public static IList <float?> checkStability(LangDescriptor language)
{
IList <float?> errorRates = new List <float?>();
// format the corpus into tmp dir
LeaveOneOutValidator validator0 = new LeaveOneOutValidator(language.corpusDir, language);
Triple <IList <Formatter>, IList <float>, IList <float> > results0 = validator0.validateDocuments(false, "/tmp/stability/1");
errorRates.Add(BuffUtils.median(results0.c));
IList <Formatter> formatters0 = results0.a;
// now try formatting it over and over
for (int i = 1; i <= STAGES; i++)
{
string inputDir = "/tmp/stability/" + i;
string outputDir = "/tmp/stability/" + (i + 1);
LeaveOneOutValidator validator = new LeaveOneOutValidator(inputDir, language);
Triple <IList <Formatter>, IList <float>, IList <float> > results = validator.validateDocuments(false, outputDir);
IList <Formatter> formatters = results.a;
IList <float?> distances = new List <float?>();
for (int j = 0; j < formatters.Count; j++)
{
Formatter f0 = formatters0[j];
Formatter f = formatters[j];
float editDistance = Dbg.normalizedLevenshteinDistance(f.Output, f0.Output);
distances.Add(editDistance);
}
errorRates.Add(BuffUtils.median(distances));
}
return(errorRates);
}
public void OnBuffSetted(Buff buff, NebulaObject source)
{
if (source != null && noTarget && (nebulaObject.getItemType() != ItemType.Avatar))
{
if (BuffUtils.IsDebuff(buff.buffType))
{
if (nebulaObject.IsBot())
{
var weap = GetComponent <BaseWeapon>();
var character = GetComponent <CharacterObject>();
var sourceCharacter = source.GetComponent <CharacterObject>();
if (weap != null && character != null && sourceCharacter != null)
{
var relation = character.RelationTo(sourceCharacter);
if (relation == FractionRelation.Enemy || relation == FractionRelation.Neutral)
{
SetTarget(source);
}
}
}
}
}
}
public static string testAllLanguages(LangDescriptor[] languages, string[] corpusDirs, string imageFileName)
{
IList <string> languageNames = BuffUtils.map(languages, l => l.name + "_err");
// Collections.sort(languageNames);
IDictionary <string, int?> corpusSizes = new Dictionary <string, int?>();
for (int i = 0; i < languages.Length; i++)
{
LangDescriptor language = languages[i];
IList <string> filenames = Tool.getFilenames(corpusDirs[i], language.fileRegex);
corpusSizes[language.name] = filenames.Count;
}
IList <string> languageNamesAsStr = BuffUtils.map(languages, l => '"' + l.name + "\\nn=" + corpusSizes[l.name] + '"');
// Collections.sort(languageNamesAsStr);
StringBuilder data = new StringBuilder();
for (int i = 0; i < languages.Length; i++)
{
LangDescriptor language = languages[i];
string corpus = corpusDirs[i];
LeaveOneOutValidator validator = new LeaveOneOutValidator(corpus, language);
Triple <IList <Formatter>, IList <float>, IList <float> > results = validator.validateDocuments(true, "/tmp");
IList <Formatter> formatters = results.a;
IList <float> distances = results.b;
IList <float> errors = results.c;
// data.append(language.name+"_dist = "+distances+"\n");
data.Append(language.name + "_err = " + errors + "\n");
}
string python = "#\n" + "# AUTO-GENERATED FILE. DO NOT EDIT\n" + "# CodeBuff %s '%s'\n" + "#\n" + "import numpy as np\n" + "import pylab\n" + "import matplotlib.pyplot as plt\n\n" + "%s\n" + "language_data = %s\n" + "labels = %s\n" + "fig = plt.figure()\n" + "ax = plt.subplot(111)\n" + "ax.boxplot(language_data,\n" + " whis=[10, 90], # 10 and 90 %% whiskers\n" + " widths=.35,\n" + " labels=labels,\n" + " showfliers=False)\n" + "ax.set_xticklabels(labels, rotation=60, fontsize=18)\n" + "ax.tick_params(axis='both', which='major', labelsize=18)\n" + "plt.xticks(range(1,len(labels)+1), labels, rotation=60, fontsize=18)\n" + "pylab.ylim([0,.28])\n" + "ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)\n" + "ax.set_xlabel(\"Grammar and corpus size\", fontsize=20)\n" + "ax.set_ylabel(\"Misclassification Error Rate\", fontsize=20)\n" + "# ax.set_title(\"Leave-one-out Validation Using Error Rate\\nBetween Formatted and Original File\")\n" + "plt.tight_layout()\n" + "fig.savefig('images/%s', format='pdf')\n" + "plt.show()\n";
return(string.Format(python, Tool.version, DateTime.Now, data, languageNames, languageNamesAsStr, imageFileName));
}
private void InitVariables()
{
if (mSpeedDebuffs == null)
{
mSpeedDebuffs = BuffUtils.GetDebuffsForParameter(BuffParameter.speed).ToList();
}
}
public virtual Triple <Formatter, float, float> validate(LangDescriptor language, IList <InputDocument> documents, string fileToExclude, int k, FeatureMetaData[] injectWSFeatures, FeatureMetaData[] alignmentFeatures, string outputDir, bool computeEditDistance, bool collectAnalysis)
{
string path = System.IO.Path.GetFullPath(fileToExclude);
IList <InputDocument> others = BuffUtils.filter(documents, d => !d.fileName.Equals(path));
IList <InputDocument> excluded = BuffUtils.filter(documents, d => d.fileName.Equals(path));
Debug.Assert(others.Count == documents.Count - 1);
// kNNClassifier.resetCache();
if (excluded.Count == 0)
{
Console.Error.WriteLine("Doc not in corpus: " + path);
return(null);
}
InputDocument testDoc = excluded[0];
DateTime start = System.DateTime.Now;
Corpus corpus = new Corpus(others, language);
corpus.train();
DateTime stop = System.DateTime.Now;
Formatter formatter = new Formatter(corpus, language.indentSize, k, injectWSFeatures, alignmentFeatures);
InputDocument originalDoc = testDoc;
DateTime format_start = System.DateTime.Now;
string output = formatter.format(testDoc, collectAnalysis);
DateTime format_stop = System.DateTime.Now;
float editDistance = 0;
if (computeEditDistance)
{
editDistance = Dbg.normalizedLevenshteinDistance(testDoc.content, output);
}
ClassificationAnalysis analysis = new ClassificationAnalysis(originalDoc, formatter.AnalysisPerToken);
Console.WriteLine(testDoc.fileName + ": edit distance = " + editDistance + ", error rate = " + analysis.ErrorRate);
if (!string.ReferenceEquals(outputDir, null))
{
string dir = outputDir + "/" + language.name + "/" + Tool.version;
if (!System.IO.Directory.Exists(dir))
{
System.IO.Directory.CreateDirectory(dir);
}
org.antlr.codebuff.misc.Utils.writeFile(dir + "/" + System.IO.Path.GetFileName(testDoc.fileName), output);
}
var tms = (stop - start);
var fms = format_stop - format_start;
trainingTimes.Add((double)tms.Milliseconds);
float tokensPerMS = testDoc.tokens.Size / (float)fms.TotalMilliseconds;
formattingTokensPerMS.Add((double)tokensPerMS);
Console.Write("Training time = {0:D} ms, formatting {1:D} ms, {2,5:F3} tokens/ms ({3:D} tokens)\n", tms, fms, tokensPerMS, testDoc.tokens.Size);
// System.out.printf("classify calls %d, hits %d rate %f\n",
// kNNClassifier.nClassifyCalls, kNNClassifier.nClassifyCacheHits,
// kNNClassifier.nClassifyCacheHits/(float) kNNClassifier.nClassifyCalls);
// System.out.printf("kNN calls %d, hits %d rate %f\n",
// kNNClassifier.nNNCalls, kNNClassifier.nNNCacheHits,
// kNNClassifier.nNNCacheHits/(float) kNNClassifier.nNNCalls);
return(new Triple <Formatter, float, float>(formatter, editDistance, analysis.ErrorRate));
}
/// <summary>
/// Select one document at random, then n others w/o replacement as corpus </summary>
public virtual org.antlr.codebuff.misc.Pair <InputDocument, IList <InputDocument> > selectSample(IList <InputDocument> documents, int n)
{
int i = random.Next(documents.Count);
InputDocument testDoc = documents[i];
IList <InputDocument> others = BuffUtils.filter(documents, d => d != testDoc);
IList <InputDocument> corpusSubset = getRandomDocuments(others, n);
return(new org.antlr.codebuff.misc.Pair <InputDocument, IList <InputDocument> >(testDoc, corpusSubset));
}
public static void Main(string[] args)
{
string langname = args[0].Substring(1);
string testFilename = args[1];
LangDescriptor language = null;
for (int i = 0; i < languages.length; i++)
{
if (languages[i].name.Equals(langname))
{
language = languages[i];
break;
}
}
if (language == null)
{
Log.WriteLine("Language " + langname + " unknown");
return;
}
// load all files up front
DateTime load_start = System.DateTime.Now;
IList <string> allFiles = Tool.getFilenames(language.corpusDir, language.fileRegex);
IList <InputDocument> documents = Tool.load(allFiles, language);
DateTime load_stop = System.DateTime.Now;
DateTime load_time = (load_stop - load_start) / 1000000;
Log.Write("Loaded {0:D} files in {1:D}ms\n", documents.Count, load_time);
string path = System.IO.Path.GetFullPath(testFilename);
IList <InputDocument> others = BuffUtils.filter(documents, d => !d.fileName.Equals(path));
IList <InputDocument> excluded = BuffUtils.filter(documents, d => d.fileName.Equals(path));
Debug.Assert(others.Count == documents.Count - 1);
if (excluded.Count == 0)
{
Log.WriteLine("Doc not in corpus: " + path);
return;
}
InputDocument testDoc = excluded[0];
IList <int> training = new List <int>();
IList <int> formatting = new List <int>();
for (int i = 1; i <= TRIALS; i++)
{
org.antlr.codebuff.misc.Pair <int, int> timing = test(language, others, testDoc);
training.Add(timing.a);
formatting.Add(timing.b);
}
// drop first four
training = training.subList(5, training.Count);
formatting = formatting.subList(5, formatting.Count);
Log.Write("median of [5:{0:D}] training {1:D}ms\n", TRIALS - 1, BuffUtils.median(training));
Log.Write("median of [5:{0:D}] formatting {1:D}ms\n", TRIALS - 1, BuffUtils.median(formatting));
}
public void ScaleDebuffInterval(float mult)
{
foreach (var bonusPair in bonuses)
{
if (BuffUtils.IsDebuff(bonusPair.Key))
{
bonusPair.Value.ScaleBuffInterval(mult);
}
}
}
public virtual Triple <IList <Formatter>, IList <float>, IList <float> > validateDocuments(FeatureMetaData[] injectWSFeatures, FeatureMetaData[] alignmentFeatures, bool computeEditDistance, string outputDir)
{
IList <Formatter> formatters = new List <Formatter>();
IList <float> distances = new List <float>();
IList <float> errors = new List <float>();
System.DateTime start = System.DateTime.Now;
try
{
IList <string> allFiles = Tool.getFilenames(rootDir, language.fileRegex);
IList <InputDocument> documents = Tool.load(allFiles, language);
IList <InputDocument> parsableDocuments = BuffUtils.filter(documents, d => d.tree != null);
System.DateTime stop = System.DateTime.Now;
//Console.Write("Load/parse all docs from {0} time {1:D} ms\n", rootDir, (stop - start) / 1000000);
int ncpu = 1;
if (FORCE_SINGLE_THREADED)
{
ncpu = 2;
}
for (int i = 0; i < parsableDocuments.Count; i++)
{
string fileName = parsableDocuments[i].fileName;
{
try
{
Triple <Formatter, float, float> results = validate(language, parsableDocuments, fileName,
Formatter.DEFAULT_K, injectWSFeatures, alignmentFeatures, outputDir, computeEditDistance, false);
formatters.Add(results.a);
float editDistance = results.b;
distances.Add(editDistance);
float errorRate = results.c;
errors.Add(errorRate);
}
catch (Exception t)
{
System.Console.WriteLine(t.StackTrace);
}
return(null);
}
}
}
finally
{
DateTime final_stop = System.DateTime.Now;
double medianTrainingTime = BuffUtils.median(trainingTimes);
double medianFormattingPerMS = BuffUtils.median(formattingTokensPerMS);
Console.Write("Total time {0:D}ms\n", final_stop - start);
Console.Write("Median training time {0:D}ms\n", medianTrainingTime);
Console.Write("Median formatting time tokens per ms {0,5:F4}ms, min {1,5:F4} max {2,5:F4}\n", medianFormattingPerMS, BuffUtils.min(formattingTokensPerMS), BuffUtils.max(formattingTokensPerMS));
}
return(new Triple <IList <Formatter>, IList <float>, IList <float> >(formatters, distances, errors));
}
public static IList <Tree> getSeparators <T1>(ParserRuleContext ctx, IList <T1> siblings)
where T1 : Antlr4.Runtime.ParserRuleContext
{
ParserRuleContext first = siblings[0] as ParserRuleContext;
ParserRuleContext last = siblings[siblings.Count - 1] as ParserRuleContext;
int start = BuffUtils.indexOf(ctx, first);
int end = BuffUtils.indexOf(ctx, last);
IEnumerable <ITree> xxxx = Trees.GetChildren(ctx).Where((n, i) => i >= start && i < end + 1);
IList <Tree> elements = xxxx.ToList();
return(BuffUtils.filter(elements, c => c is TerminalNode));
}
public static void Main(string[] args)
{
LangDescriptor[] languages = new LangDescriptor[] { Tool.ANTLR4_DESCR };
IList <string> corpusDirs = BuffUtils.map(languages, l => l.corpusDir);
string[] dirs = corpusDirs.ToArray();
string python = testAllLanguages(languages, dirs, "leave_one_out.pdf");
string fileName = "python/src/leave_one_out.py";
org.antlr.codebuff.misc.Utils.writeFile(fileName, python);
Console.WriteLine("wrote python code to " + fileName);
}
public static IList <float> getCategoryRatios(ICollection <int> catCounts)
{
IList <float> ratios = new List <float>();
int n = BuffUtils.sum(catCounts);
foreach (int count in catCounts)
{
float probCat = count / (float)n;
ratios.Add(probCat);
}
return(ratios);
}
public static void Main(string[] args)
{
LangDescriptor[] languages = new LangDescriptor[] { JAVA_DESCR, JAVA8_DESCR, JAVA_GUAVA_DESCR };
IList <string> corpusDirs = BuffUtils.map(languages, l => l.corpusDir);
string[] dirs = corpusDirs.ToArray();
string python = LeaveOneOutValidator.testAllLanguages(languages, dirs, "all_java_leave_one_out.pdf");
string fileName = "python/src/all_java_leave_one_out.py";
org.antlr.codebuff.misc.Utils.writeFile(fileName, python);
Log.WriteLine("wrote python code to " + fileName);
}
/// <summary>
/// Complete block debuf action. Check if we has buff on block debuff and than remove this buff from list
/// </summary>
/// <param name="buff"></param>
/// <returns></returns>
private bool IsDebuffBlocked(Buff buff)
{
if (BuffUtils.IsDebuff(buff.buffType))
{
var bonus = GetBonus(BonusType.block_debuff);
if (bonus != null && Mathf.NotEqual(bonus.value, 0.0f))
{
bonus.Clear();
return(true);
}
}
return(false);
}
public ConcurrentBag <BuffInfo> GetAllDebuffInfo()
{
ConcurrentBag <BuffInfo> result = new ConcurrentBag <BuffInfo>();
foreach (var pBonus in bonuses)
{
if (BuffUtils.IsDebuff(pBonus.Key))
{
foreach (var pBuff in pBonus.Value.GetBuffInfoCollection())
{
result.Add(pBuff);
}
}
}
return(result);
}
public virtual IDictionary <ParentSiblingListKey, SiblingListStats> getListStats(IDictionary <ParentSiblingListKey, IList <int> > map)
{
IDictionary <ParentSiblingListKey, SiblingListStats> listSizes = new Dictionary <ParentSiblingListKey, SiblingListStats>();
foreach (ParentSiblingListKey pair in map.Keys)
{
IList <int> lens = map[pair];
var new_lens = lens.OrderBy(i => i).ToList();
lens = new_lens;
int n = lens.Count;
int? min = lens[0];
int? median = lens[n / 2];
int? max = lens[n - 1];
double @var = BuffUtils.variance(lens);
listSizes[pair] = new SiblingListStats(n, min.Value, median.Value, @var, max.Value);
}
return(listSizes);
}
public static void runCaptureForOneLanguage(LangDescriptor language)
{
IList <string> filenames = Tool.getFilenames(language.corpusDir, language.fileRegex);
IList <InputDocument> documents = Tool.load(filenames, language);
foreach (string fileName in filenames)
{
// Examine info for this file in isolation
Corpus fileCorpus = new Corpus(fileName, language);
fileCorpus.train();
Console.WriteLine(fileName);
// examineCorpus(corpus);
ArrayListMultiMap <FeatureVectorAsObject, int> ws = getWSContextCategoryMap(fileCorpus);
ArrayListMultiMap <FeatureVectorAsObject, int> hpos = getHPosContextCategoryMap(fileCorpus);
// Compare with corpus minus this file
string path = fileName;
IList <InputDocument> others = BuffUtils.filter(documents, d => !d.fileName.Equals(path));
Corpus corpus = new Corpus(others, language);
corpus.train();
// examineCorpus(corpus);
ArrayListMultiMap <FeatureVectorAsObject, int> corpus_ws = getWSContextCategoryMap(corpus);
ArrayListMultiMap <FeatureVectorAsObject, int> corpus_hpos = getHPosContextCategoryMap(corpus);
foreach (FeatureVectorAsObject x in ws.Keys)
{
HashBag <int> fwsCats = getCategoriesBag(ws[x]);
IList <float> fwsRatios = getCategoryRatios(fwsCats.Values);
HashBag <int> wsCats = getCategoriesBag(corpus_ws[x]);
IList <float> wsRatios = getCategoryRatios(wsCats.Values);
// compare file predictions with corpus predictions
if (!fwsRatios.SequenceEqual(wsRatios))
{
Console.WriteLine(fwsRatios + " vs " + wsRatios);
}
HashBag <int> fhposCats = getCategoriesBag(hpos[x]);
HashBag <int> hposCats = getCategoriesBag(corpus_hpos[x]);
}
break;
}
}
public override bool TryCast(NebulaObject source, PlayerSkill skill, out Hashtable info)
{
info = new Hashtable();
if (!CheckForShotEnemy(source, skill))
{
return(false);
}
float dmgMult = skill.data.Inputs.Value <float>("dmg_mult");
float effectProb = skill.data.Inputs.Value <float>("effect_prob");
var sourceWeapon = source.GetComponent <BaseWeapon>();
var targetBonuses = source.GetComponent <PlayerTarget>().targetObject.GetComponent <PlayerBonuses>();
bool mastery = RollMastery(source);
if (mastery)
{
dmgMult *= 2;
effectProb *= 2;
}
WeaponHitInfo hit;
var shotInfo = sourceWeapon.Fire(out hit, skill.data.Id, dmgMult);
if (hit.normalOrMissed)
{
if (Rand.Float01() < effectProb)
{
BuffParameter prm = CommonUtils.GetRandomEnumValue <BuffParameter>(new List <BuffParameter>());
BonusType[] debuffs = BuffUtils.GetBuffsForParameter(prm);
foreach (var dbf in debuffs)
{
targetBonuses.RemoveBuffs(dbf);
}
}
source.GetComponent <MmoMessageComponent>().SendShot(EventReceiver.OwnerAndSubscriber, shotInfo);
return(true);
}
else
{
source.GetComponent <MmoMessageComponent>().SendShot(EventReceiver.OwnerAndSubscriber, shotInfo);
return(false);
}
}
public static void writePython(LangDescriptor[] languages, IList <int?> ks, float[][] medians)
{
StringBuilder data = new StringBuilder();
StringBuilder plot = new StringBuilder();
for (int i = 0; i < languages.Length; i++)
{
LangDescriptor language = languages[i];
IList <float?> filteredMedians = BuffUtils.filter(Arrays.asList(medians[i]), m => m != null);
data.Append(language.name + '=' + filteredMedians + '\n');
plot.Append(string.Format("ax.plot(ks, {0}, label=\"{1}\", marker='{2}', color='{3}')\n", language.name, language.name, nameToGraphMarker.get(language.name), nameToGraphColor.get(language.name)));
}
string python = "#\n" + "# AUTO-GENERATED FILE. DO NOT EDIT\n" + "# CodeBuff %s '%s'\n" + "#\n" + "import numpy as np\n" + "import matplotlib.pyplot as plt\n\n" + "%s\n" + "ks = %s\n" + "fig = plt.figure()\n" + "ax = plt.subplot(111)\n" + "%s" + "ax.tick_params(axis='both', which='major', labelsize=18)\n" + "ax.set_xlabel(\"$k$ nearest neighbors\", fontsize=20)\n" + "ax.set_ylabel(\"Median error rate\", fontsize=20)\n" + "#ax.set_title(\"k Nearest Neighbors vs\\nLeave-one-out Validation Error Rate\")\n" + "plt.legend(fontsize=18)\n\n" + "fig.savefig('images/vary_k.pdf', format='pdf')\n" + "plt.show()\n";
string code = string.format(python, Tool.version, DateTime.Now, data, ks, plot);
string fileName = "python/src/vary_k.py";
org.antlr.codebuff.misc.Utils.writeFile(fileName, code);
Log.WriteLine("wrote python code to " + fileName);
}
/// <summary>
/// Remove any positive Bonus Type from object
/// </summary>
public void RemoveAnyPositiveBuff()
{
bool buffFounded = false;
BonusType foundedBuffType = BonusType.block_heal;
foreach (var pBonus in bonuses)
{
if (BuffUtils.IsBuff(pBonus.Key))
{
foundedBuffType = pBonus.Key;
buffFounded = true;
break;
}
}
if (buffFounded)
{
PlayerBonus removedBonus = null;
bonuses.TryRemove(foundedBuffType, out removedBonus);
}
}
public static void examineCorpus(Corpus corpus)
{
ArrayListMultiMap <FeatureVectorAsObject, int> wsByFeatureVectorGroup = ArrayListMultiMap <FeatureVectorAsObject, int> .create();
ArrayListMultiMap <FeatureVectorAsObject, int> hposByFeatureVectorGroup = ArrayListMultiMap <FeatureVectorAsObject, int> .create();
int numContexts = corpus.featureVectors.Count;
for (int i = 0; i < numContexts; i++)
{
int[] X = corpus.featureVectors[i];
int y1 = corpus.injectWhitespace[i];
int y2 = corpus.hpos[i];
wsByFeatureVectorGroup.Add(new FeatureVectorAsObject(X, Trainer.FEATURES_INJECT_WS), y1);
hposByFeatureVectorGroup.Add(new FeatureVectorAsObject(X, Trainer.FEATURES_HPOS), y2);
}
IList <double> wsEntropies = new List <double>();
IList <double> hposEntropies = new List <double>();
foreach (FeatureVectorAsObject x in wsByFeatureVectorGroup.Keys)
{
var cats = wsByFeatureVectorGroup[x];
var cats2 = hposByFeatureVectorGroup[x];
HashBag <int> wsCats = getCategoriesBag(cats);
HashBag <int> hposCats = getCategoriesBag(cats2);
double wsEntropy = getNormalizedCategoryEntropy(getCategoryRatios(wsCats.Values));
double hposEntropy = getNormalizedCategoryEntropy(getCategoryRatios(hposCats.Values));
wsEntropies.Add(wsEntropy);
hposEntropies.Add(hposEntropy);
Console.Write("{0,130} : {1},{2} {3},{4}\n", x, wsCats, wsEntropy, hposCats, hposEntropy);
}
Console.WriteLine("MEAN " + BuffUtils.mean(wsEntropies));
Console.WriteLine("MEAN " + BuffUtils.mean(hposEntropies));
float contextRichness = wsEntropies.Count / (float)numContexts; // 0..1 where 1 means every token had different context
Console.WriteLine("Context richness = " + contextRichness + " uniq ctxs=" + wsEntropies.Count + ", nctxs=" + numContexts);
}
public static void computeConsistency(LangDescriptor language, bool report)
{
if (report)
{
Console.WriteLine("-----------------------------------");
Console.WriteLine(language.name);
Console.WriteLine("-----------------------------------");
}
Corpus corpus = new Corpus(language.corpusDir, language);
corpus.train();
// a map of feature vector to list of exemplar indexes of that feature
MyMultiMap <FeatureVectorAsObject, int> wsContextToIndex = new MyMultiMap <FeatureVectorAsObject, int>();
MyMultiMap <FeatureVectorAsObject, int> hposContextToIndex = new MyMultiMap <FeatureVectorAsObject, int>();
int n = corpus.featureVectors.Count;
for (int i = 0; i < n; i++)
{
int[] features = corpus.featureVectors[i];
wsContextToIndex.Map(new FeatureVectorAsObject(features, Trainer.FEATURES_INJECT_WS), i);
hposContextToIndex.Map(new FeatureVectorAsObject(features, Trainer.FEATURES_HPOS), i);
}
int num_ambiguous_ws_vectors = 0;
int num_ambiguous_hpos_vectors = 0;
// Dump output grouped by ws vs hpos then feature vector then category
if (report)
{
Console.WriteLine(" --- INJECT WS ---");
}
IList <double> ws_entropies = new List <double>();
foreach (FeatureVectorAsObject fo in wsContextToIndex.Keys)
{
var exemplarIndexes = wsContextToIndex[fo];
// we have group by feature vector, now group by cat with that set for ws
MyMultiMap <int, int> wsCatToIndexes = new MyMultiMap <int, int>();
foreach (int i in exemplarIndexes)
{
wsCatToIndexes.Map(corpus.injectWhitespace[i], i);
}
if (wsCatToIndexes.Count == 1)
{
continue;
}
if (report)
{
Console.WriteLine("Feature vector has " + exemplarIndexes.size() + " exemplars");
}
IList <int> catCounts = BuffUtils.map(wsCatToIndexes.Values, (x) => x.size());
double wsEntropy = Entropy.getNormalizedCategoryEntropy(Entropy.getCategoryRatios(catCounts));
if (report)
{
Console.Write("entropy={0,5:F4}\n", wsEntropy);
}
wsEntropy *= exemplarIndexes.size();
ws_entropies.Add(wsEntropy);
num_ambiguous_ws_vectors += exemplarIndexes.size();
if (report)
{
Console.Write(Trainer.featureNameHeader(Trainer.FEATURES_INJECT_WS));
}
if (report)
{
foreach (int cat in wsCatToIndexes.Keys)
{
var indexes = wsCatToIndexes[cat];
foreach (int i in indexes)
{
string display = getExemplarDisplay(Trainer.FEATURES_INJECT_WS, corpus, corpus.injectWhitespace, i);
Console.WriteLine(display);
}
Console.WriteLine();
}
}
}
if (report)
{
Console.WriteLine(" --- HPOS ---");
}
IList <double> hpos_entropies = new List <double>();
foreach (FeatureVectorAsObject fo in hposContextToIndex.Keys)
{
MyHashSet <int> exemplarIndexes = hposContextToIndex[fo];
// we have group by feature vector, now group by cat with that set for hpos
MyMultiMap <int, int> hposCatToIndexes = new MyMultiMap <int, int>();
foreach (int i in exemplarIndexes)
{
hposCatToIndexes.Map(corpus.hpos[i], i);
}
if (hposCatToIndexes.Count == 1)
{
continue;
}
if (report)
{
Console.WriteLine("Feature vector has " + exemplarIndexes.size() + " exemplars");
}
IList <int> catCounts = BuffUtils.map(hposCatToIndexes.Values, (x) => x.size());
double hposEntropy = Entropy.getNormalizedCategoryEntropy(Entropy.getCategoryRatios(catCounts));
if (report)
{
Console.Write("entropy={0,5:F4}\n", hposEntropy);
}
hposEntropy *= exemplarIndexes.size();
hpos_entropies.Add(hposEntropy);
num_ambiguous_hpos_vectors += exemplarIndexes.size();
if (report)
{
Console.Write(Trainer.featureNameHeader(Trainer.FEATURES_HPOS));
}
if (report)
{
foreach (int cat in hposCatToIndexes.Keys)
{
var indexes = hposCatToIndexes[cat];
foreach (int?i in indexes)
{
string display = getExemplarDisplay(Trainer.FEATURES_HPOS, corpus, corpus.hpos, i.Value);
Console.WriteLine(display);
}
Console.WriteLine();
}
}
}
Console.WriteLine();
Console.WriteLine(language.name);
Console.WriteLine("There are " + wsContextToIndex.Count + " unique ws feature vectors out of " + n + " = " + string.Format("{0,3:F1}%", 100.0 * wsContextToIndex.Count / n));
Console.WriteLine("There are " + hposContextToIndex.Count + " unique hpos feature vectors out of " + n + " = " + string.Format("{0,3:F1}%", 100.0 * hposContextToIndex.Count / n));
float prob_ws_ambiguous = num_ambiguous_ws_vectors / (float)n;
Console.Write("num_ambiguous_ws_vectors = {0,5:D}/{1,5:D} = {2,5:F3}\n", num_ambiguous_ws_vectors, n, prob_ws_ambiguous);
float prob_hpos_ambiguous = num_ambiguous_hpos_vectors / (float)n;
Console.Write("num_ambiguous_hpos_vectors = {0,5:D}/{1,5:D} = {2,5:F3}\n", num_ambiguous_hpos_vectors, n, prob_hpos_ambiguous);
// Collections.sort(ws_entropies);
// System.out.println("ws_entropies="+ws_entropies);
Console.WriteLine("ws median,mean = " + BuffUtils.median(ws_entropies) + "," + BuffUtils.mean(ws_entropies));
double expected_ws_entropy = (BuffUtils.sumDoubles(ws_entropies) / num_ambiguous_ws_vectors) * prob_ws_ambiguous;
Console.WriteLine("expected_ws_entropy=" + expected_ws_entropy);
Console.WriteLine("hpos median,mean = " + BuffUtils.median(hpos_entropies) + "," + BuffUtils.mean(hpos_entropies));
double expected_hpos_entropy = (BuffUtils.sumDoubles(hpos_entropies) / num_ambiguous_hpos_vectors) * prob_hpos_ambiguous;
Console.WriteLine("expected_hpos_entropy=" + expected_hpos_entropy);
}
public override bool TryCast(NebulaObject source, PlayerSkill skill, out Hashtable info)
{
info = new Hashtable();
if (NotEnemyCheck(source, skill, info))
{
return(false);
}
var targ = source.Target().targetObject;
var sourceCharacter = source.Character();
var sourceWeapon = source.Weapon();
var message = source.GetComponent <MmoMessageComponent>();
float dmgMult = skill.GetFloatInput("dmg_mult");
float radius = skill.GetFloatInput("radius");
bool mastery = RollMastery(source);
if (mastery)
{
dmgMult *= 2;
radius *= 2;
}
WeaponHitInfo hit;
var shot = sourceWeapon.Fire(out hit, skill.data.Id, dmgMult);
BonusType[] speedDebuffs = BuffUtils.GetDebuffsForParameter(BuffParameter.speed);
if (hit.normalOrMissed)
{
message.SendShot(EventReceiver.OwnerAndSubscriber, shot);
var items = source.mmoWorld().GetItems((item) => {
var itemBonuses = item.Bonuses();
var itemCharacter = item.Character();
var itemDamagable = item.Damagable();
bool allComponentPresent = itemBonuses && itemCharacter && itemDamagable;
if (allComponentPresent)
{
if (item.Id != targ.Id)
{
float distanceToTarg = targ.transform.DistanceTo(item.transform);
if (distanceToTarg <= radius)
{
if (itemBonuses.ContainsAny(speedDebuffs))
{
var relation = sourceCharacter.RelationTo(itemCharacter);
if (relation == FractionRelation.Enemy || relation == FractionRelation.Neutral)
{
return(true);
}
}
}
}
}
return(false);
});
foreach (var pitem in items)
{
WeaponHitInfo itemHit;
var itemShot = sourceWeapon.Fire(pitem.Value, out itemHit, skill.data.Id, dmgMult);
if (hit.normalOrMissed)
{
message.SendShot(EventReceiver.OwnerAndSubscriber, itemShot);
}
else
{
message.SendShot(EventReceiver.OwnerAndSubscriber, shot);
}
}
return(true);
}
else
{
source.GetComponent <MmoMessageComponent>().SendShot(EventReceiver.OwnerAndSubscriber, shot);
return(false);
}
}
private bool IsBuff(BonusType type)
{
return(!BuffUtils.IsDebuff(type));
}
public static string Main(object[] args)
{
Log.Reset();
try
{
if (args.Length < 7)
{
Log.WriteLine("org.antlr.codebuff.Tool -g grammar-name -rule start-rule -corpus root-dir-of-samples \\\n" + " [-files file-extension] [-indent num-spaces] \\" + " [-comment line-comment-name] [-o output-file] file-to-format");
return(Log.Message());
}
formatted_output = null;
string outputFileName = "";
string grammarName = null;
string startRule = null;
string corpusDir = null;
string indentS = "4";
string commentS = null;
string input_file_name = null;
string fileExtension = null;
int i = 0;
Type parserClass = null;
Type lexerClass = null;
while (i < args.Length && ((string)args[i]).StartsWith("-", StringComparison.Ordinal))
{
switch (args[i])
{
case "-g":
i++;
grammarName = (string)args[i++];
break;
case "-lexer":
i++;
lexerClass = (Type)args[i++];
break;
case "-parser":
i++;
parserClass = (Type)args[i++];
break;
case "-rule":
i++;
startRule = (string)args[i++];
break;
case "-corpus":
i++;
corpusDir = (string)args[i++];
break;
case "-files":
i++;
fileExtension = (string)args[i++];
break;
case "-indent":
i++;
indentS = (string)args[i++];
break;
case "-comment":
i++;
commentS = (string)args[i++];
break;
case "-o":
i++;
outputFileName = (string)args[i++];
break;
case "-inoutstring":
i++;
formatted_output = "";
outputFileName = null;
break;
}
}
input_file_name = (string)args[i]; // must be last
Log.WriteLine("gramm: " + grammarName);
string parserClassName = grammarName + "Parser";
string lexerClassName = grammarName + "Lexer";
Lexer lexer = null;
if (lexerClass == null || parserClass == null)
{
Log.WriteLine("You must specify a lexer and parser.");
}
if (parserClass == null | lexerClass == null)
{
return(Log.Message());
}
int indentSize = int.Parse(indentS);
int singleLineCommentType = -1;
if (!string.ReferenceEquals(commentS, null))
{
try
{
lexer = getLexer(lexerClass, null);
}
catch (Exception e)
{
Log.WriteLine("Can't instantiate lexer " + lexerClassName);
Log.WriteLine(e.StackTrace);
}
if (lexer == null)
{
return(Log.Message());
}
IDictionary <string, int> tokenTypeMap = lexer.TokenTypeMap;
if (tokenTypeMap.ContainsKey(commentS))
{
singleLineCommentType = tokenTypeMap[commentS];
}
}
string fileRegex = null;
if (!string.ReferenceEquals(fileExtension, null))
{
var pattern = "";
var allowable_suffices = fileExtension.Split(';').ToList <string>();
foreach (var s in allowable_suffices)
{
var no_dot = s.Substring(s.IndexOf('.') + 1);
pattern = pattern == "" ? ("(" + no_dot) : (pattern + "|" + no_dot);
}
pattern = pattern + ")";
fileRegex = ".*\\." + pattern;
}
LangDescriptor language = new LangDescriptor(grammarName, corpusDir, fileRegex, lexerClass, parserClass, startRule, indentSize, singleLineCommentType);
////////
// load all corpus files up front
IList <string> allFiles = getFilenames(language.corpusDir, language.fileRegex);
IList <InputDocument> documents = load(allFiles, language);
// Handle formatting of document if it's passed as a string or not.
if (unformatted_input == null)
{
// Don't include file to format in corpus itself.
string path = System.IO.Path.GetFullPath(input_file_name);
IList <InputDocument> others = BuffUtils.filter(documents, d => !d.fileName.Equals(path));
// Perform training of formatter.
Corpus corpus = new Corpus(others, language);
corpus.train();
// Parse code contained in file.
InputDocument unformatted_document = parse(input_file_name, language);
// Format document.
Formatter formatter = new Formatter(corpus, language.indentSize, Formatter.DEFAULT_K, Trainer.FEATURES_INJECT_WS, Trainer.FEATURES_HPOS);
formatted_output = formatter.format(unformatted_document, false);
}
else
{
// Perform training of formatter.
Corpus corpus = new Corpus(documents, language);
corpus.train();
// Parse code that was represented as a string.
InputDocument unformatted_document = parse(input_file_name, unformatted_input, language);
// Format document.
Formatter formatter = new Formatter(corpus, language.indentSize, Formatter.DEFAULT_K, Trainer.FEATURES_INJECT_WS, Trainer.FEATURES_HPOS);
formatted_output = formatter.format(unformatted_document, false);
}
///////
if (outputFileName != null && outputFileName == "")
{
Log.WriteLine(formatted_output);
}
else if (!string.IsNullOrEmpty(outputFileName))
{
org.antlr.codebuff.misc.Utils.writeFile(outputFileName, formatted_output);
}
}
catch (Exception e)
{
throw e;
}
return(formatted_output);
}
/// <summary>
/// Return a new map from rulename to List of (a,b) pairs stripped of
/// tuples (a,b) where a or b is in rule repeated token set.
/// E.g., before removing repeated token ',', we see:
///
/// elementValueArrayInitializer: 4:'{',',' 1:'{','}' 4:',','}'
///
/// After removing tuples containing repeated tokens, we get:
///
/// elementValueArrayInitializer: 1:'{','}'
/// </summary>
protected internal virtual IDictionary <RuleAltKey, IList <org.antlr.codebuff.misc.Pair <int, int> > > stripPairsWithRepeatedTokens()
{
IDictionary <RuleAltKey, IList <org.antlr.codebuff.misc.Pair <int, int> > > ruleToPairsWoRepeats = new Dictionary <RuleAltKey, IList <org.antlr.codebuff.misc.Pair <int, int> > >();
// For each rule
foreach (RuleAltKey ruleAltKey in ruleToPairsBag.Keys)
{
ISet <int> ruleRepeatedTokens = null;
ruleToRepeatedTokensSet.TryGetValue(ruleAltKey, out ruleRepeatedTokens);
ISet <org.antlr.codebuff.misc.Pair <int, int> > pairsBag = null;
ruleToPairsBag.TryGetValue(ruleAltKey, out pairsBag);
// If there are repeated tokens for this rule
if (ruleRepeatedTokens != null)
{
// Remove all (a,b) for b in repeated token set
IList <org.antlr.codebuff.misc.Pair <int, int> > pairsWoRepeats = BuffUtils.filter(pairsBag, p => !ruleRepeatedTokens.Contains(p.a) && !ruleRepeatedTokens.Contains(p.b));
ruleToPairsWoRepeats[ruleAltKey] = pairsWoRepeats;
}
else
{
ruleToPairsWoRepeats[ruleAltKey] = new List <org.antlr.codebuff.misc.Pair <int, int> >(pairsBag);
}
}
return(ruleToPairsWoRepeats);
}
public static void Main(string[] args)
{
if (args.Length < 2)
{
Console.Error.WriteLine("Dbg [-leave-one-out] [-java|-java8|-antlr|-sqlite|-tsql] test-file");
}
int arg = 0;
bool leaveOneOut = true;
bool collectAnalysis = true;
string language = args[arg++];
language = language.Substring(1);
string testFilename = args[arg];
string output = "???";
InputDocument testDoc = null;
IList <TokenPositionAnalysis> analysisPerToken = null;
org.antlr.codebuff.misc.Pair <string, IList <TokenPositionAnalysis> > results;
LangDescriptor lang = null;
System.DateTime start, stop;
for (int i = 0; i < Tool.languages.Length; i++)
{
if (Tool.languages[i].name.Equals(language))
{
lang = Tool.languages[i];
break;
}
}
if (lang != null)
{
start = System.DateTime.Now;
LeaveOneOutValidator validator = new LeaveOneOutValidator(lang.corpusDir, lang);
Triple <Formatter, float, float> val = validator.validateOneDocument(testFilename, null, collectAnalysis);
testDoc = Tool.parse(testFilename, lang);
stop = System.DateTime.Now;
Formatter formatter = val.a;
output = formatter.Output;
Console.WriteLine("output len = " + output.Length);
float editDistance = normalizedLevenshteinDistance(testDoc.content, output);
Console.WriteLine("normalized Levenshtein distance: " + editDistance);
analysisPerToken = formatter.AnalysisPerToken;
Regex rex = new Regex("^\\s+$");
CommonTokenStream original_tokens = Tool.tokenize(testDoc.content, lang.lexerClass);
IList <Token> wsTokens = BuffUtils.filter(original_tokens.GetTokens(), t => rex.IsMatch(t.Text));
string originalWS = tokenText(wsTokens);
Console.WriteLine("origin ws tokens len: " + originalWS.Length);
CommonTokenStream formatted_tokens = Tool.tokenize(output, lang.lexerClass);
wsTokens = BuffUtils.filter(formatted_tokens.GetTokens(), t => rex.IsMatch(t.Text));
string formattedWS = tokenText(wsTokens);
Console.WriteLine("formatted ws tokens len: " + formattedWS.Length);
editDistance = levenshteinDistance(originalWS, formattedWS);
editDistance /= Math.Max(testDoc.content.Length, output.Length);
Console.WriteLine("Levenshtein distance of ws normalized to output len: " + editDistance);
ClassificationAnalysis analysis = new ClassificationAnalysis(testDoc, analysisPerToken);
Console.WriteLine(analysis);
}
if (lang != null)
{
// GUIController controller;
// controller = new GUIController(analysisPerToken, testDoc, output, lang.lexerClass);
//controller.show();
// System.out.println(output);
//Console.Write("formatting time {0:D}s\n", (stop - start) / 1000000);
Console.Write("classify calls {0:D}, hits {1:D} rate {2:F}\n", kNNClassifier.nClassifyCalls, kNNClassifier.nClassifyCacheHits, kNNClassifier.nClassifyCacheHits / (float)kNNClassifier.nClassifyCalls);
Console.Write("kNN calls {0:D}, hits {1:D} rate {2:F}\n", kNNClassifier.nNNCalls, kNNClassifier.nNNCacheHits, kNNClassifier.nNNCacheHits / (float)kNNClassifier.nNNCalls);
}
}
public static void Main(string[] args)
{
if (args.Length < 7)
{
Console.Error.WriteLine("org.antlr.codebuff.Tool -g grammar-name -rule start-rule -corpus root-dir-of-samples \\\n" + " [-files file-extension] [-indent num-spaces] \\" + " [-comment line-comment-name] [-o output-file] file-to-format");
return;
}
formatted_output = null;
string outputFileName = "";
string grammarName = null;
string startRule = null;
string corpusDir = null;
string indentS = "4";
string commentS = null;
string input_file_name = null;
string fileExtension = null;
int i = 0;
while (i < args.Length && args[i].StartsWith("-", StringComparison.Ordinal))
{
switch (args[i])
{
case "-g":
i++;
grammarName = args[i++];
break;
case "-rule":
i++;
startRule = args[i++];
break;
case "-corpus":
i++;
corpusDir = args[i++];
break;
case "-files":
i++;
fileExtension = args[i++];
break;
case "-indent":
i++;
indentS = args[i++];
break;
case "-comment":
i++;
commentS = args[i++];
break;
case "-o":
i++;
outputFileName = args[i++];
break;
case "-inoutstring":
i++;
formatted_output = "";
outputFileName = null;
break;
}
}
input_file_name = args[i]; // must be last
Console.WriteLine("gramm: " + grammarName);
string parserClassName = grammarName + "Parser";
string lexerClassName = grammarName + "Lexer";
Type parserClass = null;
Type lexerClass = null;
Lexer lexer = null;
try
{
parserClass = (Type)Type.GetType(parserClassName);
lexerClass = (Type)Type.GetType(lexerClassName);
}
catch (Exception e)
{
Console.Error.WriteLine("Can't load " + parserClassName + " or maybe " + lexerClassName);
Console.Error.WriteLine("Make sure they are generated by ANTLR, compiled, and in CLASSPATH");
System.Console.WriteLine(e.StackTrace);
}
if (parserClass == null | lexerClass == null)
{
return; // don't return from catch!
}
int indentSize = int.Parse(indentS);
int singleLineCommentType = -1;
if (!string.ReferenceEquals(commentS, null))
{
try
{
lexer = getLexer(lexerClass, null);
}
catch (Exception e)
{
Console.Error.WriteLine("Can't instantiate lexer " + lexerClassName);
System.Console.WriteLine(e.StackTrace);
}
if (lexer == null)
{
return;
}
IDictionary <string, int> tokenTypeMap = lexer.TokenTypeMap;
if (tokenTypeMap.ContainsKey(commentS))
{
singleLineCommentType = tokenTypeMap[commentS];
}
}
string fileRegex = null;
if (!string.ReferenceEquals(fileExtension, null))
{
fileRegex = ".*\\." + fileExtension;
}
LangDescriptor language = new LangDescriptor(grammarName, corpusDir, fileRegex, lexerClass, parserClass, startRule, indentSize, singleLineCommentType);
////////
// load all corpus files up front
IList <string> allFiles = getFilenames(language.corpusDir, language.fileRegex);
IList <InputDocument> documents = load(allFiles, language);
// Handle formatting of document if it's passed as a string or not.
if (unformatted_input == null)
{
// Don't include file to format in corpus itself.
string path = System.IO.Path.GetFullPath(input_file_name);
IList <InputDocument> others = BuffUtils.filter(documents, d => !d.fileName.Equals(path));
// Perform training of formatter.
Corpus corpus = new Corpus(others, language);
corpus.train();
// Parse code contained in file.
InputDocument unformatted_document = parse(input_file_name, language);
// Format document.
Formatter formatter = new Formatter(corpus, language.indentSize, Formatter.DEFAULT_K, Trainer.FEATURES_INJECT_WS, Trainer.FEATURES_HPOS);
formatted_output = formatter.format(unformatted_document, false);
}
else
{
// Perform training of formatter.
Corpus corpus = new Corpus(documents, language);
corpus.train();
// Parse code that was represented as a string.
InputDocument unformatted_document = parse(input_file_name, unformatted_input, language);
// Format document.
Formatter formatter = new Formatter(corpus, language.indentSize, Formatter.DEFAULT_K, Trainer.FEATURES_INJECT_WS, Trainer.FEATURES_HPOS);
formatted_output = formatter.format(unformatted_document, false);
}
///////
if (outputFileName != null && outputFileName == "")
{
System.Console.WriteLine(formatted_output);
}
else if (!string.IsNullOrEmpty(outputFileName))
{
org.antlr.codebuff.misc.Utils.writeFile(outputFileName, formatted_output);
}
}
public static void runCaptureForOneLanguage(LangDescriptor language)
{
IList <string> filenames = Tool.getFilenames(language.corpusDir, language.fileRegex);
IList <float> selfEditDistances = new List <float>();
foreach (string fileName in filenames)
{
Corpus corpus = new Corpus(fileName, language);
corpus.train();
InputDocument testDoc = Tool.parse(fileName, corpus.language);
Formatter formatter = new Formatter(corpus, language.indentSize);
string output = formatter.format(testDoc, false);
// System.out.println(output);
float editDistance = Dbg.normalizedLevenshteinDistance(testDoc.content, output);
Log.WriteLine(fileName + " edit distance " + editDistance);
selfEditDistances.Add(editDistance);
}
{
Corpus corpus = new Corpus(language.corpusDir, language);
corpus.train();
IList <float> corpusEditDistances = new List <float>();
foreach (string fileName in filenames)
{
InputDocument testDoc = Tool.parse(fileName, corpus.language);
Formatter formatter = new Formatter(corpus, language.indentSize);
string output = formatter.format(testDoc, false);
// System.out.println(output);
float editDistance = Dbg.normalizedLevenshteinDistance(testDoc.content, output);
Log.WriteLine(fileName + "+corpus edit distance " + editDistance);
corpusEditDistances.Add(editDistance);
}
// heh this gives info on within-corpus variability. i.e., how good/consistent is my corpus?
// those files with big difference are candidates for dropping from corpus or for cleanup.
IList <string> labels = BuffUtils.map(filenames, f => '"' + System.IO.Path.GetFileName(f) + '"');
string python = "#\n" + "# AUTO-GENERATED FILE. DO NOT EDIT\n" + "# CodeBuff <version> '<date>'\n" + "#\n" +
"import numpy as np\n" + "import matplotlib.pyplot as plt\n\n" + "fig = plt.figure()\n" +
"ax = plt.subplot(111)\n" + "labels = <labels>\n" + "N = len(labels)\n\n" +
"featureIndexes = range(0,N)\n" + "<lang>_self = <selfEditDistances>\n" +
"<lang>_corpus = <corpusEditDistances>\n" +
"<lang>_diff = np.abs(np.subtract(<lang>_self, <lang>_corpus))\n\n" +
"all = zip(<lang>_self, <lang>_corpus, <lang>_diff, labels)\n" +
"all = sorted(all, key=lambda x : x[2], reverse=True)\n" +
"<lang>_self, <lang>_corpus, <lang>_diff, labels = zip(*all)\n\n" +
"ax.plot(featureIndexes, <lang>_self, label=\"<lang>_self\")\n" +
"#ax.plot(featureIndexes, <lang>_corpus, label=\"<lang>_corpus\")\n" +
"ax.plot(featureIndexes, <lang>_diff, label=\"<lang>_diff\")\n" +
"ax.set_xticklabels(labels, rotation=60, fontsize=8)\n" +
"plt.xticks(featureIndexes, labels, rotation=60)\n" +
"ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)\n\n" +
"ax.text(1, .25, 'median $f$ self distance = %5.3f, corpus+$f$ distance = %5.3f' %" +
" (np.median(<lang>_self),np.median(<lang>_corpus)))\n" + "ax.set_xlabel(\"File Name\")\n" +
"ax.set_ylabel(\"Edit Distance\")\n" +
"ax.set_title(\"Difference between Formatting File <lang> $f$\\nwith Training=$f$ and Training=$f$+Corpus\")\n" +
"plt.legend()\n" + "plt.tight_layout()\n" + "fig.savefig(\"images/" + language.name +
"_one_file_capture.pdf\", format='pdf')\n" + "plt.show()\n";
ST pythonST = new ST(python);
pythonST.add("lang", language.name);
pythonST.add("version", version);
pythonST.add("date", DateTime.Now);
pythonST.add("labels", labels.ToString());
pythonST.add("selfEditDistances", selfEditDistances.ToString());
pythonST.add("corpusEditDistances", corpusEditDistances.ToString());
string code = pythonST.render();
{
string fileName = "python/src/" + language.name + "_one_file_capture.py";
org.antlr.codebuff.misc.Utils.writeFile(fileName, code);
Log.WriteLine("wrote python code to " + fileName);
}
}
}
