//看看本type是否在参考字典中存在：
public void Compare(Dictionary <string, CSharpType_t> other)
{
CompareResult.Clear();
//首先查找TypeWithNS完整的匹配的class，直接返回...
CSharpType_t eg = null;
other.TryGetValue(this.TypeName, out eg);
if (eg != null && this.TypeWithNS == eg.TypeWithNS)
{
CSharpTypeCompareResult_t res = Compare(eg);
if (res.percent > 80)
{
CompareResult.Insert(res);
return;
}
}
//忽略.成员数太小的Type
if (this.Members.Count < 2)
{
return;
}
//遍历参考
foreach (var p in other)
{
//比较类型名字:
if (CSharpType_t.CONFIG_Type_LevenshteinDistance)
{
if (this.TypeName.Length > 4)
{
double Similarity;
int Distance = CCLevenshtein.LevenshteinDistance(TypeName, p.Value.TypeName, out Similarity, false);
if (Similarity > 0.5)
{
CSharpTypeCompareResult_t n = new CSharpTypeCompareResult_t();
n.percent = (int)(Similarity * 1000);
n.refType = p.Value;
CompareNSResult.Insert(n);
}
}
}
//比较字典中的每个type,计算相似度:
if (p.Value.Members.Count > 1)
{
CSharpTypeCompareResult_t res = Compare(p.Value);
if (res.percent > 15)
{
CompareResult.Insert(res);
}
}
}
}
//zTODO: 如果匹配一致？包括完美一致？
//使用词语近似性算法：LevenshteinDistance
public MemberCompareResult_t Compare(CSharpMember_t src)
{
if (Members.Count == 0)
{
return(null);
}
MemberCompareResult_t mcr = new MemberCompareResult_t(src);
Int32 Distance;
Double Similarity;
for (int i = 0; i < Members.Count; ++i)
{
if (UseSign[i] == true)
{
continue;
}
if (Members[i].Name == src.Name)
{
this.UseSign[i] = true;
mcr.Distance = 0;
mcr.Similarity = 1;
mcr.dst = Members[i];
return(mcr);
}
//忽略太短的词语
if (CONFIG_Member_LevenshteinDistance)
{
if (src.Name.Length > 4)
{
Distance = CCLevenshtein.LevenshteinDistance(Members[i].Name, src.Name, out Similarity, false);
if (Similarity > mcr.Similarity)
{
mcr.Distance = Distance;
mcr.Similarity = Similarity;
mcr.dst = Members[i];
}
}
}
}
return(mcr);
}
