"metadata": {},
"source": [
+ "\n",
+ "\n",
+ "#### Part 2: Render the image given by your program. What eight capital letters appear on your CRT?\n",
+ "\n",
"For Part 2 I'm glad I kept all the `(cycle, X)` pairs. I just need to map `cycle` to `(x, y)` positions on the screen, and plot the result. Then I'll use my eyeballs (not an OCR program) to determine what letters are indicated."
]
},
{
"cell_type": "code",
- "execution_count": 35,
+ "execution_count": 36,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "0.013 seconds for correct answer: PLPAFBCL\n"
+ "0.012 seconds for correct answer: PLPAFBCL\n"
]
},
{
@@ -1304,10 +1343,10 @@
"source": [
"def render(program):\n",
" \"\"\"As the cycle number scans a 40-pixel wide CRT, turn on pixels\n",
- " where register X and the scan position differ by 1 or less.x\"\"\"\n",
+ " where register X and the scan position differ by 1 or less.\"\"\"\n",
" points = []\n",
- " for (c, X) in run(program):\n",
- " x, y = (c - 1) % 40, (c - 1) // 40\n",
+ " for (cycle, X) in run(program):\n",
+ " x, y = (cycle - 1) % 40, (cycle - 1) // 40\n",
" if abs(X - x) <= 1:\n",
" points.append((x, y))\n",
" square_plot(points)\n",
@@ -1321,12 +1360,12 @@
"source": [
"# [Day 11](https://adventofcode.com/2022/day/11): Monkey in the Middle\n",
"\n",
- "The input is separated into paragraphs but each one has a complex structure describing a monkey. I'll define the function `parse_monkey` to parse the paragraph into an instance of the class `Monkey`. I'll use a regular expression, but I'll keep it as simple as possible, so I don't have [two problems](http://regex.info/blog/2006-09-15/247). The `Monkey` class has seven fields; the regular expression has seven groups, each of which is either digits `(\\d+)` or any characters `(.+)`."
+ "The input is separated into paragraphs where each paragraph is a complex structure describing a monkey. The function `parse_monkey` will parse the paragraph into an instance of the class `Monkey`. I'll use a regular expression, but I'll keep it as simple as possible, so I don't have [two problems](http://regex.info/blog/2006-09-15/247). The `Monkey` class has seven fields; the regular expression has seven `groups`, each of which is either digits `(\\d+)` or any characters `(.+)`. Nothing fancy!"
]
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": 37,
"metadata": {},
"outputs": [
{
@@ -1348,21 +1387,22 @@
"────────────────────────────────────────────────────────────────────────────────────────────────────\n",
"Parsed representation ➜ 8 Monkeys:\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────\n",
- "Monkey(num=0, items=(98, 97, 98, 55, 56, 72), op='*', arg=13, test=11, true=4, false=7)\n",
- "Monkey(num=1, items=(73, 99, 55, 54, 88, 50, 55), op='+', arg=4, test=17, true=2, false=6)\n",
- "Monkey(num=2, items=(67, 98), op='*', arg=11, test=5, true=6, false=5)\n",
- "Monkey(num=3, items=(82, 91, 92, 53, 99), op='+', arg=8, test=13, true=1, false=2)\n",
- "Monkey(num=4, items=(52, 62, 94, 96, 52, 87, 53, 60), op='*', arg='old', test=19, true=3, false=1)\n",
- "Monkey(num=5, items=(94, 80, 84, 79), op='+', arg=5, test=2, true=7, false=0)\n",
- "Monkey(num=6, items=(89,), op='+', arg=1, test=3, true=0, false=5)\n",
- "Monkey(num=7, items=(70, 59, 63), op='+', arg=3, test=7, true=4, false=3)\n"
+ "Monkey(n=0, items=(98, 97, 98, 55, 56, 72), op='*', arg=13, test=11, t=4, f=7)\n",
+ "Monkey(n=1, items=(73, 99, 55, 54, 88, 50, 55), op='+', arg=4, test=17, t=2, f=6)\n",
+ "Monkey(n=2, items=(67, 98), op='*', arg=11, test=5, t=6, f=5)\n",
+ "Monkey(n=3, items=(82, 91, 92, 53, 99), op='+', arg=8, test=13, t=1, f=2)\n",
+ "Monkey(n=4, items=(52, 62, 94, 96, 52, 87, 53, 60), op='*', arg='old', test=19, t=3, f=1)\n",
+ "Monkey(n=5, items=(94, 80, 84, 79), op='+', arg=5, test=2, t=7, f=0)\n",
+ "Monkey(n=6, items=(89,), op='+', arg=1, test=3, t=0, f=5)\n",
+ "Monkey(n=7, items=(70, 59, 63), op='+', arg=3, test=7, t=4, f=3)\n"
]
}
],
"source": [
- "Monkey = namedtuple('Monkey', 'num, items, op, arg, test, true, false')\n",
+ "Monkey = namedtuple('Monkey', 'n, items, op, arg, test, t, f')\n",
"\n",
- "monkey_regex = \"\"\"Monkey (\\d+):\n",
+ "monkey_regex = \"\"\"\\\n",
+ "Monkey (\\d+):\n",
" Starting items: (.+)\n",
" Operation: new = old (.) (.+)\n",
" Test: divisible by (\\d+)\n",
@@ -1371,9 +1411,8 @@
"\n",
"def parse_monkey(text) -> Monkey:\n",
" \"\"\"Parse a paragraph of text into a `Monkey`.\"\"\"\n",
- " match = re.search(monkey_regex, text)\n",
- " num, items, op, arg, test, true, false = match.groups()\n",
- " return Monkey(int(num), ints(items), op, atom(arg), int(test), int(true), int(false))\n",
+ " [(n, items, op, arg, test, t, f)] = re.findall(monkey_regex, text)\n",
+ " return Monkey(int(n), ints(items), op, atom(arg), int(test), int(t), int(f))\n",
"\n",
"in11 = parse(11, parse_monkey, paragraphs, show=8)"
]
@@ -1384,12 +1423,16 @@
"source": [
"#### Part 1: What is the level of monkey business after 20 rounds of stuff-slinging simian shenanigans?\n",
"\n",
- "Following the instructions for inspecting and throwing items requires careful attention, but is only a dozen lines or so. One thing to note: my `Monkey` class is immutable, That's a good thing: I don't want to modify the monkeys, because I want to be able to re-run calculations without having to re-parse the monkeys. So instead, my `inspect` function will keep track of which monkey has which items by using a dict, `items`. The whole point of `inspect` is to keep track of the number of items each monkey inspects in the `inspected` Counter, and return the Counter at the end. Then the function `monkey_business` can pick out the two busiest monkeys to compute the puzzle's final answer."
+ "Following the instructions for inspecting and throwing items requires careful attention, but is only a dozen lines or so. \n",
+ "\n",
+ "One thing to note: the monkeys will add and remove items from their purview, but my `Monkey` class is immutable. That's a good thing! I don't want to mutate the monkey data structures, because then I would have to re-parse the input file if I wanted to run a computation again. So instead, my `inspect` function will keep track of which monkey has which items by using a dict, `items`. \n",
+ "\n",
+ "The whole point of `inspect` is to keep track of the number of items each monkey inspects in the `inspected` Counter, and return the Counter at the end. Then the function `monkey_business` can pick out the two busiest monkeys to compute the puzzle's final answer."
]
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 38,
"metadata": {},
"outputs": [
{
@@ -1402,53 +1445,27 @@
],
"source": [
"def inspect(monkeys, rounds=1) -> Counter:\n",
- " \"\"\"Simulate the monkeys doing inspections for `rounds`; return the Counter of items inspected.\"\"\"\n",
+ " \"\"\"Simulate the monkeys doing inspections for `rounds`.\n",
+ " Don't mutate monkeys. Return a Counter of items inspected by each monkey.\"\"\"\n",
" inspected = Counter()\n",
- " items = {monkey.num: list(monkey.items) for monkey in monkeys}\n",
+ " items = {monkey.n: list(monkey.items) for monkey in monkeys}\n",
" ops = {'+': operator.add, '*': operator.mul, '-': operator.sub}\n",
" for round in range(rounds):\n",
" for monkey in monkeys:\n",
- " inspected[monkey.num] += len(items[monkey.num])\n",
- " for old in items[monkey.num]:\n",
- " new = ops[monkey.op](old, (old if monkey.arg == 'old' else monkey.arg)) // 3\n",
- " throw = (monkey.true if (new % monkey.test == 0) else monkey.false)\n",
+ " inspected[monkey.n] += len(items[monkey.n])\n",
+ " for old in items[monkey.n]:\n",
+ " arg = (old if monkey.arg == 'old' else monkey.arg)\n",
+ " new = ops[monkey.op](old, arg) // 3\n",
+ " throw = (monkey.t if (new % monkey.test == 0) else monkey.f)\n",
" items[throw].append(new)\n",
- " items[monkey.num] = [] \n",
+ " items[monkey.n] = [] \n",
" return inspected\n",
"\n",
"def monkey_business(inspected) -> int:\n",
" \"\"\"The product of the number of inspections by the two busiest monkeys.\"\"\"\n",
" return prod(sorted(inspected.values())[-2:])\n",
"\n",
- "answer(10.1, 54036, lambda: monkey_business(inspect(in11, 20)))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 38,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "CPU times: user 1.37 ms, sys: 7 µs, total: 1.37 ms\n",
- "Wall time: 1.37 ms\n"
- ]
- },
- {
- "data": {
- "text/plain": [
- "11140"
- ]
- },
- "execution_count": 38,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "%time len(str(13**10000))"
+ "answer(11.1, 54036, lambda: monkey_business(inspect(in11, 20)))"
]
},
{
@@ -1457,11 +1474,11 @@
"source": [
"#### Part 2: Worry levels are no longer divided by three after each item is inspected; you'll need to find another way to keep your worry levels manageable. Starting again from the initial state in your puzzle input, what is the level of monkey business after 10000 rounds?\n",
"\n",
- "The puzzle instructions are warning me that worry levels will get quite high. Certainly too high for a 64-bit int, but probably much higher. For example, monkey 0 multiplies the worry level by 13, and 1310,000 is a number with more than 10,000 digits. \n",
+ "The puzzle instructions are warning me that worry levels will be so high that they are unmanageable. Did they mean too high for a 64-bit int, or too high even for a language like Python with arbitrary-length integers? I ran `inspect` for 200 rounds and found the largest worry level was over a million digits. I don't think a run for 10,000 rounds is feasible.\n",
"\n",
- "\"No problem!,\" I thought to myself; since each monkey only uses the worry level to see if it is divisible by their test number, we can just use the worry level modulo the test number. I tried that, and was pleased that 10,000 rounds executed very quickly. But I was disappointed AoC told me my answer was wrong. \n",
+ "\"No problem!,\" I thought to myself; since each monkey uses the worry level for one purpose only–to see if it is divisible by their test number–we should be able to compute with the worry level modulo the test number. I tried that, but AoC told me that my answer was wrong. \n",
"\n",
- "So I thought to myself again. I figured out that the issue is that worry levels get passed around, and the next monkey will have a different test number. So I want to be working with worry levels modulo the product of *all* the monkey's test numbers. (It could be the least common multiple, but product works fine). I tried that and it works. I re-wrote `inspect` to specify the boredom level; by default it is 3, to do the calculation for Part 1, but if you specify `boredom=None`, then the calculation works for Part 2."
+ "So I thought to myself again. Harder. My error was that worry levels get passed from one monkey to the next, and the next monkey will have a different test number, and should be dealing with worry levels modulo *that* test number. So I should be working with worry levels modulo the product of *all* the monkeys' test numbers; I call this product `m`. (I could use the least common multiple, but product works fine). My revision of`inspect` is backwards compatible, does all worry computations modulo `m`, and takes an optional argument, the `boredom` factor, which by default is 3 (for Part 1), but you specify `boredom=1` for Part 2."
]
},
{
@@ -1474,30 +1491,236 @@
"output_type": "stream",
"text": [
"0.001 seconds for correct answer: 54,036\n",
- "0.282 seconds for correct answer: 13,237,873,355\n"
+ "0.285 seconds for correct answer: 13,237,873,355\n"
]
}
],
"source": [
"def inspect(monkeys, rounds=1, boredom=3) -> Counter:\n",
- " \"\"\"Simulate the monkeys doing inspections for `rounds`; return the Counter of items inspected.\"\"\"\n",
+ " \"\"\"Simulate the monkeys doing inspections for `rounds`.\n",
+ " Don't mutate monkeys. Return a Counter of items inspected by each monkey.\n",
+ " Compute worry levels modulo the product of all the monkeys' test numbers.\"\"\"\n",
" inspected = Counter()\n",
- " items = {monkey.num: list(monkey.items) for monkey in monkeys}\n",
+ " items = {monkey.n: list(monkey.items) for monkey in monkeys}\n",
" ops = {'+': operator.add, '*': operator.mul, '-': operator.sub}\n",
" m = prod(monkey.test for monkey in monkeys)\n",
" for round in range(rounds):\n",
" for monkey in monkeys:\n",
- " inspected[monkey.num] += len(items[monkey.num])\n",
- " for old in items[monkey.num]:\n",
- " new = ops[monkey.op](old, (old if monkey.arg == 'old' else monkey.arg)) % m\n",
- " if boredom: new = new // boredom\n",
- " throw = (monkey.true if (new % monkey.test == 0) else monkey.false)\n",
+ " inspected[monkey.n] += len(items[monkey.n])\n",
+ " for old in items[monkey.n]:\n",
+ " arg = (old if monkey.arg == 'old' else monkey.arg)\n",
+ " new = (ops[monkey.op](old, arg) % m) // boredom\n",
+ " throw = (monkey.t if (new % monkey.test == 0) else monkey.f)\n",
" items[throw].append(new)\n",
- " items[monkey.num] = [] \n",
+ " items[monkey.n] = [] \n",
" return inspected\n",
"\n",
- "answer(10.1, 54036, lambda: monkey_business(inspect(in11, 20)))\n",
- "answer(10.2, 13237873355, lambda: monkey_business(inspect(in11, 10_000, boredom=None)))"
+ "answer(11.1, 54036, lambda: monkey_business(inspect(in11, 20)))\n",
+ "answer(11.2, 13237873355, lambda: monkey_business(inspect(in11, 10_000, boredom=1)))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# [Day 12](https://adventofcode.com/2022/day/12): Hill Climbing Algorithm\n",
+ "\n",
+ "The input is a grid of heights, from `'a'` (low) to `'z'` (high), with two special heights, `'S'` for the start location (the lowest) and `'E'` for the end location (the highest height, with the best signal reception). I'll use `Grid(parse(...))` as I've done before, and define `hill_height` to translate the letter heights to integers:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+ "Puzzle input ➜ 41 lines:\n",
+ "────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+ "abccccccccaaaaaaaccaaaaaaaaaaaaaaaaccccccccccccccccccccccccccccccccccccaaaaaa\n",
+ "abccccccccaaaaaaaccaaaaaaaaaaaaaaaaccccccccccccccccccccccccccccccccccccaaaaaa\n",
+ "abccccccccccaaaaaaccaaaaaaaaaaaaaaaaccccccccccccccccacccccccccccccccccccaaaaa\n",
+ "abcccccaaaacaaaaaaccaaaaaaaaaaaaaaaaacccccccccccccccaaaccccaccccccccccccccaaa\n",
+ "abccccaaaaacaaccccccaaaaaacaaacaacaaaaaaacccccccccccaaaacccaacccccccccccccaaa\n",
+ "abaaccaaaaaaccccaaacaaaacacaaacaaccaaaaaacccccccccccaklaccccccccccccccccccaac\n",
+ "...\n",
+ "────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+ "Parsed representation ➜ 41 tuples:\n",
+ "────────────────────────────────────────────────────────────────────────────────────────────────────\n",
+ "(1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...\n",
+ "(1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...\n",
+ "(1, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...\n",
+ "(1, 2, 3, 3, 3, 3, 3, 1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...\n",
+ "(1, 2, 3, 3, 3, 3, 1, 1, 1, 1, 1, 3, 1, 1, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 1, 1, 3, 1, 1, 1, 3, 1, ...\n",
+ "(1, 2, 1, 1, 3, 3, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 1, 1, 1, 3, 1, 1, 1, 1, 3, 1, 3, 1, 1, 1, 3, 1, ...\n",
+ "...\n"
+ ]
+ }
+ ],
+ "source": [
+ "def hill_height(line, heights='SabcdefghijklmnopqrstuvwxyzE') -> Tuple[int]: \n",
+ " \"\"\"Translate each letter in `line` into a height from 0 to 27.\"\"\"\n",
+ " return tuple(map(heights.index, line))\n",
+ "\n",
+ "in12 = Grid(parse(12, hill_height))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Part 1: What is the fewest steps required to move from your current position to the location that should get the best signal?\n",
+ "\n",
+ "The function `hill_climb` will pick out the initial and goal locations and call `A_star_search`. This isn't a generic `GridProblem` though, because we can't transition to *any* neighbor, only to the ones that are no more than one unit higher. The class `HillClimbProblem` imposes that constraint:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.035 seconds for correct answer: 394\n"
+ ]
+ }
+ ],
+ "source": [
+ "def hill_climb(grid) -> Node:\n",
+ " \"\"\"Find the initial and goal locations in grid, and return a least-cost path.\"\"\"\n",
+ " initial = the(loc for loc in grid if grid[loc] == 0)\n",
+ " goal = the(loc for loc in grid if grid[loc] == 27)\n",
+ " return A_star_search(HillClimbProblem(initial, goal, grid=grid))\n",
+ "\n",
+ "class HillClimbProblem(GridProblem):\n",
+ " \"\"\"A GridProblem where you can't climb upward more than one height amount per step.\"\"\"\n",
+ " \n",
+ " def action_cost(self, s1, a, s2): return 1\n",
+ " \n",
+ " def actions(self, loc):\n",
+ " \"\"\"All neighboring squares that are no more than one unit higher.\"\"\"\n",
+ " grid = self.grid\n",
+ " return [p for p in grid.neighbors(loc) if grid[p] <= grid[loc] + 1]\n",
+ " \n",
+ "answer(12.1, 394, lambda: hill_climb(in12).path_cost)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Part 2: What is the fewest steps required to move starting from any square with elevation *a* to the location that should get the best signal?\n",
+ "\n",
+ "Part 2 asks what the shortest path would be if we could start at any location with height 1 (represented by an `'a'` in the input). I could repeat the search for each such location. How many would that be?"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "930"
+ ]
+ },
+ "execution_count": 42,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "Counter(in12.values())[1]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Almost a thousand locations; so the search would take over 30 seconds. [Who's got that kind of time?](https://www.gocomics.com/calvinandhobbes/1995/08/17) Instead I'll invent yet another problem subclass, `HillClimbProblem2`, which starts at a dummy state that is off the grid, and can transition with zero cost from that state to any location with height 1:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 43,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.038 seconds for correct answer: 388\n"
+ ]
+ }
+ ],
+ "source": [
+ "off_grid = (-1, -1) # A dummy location that is not on grid\n",
+ "\n",
+ "def hill_climb2(grid) -> Node:\n",
+ " goal = the(loc for loc in grid if grid[loc] == 27)\n",
+ " return A_star_search(HillClimbProblem2(off_grid, goal, grid=grid))\n",
+ "\n",
+ "class HillClimbProblem2(GridProblem):\n",
+ " \"\"\"A GridProblem where heights are letters, and you can't climb upward more than one letter.\"\"\"\n",
+ " \n",
+ " def action_cost(self, s1, a, s2): return 0 if s1 == off_grid else 1\n",
+ " \n",
+ " def actions(self, loc):\n",
+ " grid = self.grid\n",
+ " if loc == off_grid:\n",
+ " return [p for p in grid if grid[p] == 1] # Go to any location with an `a`\n",
+ " else:\n",
+ " return [p for p in grid.neighbors(loc) if grid[p] <= grid[loc] + 1]\n",
+ " \n",
+ "answer(12.2, 388, lambda: hill_climb2(in12).path_cost)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Part 3: Exploration\n",
+ "\n",
+ "I'm interested in seeing what the landscape looks like. We can repurpose the code used to show the forest:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 44,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "path = path_states(hill_climb(in12))\n",
+ "\n",
+ "square_plot(path, 'r-',\n",
+ " extra=lambda: plt.scatter(*T(in12), c=list(in12.values()), \n",
+ " cmap=plt.get_cmap('YlGn')))"
]
},
{
@@ -1511,7 +1734,7 @@
},
{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": 45,
"metadata": {},
"outputs": [
{
@@ -1521,7 +1744,7 @@
" 1.2: '0.000 seconds for correct answer: 206,582',\n",
" 2.1: '0.001 seconds for correct answer: 13,268',\n",
" 2.2: '0.001 seconds for correct answer: 15,508',\n",
- " 3.1: '0.001 seconds for correct answer: 8,401',\n",
+ " 3.1: '0.000 seconds for correct answer: 8,401',\n",
" 3.2: '0.000 seconds for correct answer: 2,641',\n",
" 4.1: '0.000 seconds for correct answer: 477',\n",
" 4.2: '0.000 seconds for correct answer: 830',\n",
@@ -1531,15 +1754,19 @@
" 6.2: '0.002 seconds for correct answer: 3,059',\n",
" 7.1: '0.001 seconds for correct answer: 1,232,307',\n",
" 7.2: '0.001 seconds for correct answer: 7,268,994',\n",
- " 8.1: '0.048 seconds for correct answer: 1,829',\n",
+ " 8.1: '0.049 seconds for correct answer: 1,829',\n",
" 8.2: '0.054 seconds for correct answer: 291,840',\n",
" 9.1: '0.025 seconds for correct answer: 6,236',\n",
- " 9.2: '0.111 seconds for correct answer: 2,449',\n",
- " 10.1: '0.001 seconds for correct answer: 54,036',\n",
- " 10.2: '0.282 seconds for correct answer: 13,237,873,355'}"
+ " 9.2: '0.109 seconds for correct answer: 2,449',\n",
+ " 10.1: '0.000 seconds for correct answer: 12,560',\n",
+ " 10.2: '0.012 seconds for correct answer: PLPAFBCL',\n",
+ " 11.1: '0.001 seconds for correct answer: 54,036',\n",
+ " 11.2: '0.285 seconds for correct answer: 13,237,873,355',\n",
+ " 12.1: '0.035 seconds for correct answer: 394',\n",
+ " 12.2: '0.038 seconds for correct answer: 388'}"
]
},
- "execution_count": 40,
+ "execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}