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/**
* (C) Copyright 2012-2013 A-cube lab - Università di Pisa - Dipartimento di Informatica.
* BAT-Framework is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
* BAT-Framework is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
* You should have received a copy of the GNU General Public License along with BAT-Framework. If not, see .
*/
package it.unipi.di.acube.batframework.utils;
import it.unipi.di.acube.batframework.cache.BenchmarkCache;
import it.unipi.di.acube.batframework.data.*;
import it.unipi.di.acube.batframework.metrics.*;
import it.unipi.di.acube.batframework.problems.*;
import java.io.*;
import java.util.*;
/**
* This class contains all the methods to dump the result of an experiment, both
* to the screen (methods print*), in latex form (methods latex*), or as gnuplot
* data used to generate charts (methods gnuplot*).
*
*/
public class DumpResults {
private static final Locale LOCALE = Locale.US;
private static final String CHARTS_DIR = "charts/";
private static class StringLengthComparator implements Comparator {
public int compare(String o1, String o2) {
return o1.length() - o2.length();
}
}
/**
* Writes (as {@code .dat} gnuplot data) the micro-F1, micro-precision and
* micro-recall achieved for each combination of Match relation - Annotator
* - Dataset, varying the score threshold in [0,1], to a file in the form
* matchrelation_datasetname_f1_threshold_annotatorname.dat. Note that this
* will generate
* {@code 3 * matchRels.size() * annotators.size() * dss.size()} files. Also
* note that the experiments must have already been performed and their
* results stored in {@code threshRecords}.
*
* @param matchRels
* the set of Match relations.
* @param annotators
* the set of annotators.
* @param dss
* the set of datasets.
* @param api
* the API to Wikipedia (needed to print information about
* annotations/tags).
* @param threshRecords
* the hashmap in the form metric -> annotator -> dataset ->
* (threshold, results) where the results are stored.
* @param
* the type of system.
* @param
* the type of system's output.
* @param
* the type of dataset.
* @throws IOException
* if something went wrong while querying the Wikipedia API.
*/
public static void gnuplotCorrectnessPerformance(
Vector> matchRels,
List annotators,
Vector dss,
WikipediaApiInterface api,
HashMap>>> threshRecords)
throws IOException {
for (MatchRelation m : matchRels)
for (T3 ds : dss) {
for (T1 t : annotators) {
System.out.println("Writing to gnuplot-file "
+ ds.getName() + "/" + t.getName()
+ " with varying score threshold...");
String prefix = CHARTS_DIR
+ m.getName().replaceAll("[^a-zA-Z0-9]", "")
.toLowerCase();
String suffix = t.getName().replaceAll("[^a-zA-Z0-9]", "")
.toLowerCase()
+ "_"
+ ds.getName().replaceAll("[^a-zA-Z0-9]", "")
.toLowerCase() + ".dat";
OutputStreamWriter precOs = new OutputStreamWriter(
new FileOutputStream(prefix
+ "_precision_threshold_" + suffix));
OutputStreamWriter recOs = new OutputStreamWriter(
new FileOutputStream(prefix + "_recall_threshold_"
+ suffix));
OutputStreamWriter f1Os = new OutputStreamWriter(
new FileOutputStream(prefix + "_f1_threshold_"
+ suffix));
HashMap records = RunExperiments
.getRecords(threshRecords, m.getName(),
t.getName(), ds.getName());
List thresholds = new Vector(records.keySet());
Collections.sort(thresholds);
for (Float thr : thresholds) {
MetricsResultSet rs = records.get(thr);
System.out.printf(
LOCALE,
t.getName() + " - " + ds.getName() + " " + thr
+ " tp:" + rs.getGlobalTp() + " fp:"
+ rs.getGlobalFp() + " fn:"
+ rs.getGlobalFn() + " prec:"
+ rs.getMicroPrecision() + " rec:"
+ rs.getMicroRecall() + " f1:"
+ rs.getMicroF1() + "\n");
precOs.write(String.format(LOCALE, "%f\t%f%n", thr,
rs.getMicroPrecision()));
recOs.write(String.format(LOCALE, "%f\t%f%n", thr,
rs.getMicroRecall()));
f1Os.write(String.format(LOCALE, "%f\t%f%n", thr,
rs.getMicroF1()));
}
precOs.close();
recOs.close();
f1Os.close();
}
}
System.out.println("Flushing Wikipedia API cache...");
api.flush();
}
/**
* Writes a file {@code runtime_f1.dat} storing (avg. runtime, achieved best
* micro-F1) pairs for a single dataset and a single match relation. Note
* that the experiments must have already been performed and their results
* stored in {@code threshRecords}.
*
* @param matchRelName
* The match relation used to compute the micro-F1.
* @param a2wAnnotators
* The set of A2W Annotators for which a pair must be included in
* the output.
* @param sa2wAnnotators
* The set of Sa2W Annotators for which a pair must be included.
* @param datasetName
* The name of the dataset for which the pairs must be included.
* @param api
* the API to Wikipedia (needed to print information about
* annotations/tags).
* @param threshRecords
* the hashmap in the form metric -> annotator -> dataset ->
* (threshold, results) where the results are stored.
* @throws IOException
* if something went wrong while querying the Wikipedia API.
* @throws Exception
* if the cache does not contain records about the given
* dataset/annotator avg. time.
*/
public static void gnuplotRuntimeF1(
String matchRelName,
Vector a2wAnnotators,
Vector sa2wAnnotators,
String datasetName,
WikipediaApiInterface api,
HashMap>>> threshRecords)
throws IOException, Exception {
OutputStreamWriter runTimeF1Stream = new OutputStreamWriter(
new FileOutputStream(CHARTS_DIR + "runtime_f1.dat"));
if (a2wAnnotators != null)
for (A2WSystem t : a2wAnnotators)
runTimeF1Stream.write(String.format(LOCALE, "%f\t%d\t\"%s\"\n",
RunExperiments.getBestRecord(threshRecords,
matchRelName, t.getName(), datasetName).second
.getMicroF1(), (int) BenchmarkCache
.getAvgA2WTimingsForDataset(t.getName(),
datasetName), t.getName()));
if (sa2wAnnotators != null)
for (Sa2WSystem t : sa2wAnnotators)
runTimeF1Stream.write(String.format(LOCALE, "%f\t%d\t\"%s\"\n",
RunExperiments.getBestRecord(threshRecords,
matchRelName, t.getName(), datasetName).second
.getMicroF1(), (int) BenchmarkCache
.getAvgSa2WTimingsForDataset(t.getName(),
datasetName), t.getName()));
runTimeF1Stream.close();
}
/**
* Print a latex tables reporting the best micro-F1 achieved by each
* (annotator, dataset) pair. A Latex table is printed for the metrics based
* on each match relation passed in {@code matchRels}.
*
* @param matchRels
* the set of Match relations for which a table will be printed.
* @param a2wAnnotators
* The set of A2W Annotators for which the best result will be
* included in the output.
* @param d2wAnnotators
* The set of D2W Annotators for which the best result will be
* included in the output.
* @param sa2wAnnotators
* The set of Sa2W Annotators for which the best result will be
* included.
* @param sc2wAnnotators
* The set of Sc2W Annotators for which the best result will be
* included.
* @param c2wAnnotators
* The set of C2W Annotators for which the best result will be
* included in the output.
* @param dss
* The datasets for which the best result will be included.
* @param includeTpFpFn
* true if the output table has to include the total number of
* tp/fp/fn
* @param threshRecords
* the hashmap in the form metric -> annotator -> dataset ->
* (threshold, results) where the results are stored.
* @param includeMicro
* whether or not to include micro-measures in the table
* @param includeMacro
* whether or not to include macro-measures in the table
* @param includeTpFpFn
* whether or not to include TP, FP and FN count in the table
* @param
* the type of data on which the match relation operates.
* @param
* the type of dataset.
*/
public static void latexCorrectnessPerformance(
Vector> matchRels,
Vector a2wAnnotators,
Vector d2wAnnotators,
Vector sa2wAnnotators,
Vector sc2wAnnotators,
Vector c2wAnnotators,
Vector dss,
boolean includeTpFpFn,
boolean includeMicro,
boolean includeMacro,
HashMap>>> threshRecords) {
System.out.println("Correctness performance - latex output");
Vector allAnns = new Vector();
if (sa2wAnnotators != null)
allAnns.addAll(sa2wAnnotators);
if (sc2wAnnotators != null)
allAnns.addAll(sc2wAnnotators);
if (a2wAnnotators != null)
allAnns.addAll(a2wAnnotators);
if (d2wAnnotators != null)
allAnns.addAll(d2wAnnotators);
if (c2wAnnotators != null)
allAnns.addAll(c2wAnnotators);
for (MatchRelation m : matchRels) {
System.out.println("+++ Match Relation: " + m.getName());
System.out
.printf(LOCALE,
"\\hline \n Dataset & Annotator & Best Threshold"
+ (includeMicro ? " & $F1_{micro}$ & $P_{micro}$ & $R_{micro}$ "
: "")
+ (includeMacro ? " & $F1_{macro}$ & $P_{macro}$ & $R_{macro}$ "
: "")
+ (includeTpFpFn ? "& tp & fp & fn" : "")
+ "\\\\ \n \\hline%n");
for (TopicDataset d : dss) {
long len = 0;
for (String s : d.getTextInstanceList())
len += s.length();
System.out
.printf(LOCALE,
"\\multirow{%d}{*}{\\parbox{.20\\textwidth}{%s \\newline(avg-len\\newline %d chars)}} %n",
allAnns.size(), d.getName(),
(int) ((float) len / (float) d.getSize()));
for (TopicSystem t : allAnns) {
Pair values = RunExperiments
.getBestRecord(threshRecords, m.getName(),
t.getName(), d.getName());
System.out.printf(LOCALE, "& %s & $%.3f$ ", t.getName(),
values.first);
if (includeMicro)
System.out.printf(LOCALE,
"& $%.1f$ & $%.1f$ & $%.1f$ ",
values.second.getMicroF1() * 100f,
values.second.getMicroPrecision() * 100f,
values.second.getMicroRecall() * 100f);
if (includeMacro)
System.out.printf(LOCALE,
"& $%.1f$ & $%.1f$ & $%.1f$ ",
values.second.getMacroF1() * 100f,
values.second.getMacroPrecision() * 100f,
values.second.getMacroRecall() * 100f);
if (includeTpFpFn)
System.out.printf(LOCALE, "& $%d$ & $%d$ & $%d$",
values.second.getGlobalTp(),
values.second.getGlobalFp(),
values.second.getGlobalFn());
int nColumns = 3 + (includeTpFpFn?3:0)+(includeMacro?3:0)+(includeMicro?3:0);
System.out.printf(LOCALE, " \\\\ \\cline{2-"
+ nColumns + "}%n");
}
System.out.printf(LOCALE, "\\hline%n");
}
}
}
/**
* Print a set of latex tables reporting the similarity between annotators
* in solving the Sa2W problem, for each dataset given in {@code dssA2W}. A
* table will be printed for each of these focuses:
* 1- similarity of the whole output ("wholeOutput")
* 2- similarity of the output, restricted to the true positives ("TPonly")
* 3- similarity of the mentions ("mention")
* 4- similarity of the concepts ("concept")
*
* @param dssA2W
* the datasets for which the set of tables will be printed.
* @param sa2wAnnotators
* the Sa2W annotators whose similarity will be printed.
* @param threshRecords
* the hashmap in the form metric -> annotator -> dataset ->
* (threshold, results) where the results are stored.
* @param api
* the API to Wikipedia (needed to print information about
* annotations/tags).
* @param
* the type of dataset.
* @throws Exception
* if anything went wrong while retrieving the results.
*/
public static void latexSimilarityA2W(
Vector dssA2W,
Vector sa2wAnnotators,
HashMap>>> threshRecords,
WikipediaApiInterface api) throws Exception {
/** Difference between systems & "Jaccard" measure */
for (String focus : new String[] { "wholeOutput", "TPonly", "mention",
"concept", "mention/concept" }) {
System.out.println("Similarity measures - latex output - " + focus);
for (A2WDataset ds : dssA2W) {
System.out.println("Dataset: " + ds.getName());
for (Sa2WSystem t : sa2wAnnotators)
System.out.printf(LOCALE, "&%s", t.getName());
System.out.printf(LOCALE, "\\\\%n");
System.out.printf(LOCALE, "\\hline%n");
for (int i = 0; i < sa2wAnnotators.size(); i++) {
Sa2WSystem t1 = sa2wAnnotators.get(i);
System.out.printf(LOCALE, t1.getName());
for (int j = 0; j < sa2wAnnotators.size(); j++) {
if (j < i) {
System.out.printf(LOCALE, "&");
continue;
}
Sa2WSystem t2 = sa2wAnnotators.get(j);
List> t1Annotations = BenchmarkCache
.doSa2WAnnotations(t1, ds, null, 0);
List> t2Annotations = BenchmarkCache
.doSa2WAnnotations(t2, ds, null, 0);
List> out1 = null;
List> out2 = null;
MatchRelation m = null;
Metrics metrics = new Metrics();
if (focus.equals("wholeOutput")) {
m = new WeakAnnotationMatch(api);
out1 = ProblemReduction.Sa2WToA2WList(
t1Annotations, RunExperiments
.getBestRecord(threshRecords,
m.getName(), t1.getName(),
ds.getName()).first);
out2 = ProblemReduction.Sa2WToA2WList(
t2Annotations, RunExperiments
.getBestRecord(threshRecords,
m.getName(), t2.getName(),
ds.getName()).first);
System.out
.printf(LOCALE, "&$%.1f$",
metrics.macroSimilarity(out1, out2,
m) * 100);
} else if (focus.equals("TPonly")) {
m = new WeakAnnotationMatch(api);
List> reducedT1Tags = ProblemReduction
.Sa2WToA2WList(
t1Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t1.getName(), ds.getName()).first);
List> reducedT2Tags = ProblemReduction
.Sa2WToA2WList(
t2Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t2.getName(), ds.getName()).first);
out1 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT1Tags, m);
out2 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT2Tags, m);
System.out
.printf(LOCALE, "&$%.1f$",
metrics.macroSimilarity(out1, out2,
m) * 100);
} else if (focus.equals("mention")) {
m = new MentionAnnotationMatch();
List> reducedT1Tags = ProblemReduction
.Sa2WToA2WList(
t1Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t1.getName(), ds.getName()).first);
List> reducedT2Tags = ProblemReduction
.Sa2WToA2WList(
t2Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t2.getName(), ds.getName()).first);
out1 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT1Tags, m);
out2 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT2Tags, m);
System.out
.printf(LOCALE, "&$%.1f$",
metrics.macroSimilarity(out1, out2,
m) * 100);
} else if (focus.equals("concept")) {
m = new ConceptAnnotationMatch(api);
List> reducedT1Tags = ProblemReduction
.Sa2WToA2WList(
t1Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t1.getName(), ds.getName()).first);
List> reducedT2Tags = ProblemReduction
.Sa2WToA2WList(
t2Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t2.getName(), ds.getName()).first);
out1 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT1Tags, m);
out2 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT2Tags, m);
System.out
.printf(LOCALE, "&$%.1f$",
metrics.macroSimilarity(out1, out2,
m) * 100);
} else if (focus.equals("mention/concept")) {
m = new MentionAnnotationMatch();
List> reducedT1Tags = ProblemReduction
.Sa2WToA2WList(
t1Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t1.getName(), ds.getName()).first);
List> reducedT2Tags = ProblemReduction
.Sa2WToA2WList(
t2Annotations,
RunExperiments.getBestRecord(
threshRecords, m.getName(),
t2.getName(), ds.getName()).first);
out1 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT1Tags, m);
out2 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT2Tags, m);
m = new ConceptAnnotationMatch(api);
System.out
.printf(LOCALE, "&$%.0f$/",
metrics.macroSimilarity(out1, out2,
m) * 100);
reducedT1Tags = ProblemReduction.Sa2WToA2WList(
t1Annotations, RunExperiments
.getBestRecord(threshRecords,
m.getName(), t1.getName(),
ds.getName()).first);
reducedT2Tags = ProblemReduction.Sa2WToA2WList(
t2Annotations, RunExperiments
.getBestRecord(threshRecords,
m.getName(), t2.getName(),
ds.getName()).first);
out1 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT1Tags, m);
out2 = metrics.getTp(ds.getA2WGoldStandardList(),
reducedT2Tags, m);
System.out
.printf(LOCALE, "$%.0f$",
metrics.macroSimilarity(out1, out2,
m) * 100);
}
}
System.out.printf(LOCALE, "\\\\%n");
System.out.printf(LOCALE, "\\hline%n");
}
}
}
}
/**
* Print a set of latex tables reporting the similarity between annotators
* in solving the C2W problem, for each dataset given in {@code dssC2W}.
*
* @param dssC2W
* the datasets for which the set of tables will be printed.
* @param sa2wAnnotators
* the Sa2W annotators whose similarity will be printed.
* @param threshRecords
* the hashmap in the form metric -> annotator -> dataset ->
* (threshold, results) where the results are stored.
* @param api
* the API to Wikipedia (needed to print information about
* annotations/tags).
* @throws Exception
* if anything went wrong while retrieving the results.
*/
public static void latexSimilarityC2W(
Vector dssC2W,
Vector sa2wAnnotators,
HashMap>>> threshRecords,
WikipediaApiInterface api) throws Exception {
System.out.println("Similarity measures - latex output - tp C2W");
for (C2WDataset ds : dssC2W) {
System.out.println("Dataset: " + ds.getName());
for (Sa2WSystem t : sa2wAnnotators)
System.out.printf(LOCALE, "&" + t.getName());
System.out.printf(LOCALE, "\\\\%n");
System.out.printf(LOCALE, "\\hline%n");
for (int i = 0; i < sa2wAnnotators.size(); i++) {
Sa2WSystem t1 = sa2wAnnotators.get(i);
System.out.printf(LOCALE, t1.getName());
for (int j = 0; j < sa2wAnnotators.size(); j++) {
if (j < i) {
System.out.printf(LOCALE, "&");
continue;
}
Sa2WSystem t2 = sa2wAnnotators.get(j);
MatchRelation m = new StrongTagMatch(api);
Metrics metrics = new Metrics();
List> t1Annotations = BenchmarkCache
.doSa2WAnnotations(t1, ds, null, 0);
List> t2Annotations = BenchmarkCache
.doSa2WAnnotations(t2, ds, null, 0);
List> reducedT1Anns = ProblemReduction
.Sa2WToA2WList(t1Annotations, RunExperiments
.getBestRecord(threshRecords, m.getName(),
t1.getName(), ds.getName()).first);
List> reducedT2Anns = ProblemReduction
.Sa2WToA2WList(t2Annotations, RunExperiments
.getBestRecord(threshRecords, m.getName(),
t2.getName(), ds.getName()).first);
List> reducedT1Tags = ProblemReduction
.A2WToC2WList(reducedT1Anns);
List> reducedT2Tags = ProblemReduction
.A2WToC2WList(reducedT2Anns);
List> tponlyTagsT1 = metrics.getTp(
ds.getC2WGoldStandardList(), reducedT1Tags, m);
List> tponlyTagsT2 = metrics.getTp(
ds.getC2WGoldStandardList(), reducedT2Tags, m);
System.out.printf(LOCALE, "&$%.3f$", metrics
.macroSimilarity(tponlyTagsT1, tponlyTagsT2, m));
}
System.out.printf(LOCALE, "\\\\%n");
System.out.printf(LOCALE, "\\hline%n");
}
}
}
/**
* Prints (in latex form) a table representing the average time needed by
* all systems to solve the instance of a dataset. Rows are grouped by
* dataset and are in the form (dataset, annotator, avg. time).
*
* @param a2wAnnotators
* The A2W annotators that will be included in the output.
* @param sa2wAnnotators
* The Sa2W annotators that will be included in the output.
* @param sc2wAnnotators
* The Sc2W annotators that will be included in the output.
* @param dss
* The datasets that will be included in the output.
* @param
* the type of dataset.
* @throws Exception
* if the cache does not contain records about the given
* dataset/annotator avg. time.
*/
public static void latexTimingPerformance(
Vector a2wAnnotators, Vector sa2wAnnotators,
Vector sc2wAnnotators, Vector dss) throws Exception {
System.out.println("Timing performance - latex output");
int allAnnsSize = 0;
if (sa2wAnnotators != null)
allAnnsSize += sa2wAnnotators.size();
if (a2wAnnotators != null)
allAnnsSize += a2wAnnotators.size();
if (sc2wAnnotators != null)
allAnnsSize += sc2wAnnotators.size();
System.out.printf(LOCALE,
"\\hline \nDataset & Tagger & Average Time\\\\ \n \\hline%n");
for (TopicDataset d : dss) {
long len = 0;
for (String s : d.getTextInstanceList())
len += s.length();
System.out
.printf(LOCALE,
"\\multirow{%d}{*}{\\parbox{.40\\textwidth}{%s \\newline(len %d)}} %n",
allAnnsSize, d.getName(),
(int) ((float) len / (float) d.getSize()));
if (a2wAnnotators != null)
for (A2WSystem t : a2wAnnotators)
System.out.printf(
LOCALE,
"& %s & $%d$ms \\\\ \\cline{2-3}%n",
t.getName(),
(int) BenchmarkCache.getAvgA2WTimingsForDataset(
t.getName(), d.getName()));
if (sa2wAnnotators != null)
for (Sa2WSystem t : sa2wAnnotators)
System.out.printf(
LOCALE,
"& %s & $%d$ms \\\\ \\cline{2-3}%n",
t.getName(),
(int) BenchmarkCache.getAvgSa2WTimingsForDataset(
t.getName(), d.getName()));
System.out.printf(LOCALE, "\\hline%n");
}
}
/**
* Prints (in latex form) a table representing the average time needed by a
* system to solve the instance of a dataset. Rows are in the form
* (annotator, avg. time for system 1, avg. time for system 2, ...).
*
* @param sa2wAnnotators
* The Sa2W annotators that will be included in the output.
* @param sc2wAnnotators
* The Sc2W annotators that will be included in the output.
* @param dss
* The datasets that will be included in the output.
* @param
* the type of dataset.
* @throws Exception
* if the cache does not contain records about the given
* dataset/annotator avg. time.
*/
public static void latexTimingPerformance2(
Vector sa2wAnnotators, Vector sc2wAnnotators,
Vector dss) throws Exception {
System.out.println("Timing performance - latex output 2");
System.out.printf(LOCALE, "\\hline \nSystem ");
for (TopicDataset ds : dss)
System.out.printf(LOCALE, " & " + ds.getName());
System.out.printf(LOCALE, " \n \\hline%n");
if (sa2wAnnotators != null)
for (Sa2WSystem t : sa2wAnnotators) {
System.out.printf(LOCALE, t.getName());
for (TopicDataset d : dss)
System.out.printf(
LOCALE,
" & $%d$ ",
(int) BenchmarkCache.getAvgSa2WTimingsForDataset(
t.getName(), d.getName()));
System.out.printf(LOCALE, "\\\\%n");
System.out.printf(LOCALE, "\\hline%n");
}
if (sc2wAnnotators != null)
for (Sc2WSystem t : sc2wAnnotators) {
System.out.printf(LOCALE, t.getName());
for (TopicDataset d : dss)
System.out.printf(
LOCALE,
" & $%d$ ",
(int) BenchmarkCache.getAvgSa2WTimingsForDataset(
t.getName(), d.getName()));
System.out.printf(LOCALE, "\\\\%n");
System.out.printf(LOCALE, "\\hline%n");
}
}
public static void printCorrectnessPerformance(
Vector> matchRels,
Vector a2wAnnotators,
Vector sa2wAnnotators,
Vector c2wAnnotators,
Vector d2wAnnotators,
Vector dss,
HashMap>>> threshRecords,
boolean printMicro, boolean printMacro, boolean printTpFpFn,
float threshold) {
Vector allAnns = new Vector();
if (sa2wAnnotators != null)
allAnns.addAll(sa2wAnnotators);
if (c2wAnnotators != null)
allAnns.addAll(c2wAnnotators);
if (a2wAnnotators != null)
allAnns.addAll(a2wAnnotators);
if (d2wAnnotators != null)
allAnns.addAll(d2wAnnotators);
System.out.println("Correctness performance [F1/prec/rec]");
for (MatchRelation metric : matchRels) {
System.out.printf(LOCALE, "Best results (metrics: %s):%n",
metric.getName());
for (TopicDataset d : dss)
for (TopicSystem t : allAnns) {
Pair result = null;
if (threshold >= 0)
result = new Pair(threshold,
RunExperiments.getRecords(threshRecords,
metric.getName(), t.getName(),
d.getName()).get(threshold));
else
result = RunExperiments.getBestRecord(threshRecords,
metric.getName(), t.getName(), d.getName());
System.out.printf(LOCALE, "%s\t%s\t%.3f\t", d.getName(),
t.getName(), result.first);
if (printMicro)
System.out.printf(LOCALE, "[mic: %.3f\t%.3f\t%.3f] ",
result.second.getMicroF1(),
result.second.getMicroPrecision(),
result.second.getMicroRecall());
if (printMacro)
System.out.printf(LOCALE, "[mac: %.3f\t%.3f\t%.3f] ",
result.second.getMacroF1(),
result.second.getMacroPrecision(),
result.second.getMacroRecall());
if (printTpFpFn)
System.out.printf(LOCALE, "TP/FP/FN: %d/%d/%d",
result.second.getGlobalTp(),
result.second.getGlobalFp(),
result.second.getGlobalFn());
System.out.println();
}
}
}
/**
* Print the best micro- and macro- measures achieved by each (annotator,
* dataset) pair along with other data. Data is printed for the metrics
* based on each match relation passed in {@code matchRels}.
*
* @param matchRels
* the set of Match relations for which a table will be printed.
* @param a2wAnnotators
* The set of A2W Annotators for which the best result will be
* included in the output.
* @param d2wAnnotators
* The set of D2W Annotators for which the best result will be
* included in the output.
* @param sa2wAnnotators
* The set of Sa2W Annotators for which the best result will be
* included.
* @param c2wAnnotators
* The set of Sc2W Annotators for which the best result will be
* included.
* @param dss
* The datasets for which the best result will be included.
* @param threshRecords
* the hashmap in the form metric -> annotator -> dataset ->
* (threshold, results) where the results are stored.
* @param
* the type of data on which the match relation operates.
* @param
* the type of dataset.
*/
public static void printCorrectnessPerformance(
Vector> matchRels,
Vector a2wAnnotators,
Vector sa2wAnnotators,
Vector c2wAnnotators,
Vector d2wAnnotators,
Vector dss,
HashMap>>> threshRecords) {
printCorrectnessPerformance(matchRels, a2wAnnotators, sa2wAnnotators,
c2wAnnotators, d2wAnnotators, dss, threshRecords, true, true,
false, -1);
}
/**
* Prints the similarity, dissimilarity, and union of the results for each
* pair of annotators.
*
* @param dssA2W
* The datasets for which the data will be printed.
* @param sa2wAnnotators
* The annotators for which the data will be printed.
* @param api
* the API to Wikipedia (needed to print information about
* annotations/tags).
* @param threshRecords
* the hashmap in the form metric -> annotator -> dataset ->
* (threshold, results) where the results are stored.
* @throws Exception
* if something went wrong while retrieving the results.
*/
public static void printDissimilarityA2W(
Vector dssA2W,
Vector sa2wAnnotators,
HashMap>>> threshRecords,
WikipediaApiInterface api) throws Exception {
Metrics metrics = new Metrics();
WeakAnnotationMatch m = new WeakAnnotationMatch(api);
for (A2WDataset ds : dssA2W) {
System.out.println("Dataset: " + ds.getName());
for (int i = 0; i < sa2wAnnotators.size(); i++) {
Sa2WSystem t1 = sa2wAnnotators.get(i);
for (int j = 0; j < sa2wAnnotators.size(); j++) {
if (j <= i)
continue;
Sa2WSystem t2 = sa2wAnnotators.get(j);
System.out.println("Annotator1: " + t1.getName());
System.out.println("Annotator2: " + t2.getName());
List> t1Annotations = BenchmarkCache
.doSa2WAnnotations(t1, ds, null, 0);
List> t2Annotations = BenchmarkCache
.doSa2WAnnotations(t2, ds, null, 0);
List> reducedT1Tags = ProblemReduction
.Sa2WToA2WList(t1Annotations, RunExperiments
.getBestRecord(threshRecords, m.getName(),
t1.getName(), ds.getName()).first);
List> reducedT2Tags = ProblemReduction
.Sa2WToA2WList(t2Annotations, RunExperiments
.getBestRecord(threshRecords, m.getName(),
t2.getName(), ds.getName()).first);
List> out1Tp = metrics.getTp(
ds.getA2WGoldStandardList(), reducedT1Tags, m);
List> out2Tp = metrics.getTp(
ds.getA2WGoldStandardList(), reducedT2Tags, m);
List> out1Fp = metrics.getFp(
ds.getA2WGoldStandardList(), reducedT1Tags, m);
List> out2Fp = metrics.getFp(
ds.getA2WGoldStandardList(), reducedT2Tags, m);
long tpUnion = metrics.listUnion(out1Tp, out2Tp, m);
int tpdiss1 = metrics.dissimilarityListCount(out1Tp,
out2Tp, m);
int tpdiss2 = metrics.dissimilarityListCount(out2Tp,
out1Tp, m);
int tpsim = metrics.similarityListCount(out1Tp, out2Tp, m);
long fpUnion = metrics.listUnion(out1Fp, out2Fp, m);
int fpdiss1 = metrics.dissimilarityListCount(out1Fp,
out2Fp, m);
int fpdiss2 = metrics.dissimilarityListCount(out2Fp,
out1Fp, m);
int fpsim = metrics.similarityListCount(out1Fp, out2Fp, m);
System.out.printf(LOCALE,
"Ann1 dissimilarity tp/fp: %d(%.2f)/%d(%.2f)%n",
tpdiss1, (float) tpdiss1
/ (float) (tpdiss1 + fpdiss1), fpdiss1,
(float) fpdiss1 / (float) (tpdiss1 + fpdiss1));
System.out.printf(LOCALE,
"Ann2 dissimilarity tp/fp: %d(%.2f)/%d(%.2f)%n",
tpdiss2, (float) tpdiss2
/ (float) (tpdiss2 + fpdiss2), fpdiss2,
(float) fpdiss2 / (float) (tpdiss2 + fpdiss2));
System.out.printf(LOCALE,
"Anns similarity tp/fp: %d(%.2f)/%d(%.2f)%n",
tpsim, (float) tpsim / (float) (tpsim + fpsim),
fpsim, (float) fpsim / (float) (tpsim + fpsim));
System.out.printf(LOCALE,
"Anns union tp/fp: %d(%.2f)/%d(%.2f)%n", tpUnion,
(float) tpUnion / (float) (tpUnion + fpUnion),
fpUnion, (float) fpUnion
/ (float) (tpUnion + fpUnion));
}
}
}
}
/**
* Prints the document in a dataset with the most redirect documents for
* each (dataset, annotator) pair. (Mainly for debug purposes.)
*
* @param dss
* The datasets.
* @param sa2wAnnotators
* The annotators.
* @param api
* the API to Wikipedia (needed to find out if an
* annotations/tags is a redirect).
* @throws Exception
* if something went wrong while retrieving the results.
*/
public static void printMostRedirectDocument(Vector dss,
Vector sa2wAnnotators, WikipediaApiInterface api)
throws Exception {
System.out.println("Returned Redirect");
for (A2WDataset ds : dss) {
for (Sa2WSystem t : sa2wAnnotators) {
int totalTags = 0;
int totalRedirects = 0;
System.out
.printf(LOCALE,
"Finding document with most redirect tags for dataset:%s tagger:%s%n",
ds.getName(), t.getName());
List> compRes = BenchmarkCache
.doSa2WAnnotations(t, ds, null, 0);
int bestCount = -1;
for (int i = 0; i < compRes.size(); i++) {
HashSet comp = compRes.get(i);
int count = 0;
HashSet distinctRedirects = new HashSet();
for (ScoredAnnotation tag : comp)
if (api.isRedirect(tag.getConcept())) {
count++;
distinctRedirects.add(tag.getConcept());
}
if (bestCount < distinctRedirects.size())
bestCount = distinctRedirects.size();
totalTags += compRes.size();
totalRedirects += count;
}
System.out.printf(LOCALE,
"Tags found=%d Redirects=%d redirect/total=%.3f",
totalTags, totalRedirects, (float) totalRedirects
/ (float) totalTags);
}
}
}
/**
* Print data about correctness performance (f1, precision, recall, ...) for
* a given (annotator, dataset) pair.
*
* @param ann
* the annotator.
* @param m
* the match relation which the measurements are based upon.
* @param goldStandard
* the gold standard for the dataset.
* @param output
* the output found by the tagger.
* @param api
* the API to Wikipedia (needed to print information about
* annotations/tags).
* @param
* the type of system output and dataset.
* @throws IOException
* if something went wrong while querying the Wikipedia API.
*/
public static void printCorrectnessPerformance(
TopicSystem ann, MatchRelation m, List> goldStandard,
List> output, WikipediaApiInterface api)
throws IOException {
Metrics metrics = new Metrics();
MetricsResultSet rs = metrics.getResult(output, goldStandard, m);
System.out.format(LOCALE,
"%s tp:%d fp:%d fn:%d precision: %.3f recall:%.3f F1:%.3f%n",
ann.getName(), rs.getGlobalTp(), rs.getGlobalFp(),
rs.getGlobalFn(), rs.getMacroPrecision(), rs.getMacroRecall(),
rs.getMacroF1());
System.out.format(LOCALE,
"%s micro-precision:%.3f micro-recall:%.3f micro-F1:%.3f%n",
ann.getName(), rs.getMicroPrecision(), rs.getMicroRecall(),
rs.getMicroF1());
}
/**
* Prints a table representing the average time needed by all systems to
* solve the instance of a dataset. Rows are grouped by dataset and are in
* the form (dataset, annotator, avg. time).
*
* @param a2wAnnotators
* The A2W annotators that will be included in the output.
* @param sa2wAnnotators
* The Sa2W annotators that will be included in the output.
* @param sc2wAnnotators
* The Sa2W annotators that will be included in the output.
* @param dss
* The datasets that will be included in the output.
* @throws Exception
* if the cache does not contain records about the given
* dataset/annotator avg. time.
*/
public static void printTimingPerformance(Vector a2wAnnotators,
Vector sa2wAnnotators,
Vector sc2wAnnotators, Vector dss)
throws Exception {
if (sa2wAnnotators == null)
sa2wAnnotators = new Vector();
if (a2wAnnotators == null)
a2wAnnotators = new Vector();
if (sc2wAnnotators == null)
sc2wAnnotators = new Vector();
System.out.println("Timing performance:");
for (A2WDataset d : dss) {
for (A2WSystem t : a2wAnnotators) {
System.out.printf(LOCALE,
"Average time for T2W tagger=%s dataset=%s: %.3f%n", t
.getName(), d.getName(), BenchmarkCache
.getAvgA2WTimingsForDataset(t.getName(),
d.getName()));
if (d.getSize() != BenchmarkCache.getA2WTimingsForDataset(
t.getName(), d.getName()).size())
System.out
.printf(LOCALE,
"ERROR: size of dataset %s and computed results by %s mismatch! %d != %d",
d.getName(),
t.getName(),
d.getSize(),
BenchmarkCache.getA2WTimingsForDataset(
t.getName(), d.getName()).size());
}
for (Sa2WSystem t : sa2wAnnotators) {
System.out.printf(LOCALE,
"Average time for St2W tagger=%s dataset=%s: %.3f%n", t
.getName(), d.getName(), BenchmarkCache
.getAvgSa2WTimingsForDataset(t.getName(),
d.getName()));
if (d.getSize() != BenchmarkCache.getSa2WTimingsForDataset(
t.getName(), d.getName()).size())
System.out
.printf(LOCALE,
"ERROR: size of dataset %s and computed results by %s mismatch! %d != %d",
d.getName(),
t.getName(),
d.getSize(),
BenchmarkCache.getSa2WTimingsForDataset(
t.getName(), d.getName()).size());
}
}
}
/**
* For each dataset passed in {@code annotators}, writes one gnuplot
* {@code timing_annotator_dataset.dat} file containing the time needed by
* the annotator to annotate each document of a dataset, ordered by the
* amount of time.
* Note that the experiments must have already been performed and their
* results stored in the cache when this method is called.
*
* @param annotators
* the set of annotators for which a file will be created.
* @param ds
* the dataset.
* @throws Exception
* if there were errors in writing the file or in retrieving the
* timing.
*/
public static void gnuplotTraceTiming(Vector annotators,
A2WDataset ds) throws Exception {
for (Sa2WSystem annotator : annotators) {
String suffix = annotator.getName().replaceAll("[^a-zA-Z0-9]", "")
.toLowerCase()
+ "_"
+ ds.getName().replaceAll("[^a-zA-Z0-9]", "").toLowerCase()
+ ".dat";
OutputStreamWriter relOs = new OutputStreamWriter(
new FileOutputStream(CHARTS_DIR + "timing_" + suffix));
Vector texts = new Vector(ds.getTextInstanceList());
Collections.sort(texts, new StringLengthComparator());
for (String text : texts) {
long time = BenchmarkCache.getSa2WTiming(annotator.getName(),
ds.getName(), text);
relOs.write(String.format(LOCALE, "%d\t%d%n", text.length(),
time));
}
relOs.close();
}
}
}
