namespace tf {

/** @page ParallelFind Parallel Find

%Taskflow provides template functions for constructing
tasks to perform parallel iterations over ranges of items.

@tableofcontents

@section ParallelFindIncludeTheHeader Include the Header

You need to include the header file, `%taskflow/algorithm/find.hpp`, 
for using parallel-find algorithms.

@code{.cpp}
#include <taskflow/algorithm/find.hpp>
@endcode

@section WhatIsAFindAlgorithm What is a Find Algorithm?

A find algorithm allows you to find an element in a range 
<tt>[first, last)</tt>
that satisfies a specific criteria.
The algorithm returns an iterator to the first found element in the range
or returns @c last if there is no such iterator.
%Taskflow provides the following parallel-find algorithms:

+ tf::Taskflow::find_if(B first, E last, T& result, UOP predicate, P&& part)
+ tf::Taskflow::find_if_not(B first, E last, T& result, UOP predicate, P&& part)
+ tf::Taskflow::min_element(B first, E last, T& result, C comp, P&& part)
+ tf::Taskflow::max_element(B first, E last, T& result, C comp, P&& part)

@section CreateAParallelFindIfTask Create a Parallel Find-If Task

tf::Taskflow::find_if
performs parallel iterations to find the first element 
in the range <tt>[first, last)</tt> that makes the given predicate return
@c true.
It resembles a parallel implementation of the following loop:

@code{.cpp}
template<typename InputIt, typename UnaryPredicate>
InputIt find_if(InputIt first, InputIt last, UnaryPredicate predicate) {
  for(; first != last; ++first) {
    if(predicate(*first)) {
      return first;
    }
  }
  return last;
}
@endcode

The example below creates a task to find the element that is equal
to 22 from an input range of 10 elements.
The result will be stored in the forth argument passed by reference:

@code{.cpp}
std::vector<int> input = {1, 9, 22, 3, -6, 13, 12, 0, 9, 11};
std::vector<int>::iterator result;
taskflow.find_if(
  input.begin(), input.end(), [](int i){ return i == 22; }, result
);
executor.run(taskflow);
assert(*result == 22);
@endcode

@section ParallelFindCaptureIteratorsByReference Capture Iterators by Reference

You can pass iterators by reference using @std_ref
to marshal parameters update between dependent tasks.
This is especially useful when the range iterators are not known
at the time of creating a find-if task,
but need initialization from another task.

@code{.cpp}
std::vector<int> input;
std::vector<int>::iterator result, first, last;

// task to set up the range iterators
tf::Task init = taskflow.emplace([&](){
  input = {1, 9, 22, 3, -6, 13, 12, 0, 9, 11};
  first = input.begin(),
  last  = input.end();
});

// task to perform parallel find
tf::Task task = taskflow.find_if(
  std::ref(first), std::ref(last), result, [](int i){ return i == 22; }
);

init.precede(task);

executor.run(taskflow);
assert(*result == 22);
@endcode

In the above example, when @c init finishes, @c input has been initialized to 10 elements with
@c first and @c last pointing to the data range of @c input.
The find-if task will then work on this initialized range as a result of
passing iterators by reference.

@section CreateAParallelFindIfNotTask Create a Parallel Find-If-Not Task

tf::Taskflow::find_if_not
performs parallel iterations to find the first element 
in the range <tt>[first, last)</tt> that makes the given predicate return
@c false.
It resembles a parallel implementation of the following loop:

@code{.cpp}
template<typename InputIt, typename UnaryPredicate>
InputIt find_if(InputIt first, InputIt last, UnaryPredicate predicate) {
  for(; first != last; ++first) {
    if(!predicate(*first)) {
      return first;
    }
  }
  return last;
}
@endcode

The example below creates a task to find the element that is @em NOT equal
to 22 from an input range of 10 elements. The result
will be stored in the forth argument passed by reference:

@code{.cpp}
std::vector<int> input = {1, 1, 22, 1, 1, 1, 1, 1, 1, 1};
std::vector<int>::iterator result;
taskflow.find_if_not(
  input.begin(), input.end(), result, [](int i){ return i == 1; }
);
executor.run(taskflow);
assert(*result == 22);
@endcode

Similar to @ref ParallelFindCaptureIteratorsByReference,
iterators of tf::Taskflow::find_if_not are templated to 
allow passing iterators by reference using @std_ref.
This is especially useful when the range iterators are not known
at the time of creating a find-if-not task,
but need initialization from another task.

@section ParallelFindMinMaxElement Find the Smallest and the Largest Elements

tf::Taskflow::min_element finds the smallest element in a range
<tt>[first, last)</tt> using the given comparison function object.
The example below finds the smallest element, i.e., -1, 
from an input range of 10 elements and stores the iterator
to that smallest element in @c result:

@code{.cpp}
std::vector<int> input = {1, 1, 1, 1, 1, -1, 1, 1, 1, 1};
std::vector<int>::iterator result;
taskflow.min_element(
  input.begin(), input.end(), std::less<int>(), result
);
executor.run(taskflow).wait();
assert(*result == -1);
@endcode

Similarly, tf::Taskflow::max_element finds the largest element
in a range <tt>[first, last)</tt> using the given comparison function object.
The example below finds the largest element, i.e., 2,
from an input range of 10 elements and stores the iterator
to that largest element in @c result:

@code{.cpp}
std::vector<int> input = {1, 1, 1, 1, 1, 2, 1, 1, 1, 1};
std::vector<int>::iterator result;
taskflow.max_element(
  input.begin(), input.end(), std::less<int>(), result
);
executor.run(taskflow).wait();
assert(*result == 2);
@endcode

@attention
When using tf::Taskflow::max_element to find the large element,
we will still need to use std::less as our comparison function.
Details can be referred to 
[std::max_element](https://en.cppreference.com/w/cpp/algorithm/max_element).

@section ParallelFindConfigureAPartitioner Configure a Partitioner

You can configure a partitioner for parallel-find tasks
(tf::Taskflow::find_if, tf::Taskflow::find_if_not, 
tf::Taskflow::min_element, tf::Taskflow::max_element)
to run with different scheduling methods, 
such as guided partitioning, dynamic partitioning, and static partitioning.
The following example creates two parallel-find tasks using two different
partitioners, one with the static partitioning algorithm and 
another one with the guided partitioning algorithm:

@code{.cpp}
std::vector<int> vec(1024, -1);
std::vector<int>::iterator result;

tf::ExecutionPolicy<tf::StaticPartitioner> static_partitioner;
tf::ExecutionPolicy<tf::GuidedPartitioner> guided_partitioner;

// create a parallel-find task with a static partitioner
taskflow.find_if(
  vec.begin(), vec.end(), result, [&](int i) { return i == -1; }, static_partitioner
);

// create a parallel-find task with a guided partitioner
taskflow.find_if(
  vec.begin(), vec.end(), result, [&](int i) { return i == -1; }, guided_partitioner
);
@endcode

@attention
By default, parallel-find tasks use tf::DefaultPartitioner
if no partitioner is specified. 

*/

}






