private static void Run(Options opt)
{
var startup = new Startup(
new FileWrapper()
);
var filePath = startup.GetPathInProject(opt.FileName);
IBlobCounterWrapper blobCounterWrapper = new BlobCounterWrapper();
ISimpleShapeCheckerWrapper simpleShapeCheckerWrapper = new SimpleShapeCheckerWrapper();
IColorFilteringWrapper colorFilteringWrapper = new ColorFilteringWrapper();
IPostItAnalysis postItAnalysis = new PostItAnalysis(blobCounterWrapper, simpleShapeCheckerWrapper, colorFilteringWrapper);
ICountByColor countByColor = new CountByColor(postItAnalysis);
try
{
if (startup.VerifyFile(filePath))
{
var resultsGetter = new ResultsGetter(countByColor);
var result = resultsGetter.Get(filePath);
var resultsPrinter = new ResultsPrinter();
resultsPrinter.Print(result);
}
}
catch (ArgumentException e)
{
Console.WriteLine(e.Message);
}
}
public void GettingWinnerBySearchEngineReturnsExpectedLinesForMultipleSearchTerms()
{
//Arrange
var searchResults = new List <SearchResult> {
new SearchResult {
SearchEngineUsed = "Google", NumberOfResults = 1000, ProgrammingLanguage = ".net"
},
new SearchResult {
SearchEngineUsed = "MSN Search", NumberOfResults = 2001, ProgrammingLanguage = ".net"
},
new SearchResult {
SearchEngineUsed = "Google", NumberOfResults = 1001, ProgrammingLanguage = "java"
},
new SearchResult {
SearchEngineUsed = "MSN Search", NumberOfResults = 2000, ProgrammingLanguage = "java"
}
};
//Act
var lines = ResultsPrinter.GetWinnerBySearchEngine(searchResults);
//Assert
var expectedLines = new List <string> {
"Google winner: java", "MSN Search winner: .net"
};
Assert.IsTrue(lines.Intersect(expectedLines).Count() == lines.Count());
}
public async Task Handle(ConfigOptions options)
{
var request = MapOptionsToRequest(options);
var result = await _whenAuthorize.ThenAsync(request).ConfigureAwait(false);
ResultsPrinter.Print(result);
}
private static void PrintRecs(MalRecResults <IEnumerable <RecEngine.IRecommendation> > recs, IDictionary <int, RecEngine.MAL.MalListEntry> animeList, decimal targetScore)
{
if (!recs.Results.Any())
{
Console.WriteLine("No recommendations.");
return;
}
ResultsPrinter resultsPrinter = new ResultsPrinter();
resultsPrinter.PrintResults(recs, animeList, targetScore);
}
public async Task Handle(ServerListOptions options)
{
ServerList servers = new ServerList();
if (options.Local == false)
{
var request = new GetServerList();
servers = await _whenGetServerList.ThenAsync(request).ConfigureAwait(false);
}
if (options.Local)
{
var request = new GetLocalServerList();
servers = await _whenGetLocalServerList.ThenAsync(request).ConfigureAwait(false);
}
ResultsPrinter.Print(servers);
}
static void Main(string[] programmingLanguages)
{
//Resolve Dependencies
var container = SearchFightContainer.BuildContainer();
var queryMaker = container.GetInstance <IQueryMaker>();
//Call Controller
try
{
var searchFightCon = new SearchFightController(queryMaker);
var viewModel = searchFightCon.StartSearchFight(programmingLanguages);
ResultsPrinter.Print(viewModel);
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
}
public void GettingResultsByProgrammingLanguageReturnsExpectedLineForOneSearchTerm()
{
//Arrange
var searchResults = new List <SearchResult> {
new SearchResult {
SearchEngineUsed = "Google", NumberOfResults = 1000, ProgrammingLanguage = ".net"
},
new SearchResult {
SearchEngineUsed = "MSN Search", NumberOfResults = 2000, ProgrammingLanguage = ".net"
}
};
//Act
var lines = ResultsPrinter.GetResultsByProgrammingLanguage(searchResults);
//Assert
var expectedLine = ".net: Google: 1000 MSN Search: 2000 ";
foreach (var line in lines)
{
Assert.AreEqual(line, expectedLine);
}
}
/*
* FeatureFactory class to use for generating features from relations for relation extraction.
* Default is "edu.stanford.nlp.ie.machinereading.RelationFeatureFactory"
*/
//private Class<RelationFeatureFactory> relationFeatureFactoryClass = edu.stanford.nlp.ie.machinereading.RelationFeatureFactory.class;
/*
* comma-separated list of feature types to generate for relation extraction
*/
//private String relationFeatures;
public override void PrintResults(PrintWriter pw, IList <ICoreMap> goldStandard, IList <ICoreMap> extractorOutput)
{
featureFactory = MachineReading.MakeRelationFeatureFactory(MachineReadingProperties.relationFeatureFactoryClass, MachineReadingProperties.relationFeatures, false);
mentionFactory = new RelationMentionFactory();
// generic mentions work well in this domain
ResultsPrinter.Align(goldStandard, extractorOutput);
IList <RelationMention> relations = new List <RelationMention>();
IDictionary <RelationMention, string> predictions = new Dictionary <RelationMention, string>();
for (int i = 0; i < goldStandard.Count; i++)
{
IList <RelationMention> goldRelations = AnnotationUtils.GetAllRelations(mentionFactory, goldStandard[i], true);
Sharpen.Collections.AddAll(relations, goldRelations);
foreach (RelationMention rel in goldRelations)
{
predictions[rel] = AnnotationUtils.GetRelation(mentionFactory, extractorOutput[i], rel.GetArg(0), rel.GetArg(1)).GetType();
}
}
ICounter <Pair <Pair <string, string>, string> > pathCounts = new ClassicCounter <Pair <Pair <string, string>, string> >();
foreach (RelationMention rel_1 in relations)
{
pathCounts.IncrementCount(new Pair <Pair <string, string>, string>(new Pair <string, string>(rel_1.GetArg(0).GetType(), rel_1.GetArg(1).GetType()), featureFactory.GetFeature(rel_1, "dependency_path_lowlevel")));
}
ICounter <string> singletonCorrect = new ClassicCounter <string>();
ICounter <string> singletonPredicted = new ClassicCounter <string>();
ICounter <string> singletonActual = new ClassicCounter <string>();
foreach (RelationMention rel_2 in relations)
{
if (pathCounts.GetCount(new Pair <Pair <string, string>, string>(new Pair <string, string>(rel_2.GetArg(0).GetType(), rel_2.GetArg(1).GetType()), featureFactory.GetFeature(rel_2, "dependency_path_lowlevel"))) == 1.0)
{
string prediction = predictions[rel_2];
if (prediction.Equals(rel_2.GetType()))
{
singletonCorrect.IncrementCount(prediction);
}
singletonPredicted.IncrementCount(prediction);
singletonActual.IncrementCount(rel_2.GetType());
}
}
// Group together actual relations of a type with relations that were
// predicted to be that type
// String rel1group = RelationsSentence.isUnrelatedLabel(rel1.getType())
// ? prediction1 : rel1.getType();
// String rel2group = RelationsSentence.isUnrelatedLabel(rel2.getType())
// ? prediction2 : rel2.getType();
// int groupComp = rel1group.compareTo(rel2group);
// int pathComp =
// getFeature(rel1,"generalized_dependency_path").compareTo(getFeature(rel2,"generalized_dependency_path"));
// } else if (pathComp != 0) {
// return pathComp;
_T1018869951 relComp = new _T1018869951(this);
relations.Sort(relComp);
foreach (RelationMention rel_3 in relations)
{
string prediction = predictions[rel_3];
// if (RelationsSentence.isUnrelatedLabel(prediction) &&
// RelationsSentence.isUnrelatedLabel(rel.getType())) {
// continue;
// }
string type1 = rel_3.GetArg(0).GetType();
string type2 = rel_3.GetArg(1).GetType();
string path = featureFactory.GetFeature(rel_3, "dependency_path_lowlevel");
if (!((type1.Equals("PEOPLE") && type2.Equals("PEOPLE")) || (type1.Equals("PEOPLE") && type2.Equals("LOCATION")) || (type1.Equals("LOCATION") && type2.Equals("LOCATION")) || (type1.Equals("ORGANIZATION") && type2.Equals("LOCATION")) || (type1
.Equals("PEOPLE") && type2.Equals("ORGANIZATION"))))
{
continue;
}
if (path.Equals(string.Empty))
{
continue;
}
pw.Println("\nLABEL: " + prediction);
pw.Println(rel_3);
pw.Println(path);
pw.Println(featureFactory.GetFeatures(rel_3, "dependency_path_words"));
pw.Println(featureFactory.GetFeature(rel_3, "surface_path_POS"));
}
}
public static void Main(string[] args)
{
Logger.Info("Application Started");
if (!string.IsNullOrEmpty(ConfigurationManager.AppSettings["csvpath"].ToString()))
{
CsvImporter.CsvPath = ConfigurationManager.AppSettings["csvpath"].ToString();
}
if (!string.IsNullOrEmpty(ConfigurationManager.AppSettings["jsonpath"].ToString()))
{
JsonOverrideFactory.JsonPath = ConfigurationManager.AppSettings["jsonpath"].ToString();
}
var categories =
new CategoryCreator()
.SetRawPath("Events.csv")
.SetOverrideFactory("events.json")
.Create();
var athletes =
new AthleteCreator()
.SetRawPath("Competitors.csv")
.SetOverrideFactory("athletes.json")
.Create();
var clubs = new ClubCreator(athletes).SetOverrideFactory("clubs.json").Create();
AthleteClubMapper.Map(athletes, clubs);
var startpositions = new StartPositionFactory("startpositions.json").Create();
var crews =
new CrewCreator(categories, clubs, startpositions, athletes)
.SetRawPath("Crews.csv")
.SetOverrideFactory("crews.json")
.Create()
.OrderBy(cr => cr.StartNumber)
.ToList();
// todo - this is almost certainly not the best place to do this
var bandProportions = ConfigurationManager.AppSettings["OpenBands"].Split(',').Select(i => Int32.Parse(i)).ToList();
foreach (Gender gender in (Gender[])Enum.GetValues(typeof(Gender)))
{
var openBands = categories.Where(cat => cat is EventCategory).Select(c => (EventCategory)c).Where(c => c.Gender == gender && c.UseForCRI).Select(c => c.EventId).ToList();
IList <Func <List <int> > > del = new List <Func <List <int> > >
{
() => crews.Where(cr => cr.Gender == gender).Select(cr => cr.CRI(false)).ToList(),
() => crews.Where(crew => categories.Where(cat => cat is EventCategory).Select(c => (EventCategory)c).Where(c => c.Gender == gender && c.UseForCRI).Select(c => c.EventId).Contains(crew.EventCategory.EventId)).Select(cr => cr.CRI(false)).ToList()
};
foreach (var fn in del)
{
var crisToInclude = fn(); // crews.Where(crew => openBands.Contains(crew.EventCategory.EventId)).Select(cr => cr.CRI).ToList();
crisToInclude.Sort();
if (crisToInclude.Count > 0)
{
Logger.DebugFormat("{0} crews [#{2}] {1}", gender, crisToInclude.Select(c => c.ToString()).Aggregate((h, t) => String.Format("{0}, {1}", h, t)), crisToInclude.Count);
int tally = 0;
int lower = 0;
for (int i = 0; i < bandProportions.Count; i++)
{
tally += bandProportions[i];
int upper = i + 1 == bandProportions.Count ? crisToInclude.Count - 1 : 1 + (int)Math.Floor((decimal)crisToInclude.Count * tally / 100);
Logger.DebugFormat("Band {0} [{1}, {2}{4}. #{3} ", i + 1, crisToInclude[lower], crisToInclude[upper], (i + 1 == bandProportions.Count ? 1 : 0) + upper - lower, i + 1 < bandProportions.Count ? ")" : "]"); // crisToInclude[mag-1], crisToInclude[mag]);
lower = upper;
}
foreach (var b in new List <bool> {
true, false
})
{
Logger.InfoFormat("Correlation between CRI{2} and points ({1}): {0}",
PearsonCorrelation(crews.Where(cr => cr.Gender == gender).Select(cr => (double)cr.CRI(b)).ToList(), crews.Where(cr => cr.Gender == gender).Select(cr => (double)cr.Points).ToList()),
gender,
b ? "Max" : "");
}
}
}
}
foreach (var b in new List <bool> {
true, false
})
{
Logger.InfoFormat("Correlation between CRI{1} and points (all): {0}",
PearsonCorrelation(crews.Select(cr => (double)cr.CRI(b)).ToList(), crews.Select(cr => (double)cr.Points).ToList()),
b ? "Max" : "");
}
CategoryCrewMapper.Map(categories, crews);
// TODO: move results into the config file?
if (args.Count() == 0 || args[0].ToLowerInvariant() != "results")
{
StartPositionGenerator.Generate(crews);
bool valid =
new CrewValidator(athletes).Validate(crews) &&
new ClubValidator().Validate(clubs) &&
new AthleteValidator().Validate(athletes) &&
new CategoryValidator().Validate(categories);
if (!valid)
{
return;
}
}
else
{
var starttimes = new SequenceItemFactory("start-times.json").Create();
var finishtimes = new SequenceItemFactory("finish-times.json").Create();
var penalties = new PenaltyFactory("penalties.json").Create();
var adjustments = new AdjustmentFactory("adjustments.json").Create();
// todo - is there a weighed in file?
TimeMapper.Map(crews, starttimes, finishtimes);
TimeMapper.Penalise(crews, penalties);
TimeMapper.Adjust(crews, adjustments);
CategoryResultsGenerator.Generate(categories);
ResultsPrinter.Dump(crews);
}
Logger.Info("Application stopped.");
}
