Minor cleaning 2023.
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9f96abbd43
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19
poetry.lock
generated
19
poetry.lock
generated
@ -566,6 +566,23 @@ doc = ["nb2plots (>=0.7)", "nbconvert (<7.9)", "numpydoc (>=1.6)", "pillow (>=9.
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extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.11)", "sympy (>=1.10)"]
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test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
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[[package]]
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name = "networkx-stubs"
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version = "0.0.1"
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description = "Typing stubs for NetworkX"
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optional = false
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python-versions = "*"
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files = [
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{file = "networkx-stubs-0.0.1.tar.gz", hash = "sha256:1751cbc87898328f89d79476ec6363174c05f9e48592f0953cc1077188717a21"},
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{file = "networkx_stubs-0.0.1-py3-none-any.whl", hash = "sha256:ce58dff9b9dcbfdf895d0fce20fa8a73f2e82e581004596b7552086b5bb91366"},
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]
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[package.dependencies]
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networkx = "*"
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[package.extras]
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dev = ["black", "flake8", "flake8-black", "flake8-pyi", "mypy", "setuptools", "wheel"]
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[[package]]
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name = "nodeenv"
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version = "1.8.0"
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@ -1375,4 +1392,4 @@ files = [
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[metadata]
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lock-version = "2.0"
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python-versions = "^3.10"
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content-hash = "b05e052aed9ec92c0edf386f9143271d69f3fc6e4c56a638721a16d7fcb2065b"
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content-hash = "0b582360ca444fe39469eaa4a242c74c516ef5e1cf8d4d69be7623dbbd3d6e6b"
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@ -45,6 +45,7 @@ isort = "^5.13.2"
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ruff = "^0.1.8"
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poethepoet = "^0.24.4"
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ipykernel = "^6.27.1"
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networkx-stubs = "^0.0.1"
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[build-system]
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requires = ["poetry-core"]
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@ -1,11 +1,8 @@
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import sys
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from collections import defaultdict
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from dataclasses import dataclass
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import numpy as np
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from sympy import solve, symbols
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lines = sys.stdin.read().splitlines()
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positions = [
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@ -19,7 +16,7 @@ velocities = [
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low, high = [7, 27] if len(positions) <= 10 else [200000000000000, 400000000000000]
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count = 0
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for i, (p1, v1) in enumerate(zip(positions, velocities)):
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for p2, v2 in zip(positions[i + 1:], velocities[i + 1:]):
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for p2, v2 in zip(positions[i + 1 :], velocities[i + 1 :]):
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p, r = p1[:2], v1[:2]
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q, s = p2[:2], v2[:2]
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@ -31,7 +28,7 @@ for i, (p1, v1) in enumerate(zip(positions, velocities)):
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continue
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else:
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assert rs != 0
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t = np.cross((q - p), s) / rs
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t = np.cross((q - p), s) / rs
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u = np.cross((q - p), r) / rs
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if t >= 0 and u >= 0:
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@ -50,14 +47,16 @@ print(f"answer 1 is {answer_1}")
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# p3 + t3 * v3 == p0 + t3 * v0
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# ...
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# pn + tn * vn == p0 + tn * v0
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#
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#
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# we can solve with only 3 lines since each lines contains 3
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# we can solve with only 3 lines since each lines contains 3
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# equations (x / y / z), so 3 lines give 9 equations and 9
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# variables: position (3), velocities (3) and times (3).
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n = 3
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x, y, z, vx, vy, vz, *ts = symbols('x y z vx vy vz ' + ' '.join(f't{i}' for i in range(n + 1)))
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x, y, z, vx, vy, vz, *ts = symbols(
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"x y z vx vy vz " + " ".join(f"t{i}" for i in range(n + 1))
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)
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equations = []
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for i, ti in zip(range(n), ts):
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for p, d, pi, di in zip((x, y, z), (vx, vy, vz), positions[i], velocities[i]):
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@ -1,24 +1,20 @@
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import sys
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from collections import defaultdict
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from dataclasses import dataclass
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import networkx as nx
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components = {
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(p := line.split(": "))[0]: p[1].split() for line in sys.stdin.read().splitlines()
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}
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targets = {
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t for c in components for t in components[c] if t not in components
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}
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targets = {t for c in components for t in components[c] if t not in components}
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G = nx.Graph()
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G.add_nodes_from(list(components) + list(targets))
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G.add_edges_from((u, v) for u, vs in components.items() for v in vs)
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graph = nx.Graph()
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graph.add_edges_from((u, v) for u, vs in components.items() for v in vs)
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cut = nx.minimum_edge_cut(G)
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G.remove_edges_from(cut)
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cut = nx.minimum_edge_cut(graph)
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graph.remove_edges_from(cut)
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c1, c2 = nx.connected_components(G)
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c1, c2 = nx.connected_components(graph)
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# part 1
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answer_1 = len(c1) * len(c2)
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