Example usage for com.google.common.collect Iterables get

Introduction

In this page you can find the example usage for com.google.common.collect Iterables get.

Prototype

public static <T> T get(Iterable<T> iterable, int position) 

Source Link

Document

Returns the element at the specified position in an iterable.

Usage

From source file:org.jclouds.examples.ec2.spot.MainApp.java

public static void main(String[] args) {

    if (args.length < PARAMETERS)
        throw new IllegalArgumentException(INVALID_SYNTAX);

    // Args/*  www  .  j  a  v  a  2 s. c o  m*/
    String accesskeyid = args[0];
    String secretkey = args[1];
    String group = args[2];
    String command = args[3];

    // Init
    ComputeService compute = new ComputeServiceContextFactory().createContext("aws-ec2", accesskeyid, secretkey)
            .getComputeService();

    // wait up to 60 seconds for ssh to be accessible
    RetryablePredicate<IPSocket> socketTester = new RetryablePredicate<IPSocket>(new InetSocketAddressConnect(),
            60, 1, 1, TimeUnit.SECONDS);
    try {
        if (command.equals("create")) {

            Template template = compute.templateBuilder().build();

            template.getOptions().as(AWSEC2TemplateOptions.class)
                    // set the price as 3 cents/hr
                    .spotPrice(0.03f)
                    // authorize my ssh key
                    .authorizePublicKey(Files.toString(
                            new File(System.getProperty("user.home") + "/.ssh/id_rsa.pub"), Charsets.UTF_8));

            System.out.printf(">> running one spot node type(%s) with ami(%s) in group(%s)%n",
                    template.getHardware().getProviderId(), template.getImage().getId(), group);
            // run only a single node
            NodeMetadata node = Iterables.getOnlyElement(compute.createNodesInGroup(group, 1, template));

            System.out.printf("<< running node(%s)%n", node.getId());
            IPSocket socket = new IPSocket(Iterables.get(node.getPublicAddresses(), 0), node.getLoginPort());
            if (socketTester.apply(socket)) {
                System.out.printf("<< socket ready [%s] node(%s)%n", socket, node.getId());
                System.out.printf("ssh to node with the following command:%n ssh %s@%s%n",
                        node.getCredentials().identity, socket.getAddress());
                System.exit(0);
            } else {
                System.out.printf("<< socket not ready [%s] node(%s)%n", socket, node.getId());
            }
        } else if (command.equals("destroy")) {
            System.out.printf(">> destroying nodes in group(%s)%n", group);
            Set<? extends NodeMetadata> destroyed = compute.destroyNodesMatching(NodePredicates.inGroup(group));
            System.out.printf("<< destroyed(%d)%n", destroyed.size());
            System.exit(0);
        } else {
            System.err.println(INVALID_SYNTAX);
            System.exit(1);
        }
    } catch (RunNodesException e) {
        System.err.println(e.getMessage());
        for (NodeMetadata node : e.getNodeErrors().keySet())
            compute.destroyNode(node.getId());
        System.exit(1);
    } catch (IOException e) {
        System.err.println(e.getMessage());
        System.exit(1);
    } finally {
        compute.getContext().close();
    }

}

---

From source file:com.technobium.MultinomialLogisticRegression.java

public static void main(String[] args) throws Exception {
    // this test trains a 3-way classifier on the famous Iris dataset.
    // a similar exercise can be accomplished in R using this code:
    //    library(nnet)
    //    correct = rep(0,100)
    //    for (j in 1:100) {
    //      i = order(runif(150))
    //      train = iris[i[1:100],]
    //      test = iris[i[101:150],]
    //      m = multinom(Species ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width, train)
    //      correct[j] = mean(predict(m, newdata=test) == test$Species)
    //    }//  ww  w .  j av  a2  s. co  m
    //    hist(correct)
    //
    // Note that depending on the training/test split, performance can be better or worse.
    // There is about a 5% chance of getting accuracy < 90% and about 20% chance of getting accuracy
    // of 100%
    //
    // This test uses a deterministic split that is neither outstandingly good nor bad

    RandomUtils.useTestSeed();
    Splitter onComma = Splitter.on(",");

    // read the data
    List<String> raw = Resources.readLines(Resources.getResource("iris.csv"), Charsets.UTF_8);

    // holds features
    List<Vector> data = Lists.newArrayList();

    // holds target variable
    List<Integer> target = Lists.newArrayList();

    // for decoding target values
    Dictionary dict = new Dictionary();

    // for permuting data later
    List<Integer> order = Lists.newArrayList();

    for (String line : raw.subList(1, raw.size())) {
        // order gets a list of indexes
        order.add(order.size());

        // parse the predictor variables
        Vector v = new DenseVector(5);
        v.set(0, 1);
        int i = 1;
        Iterable<String> values = onComma.split(line);
        for (String value : Iterables.limit(values, 4)) {
            v.set(i++, Double.parseDouble(value));
        }
        data.add(v);

        // and the target
        target.add(dict.intern(Iterables.get(values, 4)));
    }

    // randomize the order ... original data has each species all together
    // note that this randomization is deterministic
    Random random = RandomUtils.getRandom();
    Collections.shuffle(order, random);

    // select training and test data
    List<Integer> train = order.subList(0, 100);
    List<Integer> test = order.subList(100, 150);
    logger.warn("Training set = {}", train);
    logger.warn("Test set = {}", test);

    // now train many times and collect information on accuracy each time
    int[] correct = new int[test.size() + 1];
    for (int run = 0; run < 200; run++) {
        OnlineLogisticRegression lr = new OnlineLogisticRegression(3, 5, new L2(1));
        // 30 training passes should converge to > 95% accuracy nearly always but never to 100%
        for (int pass = 0; pass < 30; pass++) {
            Collections.shuffle(train, random);
            for (int k : train) {
                lr.train(target.get(k), data.get(k));
            }
        }

        // check the accuracy on held out data
        int x = 0;
        int[] count = new int[3];
        for (Integer k : test) {
            Vector vt = lr.classifyFull(data.get(k));
            int r = vt.maxValueIndex();
            count[r]++;
            x += r == target.get(k) ? 1 : 0;
        }
        correct[x]++;

        if (run == 199) {

            Vector v = new DenseVector(5);
            v.set(0, 1);
            int i = 1;
            Iterable<String> values = onComma.split("6.0,2.7,5.1,1.6,versicolor");
            for (String value : Iterables.limit(values, 4)) {
                v.set(i++, Double.parseDouble(value));
            }

            Vector vt = lr.classifyFull(v);
            for (String value : dict.values()) {
                System.out.println("target:" + value);
            }
            int t = dict.intern(Iterables.get(values, 4));

            int r = vt.maxValueIndex();
            boolean flag = r == t;
            lr.close();

            Closer closer = Closer.create();

            try {
                FileOutputStream byteArrayOutputStream = closer
                        .register(new FileOutputStream(new File("model.txt")));
                DataOutputStream dataOutputStream = closer
                        .register(new DataOutputStream(byteArrayOutputStream));
                PolymorphicWritable.write(dataOutputStream, lr);
            } finally {
                closer.close();
            }
        }
    }

    // verify we never saw worse than 95% correct,
    for (int i = 0; i < Math.floor(0.95 * test.size()); i++) {
        System.out.println(String.format("%d trials had unacceptable accuracy of only %.0f%%: ", correct[i],
                100.0 * i / test.size()));
    }
    // nor perfect
    System.out.println(String.format("%d trials had unrealistic accuracy of 100%%", correct[test.size() - 1]));
}

---

From source file:org.jnario.lib.JnarioIterableExtensions.java

/**
  * Returns the element at the specified position in the arguments.
  */* www. j  a v  a2 s  . co m*/
  * @param index index of the element to return
  * @return the element at the specified position in this argument list
  * @throws IndexOutOfBoundsException if the index is out of range
  *         (<tt>index &lt; 0 || index &gt;= size()</tt>)
  */
public static <T> T get(Iterable<T> iterable, int index) {
    return Iterables.get(iterable, index);
}

---

From source file:org.jclouds.googlecomputeengine.domain.SlashEncodedIds.java

public static SlashEncodedIds fromSlashEncoded(String id) {
    Iterable<String> parts = Splitter.on('/').split(checkNotNull(id, "id"));
    checkArgument(Iterables.size(parts) == 2, "id must be in format firstId/secondId");
    return new SlashEncodedIds(Iterables.get(parts, 0), Iterables.get(parts, 1));
}

---

From source file:org.jclouds.openstack.nova.v2_0.domain.zonescoped.ZoneAndId.java

public static ZoneAndId fromSlashEncoded(String id) {
    Iterable<String> parts = Splitter.on('/').split(checkNotNull(id, "id"));
    checkArgument(Iterables.size(parts) == 2, "id must be in format zoneId/id");
    return new ZoneAndId(Iterables.get(parts, 0), Iterables.get(parts, 1));
}

---

From source file:org.jclouds.elb.domain.regionscoped.RegionAndName.java

public static RegionAndName fromSlashEncoded(String name) {
    Iterable<String> parts = Splitter.on('/').split(checkNotNull(name, "name"));
    checkArgument(Iterables.size(parts) == 2, "name must be in format regionId/name");
    return new RegionAndName(Iterables.get(parts, 0), Iterables.get(parts, 1));
}

---

From source file:org.jclouds.joyent.sdc.v6_5.domain.datacenterscoped.DatacenterAndId.java

public static DatacenterAndId fromSlashEncoded(String id) {
    Iterable<String> parts = Splitter.on('/').split(checkNotNull(id, "id"));
    checkArgument(Iterables.size(parts) == 2, "id must be in format datacenterId/id");
    return new DatacenterAndId(Iterables.get(parts, 0), Iterables.get(parts, 1));
}

---

From source file:org.apache.jclouds.profitbricks.rest.domain.zonescoped.DataCenterAndId.java

public static DataCenterAndId fromSlashEncoded(String id) {
    Iterable<String> parts = Splitter.on('/').split(checkNotNull(id, "id"));
    checkArgument(Iterables.size(parts) == 2, "id must be in format dataCenterId/id");
    return new DataCenterAndId(Iterables.get(parts, 0), Iterables.get(parts, 1));
}

---

From source file:org.jclouds.azurecompute.arm.domain.RegionAndId.java

public static RegionAndId fromSlashEncoded(String id) {
    Iterable<String> parts = Splitter.on('/').split(checkNotNull(id, "id"));
    checkArgument(Iterables.size(parts) == 2, "id must be in format regionId/id");
    return new AutoValue_RegionAndId(Iterables.get(parts, 0), Iterables.get(parts, 1));
}

---

From source file:org.apache.whirr.service.puppet.predicates.PuppetPredicates.java

public static Predicate<String> isFirstPuppetRoleIn(final Iterable<String> roles) {
    return new Predicate<String>() {

        @Override/* w  ww .j  a v a2s  . co m*/
        public boolean apply(String arg0) {
            return Iterables
                    .get(Iterables.filter(roles, Predicates.containsPattern("^" + PUPPET_ROLE_PREFIX + arg0)),
                            0)
                    .equals(PUPPET_ROLE_PREFIX + arg0);
        }

        @Override
        public String toString() {
            return "isFirstPuppetRoleIn(" + roles + ")";

        }
    };

}

---

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