QScript Sentiment Analysis Functions

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function saveSentimentScores() {
    includeWeb("QScript Utility Functions");
    includeWeb("QScript Functions to Generate Outputs");
    includeWeb("QScript R Output Functions");
    includeWeb("QScript Selection Functions")
 

 
    // // Figure out what input the user has selected.
    // // R items take precendence over questions that
    // // are selected in the Data or in the selected
    // // table, but they must have the right class.
    // let selected_object;
    // const user_selections = getAllUserSelections();
    // let selected_r_items = user_selections.implicitly_selected_r_outputs;
    // let selected_text_questions = user_selections.selected_questions.filter(function (q) { return q.questionType == "Text"; });
 
    // // Look on the current page for text or wordBag items
    // let selected_raw = project.report.selectedRaw();
    // let selected_item = selected_raw[0];

    // let selected_group = user_selections.selected_top_level_pages[0];

    // let tables_on_page = [];
    // let text_on_page = [];
    // let word_bags_on_page = [];
 
    // if (selected_group != null) { // Don't look at on-page items if text variable is selected directly
    //     tables_on_page = selected_group.subItems.filter(function (item) { 
    //         return item.type == "Table" 
    //                 && item.primary != null 
    //                 && item.primary.questionType == "Text"; });
    //     text_on_page = tables_on_page.map(function (table) { return table.primary; });
    //     word_bags_on_page = selected_group.subItems.filter(function (item) { 
    //         return item.type == "R Output" 
    //                  && item.error === null 
    //                  && item.outputClasses !== null
    //                  && item.outputClasses.indexOf("wordBag") > -1; });
    // }


   



    function getBestTextSelection() {
         // Selection
        // - A WordBag output
        // - A Text Question in Data Sets
        // - A Table with a Text question in the rows (comes for free in selected_questions)
        
        const bad_selection_message = "Select either a table with text data, "
        + "a Text variable, or an item that has been created using Text Analysis > Setup Text Analysis.";
        const user_selections = getAllUserSelections();
        let selected_r_items = user_selections.selected_r_outputs;
        let selected_questions = user_selections.selected_questions;
        let selected_text_questions = selected_questions.filter(function (q) { return q.questionType == "Text"; });
        let selected_tables = user_selections.selected_tables;
        let selected_primary_text = user_selections.questions_in_rows_of_selected_tables.filter(function (q) { return q.questionType == "Text"; });

        // Can't operate on multiple R outputs.
        if (selected_r_items.length > 1) {
            log("Too many outputs selected. " + bad_selection_message);
            return null;
        }

        // If one output selected, make sure it is
        // calculated, then make sure it has the right class
        if (selected_r_items.length == 1) {
            if (!checkROutputIsValid(selected_r_items[0]))
                return null;
            if (selected_r_items[0].outputClasses.indexOf("wordBag") == -1) {
                log(bad_selection_message);
                return null;
            }
            return selected_r_items[0];
        }


        if (selected_text_questions.length > 1) {
            log(correctTerminology("Too many questions selected. ") + bad_selection_message);
            return null;
        }

        if (selected_text_questions.length == 1)
            return selected_text_questions[0];

        if (selected_primary_text.length > 1) {
            log("Too many tables selected. " + bad_selection_message);
            return null;
        }

        if (selected_primary_text.length == 1) {
            return selected_primary_text[0];
        }

        log(bad_selection_message);
        return null;
    }




 
    // if (selected_r_items.length > 1) {
    //     log("Too many inputs selected. " + bad_selection_message);
    //     return false;
    // } else if (selected_r_items.length == 1) {
    //     selected_object = selected_r_items[0];
    //     if (!checkROutputIsValid(selected_object))
    //         return false;
    //     if (selected_object.outputClasses.indexOf("wordBag") == -1) {
    //         log(bad_selection_message);
    //         return false;
    //     }
    // } else if (selected_text_questions.length > 1) {
    //     log("Too many inputs selected. " + bad_selection_message);
    //     return false;
    // } else if (selected_text_questions.length == 1 ){
    //     selected_object = selected_text_questions[0];
    // } else if (text_on_page.length + word_bags_on_page.length == 1) {
    //     if (word_bags_on_page.length == 1)
    //         selected_object = word_bags_on_page[0];
    //     else
    //         selected_object = text_on_page[0];
    // } else {
    //     log(bad_selection_message);
    //     return false;
    // }
 
    let selected_object = getBestTextSelection();
    if (selected_object == null)
        return;

 
    // Figure out the source question so we can put the new
    // variable below it, and to disambiguate in the case of
    // multiple data files.
    let source_question;
    let selected_type = selected_object.type;
    if (selected_type == "Question")
        source_question = selected_object;
    else {
        source_question = selected_object.getInput("formtextvar");
    }
 
    // Figure out the right data file to add to (if more than one)
    let target_data_file = project.dataFiles[0];
    if (project.dataFiles.length > 0) {
        target_data_file = source_question.dataFile;
    }
 
    let input_string = selected_type == "Question" ? generateDisambiguatedVariableName(selected_object.variables[0]) 
                                                   : stringToRName(selected_object.referenceName);     
    let r_expression = "library(flipTextAnalysis)\r\n"
                    +  "sentiment.scores = SaveNetSentimentScores(" + input_string 
                    + ", check.simple.suffixes = TRUE, blanks.as.missing = TRUE)"; 
 
    let new_q_name = preventDuplicateQuestionName(target_data_file, "Sentiment scores from " + selected_object.name);
    let new_var_name = selected_type == "Question" ? selected_object.variables[0].name : selected_object.name;
    new_var_name = cleanVariableName(new_var_name);
    new_var_name = preventDuplicateVariableName(target_data_file, new_var_name + "_sentiment");
    let new_var;
    try {
        new_var = target_data_file.newRVariable(r_expression, new_var_name, new_q_name, null);
    } catch (e) {
        log("Sentiment scores could not be created from this item: " + e);
        return false;
    }
    let new_question = new_var.question;
 
    // Move the new variable below its input
    target_data_file.moveAfter([new_var], source_question.variables[0]);
    insertAtHoverButtonIfShown(new_question);
    // Generating outputs
    if (!inDisplayr()) {
        var new_group = generateGroupOfSummaryTables(new_q_name, [new_question]);
        project.report.setSelectedRaw([new_group.subItems[0]]);
    }
 
    return true;
}