PST什么时候从左到右和从右到左显示上下文?
When does PST display contexts from left to right and right to left?
PST
包是否总是从右到左显示上下文?
在query()
函数中我们使用字符串来表示上下文。如果我假设上下文是从右到左指定的(因为它似乎在 print()
和 cmine()
函数中),并且我对序列 A->B->C
感兴趣,那么我应该查询:
query(S1.p1, "C-B-A")
?
此外,在 predict()
函数中,我们使用 seqdef()
定义要预测的序列。这是否意味着我应该像 TraMineR 通常那样从左到右指定它们?
x <- seqdef("A-B-C)
predict(S1.p1, x)
?
在概率后缀树 (PST) 中,当我们从根开始读取后缀时,分支定义了从右到左的后缀。在第一层,您有后缀的最后一个元素,在第二层,您有最后一个元素之前的元素,等等。打印的树显示为根在左侧,并从左到右展开。尽管如此,打印结果节点中显示的后缀应该自然地从左到右阅读。例如,节点 a-b-c
表示末尾带有 c
的后缀。这样的节点是从节点b-c
左边加上a
得到的
cmine
的结果也是如此。对于每个找到的上下文,例如a-b-c
、cmine
给出了在上下文之后立即获得每个可能状态的概率,即在示例中的 c
之后。
总而言之,序列和上下文总是从左到右显示,即使上下文是从右到左构建的。
因此,如果您想查询序列 A->B->C
,只需使用 query(S1.p1, "A-B-C")
。同样,要用 predict
预测特定序列,自然地从左到右定义序列。
序列应从左到右阅读。以下代码对此进行了验证:
library(PST)
data.seq <- seqdef("A-B-C-D-E-F")
S1.test <- pstree(data.seq, ymin = 0.001, lik = FALSE, with.missing = FALSE)
print(S1.test)
--(e)-[ p=(0.2,0.2,0.2,0.2,0.2,0.2) - n=6 ]
`--(A)-[ p=(0.001,0.995,0.001,0.001,0.001,0.001) - n=1 ]--|
`--(B)-[ p=(0.001,0.001,0.995,0.001,0.001,0.001) - n=1 ]
`--(A-B)-[ p=(0.001,0.001,0.995,0.001,0.001,0.001) - n=1 ]--|
`--(C)-[ p=(0.001,0.001,0.001,0.995,0.001,0.001) - n=1 ]
`--(B-C)-[ p=(0.001,0.001,0.001,0.995,0.001,0.001) - n=1 ]
`--(A-B-C)-[ p=(0.001,0.001,0.001,0.995,0.001,0.001) - n=1 ]--|
`--(D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]
`--(C-D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]
`--(B-C-D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]
`--(A-B-C-D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]--|
`--(E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(C-D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(B-C-D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(A-B-C-D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]--|
plot(S1.test)
这也表明绘制的树应该从下到上阅读。
PST
包是否总是从右到左显示上下文?
在query()
函数中我们使用字符串来表示上下文。如果我假设上下文是从右到左指定的(因为它似乎在 print()
和 cmine()
函数中),并且我对序列 A->B->C
感兴趣,那么我应该查询:
query(S1.p1, "C-B-A")
?
此外,在 predict()
函数中,我们使用 seqdef()
定义要预测的序列。这是否意味着我应该像 TraMineR 通常那样从左到右指定它们?
x <- seqdef("A-B-C)
predict(S1.p1, x)
?
在概率后缀树 (PST) 中,当我们从根开始读取后缀时,分支定义了从右到左的后缀。在第一层,您有后缀的最后一个元素,在第二层,您有最后一个元素之前的元素,等等。打印的树显示为根在左侧,并从左到右展开。尽管如此,打印结果节点中显示的后缀应该自然地从左到右阅读。例如,节点 a-b-c
表示末尾带有 c
的后缀。这样的节点是从节点b-c
左边加上a
得到的
cmine
的结果也是如此。对于每个找到的上下文,例如a-b-c
、cmine
给出了在上下文之后立即获得每个可能状态的概率,即在示例中的 c
之后。
总而言之,序列和上下文总是从左到右显示,即使上下文是从右到左构建的。
因此,如果您想查询序列 A->B->C
,只需使用 query(S1.p1, "A-B-C")
。同样,要用 predict
预测特定序列,自然地从左到右定义序列。
序列应从左到右阅读。以下代码对此进行了验证:
library(PST)
data.seq <- seqdef("A-B-C-D-E-F")
S1.test <- pstree(data.seq, ymin = 0.001, lik = FALSE, with.missing = FALSE)
print(S1.test)
--(e)-[ p=(0.2,0.2,0.2,0.2,0.2,0.2) - n=6 ]
`--(A)-[ p=(0.001,0.995,0.001,0.001,0.001,0.001) - n=1 ]--|
`--(B)-[ p=(0.001,0.001,0.995,0.001,0.001,0.001) - n=1 ]
`--(A-B)-[ p=(0.001,0.001,0.995,0.001,0.001,0.001) - n=1 ]--|
`--(C)-[ p=(0.001,0.001,0.001,0.995,0.001,0.001) - n=1 ]
`--(B-C)-[ p=(0.001,0.001,0.001,0.995,0.001,0.001) - n=1 ]
`--(A-B-C)-[ p=(0.001,0.001,0.001,0.995,0.001,0.001) - n=1 ]--|
`--(D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]
`--(C-D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]
`--(B-C-D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]
`--(A-B-C-D)-[ p=(0.001,0.001,0.001,0.001,0.995,0.001) - n=1 ]--|
`--(E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(C-D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(B-C-D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]
`--(A-B-C-D-E)-[ p=(0.001,0.001,0.001,0.001,0.001,0.995) - n=1 ]--|
plot(S1.test)
这也表明绘制的树应该从下到上阅读。