Специализация шаблонов

RobertDeMilo

Oct 24th, 2023

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#include <algorithm>
#include <cmath>
#include <iostream>
#include <map>
#include <set>
#include <string>
#include <utility>
#include <vector>
using namespace std;
const int MAX_RESULT_DOCUMENT_COUNT = 5;
string ReadLine() {
string s;
getline(cin, s);
return s;
}
int ReadLineWithNumber() {
int result;
cin >> result;
ReadLine();
return result;
}
vector<string> SplitIntoWords(const string& text) {
vector<string> words;
string word;
for (const char c : text) {
if (c == ' ') {
if (!word.empty()) {
words.push_back(word);
word.clear();
}
}
else {
word += c;
}
}
if (!word.empty()) {
words.push_back(word);
}
return words;
}
struct Document {
int id;
double relevance;
int rating;
};
enum class DocumentStatus {
ACTUAL,
IRRELEVANT,
BANNED,
REMOVED,
};
class SearchServer {
public:
void SetStopWords(const string& text) {
for (const string& word : SplitIntoWords(text)) {
stop_words_.insert(word);
}
}
void AddDocument(int document_id, const string& document, DocumentStatus status,
const vector<int>& ratings) {
const vector<string> words = SplitIntoWordsNoStop(document);
const double inv_word_count = 1.0 / words.size();
for (const string& word : words) {
word_to_document_freqs_[word][document_id] += inv_word_count;
}
documents_.emplace(document_id, DocumentData{ ComputeAverageRating(ratings), status });
}
//Достаточно написать новый метод —
// vector<Document> FindTopDocuments(const string& raw_query, DocumentStatus status) const.
//
// А в нём одну строчку : создали нужную лямбду и вызвали основную версию одноимённого метода.
// Не забудьте избавиться от дублирования кода : версия FindTopDocuments с одним параметром теперь может
// вызывать новую версию этого метода — с DocumentStatus.
vector<Document> FindTopDocuments(const string& raw_query, DocumentStatus doc_status = DocumentStatus::ACTUAL) const
{
return FindTopDocuments(raw_query, [doc_status](int document_id, DocumentStatus status, int rating) { return status == doc_status; });
}
template<typename Pred>
vector<Document> FindTopDocuments(const string& raw_query, Pred pred) const {
const Query query = ParseQuery(raw_query);
auto matched_documents = FindAllDocuments(query, pred);
sort(matched_documents.begin(), matched_documents.end(),
[](const Document& lhs, const Document& rhs) {
if (abs(lhs.relevance - rhs.relevance) < 1e-6) {
return lhs.rating > rhs.rating;
}
else {
return lhs.relevance > rhs.relevance;
}
});
if (matched_documents.size() > MAX_RESULT_DOCUMENT_COUNT) {
matched_documents.resize(MAX_RESULT_DOCUMENT_COUNT);
}
return matched_documents;
}
tuple<vector<string>, DocumentStatus> MatchDocument(const string& raw_query,
int document_id) const {
const Query query = ParseQuery(raw_query);
vector<string> matched_words;
for (const string& word : query.plus_words) {
if (word_to_document_freqs_.count(word) == 0) {
continue;
}
if (word_to_document_freqs_.at(word).count(document_id)) {
matched_words.push_back(word);
}
}
for (const string& word : query.minus_words) {
if (word_to_document_freqs_.count(word) == 0) {
continue;
}
if (word_to_document_freqs_.at(word).count(document_id)) {
matched_words.clear();
break;
}
}
return { matched_words, documents_.at(document_id).status };
}
int GetDocumentCount() const {
return documents_.size();
}
private:
//////////////////////////////////////////////////////////////////////////////
struct DocumentData {
int rating;
DocumentStatus status;
};
set<string> stop_words_;
map<string, map<int, double>> word_to_document_freqs_;
map<int, DocumentData> documents_;
struct QueryWord {
string data;
bool is_minus;
bool is_stop;
};
struct Query {
set<string> plus_words;
set<string> minus_words;
};
//////////////////////////////////////////////////////////////////////////////
bool IsStopWord(const string& word) const {
return stop_words_.count(word) > 0;
}
vector<string> SplitIntoWordsNoStop(const string& text) const {
vector<string> words;
for (const string& word : SplitIntoWords(text)) {
if (!IsStopWord(word)) {
words.push_back(word);
}
}
return words;
}
static int ComputeAverageRating(const vector<int>& ratings) {
if (ratings.empty()) {
return 0;
}
int rating_sum = 0;
for (const int rating : ratings) {
rating_sum += rating;
}
return rating_sum / static_cast<int>(ratings.size());
}
QueryWord ParseQueryWord(string text) const {
bool is_minus = false;
// Word shouldn't be empty
if (text[0] == '-') {
is_minus = true;
text = text.substr(1);
}
return { text, is_minus, IsStopWord(text) };
}
Query ParseQuery(const string& text) const {
Query query;
for (const string& word : SplitIntoWords(text)) {
const QueryWord query_word = ParseQueryWord(word);
if (!query_word.is_stop) {
if (query_word.is_minus) {
query.minus_words.insert(query_word.data);
}
else {
query.plus_words.insert(query_word.data);
}
}
}
return query;
}
// Existence required
double ComputeWordInverseDocumentFreq(const string& word) const {
return log(1.0 * documents_.size() / word_to_document_freqs_.at(word).size());
}
/* vector<Document> FindAllDocuments(const Query& query, DocumentStatus status) const*/
template <typename Pred>
vector<Document> FindAllDocuments(const Query& query, Pred pred) const
{
map<int, double> document_to_relevance;
for (const string& word : query.plus_words) {
if (word_to_document_freqs_.count(word) == 0) {
continue;
}
//log(1.0 * documents_.size() / word_to_document_freqs_.at(word).size());
const double inverse_document_freq = ComputeWordInverseDocumentFreq(word);
for (const auto& [document_id, term_freq] : word_to_document_freqs_.at(word))
{
bool result = pred(document_id, documents_.at(document_id).status, documents_.at(document_id).rating);
/* if (documents_.at(document_id).status == status) */
if (result)
{
document_to_relevance[document_id] += term_freq * inverse_document_freq;
}
}
}
//**********************************************************************************
for (const string& word : query.minus_words) {
if (word_to_document_freqs_.count(word) == 0) {
continue;
}
for (const auto [document_id, _] : word_to_document_freqs_.at(word)) {
document_to_relevance.erase(document_id);
}
}
//**********************************************************************************
vector<Document> matched_documents;
for (const auto [document_id, relevance] : document_to_relevance) {
matched_documents.push_back(
{ document_id, relevance, documents_.at(document_id).rating });
}
return matched_documents;
//**********************************************************************************
}
};
// ==================== для примера =========================
void PrintDocument(const Document& document) {
cout << "{ "s
<< "document_id = "s << document.id << ", "s
<< "relevance = "s << document.relevance << ", "s
<< "rating = "s << document.rating
<< " }"s << endl;
}
int main() {
SearchServer search_server;
search_server.SetStopWords("и в на"s);
search_server.AddDocument(0, "белый кот и модный ошейник"s, DocumentStatus::ACTUAL, { 8, -3 });
search_server.AddDocument(1, "пушистый кот пушистый хвост"s, DocumentStatus::ACTUAL, { 7, 2, 7 });
search_server.AddDocument(2, "ухоженный пёс выразительные глаза"s, DocumentStatus::ACTUAL, { 5, -12, 2, 1 });
search_server.AddDocument(3, "ухоженный скворец евгений"s, DocumentStatus::BANNED, { 9 });
cout << "ACTUAL by default:"s << endl;
for (const Document& document : search_server.FindTopDocuments("пушистый ухоженный кот"s)) {
PrintDocument(document);
}
cout << "BANNED:"s << endl;
for (const Document& document : search_server.FindTopDocuments("пушистый ухоженный кот"s, DocumentStatus::BANNED)) {
PrintDocument(document);
}
cout << "Even ids:"s << endl;
for (const Document& document : search_server.FindTopDocuments("пушистый ухоженный кот"s, [](int document_id, DocumentStatus status, int rating) { return document_id % 2 == 0; })) {
PrintDocument(document);
}
return 0;
}

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