我正在尝试获取RxCpp的要点,这是Microsoft的反应式扩展的本地cpp实现,看看我是否可以在项目中使用它,但是我无法理解这些概念。
如果我有一个带有以下结构的可观察对象:
struct Person
{
std::string name;
std::string sex;
int age;
}
我如何创建另一个观察者,其中包含按性别分组的人数,最小年龄,最大年龄和所有事件的平均年龄?
我查看了一些示例,但我看不出如何一次获得多个聚合。
答案 0 :(得分:3)
使用group_by按性别划分,然后合并最小/最大/平均缩减器,以产生每个性别所需的输出。
更新了计数,输出和其他评论
这对我有用:
#include "rxcpp/rx.hpp"
using namespace rxcpp;
using namespace rxcpp::sources;
using namespace rxcpp::subjects;
using namespace rxcpp::util;
using namespace std;
struct Person
{
string name;
string gender;
int age;
};
int main()
{
subject<Person> person$;
// group ages by gender
auto agebygender$ = person$.
get_observable().
group_by(
[](Person& p) { return p.gender;},
[](Person& p) { return p.age;});
// combine min max and average reductions.
auto result$ = agebygender$.
map([](grouped_observable<string, int> gp$){
// the function passed to combine_latest
// will be called once all the source streams
// (count, min, max, average) have produced a
// value. in this case, all the streams are reducers
// that produce only one value when gp$ completes.
// thus the function is only called once per gender
// with the final value of each stat.
return gp$.
count().
combine_latest(
[=](int count, int min, int max, double average){
return make_tuple(gp$.get_key(), count, min, max, average);
},
gp$.min(),
gp$.max(),
gp$.map([](int age) -> double { return age;}).average());
}).
// this map() returns observable<observable<tuple<string, int, int, int, double>>>
// the merge() returns observable<tuple<string, int, int, int, double>>
// a grouped observable is 'hot' if it is not subscribed to immiediatly (in this case by merge)
// then the values sent to it are lost.
merge();
// display results
result$.
subscribe(apply_to([](string gender, int count, int min, int max, double avg){
cout << gender << ": count = " << count << ", range = [" << min << "-" << max << "], avg = " << avg << endl;
}));
//provide input data
observable<>::from(
Person{"Tom", "Male", 32},
Person{"Tim", "Male", 12},
Person{"Stel", "Other", 42},
Person{"Flor", "Female", 24},
Person{"Fran", "Female", 97}).
subscribe(person$.get_subscriber());
return 0;
}
结果输出
Female: count = 2, range = [24-97], avg = 60.5
Male: count = 2, range = [12-32], avg = 22
Other: count = 1, range = [42-42], avg = 42