dost

@@ -1,10 +1,12 @@

 import itertools

 import math

-import random

+import re

+import sys

 import time

 import turtle

 import typing

 import collections.abc

+import Levenshtein

 Func: typing.TypeAlias = collections.abc.Callable

 DistTable: typing.TypeAlias = list[list[float]]

@@ -149,13 +151,8 @@ def scattered_hierarchy(hierarchy: BinaryTree) -> IndSeq:

 def total_len(distances: DistTable, seq: IndSeq) -> float:

     return sum(distances[i][j] for (i, j) in itertools.pairwise(seq))

-N = 100

-points: list[tuple[float, float]] = [(random.randint(0, N // 2), random.randint(0, N // 3)) for _ in range(N)]

-print(points)

-t: turtle.Turtle = turtle.Turtle()

-t.hideturtle()

-t.pen(speed=10)

-dt: DistTable = distance_table(points, math.dist)

+points: list[str] = [l.strip() for l in sys.stdin]

+dt: DistTable = distance_table(points, lambda a, b: Levenshtein.distance(a, b, weights=(1, 1, 3)))

 print(show_mat(dt))

 to = time.time()

 h: BinaryTree = distance_hierarchy(dt)

@@ -167,16 +164,11 @@ METHODS = [

     ("nearest-nb sum", lambda: greedy_min_seq(dt, score_nearest)),

     ("maximin", lambda: greedy_maximin(dt)),

 ]

-input("ready?")

 for (name, method) in METHODS:

     to = time.time()

     seq = method()

     tf = time.time()

     l = total_len(dt, seq)

     print(f"{name} method took {tf - to} s to find {seq}, length {l}")

-    t.clear()

-    for (i, (x, y)) in enumerate(points[k] for k in seq):

-        t.teleport(2000 / N * (x - 0.25 * N), 2000 / N * (y - 0.17 * N))

-        t.dot(20 / math.sqrt(i + 1))

-        t.write(i)

-    input("next?")

+    for k in seq[:int(math.sqrt(len(points)))]:

+        print("\t" + points[k])