參考鏈接：https://pypi.org/project/intervaltree/
安裝：

pip install intervaltree

或者參考：
https://anaconda.org/conda-forge/intervaltree

conda install conda-forge::intervaltree
conda install conda-forge/label/cf201901::intervaltree
conda install conda-forge/label/cf202003::intervaltree
conda install conda-forge/label/gcc7::intervaltree

首先介紹Intervel

from intervaltree import Interval, IntervalTree
iv = Interval(4,6,(4,6))
print(iv.begin)
print(iv.end)
print(iv.data)

begin, end , data = iv
print(begin)
print(end)
print(data)

這個(gè)工具用于標(biāo)記文本和時(shí)間的范圍，其中包括下限不包括上限
關(guān)于初始化

Initializing
blank tree = IntervalTree()
from an iterable of Interval objects (tree = IntervalTree(intervals))
from an iterable of tuples (tree = IntervalTree.from_tuples(interval_tuples))
創(chuàng)建一個(gè)空白的IntervalTree

from intervaltree import Interval, IntervalTree
t = IntervalTree()
t

關(guān)于插入

t = IntervalTree()
t[1:2] = "1-2"
t[4:7] = (4, 7)
t[5:9] = {5: 9}
print(t)

###增加
test1 = Interval(100,200, "test1")
print(test1)
t.add(test1)
print(t)
##使用.addi直接添加
t.addi(30,40,"test2")
t.addi(1000, 2000, "test3")
print(t)
##刪除

IntervalTree([Interval(1, 2, '1-2'), Interval(4, 7, (4, 7)), Interval(5, 9, {5: 9})])
Interval(100, 200, 'test1')
IntervalTree([Interval(1, 2, '1-2'), Interval(4, 7, (4, 7)), Interval(5, 9, {5: 9}), Interval(100, 200, 'test1')])
IntervalTree([Interval(1, 2, '1-2'), Interval(4, 7, (4, 7)), Interval(5, 9, {5: 9}), Interval(30, 40, 'test2'), Interval(100, 200, 'test1'), Interval(1000, 2000, 'test3')])

關(guān)于刪除

Deletions
tree.remove(interval) (raises ValueError if not present)
tree.discard(interval) (quiet if not present)
tree.removei(begin, end, data) (short for tree.remove(Interval(begin, end, data)))
tree.discardi(begin, end, data) (short for tree.discard(Interval(begin, end, data)))
tree.remove_overlap(point)
tree.remove_overlap(begin, end) (removes all overlapping the range)
tree.remove_envelop(begin, end) (removes all enveloped in the range)

print("初始狀態(tài)", t)
t.remove(Interval(1, 2, '1-2'))
print("第一次刪除", t)
t.discard(Interval(4, 7, (4, 7)))
print("第二次刪除", t)

#使用.removei以及.discardi簡化刪除
t.removei(5, 9, {5: 9})
print("第三次刪除",t )

###使用.remove_overlap()根據(jù)點(diǎn)的位置刪除
t.remove_overlap(35)
print("第四次刪除", t )

###使用.remove_overlap(begin, end) 根據(jù)區(qū)域是否重疊刪除
t.remove_overlap(50,101)
print("第五次刪除", t)

raw_data IntervalTree([Interval(1, 2, '1-2'), Interval(4, 7, (4, 7)), Interval(5, 9, {5: 9}), Interval(30, 40, 'test2'), Interval(100, 200, 'test1')])
第一次刪除 IntervalTree([Interval(4, 7, (4, 7)), Interval(5, 9, {5: 9}), Interval(30, 40, 'test2'), Interval(100, 200, 'test1')])
第二次刪除 IntervalTree([Interval(5, 9, {5: 9}), Interval(30, 40, 'test2'), Interval(100, 200, 'test1')])
第三次刪除 IntervalTree([Interval(30, 40, 'test2'), Interval(100, 200, 'test1')])
第四次刪除 IntervalTree([Interval(100, 200, 'test1')])
第五次刪除 IntervalTree()

根據(jù)位置(點(diǎn)或者區(qū)域信息)查找區(qū)域

##根據(jù)點(diǎn)查找
##.search有的版本中已經(jīng)被替換了
tree = IntervalTree()
tree.addi(10,30,'test1')
tree.add(Interval(20,40, "test2"))
print(tree)
print("由點(diǎn)找區(qū)域", tree[20])
print("由點(diǎn)找區(qū)域", tree.at(25))
print("由點(diǎn)找區(qū)域",tree[100])
print("尋找交集區(qū)域",tree.overlap(25,30))
print("尋找包含的區(qū)域", tree.envelop(10,15))
print("尋找包含的區(qū)域", tree.envelop(10,100))

IntervalTree([Interval(10, 30, 'test1'), Interval(20, 40, 'test2')])
由點(diǎn)找區(qū)域 {Interval(20, 40, 'test2'), Interval(10, 30, 'test1')}
由點(diǎn)找區(qū)域 {Interval(20, 40, 'test2'), Interval(10, 30, 'test1')}
由點(diǎn)找區(qū)域 set()
尋找交集區(qū)域 {Interval(20, 40, 'test2'), Interval(10, 30, 'test1')}
尋找包含的區(qū)域 set()
尋找包含的區(qū)域 {Interval(20, 40, 'test2'), Interval(10, 30, 'test1')}

判斷所屬關(guān)系

#判斷所屬關(guān)系

print(tree)
print(Interval(10, 30, 'test1') in tree)
print(tree.overlaps(30))
print(tree.containsi(20,25))
print(tree.containsi(10,30))
print(tree.containsi(10,30, "test1"))

合并

# 創(chuàng)建第一個(gè) IntervalTree 對象
tree1 = IntervalTree()
tree1.addi(10, 20)
tree1.addi(30, 40)

# 創(chuàng)建第二個(gè) IntervalTree 對象
tree2 = IntervalTree()
tree2.addi(15, 25)
tree2.addi(35, 45)

# 將兩個(gè) IntervalTree 對象合并
result_tree = tree1.union(tree2)
print("合并方法一",result_tree) 
result_tree = tree1 | tree2
print("合并方法二",result_tree)
result_tree = tree1.update(tree2)
print("合并方法三", result_tree)
tree1 |= tree2
print("合并方法四",tree1)

合并方法一 IntervalTree([Interval(10, 20), Interval(15, 25), Interval(30, 40), Interval(35, 45)])
合并方法二 IntervalTree([Interval(10, 20), Interval(15, 25), Interval(30, 40), Interval(35, 45)])
合并方法三 None
合并方法四 IntervalTree([Interval(10, 20), Interval(15, 25), Interval(30, 40), Interval(35, 45)])

###第三種不知道為啥沒成

切分區(qū)域 slicing

t = IntervalTree([Interval(0, 10), Interval(5, 15), Interval(0,13)])
t.slice(3)


IntervalTree([Interval(0, 3), Interval(3, 10), Interval(3, 13), Interval(5, 15)])

我理解為砍掉一部分區(qū)域

t = IntervalTree([Interval(0, 10), Interval(5,8)])
t.chop(3, 7)

IntervalTree([Interval(0, 3), Interval(7, 8), Interval(7, 10)])
##就把3到7的區(qū)域都砍了