public void CorrectUp()
{
var articlesFilePath = @"TestData\Index\MiddleTerm\Index.MiddleTerm.Up.xml";
var macroWordsLoader = new MacroWordsLoader(@"AppData\MacroWords.xml");
var patternsLoader = new RawPatternsLoader(@"AppData\Up.xml", Trend.Up);
var patternProvider = new PatternsProvider(patternsLoader.Patterns, macroWordsLoader.MacroWords);
var classifier = new OpinionClassifier(patternProvider);
var articles = new TestArticleLoader().LoadArticles(articlesFilePath);
foreach (var article in articles)
{
if (String.IsNullOrEmpty(article.Title) && String.IsNullOrEmpty(article.Text))
{
continue;
}
Trend result = classifier.Classify(article).Trend;
Assert.AreEqual(Trend.Up, result, "Incorrect classification for: " + article.Id + " : " + article.Text);
}
}
private static void CorrectDown(string testArticlesFilePath)
{
var patternsLoader = new RawPatternsLoader(@"AppData\TrendPatterns\Down.Unconditional.xml", Trend.Down);
var macroWordsLoader = new MacroWordsLoader(@"AppData\TrendPatterns\MacroWords.xml");
var patternProvider = new PatternsProvider(patternsLoader.Patterns, macroWordsLoader.MacroWords);
var classifier = new OpinionClassifier(patternProvider);
var articles = new TestArticleLoader().LoadArticles(testArticlesFilePath);
foreach (var article in articles)
{
if (String.IsNullOrEmpty(article.Title) && String.IsNullOrEmpty(article.Text))
{
continue;
}
var result = classifier.Classify(article);
Assert.AreEqual(Trend.Down, result, "Incorrect classification for: " + article.Id + " : " + article.Text);
if (String.IsNullOrEmpty(article.NegativeText) == false)
{
var negativeResult = classifier.Classify(article.NegativeText);
Assert.AreNotEqual(Trend.Down, negativeResult, "Incorrect classification for negative text: " + article.Id + " : " + article.Text);
}
}
}
private static void Check(string testArticlesFilePath, string rawPatternsPath, Trend trend)
{
var macroWordsLoader = new MacroWordsLoader(@"AppData\MacroWords.xml");
var patternsLoader = new RawPatternsLoader(rawPatternsPath, trend);
var patternProvider = new PatternsProvider(patternsLoader.Patterns, macroWordsLoader.MacroWords);
var classifier = new OpinionClassifier(patternProvider);
var articles = new TestArticleLoader().LoadArticles(testArticlesFilePath);
foreach (var article in articles)
{
if (String.IsNullOrEmpty(article.Title) && String.IsNullOrEmpty(article.Text))
{
continue;
}
var result = classifier.Classify(article);
Assert.AreEqual(Trend.Unknown, result.Trend, "Incorrect classification: Regex: " + result.RegexText + "\n\r : " + article.Text + " \n\r " + "Regex: " + result.RegexText);
if (String.IsNullOrEmpty(article.NegativeText) == false)
{
var negativeResult = classifier.Classify(article.NegativeText);
Assert.AreNotEqual(Trend.Unknown, negativeResult, "Incorrect classification for negative text: " + article.Id + " : " + article.Text);
}
}
}
public static void LoadPatterns()
{
var macroWordsLoader = new MacroWordsLoader(@"AppData\MacroWords.xml");
var upPatternsLoader = new RawPatternsLoader(@"AppData\BeforeOpening\Up.xml", Trend.Up);
var downPatternsLoader = new RawPatternsLoader(@"AppData\BeforeOpening\Down.xml", Trend.Down);
var neutralPatternsLoader = new RawPatternsLoader(@"AppData\BeforeOpening\Neutral.xml", Trend.Neutral);
var patterns = new List <RawPattern>();
patterns.AddRange(upPatternsLoader.Patterns);
patterns.AddRange(downPatternsLoader.Patterns);
patterns.AddRange(neutralPatternsLoader.Patterns);
var patternProvider = new PatternsProvider(patterns, macroWordsLoader.MacroWords);
_patterns = patternProvider.Patterns;
_market = FringeWithSeparators(PattenCleaner.Clean(macroWordsLoader.MacroWords.Where(x => x.Name == "Market").Select(x => x.Value).Single()));
_expect = FringeWithSeparators(PattenCleaner.Clean(macroWordsLoader.MacroWords.Where(x => x.Name == "Expect").Select(x => x.Value).Single()));
}
