下面列出了com.google.common.collect.Table#get ( ) 实例代码，或者点击链接到github查看源代码，也可以在右侧发表评论。
public void onSeedFinished(Node<Statement, Val> seed, final ForwardBoomerangResults<W> res) {
Table<Statement, Val, W> results = res.asStatementValWeightTable();
for (final Entry<Unit, Assertion> e : stmtToResults.entries()) {
if (e.getValue() instanceof ComparableResult) {
final ComparableResult<W, Val> expectedResults = (ComparableResult) e.getValue();
W w2 = results.get(new Statement((Stmt) e.getKey(), null), expectedResults.getVal());
if (w2 != null) {
expectedResults.computedResults(w2);
}
}
// check if any of the methods that should not be analyzed have been analyzed
if (e.getValue() instanceof ShouldNotBeAnalyzed) {
final ShouldNotBeAnalyzed shouldNotBeAnalyzed = (ShouldNotBeAnalyzed) e.getValue();
Unit analyzedUnit = e.getKey();
if (analyzedUnit.equals(shouldNotBeAnalyzed.unit)) {
shouldNotBeAnalyzed.hasBeenAnalyzed();
}
}
}
}
public void writeCSV(String outputFile, Table<Integer, Integer, String> resultTable)
throws IOException {
FileWriter writer = new FileWriter(outputFile);
for (Integer row : resultTable.rowKeySet()) {
boolean first = true;
for (Integer column : resultTable.columnKeySet()) {
if (!first) {
writer.append(',');
}
String value = resultTable.get(row, column);
if (value != null) {
writer.append(value);
}
first = false;
}
writer.append('\n');
}
writer.flush();
writer.close();
}
private static void parseFile(final Table<String, Integer, TreebankParse> parses, final Iterator<String> propbank,
final boolean isPropbank, final Table<String, Integer, SRLParse> result) {
SRLParse srlparse;
String file;
int number;
while (propbank.hasNext()) {
final String line = propbank.next();
// wsj/00/wsj_0003.mrg 0 24 gold expose.01 p---p 24:1-rel
// 25:2-ARG2-to 27:6-ARGM-TMP 20:1,21:1,22:1,23:1-ARG1
final String[] fields = line.split(" ");
file = fields[0].substring(fields[0].lastIndexOf("/") + 1, fields[0].length() - 4);
number = Integer.valueOf(fields[1]);
final TreebankParse treebank = parses.get(file, number);
srlparse = result.get(file, number);
if (srlparse == null) {
srlparse = new SRLParse(treebank.getWords());
result.put(file, number, srlparse);
}
srlparse.add(parseLine(line, treebank, isPropbank));
}
}
@Test
public void givenArrayTable_whenGet_returnsSuccessfully() {
final List<String> universityRowTable = Lists.newArrayList("Mumbai", "Harvard");
final List<String> courseColumnTables = Lists.newArrayList("Chemical", "IT", "Electrical");
final Table<String, String, Integer> universityCourseSeatTable = ArrayTable.create(universityRowTable, courseColumnTables);
universityCourseSeatTable.put("Mumbai", "Chemical", 120);
universityCourseSeatTable.put("Mumbai", "IT", 60);
universityCourseSeatTable.put("Harvard", "Electrical", 60);
universityCourseSeatTable.put("Harvard", "IT", 120);
final int seatCount = universityCourseSeatTable.get("Mumbai", "IT");
assertThat(seatCount).isEqualTo(60);
}
private Function<Integer, String> createIdentifierResolver(FieldName name, Table<Integer, FieldName, FieldValue> table){
Function<Integer, String> function = new Function<Integer, String>(){
@Override
public String apply(Integer row){
FieldValue value = table.get(row, name);
if(FieldValueUtil.isMissing(value)){
throw new MissingValueException(name);
}
return value.asString();
}
};
return function;
}
public QuickStringIntTable(Table<String, String, Integer> table) {
ArrayList<String> labelList = Lists.newArrayList(table.rowKeySet());
labelBase = findABase(labelList);
labelSize = labelBase.length;
data = new int[labelSize * labelSize];
for (String rowKey : table.rowKeySet()) {
for (String colKey : table.columnKeySet()) {
int rowid = labelBase[rowKey.hashCode() % labelSize];
int colid = labelBase[colKey.hashCode() % labelSize];
data[rowid * labelSize + colid] = table.get(rowKey, colKey);
}
}
}
public QuickStringDoubleTable(Table<String, String, Double> table) {
ArrayList<String> labelList = Lists.newArrayList(table.rowKeySet());
labelBase = findABase(labelList);
labelSize = labelBase.length;
data = new double[labelSize * labelSize];
for (String rowKey : table.rowKeySet()) {
for (String colKey : table.columnKeySet()) {
int rowid = labelBase[rowKey.hashCode() % labelSize];
int colid = labelBase[colKey.hashCode() % labelSize];
data[rowid * labelSize + colid] = table.get(rowKey, colKey);
}
}
}
@Test
public void givenTable_whenGet_returnsSuccessfully() {
final Table<String, String, Integer> universityCourseSeatTable = HashBasedTable.create();
universityCourseSeatTable.put("Mumbai", "Chemical", 120);
universityCourseSeatTable.put("Mumbai", "IT", 60);
universityCourseSeatTable.put("Harvard", "Electrical", 60);
universityCourseSeatTable.put("Harvard", "IT", 120);
final int seatCount = universityCourseSeatTable.get("Mumbai", "IT");
final Integer seatCountForNoEntry = universityCourseSeatTable.get("Oxford", "IT");
assertThat(seatCount).isEqualTo(60);
assertThat(seatCountForNoEntry).isEqualTo(null);
}
private static List<Service> getAndSetEntry(Table<String, String, List<Service>> services, String clusterName, String clusterType) {
List<Service> serviceList = services.get(clusterName, clusterType);
if (serviceList == null) {
serviceList = new ArrayList<>();
services.put(clusterName, clusterType, serviceList);
}
return serviceList;
}
/**
* parse the ini file and return a map with all data
*
* @param resourcePath
* The path of the input file
* @param conf
* The configuration info
* @return the result of sentry mapping data in map structure.
*/
@Override
public Map<String, Map<String, Set<String>>> parse(String resourcePath, Configuration conf)
throws Exception {
Map<String, Map<String, Set<String>>> resultMap = Maps.newHashMap();
// SimpleFileProviderBackend is used for parse the ini file
SimpleFileProviderBackend policyFileBackend = new SimpleFileProviderBackend(conf, resourcePath);
ProviderBackendContext context = new ProviderBackendContext();
context.setAllowPerDatabase(true);
// parse the ini file
policyFileBackend.initialize(context);
// SimpleFileProviderBackend parsed the input file and output the data in Table format.
Table<String, String, Set<String>> groupRolePrivilegeTable = policyFileBackend
.getGroupRolePrivilegeTable();
Map<String, Set<String>> groupRolesMap = Maps.newHashMap();
Map<String, Set<String>> rolePrivilegesMap = Maps.newHashMap();
for (String groupName : groupRolePrivilegeTable.rowKeySet()) {
for (String roleName : groupRolePrivilegeTable.columnKeySet()) {
// get the roles set for the current groupName
Set<String> tempRoles = groupRolesMap.get(groupName);
if (tempRoles == null) {
tempRoles = Sets.newHashSet();
}
Set<String> privileges = groupRolePrivilegeTable.get(groupName, roleName);
// if there has privilege for [group,role], if no privilege exist, the [group, role] info
// will be discard.
if (privileges != null) {
// update [group, role] mapping data
tempRoles.add(roleName);
groupRolesMap.put(groupName, tempRoles);
// update [role, privilege] mapping data
rolePrivilegesMap.put(roleName, privileges);
}
}
}
resultMap.put(PolicyFileConstants.GROUPS, groupRolesMap);
resultMap.put(PolicyFileConstants.ROLES, rolePrivilegesMap);
return resultMap;
}
public static <R, C, V> void add(final Table<R, C, Multiset<V>> table, final R row, final C column, final V value) {
Multiset<V> multiset = table.get(row, column);
if (multiset == null) {
multiset = HashMultiset.create();
table.put(row, column, multiset);
}
multiset.add(value);
}
/**
* Converts Guava table to a CSV table
*
* @param table table
* @param csvFormat CSV format
* @param missingValuePlaceholder print if a value is missing (empty string by default)
* @param <T> object type (string)
* @return table
* @throws IOException exception
*/
public static <T> String tableToCsv(Table<String, String, T> table, CSVFormat csvFormat,
String missingValuePlaceholder)
throws IOException
{
StringWriter sw = new StringWriter();
CSVPrinter printer = new CSVPrinter(sw, csvFormat);
List<String> firstRow = new ArrayList<>();
firstRow.add(" ");
firstRow.addAll(table.columnKeySet());
printer.printRecord(firstRow);
for (String rowKey : table.rowKeySet()) {
printer.print(rowKey);
for (String columnKey : table.columnKeySet()) {
T value = table.get(rowKey, columnKey);
if (value == null) {
printer.print(missingValuePlaceholder);
}
else {
printer.print(value);
}
}
printer.println();
}
printer.close();
return sw.toString();
}
@Test
public void crossSimCommutativeTest() {
Map<String, String> parameters = Maps.newHashMap();
parameters.put("committers","false");
parameters.put("deps","true");
parameters.put("stargazers","true");
parameters.put("freqDeps", "129");
Table<String, String, Double> table = crossSim.calculateAggregatedSimilarityValues(artifacts, parameters);
double val1 = table.get(artifacts.get(0).getFullName(), artifacts.get(1).getFullName());
double val2 = table.get(artifacts.get(1).getFullName(), artifacts.get(0).getFullName());
assertEquals(val1,val2, 0.0);
}
@Test
public void crossSimIdentityTest() {
Map<String, String> parameters = new HashMap<>();
parameters.put("committers","false");
parameters.put("deps","true");
parameters.put("stargazers","true");
parameters.put("freqDeps", "129");
Table<String, String, Double> table = crossSim.calculateAggregatedSimilarityValues(artifacts, parameters);
double val1 = table.get(artifacts.get(0).getFullName(), artifacts.get(0).getFullName());
assertEquals(val1, 1, 0.0);
}
private static int pickUtilization(Table<Integer, String, AtomicInteger> u, int year,
String category) {
AtomicInteger value = u.get(year, category);
if (value == null) {
return 0;
} else {
return value.get();
}
}
@Test
public void crossSimCommutativeTest() {
Map<String, String> parameters = new HashMap<>();
parameters.put("committers","false");
parameters.put("deps","true");
parameters.put("stargazers","true");
parameters.put("freqDeps", "129");
Table<String, String, Double> table = crossRec.calculateAggregatedSimilarityValues(artifacts, parameters);
double val1 = table.get(artifacts.get(0).getFullName(), artifacts.get(1).getFullName());
double val2 = table.get(artifacts.get(1).getFullName(), artifacts.get(0).getFullName());
assertEquals(val1,val2, 0.0001);
}
/**
* Set up the demographics to use for testing.
*/
@BeforeClass
@SuppressWarnings("rawtypes")
public static void setUp() throws IOException {
demographicsFile = Config.get("generate.demographics.default_file");
Config.set("generate.demographics.default_file", "geography/test_demographics.csv");
Table pa = Demographics.load("Pennsylvania");
philly = (Demographics) pa.get("Pennsylvania", "27237");
random = new Random();
}
protected Map<BrokerNode, Table<String, Short, List<CommitAckData>>> buildCommitAckParams(Map<String, List<ConsumeReply>> ackMap, String app) {
Map<BrokerNode, Table<String, Short, List<CommitAckData>>> result = Maps.newHashMap();
for (Map.Entry<String, List<ConsumeReply>> entry : ackMap.entrySet()) {
String topic = entry.getKey();
TopicMetadata topicMetadata = clusterManager.fetchTopicMetadata(topic, app);
if (topicMetadata == null) {
logger.warn("topic {} metadata is null", topic);
continue;
}
for (ConsumeReply consumeReply : entry.getValue()) {
PartitionMetadata partitionMetadata = topicMetadata.getPartition(consumeReply.getPartition());
if (partitionMetadata == null) {
partitionMetadata = topicMetadata.getPartitions().get(0);
}
BrokerNode leader = partitionMetadata.getLeader();
if (leader == null) {
logger.warn("topic {}, partition {}, leader is null", topic, consumeReply.getPartition());
continue;
}
Table<String, Short, List<CommitAckData>> topicConsumeAckTable = result.get(leader);
if (topicConsumeAckTable == null) {
topicConsumeAckTable = HashBasedTable.create();
result.put(leader, topicConsumeAckTable);
}
List<CommitAckData> commitAckList = topicConsumeAckTable.get(topic, consumeReply.getPartition());
if (commitAckList == null) {
commitAckList = Lists.newLinkedList();
topicConsumeAckTable.put(topic, consumeReply.getPartition(), commitAckList);
}
commitAckList.add(new CommitAckData(consumeReply.getPartition(), consumeReply.getIndex(), consumeReply.getRetryType()));
}
}
return result;
}
@Override
public void prepare(Configurator configuration, DataModule model, DataSpace space) {
super.prepare(configuration, model, space);
commentField = configuration.getString("data.model.fields.comment");
commentDimension = model.getQualityInner(commentField);
MemoryQualityAttribute attribute = (MemoryQualityAttribute) space.getQualityAttribute(commentField);
Object[] documentValues = attribute.getDatas();
// init hyper-parameters
lambda = configuration.getFloat("recommender.regularization.lambda", 0.001F);
lambdaU = configuration.getFloat("recommender.regularization.lambdaU", 0.001F);
lambdaV = configuration.getFloat("recommender.regularization.lambdaV", 0.001F);
lambdaB = configuration.getFloat("recommender.regularization.lambdaB", 0.001F);
numberOfTopics = configuration.getInteger("recommender.topic.number", 10);
learnRatio = configuration.getFloat("recommender.iterator.learnrate", 0.01F);
epocheSize = configuration.getInteger("recommender.iterator.maximum", 10);
numberOfDocuments = scoreMatrix.getElementSize();
// count the number of words, build the word dictionary and
// userItemToDoc dictionary
Map<String, Integer> wordDictionaries = new HashMap<>();
Table<Integer, Integer, Float> documentTable = HashBasedTable.create();
int rowCount = 0;
userItemToDocument = HashBasedTable.create();
for (DataInstance sample : model) {
int userIndex = sample.getQualityFeature(userDimension);
int itemIndex = sample.getQualityFeature(itemDimension);
int documentIndex = sample.getQualityFeature(commentDimension);
userItemToDocument.put(userIndex, itemIndex, rowCount);
// convert wordIds to wordIndices
String data = (String) documentValues[documentIndex];
String[] words = data.isEmpty() ? new String[0] : data.split(":");
for (String word : words) {
Integer wordIndex = wordDictionaries.get(word);
if (wordIndex == null) {
wordIndex = numberOfWords++;
wordDictionaries.put(word, wordIndex);
}
Float oldValue = documentTable.get(rowCount, wordIndex);
if (oldValue == null) {
oldValue = 0F;
}
float newValue = oldValue + 1F / words.length;
documentTable.put(rowCount, wordIndex, newValue);
}
rowCount++;
}
// build W
W = SparseMatrix.valueOf(numberOfDocuments, numberOfWords, documentTable);
userBiases = DenseVector.valueOf(userSize);
userBiases.iterateElement(MathCalculator.SERIAL, (scalar) -> {
scalar.setValue(distribution.sample().floatValue());
});
itemBiases = DenseVector.valueOf(itemSize);
itemBiases.iterateElement(MathCalculator.SERIAL, (scalar) -> {
scalar.setValue(distribution.sample().floatValue());
});
userFactors = DenseMatrix.valueOf(userSize, numberOfTopics);
userFactors.iterateElement(MathCalculator.SERIAL, (scalar) -> {
scalar.setValue(distribution.sample().floatValue());
});
itemFactors = DenseMatrix.valueOf(itemSize, numberOfTopics);
itemFactors.iterateElement(MathCalculator.SERIAL, (scalar) -> {
scalar.setValue(distribution.sample().floatValue());
});
K = initStd;
topicVector = DenseVector.valueOf(numberOfTopics);
function = new SoftMaxActivationFunction();
// init theta and phi
// TODO theta实际是documentFactors
documentFactors = DenseMatrix.valueOf(numberOfDocuments, numberOfTopics);
calculateTheta();
// TODO phi实际是wordFactors
wordFactors = DenseMatrix.valueOf(numberOfTopics, numberOfWords);
wordFactors.iterateElement(MathCalculator.SERIAL, (scalar) -> {
scalar.setValue(RandomUtility.randomFloat(0.01F));
});
logger.info("number of users : " + userSize);
logger.info("number of Items : " + itemSize);
logger.info("number of words : " + wordDictionaries.size());
}
/**
* Processes the given ruleset, deciding whether it should be kept
* or removed by looking at the given previous rules.
*/
private void processRuleset(
Table<String, String, CssRulesetNode> rules, CssRulesetNode ruleset) {
if ((referencedRules != null) && !referencedRules.isEmpty()) {
// If this rule is not referenced to in the code we remove it.
if (isSelectorUnreferenced(ruleset.getSelectors().getChildAt(0))) {
// TODO(henrywong, dgajda): Storing the set of things to clean up
// in the tree is pretty brittle - better would be to have the pass
// return the rules it finds and then manually pass them in to the
// EliminateUselessRulesets pass.
tree.getRulesetNodesToRemove().addRulesetNode(ruleset);
return;
}
}
// Make sure the node has only one declaration.
Preconditions.checkArgument(ruleset.getDeclarations().numChildren() == 1);
Preconditions.checkArgument(
ruleset.getDeclarations().getChildAt(0) instanceof CssDeclarationNode);
CssDeclarationNode declaration =
(CssDeclarationNode) ruleset.getDeclarations().getChildAt(0);
CssPropertyNode propertyNode = declaration.getPropertyName();
String propertyName = propertyNode.getPropertyName();
if (PROPERTIES_NOT_TO_BE_CHECKED.contains(propertyName)) {
return;
}
// If the declaration is star-hacked then we make the star be part of
// the property name to ensure that we do not consider hacked
// declarations as overridden by the non-hacked ones.
if (declaration.hasStarHack()) {
propertyName = "*" + propertyName;
}
String selector = PassUtil.printSelector(
ruleset.getSelectors().getChildAt(0));
CssRulesetNode previousRuleset = rules.get(selector, propertyName);
if (previousRuleset != null) {
// If the new rule is important and the saved was not, then remove the saved one.
if (isImportantRule(ruleset) && !isImportantRule(previousRuleset)) {
tree.getRulesetNodesToRemove().addRulesetNode(previousRuleset);
// Replace the non-important ruleset in the map, keep the important one.
rules.put(selector, propertyName, ruleset);
} else {
tree.getRulesetNodesToRemove().addRulesetNode(ruleset);
}
} else if (hasOverridingShorthand(propertyNode, selector, rules, ruleset)) {
tree.getRulesetNodesToRemove().addRulesetNode(ruleset);
} else if (PassUtil.hasAlternateAnnotation(declaration)) {
// The declaration has @alternate, so do not let it mask other
// declarations that precede it. However, @alternate rules may be masked
// by succeeding [email protected] rules.
} else {
rules.put(selector, propertyName, ruleset);
}
}