Added and internalized Pico theme for customization

themes/pico/static/js/search.js

@@ -0,0 +1,202 @@
+function debounce(func, wait) {
+  var timeout;
+
+  return function () {
+    var context = this;
+    var args = arguments;
+    clearTimeout(timeout);
+
+    timeout = setTimeout(function () {
+      timeout = null;
+      func.apply(context, args);
+    }, wait);
+  };
+}
+
+function makeTeaser(body, terms) {
+  var TERM_WEIGHT = 40;
+  var NORMAL_WORD_WEIGHT = 2;
+  var FIRST_WORD_WEIGHT = 8;
+  var TEASER_MAX_WORDS = 20;
+
+  var stemmedTerms = terms.map(function (w) {
+    return elasticlunr.stemmer(w.toLowerCase());
+  });
+  var termFound = false;
+  var index = 0;
+  var weighted = []; // contains elements of ["word", weight, index_in_document]
+
+  // split in sentences, then words
+  var sentences = body.toLowerCase().split(". ");
+
+  for (var i in sentences) {
+    var words = sentences[i].split(" ");
+    var value = FIRST_WORD_WEIGHT;
+
+    for (var j in words) {
+      var word = words[j];
+
+      if (word.length > 0) {
+        for (var k in stemmedTerms) {
+          if (elasticlunr.stemmer(word).startsWith(stemmedTerms[k])) {
+            value = TERM_WEIGHT;
+            termFound = true;
+          }
+        }
+        weighted.push([word, value, index]);
+        value = NORMAL_WORD_WEIGHT;
+      }
+
+      index += word.length;
+      index += 1;  // ' ' or '.' if last word in sentence
+    }
+
+    index += 1;  // because we split at a two-char boundary '. '
+  }
+
+  if (weighted.length === 0) {
+    return body;
+  }
+
+  var windowWeights = [];
+  var windowSize = Math.min(weighted.length, TEASER_MAX_WORDS);
+  // We add a window with all the weights first
+  var curSum = 0;
+  for (var i = 0; i < windowSize; i++) {
+    curSum += weighted[i][1];
+  }
+  windowWeights.push(curSum);
+
+  for (var i = 0; i < weighted.length - windowSize; i++) {
+    curSum -= weighted[i][1];
+    curSum += weighted[i + windowSize][1];
+    windowWeights.push(curSum);
+  }
+
+  // If we didn't find the term, just pick the first window
+  var maxSumIndex = 0;
+  if (termFound) {
+    var maxFound = 0;
+    // backwards
+    for (var i = windowWeights.length - 1; i >= 0; i--) {
+      if (windowWeights[i] > maxFound) {
+        maxFound = windowWeights[i];
+        maxSumIndex = i;
+      }
+    }
+  }
+
+  var teaser = [];
+  var startIndex = weighted[maxSumIndex][2];
+  for (var i = maxSumIndex; i < maxSumIndex + windowSize; i++) {
+    var word = weighted[i];
+    if (startIndex < word[2]) {
+      // missing text from index to start of `word`
+      teaser.push(body.substring(startIndex, word[2]));
+      startIndex = word[2];
+    }
+
+    // add <em/> around search terms
+    if (word[1] === TERM_WEIGHT) {
+      teaser.push("<b>");
+    }
+    startIndex = word[2] + word[0].length;
+    teaser.push(body.substring(word[2], startIndex));
+
+    if (word[1] === TERM_WEIGHT) {
+      teaser.push("</b>");
+    }
+  }
+  teaser.push("…");
+  return teaser.join("");
+}
+
+function formatSearchResultItem(item, terms) {
+  return '<div class="search-results__item">'
+  + `<h4><a href="${item.ref}">${item.doc.title}</a></h4>`
+  + `<div class="teaser">${makeTeaser(item.doc.body, terms)}</div>`
+  + '</div>';
+}
+
+function initSearch() {
+  var $searchInput = document.getElementById("searchInput");
+  var $searchResults = document.getElementById('sResults');
+  var $searchResultsItems = document.getElementById('sResultsUL')
+  var MAX_ITEMS = 5;
+
+  var options = {
+    bool: "AND",
+    fields: {
+      title: {boost: 2},
+      body: {boost: 1},
+    }
+  };
+  var currentTerm = "";
+  var index;
+  
+  var initIndex = async function () {
+    if (index === undefined) {
+      let $baseUrl = document.head.dataset['baseUrl']
+      index = fetch($baseUrl + "search_index.en.json")
+        .then(
+          async function(response) {
+            return await elasticlunr.Index.load(await response.json());
+        }
+      );
+    }
+    let res = await index;
+    return res;
+    
+  }
+
+  $searchInput.addEventListener("keyup", debounce(async function() {
+    if ($searchInput.value != '') {
+      $searchInput.classList.add("textIn")
+    } else {
+      $searchInput.classList.remove("textIn")
+    }
+    var term = $searchInput.value.trim();
+    if (term === currentTerm) {
+      return;
+    }
+    $searchResults.style.display = term === "" ? "none" : "block";
+    $searchResultsItems.innerHTML = "";
+    $searchResults.style.top = `${document.documentElement.scrollTop}px`;
+    $searchResultsItems.style.display="block";
+    $searchResultsItems.style.transition="opacity 3s";
+    
+    currentTerm = term;
+    if (term === "") {
+      return;
+    }
+
+    var results = (await initIndex()).search(term, options);
+    if (results.length === 0) {
+      $searchResults.style.display = "none";
+      return;
+    }
+    var item = document.createElement("li");
+    clSearch = `<span class="closeBtn icon icon-close" onclick="closeSearchResults();"></span>`
+    item.innerHTML = clSearch;
+    $searchResultsItems.appendChild(item);
+
+    for (var i = 0; i < Math.min(results.length, MAX_ITEMS); i++) {
+      var item = document.createElement("li");
+      item.innerHTML = formatSearchResultItem(results[i], term.split(" "));
+      $searchResultsItems.appendChild(item);
+    }
+  }, 150));
+
+  window.addEventListener('click', function(e) {
+    if ($searchResults.style.display == "block" && !$searchResults.contains(e.target)) {
+      $searchResults.style.display = "block";
+    }
+  });
+}
+
+function closeSearchResults() {
+  document.getElementById("sResults").style.display="none";
+  document.getElementById("searchInput").value="";
+  document.getElementById("searchInput").classList.remove("textIn");
+  initSearch;
+}