📅  最后修改于: 2023-12-03 14:58:06.910000             🧑  作者: Mango
在本题中,我们需要考虑如何通过水平或垂直放置给定的 N 个矩形来最大化上边界的长度。这是一个典型的矩形装箱问题,需要找到一种最优的布局方案。
为了实现最优的布局方案,我们可以使用贪心算法。下面是具体的实现步骤:
# sort rectangles by width
rectangles.sort(key=lambda r: r[0])
# find center point of each rectangle by height
centers = [(rect[1] / 2, rect[2] / 2) for rect in rectangles]
# initialize row_heights and col_heights
row_heights = [0]
col_heights = [0]
# iterate through each rectangle and place it in the best row or column
for i, rect in enumerate(rectangles):
# find the best row or column to place the current rectangle
row = min(enumerate(row_heights), key=lambda x: x[1])[0]
col = min(enumerate(col_heights), key=lambda x: x[1])[0]
# find the center point of the rectangle
center = centers[i]
# place the rectangle in the best row or column
if col_heights[col] <= row_heights[row]:
# place the rectangle in the current column
col_heights[col] += rect[2]
x = col * rect[0] + rect[0] / 2
y = col_heights[col] - rect[2] + center[0]
else:
# place the rectangle in a new column
col_heights.append(rect[2])
x = len(col_heights) * rect[0] + rect[0] / 2
y = rect[2] / 2
# update row_heights if necessary
if col_heights[col] > row_heights[row]:
row_heights[row] = col_heights[col]
# calculate the length of the top boundary
top_boundary = max(row_heights + col_heights)
print(top_boundary)