OpenSpace/modules/iswa/util/dataprocessorjson.cpp

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#include <modules/iswa/util/dataprocessorjson.h>

#include <openspace/json.h>
#include <openspace/properties/selectionproperty.h>
#include <openspace/util/histogram.h>

using json = nlohmann::json;

namespace openspace {

DataProcessorJson::DataProcessorJson() : DataProcessor() {}

DataProcessorJson::~DataProcessorJson() {}

std::vector<std::string> DataProcessorJson::readMetadata(const std::string& data,
                                                         glm::size3_t& dimensions)
{
    std::vector<std::string> options = std::vector<std::string>();
    if (!data.empty()) {
        const json& j = json::parse(data);
        json variables = j["variables"];

        for (json::iterator it = variables.begin(); it != variables.end(); it++) {
            std::string option = it.key();
            if (option == "ep") {
                const json& row = it.value();
                const json& col = row.at(0);

                dimensions = glm::size3_t(col.size(), row.size(), 1);
            }

            if (_coordinateVariables.find(option) == _coordinateVariables.end()) {
                options.push_back(std::move(option));
            }
        }
    }
    return options;
}

void DataProcessorJson::addDataValues(const std::string& data,
                                      properties::SelectionProperty& dataOptions)
{
    int numOptions = static_cast<int>(dataOptions.options().size());
    initializeVectors(numOptions);

    if (!data.empty()) {
        const json& j = json::parse(data);
        json variables = j["variables"];

        std::vector<float> sum(numOptions, 0.f);
        std::vector<std::vector<float>> optionValues(numOptions, std::vector<float>());
        const std::vector<std::string>& options = dataOptions.options();

        for (int i = 0; i < numOptions; i++) {
            const json& row = variables[options[i]];
//            int rowsize = row.size();

            for (size_t y = 0; y < row.size(); ++y) {
                const json& col = row.at(y);
                const int colsize = static_cast<int>(col.size());

                for (int x = 0; x < colsize; ++x) {
                    const float value = col.at(x);
                    optionValues[i].push_back(value);
                    _min[i] = std::min(_min[i], value);
                    _max[i] = std::max(_max[i], value);
                    sum[i] += value;
                }
            }
        }

        add(optionValues, sum);
    }
}

std::vector<float*> DataProcessorJson::processData(const std::string& data,
                                                properties::SelectionProperty& optionProp,
                                                                 glm::size3_t& dimensions)
{
    if (data.empty()) {
        return std::vector<float*>();
    }
    const json& j = json::parse(data);
    json variables = j["variables"];

    const std::set<std::string>& selectedOptions = optionProp;
    const std::vector<std::string>& options = optionProp.options();
    std::vector<int> selectedOptionsIndices;
    for (const std::string& option : selectedOptions) {
        auto it = std::find(options.begin(), options.end(), option);
        ghoul_assert(it != options.end(), "Selected option must be in all options");
        int idx = static_cast<int>(std::distance(options.begin(), it));
        selectedOptionsIndices.push_back(idx);
    }

    std::vector<float*> dataOptions(options.size(), nullptr);
    for (int option : selectedOptionsIndices) {
        // @CLEANUP: This memory is very easy to lose and should be replaced by some
        //           other mechanism (std::vector<float> most likely)
        dataOptions[option] = new float[dimensions.x * dimensions.y] { 0.f };

        json row = variables[options[option]];
        const int rowsize = static_cast<int>(row.size());

        for (int y = 0; y < rowsize; ++y) {
            json col = row.at(y);
            const int colsize = static_cast<int>(col.size());

            for (int x = 0; x < colsize; ++x) {
                const float value = col.at(x);
                const int i = x + y * colsize;

                dataOptions[option][i] = processDataPoint(value, option);
            }
        }
    }

    calculateFilterValues(selectedOptionsIndices);
    return dataOptions;
}

} //namespace openspace