如何使用二分搜索找到数组中的插入点？

Question

为了查找准确的插入点，在我们得到大致位置之后，我们可能需要向左或向右“扫描”以查找准确的插入位置，这样，例如，在Ruby中，我们可以执行arr.insert(exact_index,value)

我有下面的解决方案，但是对于begin_index>=end_index的部分的处理有点混乱。不知是否可以使用更优雅的解决方案？

（这个解决方案不关心如果找到一个精确匹配，就扫描多个匹配，所以为一个精确匹配返回的索引可能指向与该值相对应的任何索引……但我认为如果它们都是整数，我们知道找到一个精确匹配后，总是可以搜索a-1，找到左边界，或者搜索a+1找到右边界。）

我的解决方案：

DEBUGGING = true

def binary_search_helper(arr, a, begin_index, end_index)
  middle_index = (begin_index + end_index) / 2
  puts "a = #{a}, arr[middle_index] = #{arr[middle_index]}, " +
           "begin_index = #{begin_index}, end_index = #{end_index}, " +
           "middle_index = #{middle_index}" if DEBUGGING
  if arr[middle_index] == a
    return middle_index
  elsif begin_index >= end_index
    index = [begin_index, end_index].min
    return index if a < arr[index] && index >= 0  #careful because -1 means end of array
    index = [begin_index, end_index].max
    return index if a < arr[index] && index >= 0
    return index + 1
  elsif a > arr[middle_index]
    return binary_search_helper(arr, a, middle_index + 1, end_index)
  else
    return binary_search_helper(arr, a, begin_index, middle_index - 1)
  end
end

# for [1,3,5,7,9], searching for 6 will return index for 7 for insertion
# if exact match is found, then return that index
def binary_search(arr, a)
  puts "\nSearching for #{a} in #{arr}" if DEBUGGING
  return 0 if arr.empty?
  result = binary_search_helper(arr, a, 0, arr.length - 1)
  puts "the result is #{result}, the index for value #{arr[result].inspect}" if DEBUGGING
  return result
end


arr = [1,3,5,7,9]
b = 6
arr.insert(binary_search(arr, b), b)
p arr

arr = [1,3,5,7,9,11]
b = 6
arr.insert(binary_search(arr, b), b)
p arr

arr = [1,3,5,7,9]
b = 60
arr.insert(binary_search(arr, b), b)
p arr

arr = [1,3,5,7,9,11]
b = 60
arr.insert(binary_search(arr, b), b)
p arr

arr = [1,3,5,7,9]
b = -60
arr.insert(binary_search(arr, b), b)
p arr

arr = [1,3,5,7,9,11]
b = -60
arr.insert(binary_search(arr, b), b)
p arr

arr = [1]
b = -60
arr.insert(binary_search(arr, b), b)
p arr

arr = [1]
b = 60
arr.insert(binary_search(arr, b), b)
p arr

arr = []
b = 60
arr.insert(binary_search(arr, b), b)
p arr

和结果：

Searching for 6 in [1, 3, 5, 7, 9]
a = 6, arr[middle_index] = 5, begin_index = 0, end_index = 4, middle_index = 2
a = 6, arr[middle_index] = 7, begin_index = 3, end_index = 4, middle_index = 3
a = 6, arr[middle_index] = 5, begin_index = 3, end_index = 2, middle_index = 2
the result is 3, the index for value 7
[1, 3, 5, 6, 7, 9]

Searching for 6 in [1, 3, 5, 7, 9, 11]
a = 6, arr[middle_index] = 5, begin_index = 0, end_index = 5, middle_index = 2
a = 6, arr[middle_index] = 9, begin_index = 3, end_index = 5, middle_index = 4
a = 6, arr[middle_index] = 7, begin_index = 3, end_index = 3, middle_index = 3
the result is 3, the index for value 7
[1, 3, 5, 6, 7, 9, 11]

Searching for 60 in [1, 3, 5, 7, 9]
a = 60, arr[middle_index] = 5, begin_index = 0, end_index = 4, middle_index = 2
a = 60, arr[middle_index] = 7, begin_index = 3, end_index = 4, middle_index = 3
a = 60, arr[middle_index] = 9, begin_index = 4, end_index = 4, middle_index = 4
the result is 5, the index for value nil
[1, 3, 5, 7, 9, 60]

Searching for 60 in [1, 3, 5, 7, 9, 11]
a = 60, arr[middle_index] = 5, begin_index = 0, end_index = 5, middle_index = 2
a = 60, arr[middle_index] = 9, begin_index = 3, end_index = 5, middle_index = 4
a = 60, arr[middle_index] = 11, begin_index = 5, end_index = 5, middle_index = 5
the result is 6, the index for value nil
[1, 3, 5, 7, 9, 11, 60]

Searching for -60 in [1, 3, 5, 7, 9]
a = -60, arr[middle_index] = 5, begin_index = 0, end_index = 4, middle_index = 2
a = -60, arr[middle_index] = 1, begin_index = 0, end_index = 1, middle_index = 0
a = -60, arr[middle_index] = 9, begin_index = 0, end_index = -1, middle_index = -1
the result is 0, the index for value 1
[-60, 1, 3, 5, 7, 9]

Searching for -60 in [1, 3, 5, 7, 9, 11]
a = -60, arr[middle_index] = 5, begin_index = 0, end_index = 5, middle_index = 2
a = -60, arr[middle_index] = 1, begin_index = 0, end_index = 1, middle_index = 0
a = -60, arr[middle_index] = 11, begin_index = 0, end_index = -1, middle_index = -1
the result is 0, the index for value 1
[-60, 1, 3, 5, 7, 9, 11]

Searching for -60 in [1]
a = -60, arr[middle_index] = 1, begin_index = 0, end_index = 0, middle_index = 0
the result is 0, the index for value 1
[-60, 1]

Searching for 60 in [1]
a = 60, arr[middle_index] = 1, begin_index = 0, end_index = 0, middle_index = 0
the result is 1, the index for value nil
[1, 60]

Searching for 60 in []
[60]

Answer 1

这是Oracles Java中包含的java.util.Arrays.BinarySearch的代码：

    /**
     * Searches the specified array of ints for the specified value using the
     * binary search algorithm.  The array must be sorted (as
     * by the {@link #sort(int[])} method) prior to making this call.  If it
     * is not sorted, the results are undefined.  If the array contains
     * multiple elements with the specified value, there is no guarantee which
     * one will be found.
     *
     * @param a the array to be searched
     * @param key the value to be searched for
     * @return index of the search key, if it is contained in the array;
     *         otherwise, <tt>(-(<i>insertion point</i>) - 1)</tt>.  The
     *         <i>insertion point</i> is defined as the point at which the
     *         key would be inserted into the array: the index of the first
     *         element greater than the key, or <tt>a.length</tt> if all
     *         elements in the array are less than the specified key.  Note
     *         that this guarantees that the return value will be &gt;= 0 if
     *         and only if the key is found.
     */
    public static int binarySearch(int[] a, int key) {
        return binarySearch0(a, 0, a.length, key);
    }

    // Like public version, but without range checks.
    private static int binarySearch0(int[] a, int fromIndex, int toIndex,
                                     int key) {
        int low = fromIndex;
        int high = toIndex - 1;

        while (low <= high) {
            int mid = (low + high) >>> 1;
            int midVal = a[mid];

            if (midVal < key)
                low = mid + 1;
            else if (midVal > key)
                high = mid - 1;
            else
                return mid; // key found
        }
        return -(low + 1);  // key not found.
    }

算法已经被证明是合适的，我喜欢这样一个事实，你可以从结果中立即知道它是一个精确的匹配还是插入点上的一个提示。

这就是我将其翻译成Ruby的方式：

# Inserts the specified value into the specified array using the binary
# search algorithm. The array must be sorted prior to making this call.
# If it is not sorted, the results are undefined.  If the array contains
# multiple elements with the specified value, there is no guarantee
# which one will be found.
#
# @param [Array] array the ordered array into which value should be inserted
# @param [Object] value the value to insert
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Array] the resulting array
def self.insert(array, value, from_index=0,  to_index=array.length)
  array.insert insertion_point(array, value, from_index, to_index), value
end

# Searches the specified array for an insertion point ot the specified value
# using the binary search algorithm.  The array must be sorted prior to making
# this call. If it is not sorted, the results are undefined.  If the array
# contains multiple elements with the specified value, there is no guarantee
# which one will be found.
#
# @param [Array] array the ordered array into which value should be inserted
# @param [Object] value the value to insert
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Fixnum|Bignum] the position where value should be inserted
def self.insertion_point(array, value, from_index=0,  to_index=array.length)
  raise(ArgumentError, 'Invalid Range') if from_index < 0 || from_index > array.length || from_index > to_index || to_index > array.length
  binary_search = _binary_search(array, value, from_index, to_index)
  if binary_search < 0
    -(binary_search + 1)
  else
    binary_search
  end
end

# Searches the specified array for the specified value using the binary
# search algorithm.  The array must be sorted prior to making this call.
# If it is not sorted, the results are undefined.  If the array contains
# multiple elements with the specified value, there is no guarantee which
# one will be found.
#
# @param [Array] array the ordered array in which the value should be searched
# @param [Object] value the value to search for
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Fixnum|Bignum] if > 0 position of value, otherwise -(insertion_point + 1)
def self.binary_search(array, value, from_index=0,  to_index=array.length)
  raise(ArgumentError, 'Invalid Range') if from_index < 0 || from_index > array.length || from_index > to_index || to_index > array.length
  _binary_search(array, value, from_index, to_index)
end

private
# Like binary_search, but without range checks.
#
# @param [Array] array the ordered array in which the value should be searched
# @param [Object] value the value to search for
# @param [Fixnum|Bignum] from_index ordered sub-array starts at
# @param [Fixnum|Bignum] to_index ordered sub-array ends the field before
# @return [Fixnum|Bignum] if > 0 position of value, otherwise -(insertion_point + 1)
def self._binary_search(array, value, from_index, to_index)
  low = from_index
  high = to_index - 1

  while low <= high do
    mid = (low + high) / 2
    mid_val = array[mid]

    if mid_val < value
      low = mid + 1
    elsif mid_val > value
      high = mid - 1
    else
      return mid # value found
    end
  end
  -(low + 1) # value not found.
end