Example usage for com.google.gson JsonArray size

List of usage examples for com.google.gson JsonArray size

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Introduction

In this page you can find the example usage for com.google.gson JsonArray size.

Prototype

public int size()

Source Link

Document

Returns the number of elements in the array.

Usage

From source file:at.orz.arangodb.util.JsonUtils.java

License:Apache License

public static double[] toDoubleArray(JsonArray array) {
    int len = array.size();
    double[] darray = new double[len];
    for (int i = 0; i < len; i++) {
        darray[i] = toDouble(array.get(i));
    }/*www .  ja v  a  2s. c o  m*/
    return darray;
}

From source file:augsburg.se.alltagsguide.common.EventCategory.java

License:Open Source License

@NonNull
public static List<EventCategory> fromJson(@NonNull JsonArray array) {
    List<EventCategory> categories = new ArrayList<>();
    for (int i = 0; i < array.size(); i++) {
        JsonObject obj = array.get(i).getAsJsonObject();
        EventCategory category = fromJson(obj);
        if (category != null) {
            categories.add(category);/*from www  .  j a v a  2  s  . c  om*/
        }
    }
    return categories;
}

From source file:augsburg.se.alltagsguide.common.EventTag.java

License:Open Source License

@NonNull
public static List<EventTag> fromJson(@NonNull JsonArray array) {
    List<EventTag> tags = new ArrayList<>();
    for (int i = 0; i < array.size(); i++) {
        EventTag tag = fromJson(array.get(i).getAsJsonObject());
        tags.add(tag);/*from   w w  w .jav a2  s  .  c o  m*/
    }
    return tags;
}

From source file:augsburg.se.alltagsguide.serialization.EventPageSerializer.java

License:Open Source License

@NonNull
private List<EventPage> getPagesByParentId(final EventPage parent, final int parentId,
        @NonNull final JsonArray jsonPages) {
    final List<EventPage> result = new ArrayList<>();
    for (int i = 0; i < jsonPages.size(); i++) {
        JsonObject jsonPage = jsonPages.get(i).getAsJsonObject();
        if (jsonPage.get("parent").getAsInt() == parentId) {
            EventPage page = EventPage.fromJson(jsonPage);
            page.setParent(parent);/*from ww  w.j  a  va  2 s  . co m*/
            result.add(page);
        }
    }
    return result;
}

From source file:augsburg.se.alltagsguide.serialization.LanguageSerializer.java

License:Open Source License

@NonNull
private List<Language> parseLanguages(@NonNull final JsonArray jsonPages) {
    List<Language> Languages = new ArrayList<>();
    for (int i = 0; i < jsonPages.size(); i++) {
        Languages.add(Language.fromJson(jsonPages.get(i).getAsJsonObject()));
    }/*  ww w . j av a  2 s  .  co m*/
    return Languages;
}

From source file:augsburg.se.alltagsguide.serialization.LocationSerializer.java

License:Open Source License

@NonNull
private List<Location> parseLocations(@NonNull final JsonArray jsonPages) {
    List<Location> locations = new ArrayList<>();
    for (int i = 0; i < jsonPages.size(); i++) {
        locations.add(Location.fromJson(jsonPages.get(i).getAsJsonObject()));
    }/*from  www.  j av a  2  s  . c  o  m*/
    return locations;
}

From source file:augsburg.se.alltagsguide.serialization.PageSerializer.java

License:Open Source License

private List<Page> parsePages(@NonNull final JsonArray jsonPages) {
    List<Page> pages = new ArrayList<>();
    for (int i = 0; i < jsonPages.size(); i++) {
        pages.add(Page.fromJson(jsonPages.get(i).getAsJsonObject()));
    }/*from  w  w w .  ja v a  2 s.  c  o m*/
    return pages;
}

From source file:be.iminds.iot.dianne.dataset.DatasetConfigurator.java

License:Open Source License

private void parseDatasetConfiguration(File f) {
    try {/*from   w  w  w. j a  v a2 s .c  o  m*/
        // parse any adapter configurations from JSON and apply config?
        JsonParser parser = new JsonParser();
        JsonObject json = parser.parse(new JsonReader(new FileReader(f))).getAsJsonObject();

        String name = json.get("name").getAsString();
        if (name == null)
            return; // should have a name

        Hashtable<String, Object> props = new Hashtable<>();

        String dir = f.getParentFile().getAbsolutePath();
        props.put("dir", dir);

        String pid = null;

        if (json.has("adapter")) {
            String adapter = json.get("adapter").getAsString();
            pid = adapter.contains(".") ? adapter : "be.iminds.iot.dianne.dataset.adapters." + adapter;
            // in case of adapter, set Dataset target: the dataset it is adapting
            String dataset = json.get("dataset").getAsString();
            props.put("Dataset.target", "(name=" + dataset + ")");
        } else if (json.has("type")) {
            String type = json.get("type").getAsString();
            pid = "be.iminds.iot.dianne.dataset." + type;
        } else {
            // some hard coded pids
            if (name.startsWith("MNIST")) {
                pid = "be.iminds.iot.dianne.dataset.MNIST";
            } else if (name.startsWith("CIFAR-100")) {
                pid = "be.iminds.iot.dianne.dataset.CIFAR100";
            } else if (name.startsWith("CIFAR-10")) {
                pid = "be.iminds.iot.dianne.dataset.CIFAR10";
            } else if (name.startsWith("STL-10")) {
                pid = "be.iminds.iot.dianne.dataset.STL10";
            } else if (name.startsWith("SVHN")) {
                pid = "be.iminds.iot.dianne.dataset.SVHN";
            } else if (name.equalsIgnoreCase("ImageNetValidation")) {
                pid = "be.iminds.iot.dianne.dataset.ImageNet.validation";
            } else if (name.equalsIgnoreCase("ImageNetTraining")) {
                pid = "be.iminds.iot.dianne.dataset.ImageNet.training";
            } else {
                pid = "be.iminds.iot.dianne.dataset." + name;
            }
        }

        // set an aiolos instance id using the dataset name to treat
        // equally named datasets as single instance in the network
        props.put("aiolos.instance.id", name);
        // combine all offered interfaces (might be SequenceDataset or ExperiencePool)
        props.put("aiolos.combine", "*");

        // TODO use object conversion from JSON here?
        Configuration config = ca.createFactoryConfiguration(pid, null);
        json.entrySet().stream().forEach(e -> {
            if (e.getValue().isJsonArray()) {
                JsonArray a = e.getValue().getAsJsonArray();
                String[] val = new String[a.size()];
                for (int i = 0; i < val.length; i++) {
                    val[i] = a.get(i).getAsString();
                }
                props.put(e.getKey(), val);
            } else {
                props.put(e.getKey(), e.getValue().getAsString());
            }
        });
        config.update(props);
    } catch (Exception e) {
        System.err.println("Error parsing Dataset config file: " + f.getAbsolutePath());
        e.printStackTrace();
    }
}

From source file:be.iminds.iot.dianne.jsonrpc.DianneRequestHandler.java

License:Open Source License

@Override
public void handleRequest(JsonObject request, JsonWriter writer) throws IOException {
    String i = "null";
    if (request.has("id")) {
        i = request.get("id").getAsString();
    }//from   w w  w  .j a v a  2  s .com
    final String id = i;

    if (!request.has("jsonrpc")) {
        writeError(writer, id, -32600, "Invalid JSONRPC request");
        return;
    }

    if (!request.get("jsonrpc").getAsString().equals("2.0")) {
        writeError(writer, id, -32600, "Wrong JSONRPC version: " + request.get("jsonrpc").getAsString());
        return;
    }

    if (!request.has("method")) {
        writeError(writer, id, -32600, "No method specified");
        return;
    }

    String method = request.get("method").getAsString();

    // TODO use a more generic approach here?
    switch (method) {
    case "deploy":
        try {
            String description = null;
            UUID runtimeId = null;
            String[] tags = null;

            NeuralNetworkInstanceDTO nni;
            JsonArray params = request.get("params").getAsJsonArray();
            if (params.size() > 1) {
                description = params.get(1).getAsString();
            }
            if (params.size() > 2) {
                runtimeId = UUID.fromString(params.get(2).getAsString());
            }
            if (params.size() > 3) {
                tags = new String[params.size() - 3];
                for (int t = 3; t < params.size(); t++) {
                    tags[t - 3] = params.get(t).getAsString();
                }
            }

            if (params.get(0).isJsonPrimitive()) {
                String nnName = params.get(0).getAsString();
                nni = platform.deployNeuralNetwork(nnName, description, runtimeId, tags);
            } else {
                NeuralNetworkDTO nn = DianneJSONConverter.parseJSON(params.get(0).getAsJsonObject());
                nni = platform.deployNeuralNetwork(nn, description, runtimeId, tags);
            }
            writeResult(writer, id, nni.id.toString());
        } catch (Exception e) {
            writeError(writer, id, -32602, "Incorrect parameters provided: " + e.getMessage());
            return;
        }
        break;
    case "undeploy":
        try {
            JsonArray params = request.get("params").getAsJsonArray();
            if (params.get(0).isJsonPrimitive()) {
                String s = params.get(0).getAsString();
                UUID nnId = UUID.fromString(s);
                platform.undeployNeuralNetwork(nnId);
                writeResult(writer, id, nnId);
            }
        } catch (Exception e) {
            writeError(writer, id, -32602, "Incorrect parameters provided: " + e.getMessage());
            return;
        }
        break;
    case "forward":
        try {
            JsonArray params = request.get("params").getAsJsonArray();
            if (params.size() != 2) {
                throw new Exception("2 parameters expected");
            }
            if (!params.get(0).isJsonPrimitive())
                throw new Exception("first parameter should be neural network instance id");
            if (!params.get(1).isJsonArray())
                throw new Exception("second parameter should be input data");

            String s = params.get(0).getAsString();
            UUID nnId = UUID.fromString(s);
            NeuralNetworkInstanceDTO nni = platform.getNeuralNetworkInstance(nnId);
            if (nni == null) {
                writeError(writer, id, -32603, "Neural network with id " + nnId + " does not exist.");
                return;
            }
            NeuralNetwork nn = dianne.getNeuralNetwork(nni).getValue();

            JsonArray in = params.get(1).getAsJsonArray();
            Tensor input = asTensor(in);
            nn.forward(null, null, input).then(p -> {
                int argmax = TensorOps.argmax(p.getValue().tensor);
                writeResult(writer, id, nn.getOutputLabels()[argmax]);
                return null;
            }, p -> {
                writeError(writer, id, -32603, "Error during forward: " + p.getFailure().getMessage());
            });

        } catch (Exception e) {
            writeError(writer, id, -32602, "Incorrect parameters provided: " + e.getMessage());
            return;
        }
        break;
    case "learn":
    case "eval":
    case "act":
        String[] nnName = null;
        NeuralNetworkDTO nn = null;
        String dataset;
        Map<String, String> config;

        try {
            JsonArray params = request.get("params").getAsJsonArray();
            if (params.get(0).isJsonPrimitive()) {
                nnName = params.get(0).getAsString().split(",");
                for (int k = 0; k < nnName.length; k++) {
                    nnName[k] = nnName[k].trim();
                }
            } else {
                nn = DianneJSONConverter.parseJSON(params.get(0).getAsJsonObject());
            }
            dataset = params.get(1).getAsString();
            config = params.get(2).getAsJsonObject().entrySet().stream()
                    .collect(Collectors.toMap(e -> e.getKey(), e -> e.getValue().getAsString()));

        } catch (Exception e) {
            writeError(writer, id, -32602, "Incorrect parameters provided: " + e.getMessage());
            return;
        }

        // call coordinator
        if (method.equals("learn")) {
            // learn
            Promise<LearnResult> result = null;
            if (nnName != null) {
                result = coordinator.learn(dataset, config, nnName);
            } else {
                result = coordinator.learn(dataset, config, nn);
            }
            try {
                result.then(p -> {
                    writeResult(writer, id, p.getValue());
                    return null;
                }, p -> {
                    writeError(writer, id, -32603, "Error during learning: " + p.getFailure().getMessage());
                }).getValue();
            } catch (InvocationTargetException | InterruptedException e) {
                e.printStackTrace();
            }
        } else if (method.equals("eval")) {
            // eval
            Promise<EvaluationResult> result = null;
            if (nnName != null) {
                result = coordinator.eval(dataset, config, nnName);
            } else {
                result = coordinator.eval(dataset, config, nn);
            }
            try {
                result.then(p -> {
                    writeResult(writer, id, p.getValue());
                    return null;
                }, p -> {
                    writeError(writer, id, -32603, "Error during learning: " + p.getFailure().getMessage());
                }).getValue();
            } catch (InvocationTargetException | InterruptedException e) {
                e.printStackTrace();
            }
        } else if (method.equals("act")) {
            Promise<AgentResult> result = null;
            if (nnName != null) {
                result = coordinator.act(dataset, config, nnName);
            } else {
                result = coordinator.act(dataset, config, nn);
            }
            try {
                result.then(p -> {
                    writeResult(writer, id, null);
                    return null;
                }, p -> {
                    writeError(writer, id, -32603, "Error during learning: " + p.getFailure().getMessage());
                }).getValue();
            } catch (InvocationTargetException | InterruptedException e) {
                e.printStackTrace();
            }
        }
        break;
    case "learnResult":
    case "evaluationResult":
    case "agentResult":
    case "job":
    case "stop":
        UUID jobId = null;
        try {
            JsonArray params = request.get("params").getAsJsonArray();
            if (params.get(0).isJsonPrimitive()) {
                String s = params.get(0).getAsString();
                jobId = UUID.fromString(s);
            }
        } catch (Exception e) {
            writeError(writer, id, -32602, "Incorrect parameters provided: " + e.getMessage());
            return;
        }

        if (method.equals("learnResult")) {
            writeResult(writer, id, coordinator.getLearnResult(jobId));
        } else if (method.equals("evaluationResult")) {
            writeResult(writer, id, coordinator.getEvaluationResult(jobId));
        } else if (method.equals("agentResult")) {
            writeResult(writer, id, coordinator.getAgentResult(jobId));
        } else if (method.equals("stop")) {
            try {
                coordinator.stop(jobId);
            } catch (Exception e) {
                writeError(writer, id, -32603, "Error stopping job: " + e.getMessage());
            }
        } else {
            writeResult(writer, id, coordinator.getJob(jobId));
        }
        break;
    case "availableNeuralNetworks":
        writeResult(writer, id, platform.getAvailableNeuralNetworks());
        break;
    case "availableDatasets":
        writeResult(writer, id, datasets.getDatasets().stream().map(d -> d.name).collect(Collectors.toList()));
        break;
    case "queuedJobs":
        writeResult(writer, id, coordinator.queuedJobs());
        break;
    case "runningJobs":
        writeResult(writer, id, coordinator.runningJobs());
        break;
    case "finishedJobs":
        writeResult(writer, id, coordinator.finishedJobs());
        break;
    case "notifications":
        writeResult(writer, id, coordinator.getNotifications());
        break;
    case "status":
        writeResult(writer, id, coordinator.getStatus());
        break;
    case "devices":
        writeResult(writer, id, coordinator.getDevices());
        break;
    default:
        writeError(writer, id, -32601, "Method " + method + " not found");
    }
}

From source file:be.iminds.iot.dianne.jsonrpc.DianneRequestHandler.java

License:Open Source License

private Tensor asTensor(JsonArray array) {
    // support up to 3 dim input atm
    int dim0 = 1;
    int dim1 = 1;
    int dim2 = 1;

    int dims = 1;
    dim0 = array.size();
    if (array.get(0).isJsonArray()) {
        dims = 2;/*  ww w . j a va 2s. co  m*/
        JsonArray a = array.get(0).getAsJsonArray();
        dim1 = a.size();
        if (a.get(0).isJsonArray()) {
            dims = 3;
            dim2 = a.get(0).getAsJsonArray().size();
        }
    }

    int size = dim0 * dim1 * dim2;
    float[] data = new float[size];
    int k = 0;
    for (int i = 0; i < dim0; i++) {
        for (int j = 0; j < dim1; j++) {
            for (int l = 0; l < dim2; l++) {
                JsonElement e = array.get(i);
                if (e.isJsonArray()) {
                    e = e.getAsJsonArray().get(j);
                    if (e.isJsonArray()) {
                        e = e.getAsJsonArray().get(l);
                    }
                }
                data[k++] = e.getAsFloat();
            }
        }
    }

    int[] d = new int[dims];
    d[0] = dim0;
    if (dims > 1)
        d[1] = dim1;
    if (dims > 2)
        d[2] = dim2;

    return new Tensor(data, d);
}