Active object
You are encouraged to solve this task according to the task description, using any language you may know.
In object-oriented programming an object is active when its state depends on clock. Usually an active object encapsulates a task that updates the object's state. To the outer world the object looks like a normal object with methods that can be called from outside. Implementation of such methods must have a certain synchronization mechanism with the encapsulated task in order to prevent object's state corruption.
A typical instance of an active object is an animation widget. The widget state changes with the time, while as an object it has all properties of a normal widget.
The task
Implement an active integrator object. The object has an input and output. The input can be set using the method Input. The input is a function of time. The output can be queried using the method Output. The object integrates its input over the time and the result becomes the object's output. So if the input is K(t) and the output is S, the object state S is changed to S + (K(t1) + K(t0)) * (t1 - t0) / 2, i.e. it integrates K using the trapeze method. Initially K is constant 0 and S is 0.
In order to test the object:
- set its input to sin (2π f t), where the frequency f=0.5Hz. The phase is irrelevant.
- wait 2s
- set the input to constant 0
- wait 0.5s
Verify that now the object's output is approximately 0 (the sine has the period of 2s). The accuracy of the result will depend on the OS scheduler time slicing and the accuracy of the clock.
Ada
<lang ada>with Ada.Calendar; use Ada.Calendar; with Ada.Numerics; use Ada.Numerics; with Ada.Numerics.Elementary_Functions; use Ada.Numerics.Elementary_Functions; with Ada.Text_IO; use Ada.Text_IO;
procedure Test_Integrator is
type Func is access function (T : Time) return Float;
function Zero (T : Time) return Float is
begin
return 0.0;
end Zero;
Epoch : constant Time := Clock;
function Sine (T : Time) return Float is
begin
return Sin (Pi * Float (T - Epoch));
end Sine;
task type Integrator is
entry Input (Value : Func);
entry Output (Value : out Float);
entry Shut_Down;
end Integrator;
task body Integrator is
K : Func := Zero'Access;
S : Float := 0.0;
F0 : Float := 0.0;
F1 : Float;
T0 : Time := Clock;
T1 : Time;
begin
loop
select
accept Input (Value : Func) do
K := Value;
end Input;
or accept Output (Value : out Float) do
Value := S;
end Output;
or accept Shut_Down;
exit;
else
T1 := Clock;
F1 := K (T1);
S := S + 0.5 * (F1 + F0) * Float (T1 - T0);
T0 := T1;
F0 := F1;
end select;
end loop;
end Integrator;
I : Integrator;
S : Float;
begin
I.Input (Sine'Access);
delay 2.0;
I.Input (Zero'Access);
delay 0.5;
I.Output (S);
Put_Line ("Integrated" & Float'Image (S) & "s");
I.Shut_Down;
end Test_Integrator;</lang> Sample output:
Integrated-5.34100E-05s
BBC BASIC
<lang bbcbasic> INSTALL @lib$+"CLASSLIB"
INSTALL @lib$+"TIMERLIB"
INSTALL @lib$+"NOWAIT"
REM Integrator class:
DIM integ{f$, t#, v#, tid%, @init, @@exit, input, output, tick}
PROC_class(integ{})
REM Methods:
DEF integ.@init integ.f$ = "0" : integ.tid% = FN_ontimer(10, PROC(integ.tick), 1) : ENDPROC
DEF integ.@@exit PROC_killtimer(integ.tid%) : ENDPROC
DEF integ.input (f$) integ.f$ = f$ : ENDPROC
DEF integ.output = integ.v#
DEF integ.tick integ.t# += 0.01 : integ.v# += EVAL(integ.f$) : ENDPROC
REM Test:
PROC_new(myinteg{}, integ{})
PROC(myinteg.input) ("SIN(2*PI*0.5*myinteg.t#)")
PROCwait(200)
PROC(myinteg.input) ("0")
PROCwait(50)
PRINT "Final value = " FN(myinteg.output)
PROC_discard(myinteg{})</lang>
Output:
Final value = -1.43349462E-6
C
Uses POSIX threads.
<lang c>#include <stdio.h>
- include <stdlib.h>
- include <unistd.h>
- include <math.h>
- include <sys/time.h>
- include <pthread.h>
/* no need to lock the object: at worst the readout would be 1 tick off,
which is no worse than integrator's inate inaccuracy */
typedef struct { double (*func)(double); struct timeval start; double v, last_v, last_t; pthread_t id; } integ_t, *integ;
void update(integ x) { struct timeval tv; double t, v, (*f)(double);
f = x->func; gettimeofday(&tv, 0); t = ((tv.tv_sec - x->start.tv_sec) * 1000000 + tv.tv_usec - x->start.tv_usec) * 1e-6; v = f ? f(t) : 0; x->v += (x->last_v + v) * (t - x->last_t) / 2; x->last_t = t; }
void* tick(void *a) { integ x = a; while (1) { usleep(100000); /* update every .1 sec */ update(x); } }
void set_input(integ x, double (*func)(double)) { update(x); x->func = func; x->last_t = 0; x->last_v = func ? func(0) : 0; }
integ new_integ(double (*func)(double)) { integ x = malloc(sizeof(integ_t)); x->v = x->last_v = 0; x->func = 0; gettimeofday(&x->start, 0); set_input(x, func); pthread_create(&x->id, 0, tick, x); return x; }
double sine(double t) { return sin(4 * atan2(1, 1) * t); }
int main() { integ x = new_integ(sine); sleep(2); set_input(x, 0); usleep(500000); printf("%g\n", x->v);
return 0; }</lang> output
-9.99348e-05
C#
<lang csharp>using System; using System.Threading.Tasks;
using static System.Diagnostics.Stopwatch; using static System.Math; using static System.Threading.Thread;
class ActiveObject {
static double timeScale = 1.0 / Frequency;
Func<double, double> func; Task updateTask; double integral; double value; long timestamp0, timestamp;
public ActiveObject(Func<double, double> input)
{
timestamp0 = timestamp = GetTimestamp();
func = input;
value = func(0);
updateTask = Integrate();
}
public void ChangeInput(Func<double, double> input)
{
lock (updateTask)
{
func = input;
}
}
public double Value
{
get
{
lock (updateTask)
{
return integral;
}
}
}
async Task Integrate()
{
while (true)
{
await Task.Yield();
var newTime = GetTimestamp();
double newValue;
lock (updateTask)
{
newValue = func((newTime - timestamp0) * timeScale);
integral += (newValue + value) * (newTime - timestamp) * timeScale / 2;
}
timestamp = newTime;
value = newValue;
}
}
}
class Program {
static Func<double, double> Sine(double frequency) =>
t => Sin(2 * PI * frequency * t);
static void Main(string[] args)
{
var ao = new ActiveObject(Sine(0.5));
Sleep(TimeSpan.FromSeconds(2));
ao.ChangeInput(t => 0);
Sleep(TimeSpan.FromSeconds(0.5));
Console.WriteLine(ao.Value);
}
}</lang>
Output:
8.62230019255E-5
C++
<lang cpp>#include <atomic>
- include <chrono>
- include <cmath>
- include <iostream>
- include <mutex>
- include <thread>
using namespace std::chrono_literals;
class Integrator {
public: using clock_type = std::chrono::high_resolution_clock; using dur_t = std::chrono::duration<double>; using func_t = double(*)(double);
explicit Integrator(func_t f = nullptr);
~Integrator();
void input(func_t new_input);
double output() { return integrate(); }
private: std::atomic_flag continue_; std::mutex mutex; std::thread worker;
func_t func; double state = 0; //Improves precision by reducing sin result error on large values clock_type::time_point const beginning = clock_type::now(); clock_type::time_point t_prev = beginning;
void do_work(); double integrate();
};
Integrator::Integrator(func_t f) : func(f) {
continue_.test_and_set(); worker = std::thread(&Integrator::do_work, this);
}
Integrator::~Integrator() {
continue_.clear(); worker.join();
}
void Integrator::input(func_t new_input) {
integrate(); std::lock_guard<std::mutex> lock(mutex); func = new_input;
}
void Integrator::do_work() {
while(continue_.test_and_set()) {
integrate();
std::this_thread::sleep_for(1ms);
}
}
double Integrator::integrate() {
std::lock_guard<std::mutex> lock(mutex);
auto now = clock_type::now();
dur_t start = t_prev - beginning;
dur_t fin = now - beginning;
if(func)
state += (func(start.count()) + func(fin.count())) * (fin - start).count() / 2;
t_prev = now;
return state;
}
double sine(double time) {
constexpr double PI = 3.1415926535897932; return std::sin(2 * PI * 0.5 * time);
}
int main() {
Integrator foo(sine); std::this_thread::sleep_for(2s); foo.input(nullptr); std::this_thread::sleep_for(500ms); std::cout << foo.output();
}</lang> output
1.23136e-011
Clojure
<lang clojure>(ns active-object
(:import (java.util Timer TimerTask)))
(defn input [integrator k]
(send integrator assoc :k k))
(defn output [integrator]
(:s @integrator))
(defn tick [integrator t1]
(send integrator
(fn [{:keys [k s t0] :as m}]
(assoc m :s (+ s (/ (* (+ (k t1) (k t0)) (- t1 t0)) 2.0)) :t0 t1))))
(defn start-timer [integrator interval]
(let [timer (Timer. true)
start (System/currentTimeMillis)]
(.scheduleAtFixedRate timer
(proxy [TimerTask] []
(run [] (tick integrator (double (/ (- (System/currentTimeMillis) start) 1000)))))
(long 0)
(long interval))
#(.cancel timer)))
(defn test-integrator []
(let [integrator (agent {:k (constantly 0.0) :s 0.0 :t0 0.0})
stop-timer (start-timer integrator 10)]
(input integrator #(Math/sin (* 2.0 Math/PI 0.5 %)))
(Thread/sleep 2000)
(input integrator (constantly 0.0))
(Thread/sleep 500)
(println (output integrator))
(stop-timer)))
user> (test-integrator) 1.414065859052494E-5 </lang>
D
<lang D>import core.thread; import std.datetime; import std.math; import std.stdio;
void main() {
auto func = (double t) => sin(cast(double) PI * t); Integrator integrator = new Integrator(func); Thread.sleep(2000.msecs);
integrator.setFunc(t => 0.0); Thread.sleep(500.msecs);
integrator.stop(); writeln(integrator.getOutput());
}
/**
* Integrates input function K over time * S + (t1 - t0) * (K(t1) + K(t0)) / 2 */
public class Integrator {
public alias Function = double function (double);
private SysTime start; private shared bool running;
private Function func; private shared double t0; private shared double v0; private shared double sum = 0.0;
public this(Function func) {
this.start = Clock.currTime();
setFunc(func);
new Thread({
integrate();
}).start();
}
public void setFunc(Function func) {
this.func = func;
v0 = func(0.0);
t0 = 0.0;
}
public double getOutput() {
return sum;
}
public void stop() {
running = false;
}
private void integrate() {
running = true;
while (running) {
Thread.sleep(1.msecs);
update();
}
}
private void update() {
import core.atomic;
Duration t1 = (Clock.currTime() - start);
double v1 = func(t1.total!"msecs");
double rect = (t1.total!"msecs" - t0) * (v0 + v1) / 2;
atomicOp!"+="(this.sum, rect);
t0 = t1.total!"msecs";
v0 = v1;
}
}</lang>
- Output:
-3.07837e-13
E
<lang e>def makeIntegrator() {
var value := 0.0
var input := fn { 0.0 }
var input1 := input()
var t1 := timer.now()
def update() {
def t2 := timer.now()
def input2 :float64 := input()
def dt := (t2 - t1) / 1000
value += (input1 + input2) * dt / 2
t1 := t2
input1 := input2
}
var task() {
update <- ()
task <- ()
}
task()
def integrator {
to input(new) :void { input := new }
to output() :float64 { return value }
to shutdown() { task := fn {} }
}
return integrator
}
def test() {
def result
def pi := (-1.0).acos()
def freq := pi / 1000
def base := timer.now()
def i := makeIntegrator()
i.input(fn { (freq * timer.now()).sin() })
timer.whenPast(base + 2000, fn {
i.input(fn {0})
})
timer.whenPast(base + 2500, fn {
bind result := i.output()
i.shutdown()
})
return result
}</lang>
EchoLisp
We use the functions (at ..) : scheduling, (wait ...), and (every ...) ot the timer.lib. The accuracy will be function of the browser's functions setTimeout and setInterval ... <lang lisp> (require 'timer)
- returns an 'object'
- (&lamdba; message [values])
- messages
- input, output, sample, inspect
(define (make-active) (let [ (t0 #f) (dt 0) (t 0) (Kt 0) ; K(t) (S 0) (K 0)] (lambda (message . args) (case message ((output) (// S 2)) ((input ) (set! K (car args)) (set! t0 #f)) ((inspect) (printf " Active obj : t0 %v t %v S %v " t0 t Kt (// S 2 ))) ((sample) (when (procedure? K)
- recved new K
- init
(unless t0 (set! t0 (first args)) (set! t 0) (set! Kt (K 0)))
- integrate K(t) every time 'sample message is received
(set! dt (- (first args) t t0)) ;; compute once K(t) (set! S (+ S (* dt Kt))) (set! t (+ t dt)) (set! Kt (K t)) (set! S (+ S (* dt Kt)))))
(else (error "active:bad message" message)))))) </lang>
- Output:
<lang lisp> (define (experiment) (define (K t) (sin (* PI t ))) (define A (make-active)) (define (stop) (A 'input 0)) (define (sample t) (A 'sample (// t 1000))) (define (result) (writeln 'result (A 'output)))
(at 2.5 'seconds 'result) (every 10 'sample) ;; integrate every 10 ms
(A 'input K) (wait 2000 'stop))
(experiment) →
3/7/2015 20:34:18 : result result 0.0002266920372221955
(experiment) →
3/7/2015 20:34:28 : result result 0.00026510586971023164
</lang>
Erlang
I could not see what time to use between each integration so it is the argument to task(). <lang Erlang> -module( active_object ). -export( [delete/1, input/2, new/0, output/1, task/1] ). -compile({no_auto_import,[time/0]}).
delete( Object ) ->
Object ! stop.
input( Object, Fun ) ->
Object ! {input, Fun}.
new( ) ->
K = fun zero/1,
S = 0,
T0 = seconds_with_decimals(),
erlang:spawn( fun() -> loop(K, S, T0) end ).
output( Object ) ->
Object ! {output, erlang:self()},
receive
{output, Object, Output} -> Output
end.
task( Integrate_millisec ) ->
Object = new(),
{ok, _Ref} = timer:send_interval( Integrate_millisec, Object, integrate ),
io:fwrite( "New ~p~n", [output(Object)] ),
input( Object, fun sine/1 ),
timer:sleep( 2000 ),
io:fwrite( "Sine ~p~n", [output(Object)] ),
input( Object, fun zero/1 ),
timer:sleep( 500 ),
io:fwrite( "Approx ~p~n", [output(Object)] ),
delete( Object ).
loop( Fun, Sum, T0 ) ->
receive
integrate ->
T1 = seconds_with_decimals(),
New_sum = trapeze( Sum, Fun, T0, T1 ),
loop( Fun, New_sum, T1 );
stop ->
ok;
{input, New_fun} ->
loop( New_fun, Sum, T0 );
{output, Pid} ->
Pid ! {output, erlang:self(), Sum},
loop( Fun, Sum, T0 )
end.
sine( T ) ->
math:sin( 2 * math:pi() * 0.5 * T ).
seconds_with_decimals() ->
{Megaseconds, Seconds, Microseconds} = os:timestamp(),
(Megaseconds * 1000000) + Seconds + (Microseconds / 1000000).
trapeze( Sum, Fun, T0, T1 ) ->
Sum + (Fun(T1) + Fun(T0)) * (T1 - T0) / 2.
zero( _ ) -> 0. </lang>
Factor
Working with dynamic quotations requires the stack effect to be known in advance. The apply-stack-effect serves this purpose. <lang factor>USING: accessors alarms calendar combinators kernel locals math math.constants math.functions prettyprint system threads ; IN: rosettacode.active
TUPLE: active-object alarm function state previous-time ;
- apply-stack-effect ( quot -- quot' )
[ call( x -- x ) ] curry ; inline
- nano-to-seconds ( -- seconds ) nano-count 9 10^ / ;
- object-times ( active-object -- t1 t2 )
[ previous-time>> ] [ nano-to-seconds [ >>previous-time drop ] keep ] bi ;
- adding-function ( t1 t2 active-object -- function )
t2 t1 active-object function>> apply-stack-effect bi@ + t2 t1 - * 2 / [ + ] curry ;
- integrate ( active-object -- )
[ object-times ] [ adding-function ] [ swap apply-stack-effect change-state drop ] tri ;
- <active-object> ( -- object )
active-object new 0 >>state nano-to-seconds >>previous-time [ drop 0 ] >>function dup [ integrate ] curry 1 nanoseconds every >>alarm ;
- destroy ( active-object -- ) alarm>> cancel-alarm ;
- input ( object quot -- object ) >>function ;
- output ( object -- val ) state>> ;
- active-test ( -- )
<active-object> [ 2 pi 0.5 * * * sin ] input 2 seconds sleep [ drop 0 ] input 0.5 seconds sleep [ output . ] [ destroy ] bi ;
MAIN: active-test</lang>
( scratchpad ) "rosettacode.active" run -5.294207647335787e-05
FBSL
The Dynamic Assembler and Dynamic C JIT compilers integrated in FBSL v3.5 handle multithreading perfectly well. However, pure FBSL infrastructure has never been designed especially to support own multithreading nor can it handle long long integers natively. Yet a number of tasks with careful design and planning are quite feasible in pure FBSL too: <lang qbasic>#APPTYPE CONSOLE
- INCLUDE <Include\Windows.inc>
DIM Entity AS NEW Integrator(): Sleep(2000) ' respawn and do the job
Entity.Relax(): Sleep(500) ' get some rest
PRINT ">>> ", Entity.Yield(): DELETE Entity ' report and die
PAUSE
' ------------- End Program Code -------------
- DEFINE SpawnMutex CreateMutex(NULL, FALSE, "mutex")
- DEFINE LockMutex WaitForSingleObject(mutex, INFINITE)
- DEFINE UnlockMutex ReleaseMutex(mutex)
- DEFINE KillMutex CloseHandle(mutex)
CLASS Integrator
PRIVATE:
TYPE LARGE_INTEGER lowPart AS INTEGER highPart AS INTEGER END TYPE
DIM dfreq AS DOUBLE, dlast AS DOUBLE, dnow AS DOUBLE, llint AS LARGE_INTEGER DIM dret0 AS DOUBLE, dret1 AS DOUBLE, mutex AS INTEGER, sum AS DOUBLE, thread AS INTEGER
' -------------------------------------------- SUB INITIALIZE() mutex = SpawnMutex QueryPerformanceFrequency(@llint) dfreq = LargeInt2Double(llint) QueryPerformanceCounter(@llint) dlast = LargeInt2Double(llint) / dfreq thread = FBSLTHREAD(ADDRESSOF Sampler) FBSLTHREADRESUME(thread) END SUB SUB TERMINATE() ' nothing special END SUB ' --------------------------------------------
SUB Sampler() DO LockMutex Sleep(5) QueryPerformanceCounter(@llint) dnow = LargeInt2Double(llint) / dfreq dret0 = Task(dlast): dret1 = Task(dnow) sum = sum + (dret1 + dret0) * (dnow - dlast) / 2 dlast = dnow UnlockMutex LOOP END SUB
FUNCTION LargeInt2Double(obj AS VARIANT) AS DOUBLE STATIC ret ret = obj.highPart IF obj.highPart < 0 THEN ret = ret + (2 ^ 32) ret = ret * 2 ^ 32 ret = ret + obj.lowPart IF obj.lowPart < 0 THEN ret = ret + (2 ^ 32) RETURN ret END FUNCTION
PUBLIC:
METHOD Relax() LockMutex ADDRESSOF Task = ADDRESSOF Idle UnlockMutex END METHOD
METHOD Yield() AS DOUBLE LockMutex Yield = sum FBSLTHREADKILL(thread) UnlockMutex KillMutex END METHOD
END CLASS
FUNCTION Idle(BYVAL t AS DOUBLE) AS DOUBLE RETURN 0.0 END FUNCTION
FUNCTION Task(BYVAL t AS DOUBLE) AS DOUBLE RETURN SIN(2 * PI * 0.5 * t) END FUNCTION</lang>
Typical console output:
>>> -0.000769965989580346 Press any key to continue...
F#
<lang fsharp>open System open System.Threading
// current time in seconds let now() = float( DateTime.Now.Ticks / 10000L ) / 1000.0
type Integrator( intervalMs ) as x =
let mutable k = fun _ -> 0.0 // function to integrate let mutable s = 0.0 // current value let mutable t0 = now() // last time s was updated let mutable running = true // still running?
do x.ScheduleNextUpdate()
member x.Input(f) = k <- f
member x.Output() = s
member x.Stop() = running <- false
member private x.Update() = let t1 = now() s <- s + (k t0 + k t1) * (t1 - t0) / 2.0 t0 <- t1 x.ScheduleNextUpdate()
member private x.ScheduleNextUpdate() =
if running then
async { do! Async.Sleep( intervalMs )
x.Update()
}
|> Async.Start
let i = new Integrator(10)
i.Input( fun t -> Math.Sin (2.0 * Math.PI * 0.5 * t) ) Thread.Sleep(2000)
i.Input( fun _ -> 0.0 ) Thread.Sleep(500)
printfn "%f" (i.Output()) i.Stop()</lang>
Go
Using time.Tick to sample K at a constant frequency. Three goroutines are involved, main, aif, and tk. Aif controls access to the accumulator s and the integration function K. Tk and main must talk to aif through channels to access s and K. <lang go>package main
import (
"fmt" "math" "time"
)
// type for input function, k. // input is duration since an arbitrary start time t0. type tFunc func(time.Duration) float64
// active integrator object. state variables are not here, but in // function aif, started as a goroutine in the constructor. type aio struct {
iCh chan tFunc // channel for setting input function oCh chan chan float64 // channel for requesting output
}
// constructor func newAio() *aio {
var a aio a.iCh = make(chan tFunc) a.oCh = make(chan chan float64) go aif(&a) return &a
}
// input method required by task description. in practice, this method is // unnecessary; you would just put that single channel send statement in // your code wherever you wanted to set the input function. func (a aio) input(f tFunc) {
a.iCh <- f
}
// output method required by task description. in practice, this method too // would not likely be best. instead any client interested in the value would // likely make a return channel sCh once, and then reuse it as needed. func (a aio) output() float64 {
sCh := make(chan float64) a.oCh <- sCh return <-sCh
}
// integration function that returns constant 0 func zeroFunc(time.Duration) float64 { return 0 }
// goroutine serializes access to integrated function k and state variable s func aif(a *aio) {
var k tFunc = zeroFunc // integration function s := 0. // "object state" initialized to 0 t0 := time.Now() // initial time k0 := k(0) // initial sample value t1 := t0 // t1, k1 used for trapezoid formula k1 := k0
tk := time.Tick(10 * time.Millisecond) // 10 ms -> 100 Hz
for {
select {
case t2 := <-tk: // timer tick event
k2 := k(t2.Sub(t0)) // new sample value
s += (k1 + k2) * .5 * t2.Sub(t1).Seconds() // trapezoid formula
t1, k1 = t2, k2 // save time and value
case k = <-a.iCh: // input method event: function change
case sCh := <-a.oCh: // output method event: sample object state
sCh <- s
}
}
}
func main() {
a := newAio() // create object
a.input(func(t time.Duration) float64 { // 1. set input to sin function
return math.Sin(t.Seconds() * math.Pi)
})
time.Sleep(2 * time.Second) // 2. sleep 2 sec
a.input(zeroFunc) // 3. set input to zero function
time.Sleep(time.Second / 2) // 4. sleep .5 sec
fmt.Println(a.output()) // output should be near zero
}</lang> Output:
2.4517135756807704e-05
Haskell
<lang haskell>module Integrator (
newIntegrator, input, output, stop, Time, timeInterval
) where import Control.Concurrent (forkIO, threadDelay) import Control.Concurrent.MVar (MVar, newMVar, modifyMVar_, modifyMVar, readMVar) import Control.Exception (evaluate) import Data.Time (UTCTime) import Data.Time.Clock (getCurrentTime, diffUTCTime)
-- RC task main = do let f = 0.5 {- Hz -}
t0 <- getCurrentTime
i <- newIntegrator
input i (\t -> sin(2*pi * f * timeInterval t0 t)) -- task step 1
threadDelay 2000000 {- µs -} -- task step 2
input i (const 0) -- task step 3
threadDelay 500000 {- µs -} -- task step 4
result <- output i
stop i
print result
Implementation ------------------------------------------------------
-- Utilities for working with the time type type Time = UTCTime type Func a = Time -> a timeInterval t0 t1 = realToFrac $ diffUTCTime t1 t0
-- Type signatures of the module's interface newIntegrator :: Fractional a => IO (Integrator a) -- Create an integrator input :: Integrator a -> Func a -> IO () -- Set the input function output :: Integrator a -> IO a -- Get the current value stop :: Integrator a -> IO () -- Stop integration, don't waste CPU
-- Data structures data Integrator a = Integrator (MVar (IntState a)) -- MVar is a thread-safe mutable cell
deriving Eq
data IntState a = IntState { func :: Func a, -- The current function
run :: Bool, -- Whether to keep going
value :: a, -- The current accumulated value
time :: Time } -- The time of the previous update
newIntegrator = do
now <- getCurrentTime
state <- newMVar $ IntState { func = const 0,
run = True,
value = 0,
time = now }
thread <- forkIO (intThread state) -- The state variable is shared between the thread
return (Integrator state) -- and the client interface object.
input (Integrator stv) f = modifyMVar_ stv (\st -> return st { func = f }) output (Integrator stv) = fmap value $ readMVar stv stop (Integrator stv) = modifyMVar_ stv (\st -> return st { run = False })
-- modifyMVar_ takes an MVar and replaces its contents according to the provided function.
-- a { b = c } is record-update syntax: "the record a, except with field b changed to c"
-- Integration thread intThread :: Fractional a => MVar (IntState a) -> IO () intThread stv = whileM $ modifyMVar stv updateAndCheckRun
-- modifyMVar is like modifyMVar_ but the function returns a tuple of the new value
-- and an arbitrary extra value, which in this case ends up telling whileM whether
-- to keep looping.
where updateAndCheckRun st = do
now <- getCurrentTime
let value' = integrate (func st) (value st) (time st) now
evaluate value' -- avoid undesired laziness
return (st { value = value', time = now }, -- updated state
run st) -- whether to continue
integrate :: Fractional a => Func a -> a -> Time -> Time -> a integrate f value t0 t1 = value + (f t0 + f t1)/2 * dt
where dt = timeInterval t0 t1
-- Execute 'action' until it returns false. whileM action = do b <- action; if b then whileM action else return ()</lang>
J
Implementation:
<lang J>coclass 'activeobject' require'dates'
create=:setinput NB. constructor
T=:3 :0
if. nc<'T0' do. T0=:tsrep 6!:0 end. 0.001*(tsrep 6!:0)-T0
)
F=:G=:0: Zero=:0
setinput=:3 :0
zero=. getoutput '`F ignore'=: y,_:` G=: F f.d._1 Zero=: zero-G T getoutput
)
getoutput=:3 :0
Zero+G T
)</lang>
Task example (code):
<lang J>cocurrent 'testrig'
delay=: 6!:3
object=: conew 'activeobject' setinput__object 1&o.@o.` smoutput (T__object,getoutput__object)
delay 2
smoutput (T__object,getoutput__object) setinput__object 0:` smoutput (T__object,getoutput__object)
delay 0.5
smoutput (T__object,getoutput__object) </lang>
Task example (output):
0.001 0 2.002 4.71237e_6 2.004 1.25663e_5 2.504 1.25663e_5
First column is time relative to start of processing, second column is object's output at that time.
Java
<lang java>/**
* Integrates input function K over time * S + (t1 - t0) * (K(t1) + K(t0)) / 2 */
public class Integrator {
public interface Function {
double apply(double timeSinceStartInSeconds);
}
private final long start; private volatile boolean running;
private Function func; private double t0; private double v0; private double sum;
public Integrator(Function func) {
this.start = System.nanoTime();
setFunc(func);
new Thread(this::integrate).start();
}
public void setFunc(Function func) {
this.func = func;
v0 = func.apply(0.0);
t0 = 0;
}
public double getOutput() {
return sum;
}
public void stop() {
running = false;
}
private void integrate() {
running = true;
while (running) {
try {
Thread.sleep(1);
update();
} catch (InterruptedException e) {
return;
}
}
}
private void update() {
double t1 = (System.nanoTime() - start) / 1.0e9;
double v1 = func.apply(t1);
double rect = (t1 - t0) * (v0 + v1) / 2;
this.sum += rect;
t0 = t1;
v0 = v1;
}
public static void main(String[] args) throws InterruptedException {
Integrator integrator = new Integrator(t -> Math.sin(Math.PI * t));
Thread.sleep(2000);
integrator.setFunc(t -> 0.0);
Thread.sleep(500);
integrator.stop();
System.out.println(integrator.getOutput());
}
} </lang> Output:
4.783602720556498E-13
JavaScript
<lang javascript>function Integrator(sampleIntervalMS) {
var inputF = function () { return 0.0 };
var sum = 0.0;
var t1 = new Date().getTime();
var input1 = inputF(t1 / 1000);
function update() {
var t2 = new Date().getTime();
var input2 = inputF(t2 / 1000);
var dt = (t2 - t1) / 1000;
sum += (input1 + input2) * dt / 2;
t1 = t2;
input1 = input2;
}
var updater = setInterval(update, sampleIntervalMS);
return ({
input: function (newF) { inputF = newF },
output: function () { return sum },
shutdown: function () { clearInterval(updater) },
});
}</lang>
Test program as a HTML fragment:
<lang html4strict>
Test running... -
<script type="text/javascript">
var f = 0.5;
var i = new Integrator(1);
var displayer = setInterval(function () { document.getElementById("b").firstChild.data = i.output() }, 100)
setTimeout(function () {
i.input(function (t) { return Math.sin(2*Math.PI*f*t) }); // test step 1
setTimeout(function () { // test step 2
i.input(function (t) { return 0 }); // test step 3
setTimeout(function () { // test step 3
i.shutdown();
clearInterval(displayer);
document.getElementById("a").firstChild.data = "Done, should be about 0: "
}, 500);
}, 2000);
}, 1)
</script></lang>
Julia
Julia has inheritance of data structures and first-class types, but structures do not have methods. Instead, methods are functions with multiple dispatch based on argument type. <lang julia>mutable struct Integrator
func::Function
runningsum::Float64
dt::Float64
running::Bool
function Integrator(f::Function, dt::Float64)
this = new()
this.func = f
this.runningsum = 0.0
this.dt = dt
this.running = false
return this
end
end
function run(integ::Integrator, lastval::Float64 = 0.0)
lasttime = time()
while integ.running
sleep(integ.dt)
newtime = time()
measuredinterval = newtime - lasttime
newval = integ.func(measuredinterval)
integ.runningsum += (lastval + newval) * measuredinterval / 2.0
lasttime = newtime
lastval = newval
end
end
start!(integ::Integrator) = (integ.running = true; @async run(integ)) stop!(integ) = (integ.running = false) f1(t) = sin(2π * t) f2(t) = 0.0
it = Integrator(f1, 0.00001) start!(it) sleep(2.0) it.func = f2 sleep(0.5) v2 = it.runningsum println("After 2.5 seconds, integrator value was $v2")</lang>
Kotlin
Athough this is a faithful translation of the Java entry, on my machine the output of the latter is typically an order of magnitude smaller than this version. I have no idea why. <lang scala>// version 1.2.0
import kotlin.math.*
typealias Function = (Double) -> Double
/**
* Integrates input function K over time * S + (t1 - t0) * (K(t1) + K(t0)) / 2 */
class Integrator {
private val start: Long private @Volatile var running = false private lateinit var func: Function private var t0 = 0.0 private var v0 = 0.0 private var sum = 0.0
constructor(func: Function) {
start = System.nanoTime()
setFunc(func)
Thread(this::integrate).start()
}
fun setFunc(func: Function) {
this.func = func
v0 = func(0.0)
t0 = 0.0
}
fun getOutput() = sum
fun stop() {
running = false
}
private fun integrate() {
running = true
while (running) {
try {
Thread.sleep(1)
update()
}
catch(e: InterruptedException) {
return
}
}
}
private fun update() {
val t1 = (System.nanoTime() - start) / 1.0e9
val v1 = func(t1)
val rect = (t1 - t0) * (v0 + v1) / 2.0
sum += rect
t0 = t1
v0 = v1
}
}
fun main(args: Array<String>) {
val integrator = Integrator( { sin(PI * it) } )
Thread.sleep(2000)
integrator.setFunc( { 0.0 } )
Thread.sleep(500)
integrator.stop() println(integrator.getOutput())
}</lang>
Sample output:
2.884266305153741E-4
Lingo
Parent script "Integrator": <lang Lingo>property _sum property _func property _timeLast property _valueLast property _ms0 property _updateTimer
on new (me, func)
if voidP(func) then func = "0.0"
me._sum = 0.0
-- update frequency: 100/sec (arbitrary)
me._updateTimer = timeout().new("update", 10, #_update, me)
me.input(func)
return me
end
on stop (me)
me._updateTimer.period = 0 -- deactivates timer
end
-- func is a term (as string) that might contain "t" and is evaluated at runtime on input (me, func)
me._func = func me._ms0 = _system.milliseconds me._timeLast = 0.0 t = 0.0 me._valueLast = value(me._func)
end
on output (me)
return me._sum
end
on _update (me)
now = _system.milliseconds - me._ms0 t = now/1000.0 val = value(me._func) me._sum = me._sum + (me._valueLast+val)*(t - me._timeLast)/2 me._timeLast = t me._valueLast = val
end</lang>
In some movie script: <lang Lingo>global gIntegrator
-- entry point on startMovie
gIntegrator = script("Integrator").new("sin(PI * t)")
timeout().new("timer", 2000, #step1)
end
on step1 (_, timer)
gIntegrator.input("0.0")
timer.timeoutHandler = #step2
timer.period = 500
end
on step2 (_, timer)
gIntegrator.stop() put gIntegrator.output() timer.forget()
end</lang>
- Output:
-- 0.0004
Mathematica
<lang Mathematica>Block[{start = SessionTime[], K, t0 = 0, t1, kt0, S = 0},
K[t_] = Sin[2 Pi f t] /. f -> 0.5; kt0 = K[t0]; While[True, t1 = SessionTime[] - start; S += (kt0 + (kt0 = K[t1])) (t1 - t0)/2; t0 = t1; If[t1 > 2, K[t_] = 0; If[t1 > 2.5, Break[]]]]; S]</lang>
1.1309*10^-6
Curiously, this value never changes; it is always exactly the same (at 1.1309E-6). Note that closer answers could be achieved by using Mathematica's better interpolation methods, but it would require collecting the data (in a list), which would have a speed penalty large enough to negate the improved estimation.
ooRexx
Not totally certain this is a correct implementation since the value coming out is not close to zero. It does show all of the basics of multithreading and object synchronization though.
<lang ooRexx> integrater = .integrater~new(.routines~sine) -- start the integrater function call syssleep 2 integrater~input = .routines~zero -- update the integrater function call syssleep .5
say integrater~output integrater~stop -- terminate the updater thread
- class integrater
- method init
expose stopped start v last_v last_t k use strict arg k stopped = .false start = .datetime~new -- initial time stamp v = 0 last_v = 0 last_t = 0 self~input = k self~start
-- spin off a new thread and start updating. Note, this method is unguarded -- to allow other threads to make calls
- method start unguarded
expose stopped
reply -- this spins this method invocation off onto a new thread
do while \stopped call sysSleep .1 self~update -- perform the update operation end
-- turn off the thread. Since this is unguarded, -- it can be called any time, any where
- method stop unguarded
expose stopped stopped = .true
-- perform the update. Since this is a guarded method, the object -- start is protected.
- method update
expose start v last_v t last_t k
numeric digits 20 -- give a lot of precision
current = .datetime~new t = (current - start)~microseconds new_v = k~call(t) -- call the input function v += (last_v + new_v) * (t - last_t) / 2 last_t = t last_v = new_v say new value is v
-- a write-only attribute setter (this is GUARDED)
- attribute input SET
expose k last_t last_v self~update -- update current values use strict arg k -- update the call function to the provided value last_t = 0 last_v = k~call(0) -- and update to the zero value
-- the output function...returns current calculated value
- attribute output GET
expose v return v
- routine zero
return 0
- routine sine
use arg t return rxcalcsin(rxcalcpi() * t)
- requires rxmath library
</lang>
OxygenBasic
Built from scratch. The ringmaster orchestrates all the active-objects, keeping a list of each individual and its method call.
With a high precision timer the result is around -.0002 <lang oxygenbasic> double MainTime
'=============== class RingMaster '=============== ' indexbase 1 sys List[512] 'limit of 512 objects per ringmaster sys max,acts ' method Register(sys meth,obj) as sys
sys i for i=1 to max step 2 if list[i]=0 then exit for 'vacant slot next if i>=max then max+=2 List[i]<=meth,obj return i 'token for deregistration etc
end method ' method Deregister(sys *i)
if i then List[i]<=0,0 : i=0
end method ' method Clear()
max=0
end method ' method Act() 'called by the timer
sys i,q
for i=1 to max step 2
q=List[i]
if q then
call q List[i+1] 'anon object
end if
next
acts++
end method ' end class
'=================
class ActiveObject
'=================
'
double s,freq,t1,t2,v1,v2
sys nfun,acts,RingToken
RingMaster *Master
'
method fun0() as double
end method
'
method fun1() as double
return sin(2*pi()*freq*MainTime)
end method ' method func() as double
select case nfun case 0 : return fun0() case 1 : return fun1() end select 'error?
end method ' method TimeBasedDuties()
t1=t2 v1=v2 t2=MainTime v2=func s=s+(v2+v1)*(t2-t1)*0.5 'add slice to integral acts++
end method ' method RegisterWith(RingMaster*r)
@Master=@r if @Master then RingToken=Master.register @TimeBasedDuties,@this end if
end method ' method Deregister()
if @Master then Master.Deregister RingToken 'this is set to null end if
end method ' method Output() as double
return s
end method ' method Input(double fr=0,fun=0)
if fr then freq=fr nfun=fun
end method
method ClearIntegral()
s=0
end method ' end class
'SETUP TIMING SYSTEM
'===================
extern library "kernel32.dll" declare QueryPerformanceCounter (quad*c) declare QueryPerformanceFrequency(quad*f) declare Sleep(sys milliseconds) end extern ' quad scount,tcount,freq QueryPerformanceFrequency freq double tscale=1/freq double t1,t2 QueryPerformanceCounter scount
macro PrecisionTime(time)
QueryPerformanceCounter tcount time=(tcount-scount)*tscale
end macro
'====
'TEST
'====
double integral double tevent1,tevent2 RingMaster Rudolpho ActiveObject A ' A.RegisterWith Rudolpho A.input (fr=0.5, fun=1) 'start with the freqency function (1) ' 'SET EVENT TIMES '===============
tEvent1=2.0 'seconds tEvent2=2.5 'seconds ' PrecisionTime t1 'mark initial time MainTime=t1 ' ' 'EVENT LOOP '========== ' do
PrecisionTime t2 MainTime=t2 if t2-t1>=0.020 'seconds interval Rudolpho.Act 'service all active objects t1=t2 end if ' if tEvent1>=0 and MainTime>=tEvent1 A.input (fun=0) 'switch to null function (0) tEvent1=-1 'disable this event from happening again end if if MainTime>=tEvent2 integral=A.output() exit do 'end of session end if ' sleep 5 'hand control to OS for a while
end do
print str(integral,4)
Rudolpho.clear</lang>
Oz
<lang oz>declare
fun {Const X}
fun {$ _} X end
end
fun {Now}
{Int.toFloat {Property.get 'time.total'}} / 1000.0
end
class Integrator from Time.repeat
attr
k:{Const 0.0}
s:0.0
t1 k_t1
t2 k_t2
meth init(SampleIntervalMS)
t1 := {Now}
k_t1 := {@k @t1}
{self setRepAll(action:Update
delay:SampleIntervalMS)}
thread
{self go}
end
end
meth input(K)
k := K
end
meth output($)
@s
end
meth Update
t2 := {Now}
k_t2 := {@k @t2}
s := @s + (@k_t1 + @k_t2) * (@t2 - @t1) / 2.0
t1 := @t2
k_t1 := @k_t2
end
end
Pi = 3.14159265 F = 0.5
I = {New Integrator init(10)}
in
{I input(fun {$ T}
{Sin 2.0 * Pi * F * T}
end)}
{Delay 2000} %% ms
{I input({Const 0.0})}
{Delay 500} %% ms
{Show {I output($)}}
{I stop}</lang>
Perl
<lang perl>#!/usr/bin/perl
use strict; use 5.10.0;
package Integrator; use threads; use threads::shared;
sub new { my $cls = shift; my $obj = bless { t => 0, sum => 0, ref $cls ? %$cls : (), stop => 0, tid => 0, func => shift, }, ref $cls || $cls;
share($obj->{sum}); share($obj->{stop});
$obj->{tid} = async { my $upd = 0.1; # update every 0.1 second while (!$obj->{stop}) { { my $f = $obj->{func}; my $t = $obj->{t};
$obj->{sum} += ($f->($t) + $f->($t + $upd))* $upd/ 2; $obj->{t} += $upd; } select(undef, undef, undef, $upd); } # say "stopping $obj"; }; $obj }
sub output { shift->{sum} }
sub delete { my $obj = shift; $obj->{stop} = 1; $obj->{tid}->join; }
sub setinput { # This is surprisingly difficult because of the perl sharing model. # Func refs can't be shared, thus can't be replaced by another thread. # Have to create a whole new object... there must be a better way. my $obj = shift; $obj->delete; $obj->new(shift); }
package main;
my $x = Integrator->new(sub { sin(atan2(1, 1) * 8 * .5 * shift) });
sleep(2); say "sin after 2 seconds: ", $x->output;
$x = $x->setinput(sub {0});
select(undef, undef, undef, .5); say "0 after .5 seconds: ", $x->output;
$x->delete;</lang>
Perl 6
There is some jitter in the timer, but it is typically accurate to within a few thousandths of a second.
<lang perl6>class Integrator {
has $.f is rw = sub ($t) { 0 };
has $.now is rw;
has $.value is rw = 0;
has $.integrator is rw;
method init() {
self.value = &(self.f)(0);
self.integrator = Thread.new(
:code({
loop {
my $t1 = now;
self.value += (&(self.f)(self.now) + &(self.f)($t1)) * ($t1 - self.now) / 2;
self.now = $t1;
sleep .001;
}
}),
:app_lifetime(True)
).run
}
method Input (&f-of-t) {
self.f = &f-of-t;
self.now = now;
self.init;
}
method Output { self.value }
}
my $a = Integrator.new;
$a.Input( sub ($t) { sin(2 * π * .5 * $t) } );
say "Initial value: ", $a.Output;
sleep 2;
say "After 2 seconds: ", $a.Output;
$a.Input( sub ($t) { 0 } );
sleep .5;
say "f(0): ", $a.Output;</lang>
- Typical output:
Initial value: 0 After 2 seconds: -0.0005555887464620366 f(0): 0
PicoLisp
<lang PicoLisp>(load "@lib/math.l")
(class +Active)
- inp val sum usec
(dm T ()
(unless (assoc -100 *Run) # Install timer task
(task -100 100 # Update objects every 0.1 sec
(mapc 'update> *Actives) ) )
(=: inp '((U) 0)) # Set zero input function
(=: val 0) # Initialize last value
(=: sum 0) # Initialize sum
(=: usec (usec)) # and time
(push '*Actives This) ) # Install in notification list
(dm input> (Fun)
(=: inp Fun) )
(dm update> ()
(let (U (usec) V ((: inp) U)) # Get current time, calculate value
(inc (:: sum)
(*/
(+ V (: val)) # (K(t[1]) + K(t[0])) *
(- U (: usec)) # (t[1] - t[0]) /
2.0 ) ) # 2.0
(=: val V)
(=: usec U) ) )
(dm output> ()
(format (: sum) *Scl) ) # Get result
(dm stop> ()
(unless (del This '*Actives) # Removing the last active object?
(task -100) ) ) # Yes: Uninstall timer task
(de integrate () # Test it
(let Obj (new '(+Active)) # Create an active object
(input> Obj # Set input function
'((U) (sin (*/ pi U 1.0))) ) # to sin(π * t)
(wait 2000) # Wait 2 sec
(input> Obj '((U) 0)) # Reset input function
(wait 500) # Wait 0.5 sec
(prinl "Output: " (output> Obj)) # Print return value
(stop> Obj) ) ) # Stop active object</lang>
PureBasic
Using the open-source precompiler SimpleOOP. <lang PureBasic>Prototype.d ValueFunction(f.d, t.d)
Class IntegralClass
Time0.i
Mutex.i
S.d
Freq.d
Thread.i
Quit.i
*func.ValueFunction
Protect Method Sampler()
Repeat
Delay(1)
If This\func And This\Mutex
LockMutex(This\Mutex)
This\S + This\func(This\Freq, ElapsedMilliseconds()-This\Time0)
UnlockMutex(This\Mutex)
EndIf
Until This\Quit
EndMethod
BeginPublic
Method Input(*func.ValueFunction)
LockMutex(This\Mutex)
This\func = *func
UnlockMutex(This\Mutex)
EndMethod
Method.d Output()
Protected Result.d
LockMutex(This\Mutex)
Result = This\S
UnlockMutex(This\Mutex)
MethodReturn Result
EndMethod
Method Init(F.d, *f)
This\Freq = F
This\func = *f
This\Mutex = CreateMutex()
This\Time0 = ElapsedMilliseconds()
This\Thread = CreateThread(This\Sampler, This)
ThreadPriority(This\Thread, 10)
EndMethod
Method Release()
This\Quit = #True
WaitThread(This\Thread)
EndMethod
EndPublic
EndClass
- - Procedures for generating values
Procedure.d n(f.d, t.d)
; Returns nothing
EndProcedure
Procedure.d f(f.d, t.d)
; Returns the function of this task ProcedureReturn Sin(2*#PI*f*t)
EndProcedure
- - Test Code
- a.IntegralClass = NewObject.IntegralClass(0.5, @n()) ; Create the AO
- a\Input(@f()) ; Start sampling function f()
Delay(2000) ; Delay 2 sec
- a\Input(@n()) ; Change to sampling 'nothing'
Delay( 500) ; Wait 1/2 sec MessageRequester("Info", StrD(*a\Output())) ; Present the result
- a= FreeObject</lang>
Python
Assignment is thread-safe in Python, so no extra locks are needed in this case.
<lang python>from time import time, sleep
from threading import Thread
class Integrator(Thread):
'continuously integrate a function `K`, at each `interval` seconds'
def __init__(self, K=lambda t:0, interval=1e-4):
Thread.__init__(self)
self.interval = interval
self.K = K
self.S = 0.0
self.__run = True
self.start()
def run(self):
"entry point for the thread"
interval = self.interval
start = time()
t0, k0 = 0, self.K(0)
while self.__run:
sleep(interval)
t1 = time() - start
k1 = self.K(t1)
self.S += (k1 + k0)*(t1 - t0)/2.0
t0, k0 = t1, k1
def join(self):
self.__run = False
Thread.join(self)
if __name__ == "__main__":
from math import sin, pi ai = Integrator(lambda t: sin(pi*t)) sleep(2) print ai.S ai.K = lambda t: 0 sleep(0.5) print ai.S</lang>
Racket
<lang racket>
- lang racket
(require (only-in racket/gui sleep/yield timer%))
(define active%
(class object% (super-new) (init-field k) ; input function (field [s 0]) ; state (define t_0 0)
(define/public (input new-k) (set! k new-k)) (define/public (output) s)
(define (callback)
(define t_1 (/ (- (current-inexact-milliseconds) start) 1000))
(set! s (+ s (* (+ (k t_0) (k t_1))
(/ (- t_1 t_0) 2))))
(set! t_0 t_1))
(define start (current-inexact-milliseconds))
(new timer%
[interval 1000]
[notify-callback callback])))
(define active (new active% [k (λ (t) (sin (* 2 pi 0.5 t)))])) (sleep/yield 2) (send active input (λ _ 0)) (sleep/yield 0.5) (displayln (send active output)) </lang>
Rust
<lang rust>#![feature(mpsc_select)]
extern crate num; extern crate schedule_recv;
use num::traits::Zero; use num::Float; use schedule_recv::periodic_ms; use std::f64::consts::PI; use std::ops::Mul; use std::sync::mpsc::{self, SendError, Sender}; use std::sync::{Arc, Mutex}; use std::thread; use std::time::Duration;
pub type Actor = Sender<Box<Fn(u32) -> S + Send>>;
pub type ActorResult = Result<(), SendError<Box<Fn(u32) -> S + Send>>>;
/// Rust supports both shared-memory and actor models of concurrency, and the `Integrator` utilizes
/// both. We use an `Actor` to send the `Integrator` new functions, while we use a `Mutex`
/// (shared-memory concurrency) to hold the result of the integration.
///
/// Note that these are not the only options here--there are many, many ways you can deal with
/// concurrent access. But when in doubt, a plain old `Mutex` is often a good bet. For example,
/// this might look like a good situation for a `RwLock`--after all, there's no reason for a read
/// in the main task to block writes. Unfortunately, unless you have significantly more reads than
/// writes (which is certainly not the case here), a `Mutex` will usually outperform a `RwLock`.
pub struct Integrator<S: 'static, T: Send> {
input: Actor, output: Arc<Mutex<T>>,
}
/// In Rust, time durations are strongly typed. This is usually exactly what you want, but for a /// problem like this--where the integrated value has unusual (unspecified?) units--it can actually /// be a bit tricky. Right now, `Duration`s can only be multiplied or divided by `i32`s, so in /// order to be able to actually do math with them we say that the type parameter `S` (the result /// of the function being integrated) must yield `T` (the type of the integrated value) when /// multiplied by `f64`. We could possibly replace `f64` with a generic as well, but it would make /// things a bit more complex. impl<S, T> Integrator<S, T> where
S: Mul<f64, Output = T> + Float + Zero, T: 'static + Clone + Send + Float,
{
pub fn new(frequency: u32) -> Integrator<S, T> {
// We create a pipe allowing functions to be sent from tx (the sending end) to input (the
// receiving end). In order to change the function we are integrating from the task in
// which the Integrator lives, we simply send the function through tx.
let (tx, input) = mpsc::channel();
// The easiest way to do shared-memory concurrency in Rust is to use atomic reference
// counting, or Arc, around a synchronized type (like Mutex<T>). Arc gives you a guarantee
// that memory will not be freed as long as there is at least one reference to it.
// It is similar to C++'s shared_ptr, but it is guaranteed to be safe and is never
// incremented unless explicitly cloned (by default, it is moved).
let s: Arc<Mutex<T>> = Arc::new(Mutex::new(Zero::zero()));
let integrator = Integrator {
input: tx,
// Here is the aforementioned clone. We have to do it before s enters the closure,
// because once that happens it is moved into the closure (and later, the new task) and
// becomes inaccessible to the outside world.
output: Arc::clone(&s),
};
thread::spawn(move || -> () {
// The frequency is how often we want to "tick" as we update our integrated total. In
// Rust, timers can yield Receivers that are periodically notified with an empty
// message (where the period is the frequency). This is useful because it lets us wait
// on either a tick or another type of message (in this case, a request to change the
// function we are integrating).
let periodic = periodic_ms(frequency);
let mut t = 0;
let mut k: Box<Fn(u32) -> S + Send> = Box::new(|_| Zero::zero());
let mut k_0: S = Zero::zero();
loop {
// Here's the selection we talked about above. Note that we are careful to call
// the *non*-failing function, recv(), here. The reason we do this is because
// recv() will return Err when the sending end of a channel is dropped. While
// this is unlikely to happen for the timer (so again, you could argue for failure
// there), it's normal behavior for the sending end of input to be dropped, since
// it just happens when the Integrator falls out of scope. So we handle it cleanly
// and break out of the loop, rather than failing.
select! {
res = periodic.recv() => match res {
Ok(_) => {
t += frequency;
let k_1: S = k(t);
// Rust Mutexes are a bit different from Mutexes in many other
// languages, in that the protected data is actually encapsulated by
// the Mutex. The reason for this is that Rust is actually capable of
// enforcing (via its borrow checker) the invariant that the contents
// of a Mutex may only be read when you have acquired its lock. This
// is enforced by way of a MutexGuard, the return value of lock(),
// which implements some special traits (Deref and DerefMut) that allow
// access to the inner element "through" the guard. The element so
// acquired has a lifetime bounded by that of the MutexGuard, the
// MutexGuard can only be acquired by taking a lock, and the only way
// to release the lock is by letting the MutexGuard fall out of scope,
// so it's impossible to access the data incorrectly. There are some
// additional subtleties around the actual implementation, but that's
// the basic idea.
let mut s = s.lock().unwrap();
*s = *s + (k_1 + k_0) * (f64::from(frequency) / 2.);
k_0 = k_1;
}
Err(_) => break,
},
res = input.recv() => match res {
Ok(k_new) => k = k_new,
Err(_) => break,
}
}
}
});
integrator
}
pub fn input(&self, k: Box<Fn(u32) -> S + Send>) -> ActorResult{ // The meat of the work is done in the other thread, so to set the // input we just send along the Sender we set earlier... self.input.send(k) }
pub fn output(&self) -> T {
// ...and to read the input, we simply acquire a lock on the output Mutex and return a
// copy. Why do we have to copy it? Because, as mentioned above, Rust won't let us
// retain access to the interior of the Mutex unless we have possession of its lock. There
// are ways and circumstances in which one can avoid this (e.g. by using atomic types) but
// a copy is a perfectly reasonable solution as well, and a lot easier to reason about :)
*self.output.lock().unwrap()
}
}
/// This function is fairly straightforward. We create the integrator, set its input function k(t) /// to 2pi * f * t, and then wait as described in the Rosetta stone problem. fn integrate() -> f64 {
let object = Integrator::new(10);
object
.input(Box::new(|t: u32| {
let two_seconds_ms = 2 * 1000;
let f = 1. / f64::from(two_seconds_ms);
(2. * PI * f * f64::from(t)).sin()
}))
.expect("Failed to set input");
thread::sleep(Duration::from_secs(2));
object.input(Box::new(|_| 0.)).expect("Failed to set input");
thread::sleep(Duration::from_millis(500));
object.output()
}
fn main() {
println!("{}", integrate());
}
/// Will fail on a heavily loaded machine
- [test]
- [ignore]
fn solution() {
// We should just be able to call integrate, but can't represent the closure properly due to
// rust-lang/rust issue #17060 if we make frequency or period a variable.
// FIXME(pythonesque): When unboxed closures are fixed, fix integrate() to take two arguments.
let object = Integrator::new(10);
object
.input(Box::new(|t: u32| {
let two_seconds_ms = 2 * 1000;
let f = 1. / (two_seconds_ms / 10) as f64;
(2. * PI * f * t as f64).sin()
}))
.expect("Failed to set input");
thread::sleep(Duration::from_millis(200));
object.input(Box::new(|_| 0.)).expect("Failed to set input");
thread::sleep(Duration::from_millis(100));
assert_eq!(object.output() as u32, 0)
}</lang>
Scala
<lang Scala>object ActiveObject {
class Integrator {
import java.util._
import scala.actors.Actor._
case class Pulse(t: Double) case class Input(k: Double => Double) case object Output case object Bye
val timer = new Timer(true) var k: Double => Double = (_ => 0.0) var s: Double = 0.0 var t0: Double = 0.0
val handler = actor {
loop {
react {
case Pulse(t1) => s += (k(t1) + k(t0)) * (t1 - t0) / 2.0; t0 = t1
case Input(k) => this.k = k
case Output => reply(s)
case Bye => timer.cancel; exit
}
}
}
timer.scheduleAtFixedRate(new TimerTask {
val start = System.currentTimeMillis
def run { handler ! Pulse((System.currentTimeMillis - start) / 1000.0) }
}, 0, 10) // send Pulse every 10 ms
def input(k: Double => Double) = handler ! Input(k) def output = handler !? Output def bye = handler ! Bye }
def main(args: Array[String]) {
val integrator = new Integrator
integrator.input(t => Math.sin(2.0 * Math.Pi * 0.5 * t))
Thread.sleep(2000)
integrator.input(_ => 0.0)
Thread.sleep(500)
println(integrator.output)
integrator.bye
}
}</lang>
Smalltalk
<lang Smalltalk> Object subclass:#Integrator
instanceVariableNames:'tickRate input s thread'
classVariableNames:
poolDictionaries:
category:'Rosetta'
instance methods:
input:aFunctionOfT
input := aFunctionOfT.
startWithTickRate:r
"setup and start sampling" tickRate := r. s := 0. thread := [ self integrateLoop ] fork.
stop
"stop and return the 'final' output" thread terminate. ^ s
integrateLoop
"no need for any locks
- the assignment to s is atomic in Smallalk; its either done or not, when terminated, so who cares"
|tBegin tPrev tNow kPrev kNow deltaT delta|
tBegin := tPrev := Timestamp nowWithMilliseconds. kPrev := input value:0.
[true] whileTrue:[
Delay waitForSeconds: tickRate.
tNow := Timestamp nowWithMilliseconds.
kNow := input value:(tNow millisecondDeltaFrom:tBegin) / 1000.
deltaT := (tNow millisecondDeltaFrom:tPrev) / 1000.
delta := (kPrev + kNow) * deltaT / 2.
s := s + delta.
tPrev := tNow. kPrev := kNow.
].
class methods:
example
#( 0.5 0.1 0.05 0.01 0.005 0.001 0.0005 ) do:[:sampleRate |
|i|
i := Integrator new.
i input:[:t | (2 * Float pi * 0.5 * t) sin].
i startWithTickRate:sampleRate.
Delay waitForSeconds:2.
i input:[:t | 0].
Delay waitForSeconds:0.5.
Transcript
show:'Sample rate: '; showCR:sampleRate;
showCR:(i stop).
].
</lang> running: <lang Smalltalk>Integrator example</lang>
output:
Sample rate: 0.5 -0.0258202058271805 Sample rate: 0.1 -0.00519217893508676 Sample rate: 0.05 -0.000897807957672559 Sample rate: 0.01 -0.000650159409949159 Sample rate: 0.005 -0.00033633922519125 Sample rate: 0.001 0.000286557714782226 Sample rate: 0.0005 0.000253571129723327
for backward compatibility, the smalltalk used here returns only timestamps with second-precision from "Timestamp now". Therefore, the millisecond-precision variant was used here. An alternative would have been to ask the OS for its ticker, which is more precise.
SuperCollider
Instead of writing a class, here we just use an environment to encapsulate state. <lang SuperCollider> ( a = TaskProxy { |envir| envir.use { ~integral = 0; ~time = 0; ~prev = 0; ~running = true; loop { ~val = ~input.(~time); ~integral = ~integral + (~val + ~prev * ~dt / 2); ~prev = ~val; ~time = ~time + ~dt; ~dt.wait; } } }; )
// run the test ( fork { a.set(\dt, 0.0001); a.set(\input, { |t| sin(2pi * 0.5 * t) }); a.play(quant: 0); // play immediately 2.wait; a.set(\input, 0); 0.5.wait; a.stop; a.get(\integral).postln; // answers -7.0263424372343e-15 } ) </lang>
Swift
<lang Swift>// For NSObject, NSTimeInterval and NSThread import Foundation // For PI and sin import Darwin
class ActiveObject:NSObject {
let sampling = 0.1
var K: (t: NSTimeInterval) -> Double
var S: Double
var t0, t1: NSTimeInterval
var thread = NSThread()
func integrateK() {
t0 = t1
t1 += sampling
S += (K(t:t1) + K(t: t0)) * (t1 - t0) / 2
}
func updateObject() {
while true {
integrateK()
usleep(100000)
}
}
init(function: (NSTimeInterval) -> Double) {
S = 0
t0 = 0
t1 = 0
K = function
super.init()
thread = NSThread(target: self, selector: "updateObject", object: nil)
thread.start()
}
func Input(function: (NSTimeInterval) -> Double) {
K = function
}
func Output() -> Double {
return S
}
}
// main func sine(t: NSTimeInterval) -> Double {
let f = 0.5 return sin(2 * M_PI * f * t)
}
var activeObject = ActiveObject(function: sine)
var date = NSDate()
sleep(2)
activeObject.Input({(t: NSTimeInterval) -> Double in return 0.0})
usleep(500000)
println(activeObject.Output()) </lang> Sample output:
1.35308431126191e-16
Tcl
or
This implementation Tcl 8.6 for object support (for the active integrator object) and coroutine support (for the controller task). It could be rewritten to only use 8.5 plus the TclOO library. <lang Tcl>package require Tcl 8.6 oo::class create integrator {
variable e sum delay tBase t0 k0 aid constructor Template:Interval 1 {
set delay $interval set tBase [clock microseconds] set t0 0 set e { 0.0 } set k0 0.0 set sum 0.0 set aid [after $delay [namespace code {my Step}]]
}
destructor {
after cancel $aid
}
method input expression {
set e $expression
}
method output {} {
return $sum
}
method Eval t {
expr $e
}
method Step {} {
set aid [after $delay [namespace code {my Step}]] set t [expr {([clock microseconds] - $tBase) / 1e6}] set k1 [my Eval $t] set sum [expr {$sum + ($k1 + $k0) * ($t - $t0) / 2.}] set t0 $t set k0 $k1
}
}
set pi 3.14159265 proc pause {time} {
yield [after [expr {int($time * 1000)}] [info coroutine]]
} proc task {script} {
coroutine task_ apply [list {} "$script;set ::done ok"]
vwait done
} task {
integrator create i
i input {sin(2*$::pi * 0.5 * $t)}
pause 2
i input { 0.0 }
pause 0.5
puts [format %.15f [i output]]
}</lang> Sample output:
-0.000000168952702
Visual Basic .NET
Since this object is CPU intensive, shutting it down when done is crucial. To facilitate this, the IDisposable pattern was used.
<lang vbnet>Module Module1
Sub Main()
Using active As New Integrator
active.Operation = Function(t As Double) Math.Sin(2 * Math.PI * 0.5 * t)
Threading.Thread.Sleep(TimeSpan.FromSeconds(2))
Console.WriteLine(active.Value)
active.Operation = Function(t As Double) 0
Threading.Thread.Sleep(TimeSpan.FromSeconds(0.5))
Console.WriteLine(active.Value)
End Using
Console.ReadLine()
End Sub
End Module
Class Integrator
Implements IDisposable
Private m_Operation As Func(Of Double, Double)
Private m_Disposed As Boolean
Private m_SyncRoot As New Object
Private m_Value As Double
Public Sub New()
m_Operation = Function(void) 0.0
Dim t As New Threading.Thread(AddressOf MainLoop)
t.Start()
End Sub
Private Sub MainLoop()
Dim epoch = Now
Dim t0 = 0.0
Do
SyncLock m_SyncRoot
Dim t1 = (Now - epoch).TotalSeconds
m_Value = m_Value + (Operation(t1) + Operation(t0)) * (t1 - t0) / 2
t0 = t1
End SyncLock
Threading.Thread.Sleep(10)
Loop Until m_Disposed
End Sub
Public Property Operation() As Func(Of Double, Double)
Get
SyncLock m_SyncRoot
Return m_Operation
End SyncLock
End Get
Set(ByVal value As Func(Of Double, Double))
SyncLock m_SyncRoot
m_Operation = value
End SyncLock
End Set
End Property
Public ReadOnly Property Value() As Double
Get
SyncLock m_SyncRoot
Return m_Value
End SyncLock
End Get
End Property
Protected Overridable Sub Dispose(ByVal disposing As Boolean)
m_Disposed = True
End Sub
Public Sub Dispose() Implements IDisposable.Dispose
Dispose(True)
GC.SuppressFinalize(Me)
End Sub
End Class</lang>
Output: 0.000241446762282308
zkl
Uses cheese ball thread safety: since the integrator runs continuously and I don't want to queue the output, just sample it, strong references are used as they change atomically. <lang zkl>class Integrator{
// continuously integrate a function `K`, at each `interval` seconds'
fcn init(f,interval=1e-4){
var _interval=interval, K=Ref(f), S=Ref(0.0), run=True;
self.launch(); // start me as a thread
}
fcn liftoff{ // entry point for the thread
start:=Time.Clock.timef; // floating point seconds since Epoch
t0,k0,s:=0,K.value(0),S.value;
while(run){
Atomic.sleep(_interval); t1,k1:=Time.Clock.timef - start, K.value(t1); s+=(k1 + k0)*(t1 - t0)/2.0; S.set(s); t0,k0=t1,k1;
}
}
fcn sample { S.value }
fcn setF(f) { K.set(f) }
}</lang> <lang zkl>ai:=Integrator(fcn(t){ ((0.0).pi*t).sin() }); Atomic.sleep(2); ai.sample().println();
ai.setF(fcn{ 0 }); Atomic.sleep(0.5); ai.sample().println();</lang>
- Output:
4.35857e-09 1.11571e-07
- Programming Tasks
- Concurrency
- Object oriented
- VBScript/Omit
- Ada
- BBC BASIC
- C
- Pthread
- C sharp
- C++
- Clojure
- D
- E
- EchoLisp
- Erlang
- Factor
- FBSL
- F Sharp
- Go
- Haskell
- J
- Java
- JavaScript
- Julia
- Kotlin
- Lingo
- Mathematica
- OoRexx
- OxygenBasic
- Oz
- Perl
- Perl 6
- PicoLisp
- PureBasic
- Python
- Racket
- Rust
- Scala
- Smalltalk
- SuperCollider
- Swift
- Tcl
- TclOO
- Visual Basic .NET
- Zkl
- ACL2/Omit
- AWK/Omit
- Gnuplot/Omit
- GUISS/Omit
- LaTeX/Omit
- Locomotive Basic/Omit
- Make/Omit
- Metafont/Omit
- M4/Omit
- Maxima/Omit
- ML/I/Omit
- Octave/Omit
- PlainTeX/Omit
- TI-89 BASIC/Omit
- Retro/Omit
- UNIX Shell/Omit
- ZX Spectrum Basic/Omit