[英]Iterative euclidean distance calculation between consecutive points (x,y tuples) which belongs to a list of lines
[英]Solving a function that measures distance between points in a list of points (x, y)
我正在寫一個函數路由。 這個函數有一個強制參數points,它接受一個點列表。 如果依次訪問給定列表中的每個點,則該函數必須返回行進的總距離。 除了強制參數外,該函數還有兩個可選參數:
循環:取一個布爾值,指示路線的終點是否等於其起點(真)或不等於(假); 此參數的默認值為 False
distance:采用距離函數,用於計算給定路徑中兩個連續點之間的總距離; 如果沒有明確的值傳遞給這個參數,則必須使用歐幾里德距離
問題:任何人都知道最后一個定義 route() 如何解決這個問題:
route([(41.79, 13.59), (41.68, 14.65), (21.16, -4.79)], distance=lambda p1, p2: abs(p1[0] + p2[0]))
正確答案:146.31
我引用的部分代碼:
if cycle == False and distance is λ(p1, p2): abs(p1[0] + p2[0]):
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = euclidean(a[0], b[0])
l.append(d)
count += 1
return sum(l)
在這部分中,我陷入了第一條規則和更遠的地方。
工作正常的完整代碼(除了上面的部分):
def euclidean(a, b):
'''
>>> euclidean((42.36, 56.78), (125.65, 236.47))
198.05484139500354
'''
from math import sqrt
return sqrt(sum((a - b)**2 for a, b in zip(a, b)))
def manhattan(c, d):
'''
>>> manhattan((42.36, 56.78), (125.65, 236.47))
262.98
'''
return sum(abs(c - d) for c, d in zip(c, d))
def chessboard(e, f):
'''
>>> chessboard((42.36, 56.78), (125.65, 236.47))
179.69
'''
return max(abs(e - f) for e, f in zip(e, f))
def route(points, cycle=False, distance=None):
'''
>>> route([(6.59, 6.73), (4.59, 5.54), (5.33, -13.98)])
21.861273201261746
>>> route(cycle=True, points=[(6.59, 6.73), (4.59, 5.54), (5.33, -13.98)])
42.60956710702662
>>> route([(6.59, 6.73), (4.59, 5.54), (5.33, -13.98)], distance=manhattan)
23.45
>>> route([(6.59, 6.73), (4.59, 5.54), (5.33, -13.98)], cycle=True, distance=manhattan)
45.42
'''
if cycle == False and distance is None:
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = euclidean(a, b)
l.append(d)
count += 1
return sum(l)
if cycle == False and distance is euclidean:
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = euclidean(a, b)
l.append(d)
count += 1
return sum(l)
if cycle == False and distance is λ(p1, p2): abs(p1[0] + p2[0]):
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = euclidean(a[0], b[0])
l.append(d)
count += 1
return sum(l)
if cycle == True and distance is None:
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = euclidean(a, b)
l.append(d)
count += 1
f = points[0]
g = points[-1]
r = euclidean(g, f)
k = sum(l) + r
return k
if cycle == True and distance is euclidean:
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = euclidean(a, b)
l.append(d)
count += 1
f = points[0]
g = points[-1]
r = euclidean(g, f)
k = sum(l) + r
return k
if cycle is False and distance is manhattan:
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = manhattan(a, b)
l.append(d)
count += 1
return sum(l)
if cycle is True and distance is manhattan:
l = list()
count = 0
for items in range(len(points)-1):
a = points[items]
b = points[items+1]
d = manhattan(a, b)
l.append(d)
count += 1
f = points[0]
g = points[-1]
r = manhattan(g, f)
k = sum(l) + r
return k
我同意鄧肯。 你有太多的重復。 這里有一個更直接的方法:
euclidean = lambda p1, p2: sqrt(sum((p1_i - p2_i)**2 for p1_i, p2_i in zip(p1, p2)))
manhattan = lambda p1, p2: sum(abs(p1_i - p2_i) for p1_i, p2_i in zip(p1, p2))
chessboard = lambda p1, p2: max(abs(p1_i - p2_i) for p1_i, p2_i in zip(p1, p2))
def route(points, cycle=False, metric=euclidean):
l = 0.0
for i in range(len(points) - 1):
l += metric(points[i], points[i + 1])
if cycle:
l += metric(points[-1], points[0])
return l
可以傳遞任何度量函數,然后使用它來代替歐幾里德度量。
聲明:本站的技術帖子網頁,遵循CC BY-SA 4.0協議,如果您需要轉載,請注明本站網址或者原文地址。任何問題請咨詢:yoyou2525@163.com.