为什么这个haskey()条件总是假的？

Question

我从一个字数列表开始:

julia> import Iterators: partition
julia> import StatsBase: countmap
julia> s = split("the lazy fox jumps over the brown dog");
julia> vocab_counter = countmap(s)
Dict{SubString{String},Int64} with 7 entries:
  "brown" => 1
  "lazy"  => 1
  "jumps" => 1
  "the"   => 2
  "fox"   => 1
  "over"  => 1
  "dog"   => 1

然后我想计算不.每个单词的ngrams并将其存储在嵌套字典中.外键是ngram,内键是单词,而最内层的值是给出单词的ngram的计数.

我试过了:

ngram_word_counter = Dict{Tuple,Dict}()
for (word, count) in vocab_counter
    for ng in ngram(word, 2) # bigrams.
        if ! haskey(ngram_word_counter, ng)
            ngram_word_counter[ng] = Dict{String,Int64}()
            ngram_word_counter[ng][word] = 0
        end
        ngram_word_counter[ng][word] += 1  
    end
end

这给了我所需的数据结构:

julia> ngram_word_counter
Dict{Tuple,Dict} with 20 entries:
  ('b','r') => Dict("brown"=>1)
  ('t','h') => Dict("the"=>1)
  ('o','w') => Dict("brown"=>1)
  ('z','y') => Dict("lazy"=>1)
  ('o','g') => Dict("dog"=>1)
  ('u','m') => Dict("jumps"=>1)
  ('o','x') => Dict("fox"=>1)
  ('e','r') => Dict("over"=>1)
  ('a','z') => Dict("lazy"=>1)
  ('p','s') => Dict("jumps"=>1)
  ('h','e') => Dict("the"=>1)
  ('d','o') => Dict("dog"=>1)
  ('w','n') => Dict("brown"=>1)
  ('m','p') => Dict("jumps"=>1)
  ('l','a') => Dict("lazy"=>1)
  ('o','v') => Dict("over"=>1)
  ('v','e') => Dict("over"=>1)
  ('r','o') => Dict("brown"=>1)
  ('f','o') => Dict("fox"=>1)
  ('j','u') => Dict("jumps"=>1)

但请注意,这些值是错误的:

('t','h') => Dict("the"=>1)
('h','e') => Dict("the"=>1)

本来应该:

('t','h') => Dict("the"=>2)
('h','e') => Dict("the"=>2)

自从这个词出现两次.

仔细看后,似乎haskey(ngram_word_counter, ng)总是假=(

julia> ngram_word_counter = Dict{Tuple,Dict}()
for (word, count) in vocab_counter
    for ng in ngram(word, 2) # bigrams.
        println(haskey(ngram_word_counter, ng))
    end
end

[OUT]:

false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false

为什么这种haskey()情况总是错误的？

Answer 1

TL; DR:它应该ngram_word_counter[ng][word] += count代替ngram_word_counter[ng][word] += 1.

添加只是1忽略了多次出现的单词的多重贡献.单词出现的次数编码vocab_counter为count在for循环中变为变量的值.因此增量应该是count.

后来的调试检查是无效的,并且通常情况下,调试代码的错误会混淆问题.预期的检查可能是:

julia> ngram_word_counter = Dict{Tuple,Dict}()
for (word, count) in vocab_counter
    for ng in ngram(word, 2) # bigrams.
        println(haskey(ngram_word_counter, ng))
        ngram_word_counter[ng] = 1
    end
end