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Verwendung von Fuzzy Search und Shiny in R: Eine umfassende Anleitung
P粉924915787
P粉924915787 2024-04-01 14:09:01
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Ich versuche, dieses JS-Skript in einer DT-Datentabelle zu verwenden (von dieser Website: https://datatables.net/blog/2021-09-17):

var fsrco = $('#fuzzy-ranking').DataTable({
    fuzzySearch: {
        rankColumn: 3
    },
    sort: [[3, 'desc']]
});
 
fsrco.on('draw', function(){
    fsrco.order([3, 'desc']);
});

Verwenden Sie dieses Skript-Tag:

"http://cdn.datatables.net/plug-ins/1.11.3/features/fuzzySearch/dataTables.fuzzySearch.js"

Ich m?chte dies in eine DT-Datentabellenfunktion in einer Shiny-App integrieren, in der die Fuzzy-Suche anhand der Rangfolge angewendet wird (oben hat eine h?here ?hnlichkeit), ich m?chte jedoch nicht, dass die Rangspalte angezeigt wird.

?hnlich wie hier, aber ohne die Ranglistenspalte.

Einige grundlegende allgemeine Beispiele:

    library(shiny)
    library(DT)
    js <- c(
      "  var fsrco = $('#fuzzy-ranking').DataTable({",
      "    fuzzySearch: {",
      "        rankColumn: 3",
      "    },",
      "    sort: [[3, 'desc']]",
      "});",
      "fsrco.on('draw', function(){",
      "    fsrco.order([3, 'desc']);",
      "});"
)
    ui <- fluidPage(
      DTOutput("table")
    )
    server <- function(input, output, session){
      output[["table"]] <- renderDT({
        datatable(
          iris,
          selection = "none",
          editable = TRUE, 
          callback = JS(js),
          extensions = "KeyTable",
          options = list(
            keys = TRUE,
            url = "//cdn.datatables.net/plug-ins/1.11.3/features/fuzzySearch/dataTables.fuzzySearch.js"
          )
        )
      })
    }
    shinyApp(ui, server)

P粉924915787
P粉924915787

Antworte allen(1)
P粉310931198

這個插件是一個舊插件,它不適用于最新版本的 DataTables。

但是我們可以采用計算相似度的 JavaScript 函數(shù),并通過 SearchBuilder 擴展在自定義搜索中使用它。

首先,復(fù)制此 JavaScript 代碼并將其保存在名稱 levenshtein.js 下:

/*
BSD 2-Clause License

Copyright (c) 2018, Tadeusz ?azurski
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this
  list of conditions and the following disclaimer.

* Redistributions in binary form must reproduce the above copyright notice,
  this list of conditions and the following disclaimer in the documentation
  and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/

function levenshtein(__this, that, limit) {
  var thisLength = __this.length,
    thatLength = that.length,
    matrix = [];

  // If the limit is not defined it will be calculate from this and that args.
  limit = (limit || (thatLength > thisLength ? thatLength : thisLength)) + 1;

  for (var i = 0; i  (limit || 100)) {
    return prepare(limit || 100);
  }
  if (thisLength === 0) {
    return prepare(thatLength);
  }
  if (thatLength === 0) {
    return prepare(thisLength);
  }

  // Calculate matrix.
  var j, this_i, that_j, cost, min, t;
  for (i = 1; i  4) return prepare(thisLength);

      that_j = that[j - 1];
      cost = this_i === that_j ? 0 : 1; // Step 5
      // Calculate the minimum (much faster than Math.min(...)).
      min = matrix[i - 1][j] + 1; // Devarion.
      if ((t = matrix[i][j - 1] + 1)  1 &&
        j > 1 &&
        this_i === that[j - 2] &&
        __this[i - 2] === that_j &&
        (t = matrix[i - 2][j - 2] + cost) 

現(xiàn)在,這是 R 代碼:

library(DT)

dtable ').on('input', function() { fn(that, this) });",
              "  if (preDefined !== null) {",
              "     $(el).val(preDefined[0]);",
              "  }",
              "  return el;",
              "}"
            ),
            inputValue = JS(
              "function (el) {",
              "  return [$(el[0]).val()];",
              "}"
            ),
            isInputValid = JS(
              "function (el, that) {",
              "  return $(el[0]).val().length !== 0;",
              "}"
            ),
            search = JS(
              "function (value, pattern) {",
              "  var fuzzy = levenshtein(value, pattern[0]);",
              "  return fuzzy.similarity > 0.25;",
              "}"
            )
          )
        )
      )
    )
  )
)

path 

必須選擇相似度的閾值。這里我取的是0.25

return fuzzy.similarity > 0.25;

編輯

要在 Shiny 中使用,請使用 server=FALSE:

renderDT({
  dtable
}, server = FALSE)
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