I have to make a random numer (1 and 2) in .lua, and change this value every 3 seconds.
I have a variable = randomMode, this randomMode have to change every 3 seconds (1 or 2)
You could try making a kind of timer that changes the value. For example the main program loop could to change the variable every 3 seconds by using time stamps.
If you cant use a good way to implement a timer, maybe just checking time stamps since last call is good enough. For example this function randomizes the number on each call to GetRandomMode if more than 3 seconds has passed:
local lastChange = os.time()
local mode = math.random(1, 2)
function GetRandomMode()
local now = os.time()
if os.difftime(now, lastChange) > 3 then
lastChange = now
mode = math.random(1, 2)
end
return mode
end
Related
Can someone advise what unit of time t_duration is in, below:
local timer = os.clock()
*insert script here*
t_duration = string.format("%.9f", os.clock() - timer)
I am getting conflicting answers elsewhere.
Have been unable to test properly myself.
The first time called os.clock() in timer will be substracted from the actual os.clock() in t_duration with a constant format of 9 digits after the floatingpoint.
In short: It will be measure the runtime of *insert script here* in seconds as a floatingpoint converted to a string with string.format()
PS: "seconds" is not a integer it will be a floatingpoint number
Example:
> print(os.clock())
1.892664
> print(string.format("%.9f", os.clock()))
1.911050000
With Lua i learned a new Datatype: HEX FLOAT
> print(string.format("%a", os.clock()))
0x1.f96638433d6c7p+0
> print(0x1.f96638433d6c7p+0)
1.974216
In my experience Matlab performs publish subscribe operations with ROS slow for some reason. I work with components as defined in an object class as shown below, where I made a test-class. Normally objects of comparable structure are used to control mobile robots.
To quantify performance tested required time for an operation and got the following results:
1x publishing a message + 1x simple subscriber callback : 3.7ms
Simply counting in a callback (per count): 2.1318e-03 ms
Creating a new message with msg1 = rosmessage(obj.publisher) adds 3.6-4.3ms per iteration
Pinging myself indicated communication latency of 0.05 ms
The times required for a simple publish + start of a subscribe callback seems oddly slow.
I want to have multiple system components as objects in my workspace such that they respond to ROS topic updates or on timer events. The pc used for testing is not a monster but should not be garbage either.
Do you also think the shown time requirements are unneccesary large? this allows barely to publish a single topic at 200hz without doing anything else. Normally I have multiple lower frequency topics (e.g.20hz) but the total consumed time becomes significant.
Do you know any practices to make the system operate quicker?
What do you think of the OOP style of making control system components in general?
classdef subpubspeedMonitor < handle
% Use: call in matlab console, after initializing ros:
%
% SPM1 = subpubspeedMonitor()
%
% This will create an object which starts a set repetitive task upon creation
% and finally destructs itself after posting results in console.
properties
node
subscriber
publisher
timestart
messagetotal
end
methods
function obj = subpubspeedMonitor()
obj.node = ros.Node('subspeedmonitor1');
obj.subscriber = ros.Subscriber(obj.node,'topic1','sensor_msgs/NavSatFix',{#obj.rosSubCallback});
obj.publisher = ros.Publisher(obj.node,'topic1','sensor_msgs/NavSatFix');
obj.timestart = tic;
obj.messagetotal = 0;
msg1 = rosmessage(obj.publisher);
% Choose to evaluate subscriber + publisher loop or just counting
if 1
send(obj.publisher,msg1);
else
countAndDisplay(obj)
end
end
%% Test method one: repetitive publishing and subscribing
function rosSubCallback(obj,~,msg_) % ~3.7 ms per loop for a simple publish+subscribe action
% Latency to self is 0.05ms on average, according to "pinging" in terminal
obj.messagetotal = obj.messagetotal+1;
if obj.messagetotal <10000
%msg1 = rosmessage(obj.publisher); % this line adds 4.3000ms per loop
msg_.Longitude = 51; % this line adds 0.25000 ms per loop
send(obj.publisher,msg_)
else
% Display some results
timepassed = toc(obj.timestart);
time_per_pubsub = timepassed/obj.messagetotal
delete(obj);
end
end
%% Test method two: simply counting
function countAndDisplay(obj) % this costs 2.1318e-03 ms(!) per loop
obj.messagetotal = obj.messagetotal+1;
if obj.messagetotal <10000
%msg1 = rosmessage(obj.publisher); %adds 3.6ms per loop
%i = 1% adds 5.7532e-03 ms per loop
%msg1 = rosmessage("std_msgs/Bool"); %adds 1.5ms per loop
countAndDisplay(obj);
else
% Display some results
timepassed = toc(obj.timestart);
time_per_count_FCN = timepassed/obj.messagetotal
delete(obj);
end
end
%% Deconstructor
function delete(obj)
delete(obj.subscriber)
delete(obj.publisher)
delete(obj.node)
end
end
end
I am using Observable.interval to schedule code execuiton at specified times:
let obs = Observable.interval(50).subscribe(()=>{
console.log(this.currentFrame+" "+new Date().getTime());
this.currentFrame++
});
This is the output. As you can see, after 6 iterations I already have a 10ms drift. How can I use Observable.interval, but also specify that it needs to recalculate next iteration based on the current drift?
0 1513972329849
1 1513972329901
2 1513972329952
3 1513972330004
4 1513972330057
5 1513972330110
Until #cartant's fix gets repulled, you could use expand and create the behavior yourself. Assuming delay will always drift forward, try the following:
function correcting_interval(interval) {
const start_time = new Date().getTime();
return Observable.of(-1)
.expand(v => Observable.of(v + 1).delay(interval - (new Date().getTime() - start_time) % interval))
.skip(1);
}
I am trying to generate a random number, every random seconds (the final purpose would be to change the color of a block from time to time, randomly).
For that, I am using the Hump library (http://vrld.github.io/hump/#hump.timer).
Here is my code at the moment, I am true beginner in LUA/Love2d coding.
It generates a number, and displays it every seconds, instead of every random seconds... (but the random seconds is also generated).
I don't really understand why it is not working.
local Timer = require "timer"
function love.load()
text="t"
number2=1
end
local f = function()
math.randomseed(os.time())
number = math.random( 2,10 )
text="in " .. number2 .. " seconds (random)... random number =" .. number
return true
end
function love.update(dt)
number2 = math.random( 2,4 )
Timer.update(number2)
Timer.addPeriodic(number2, f)
end
function love.draw()
love.graphics.print( text, 330, 300 )
end
Thanks for any help !
While I am not familiar with Hump, it seems that you can easily use the timer's add function for your purpose, as it will call the function exactly once after x seconds, allowing you to schedule the next execution with a different delay:
local timer = require("timer")
local text = ""
local function tick()
-- Generate random number
local newNumber = math.random(2, 10)
local newDelay = math.random(2, 4)
text = ("Current number: %d, next in %d seconds!"):format(newNumber, newDelay)
-- Actually schedule the next call
timer.add(newDelay, tick)
end
function love.load()
tick()
end
function love.update(dt)
timer.update(dt)
end
function love.draw()
love.graphics.print(text, 330, 300)
end
I will have to admit the title of this question sucks... I couldn't get the best description out. Let me see if I can give an example.
I have about 2700 customers with my software at one time was installed on their server. 1500 or so still do. Basically what I have going on is an Auto Diagnostics to help weed out people who have uninstalled or who have problems with the software for us to assist with. Currently we have a cURL fetching their website for our software and looking for a header return.
We have 8 different statuses that are returned
GREEN - Everything works (usually pretty quick 0.5 - 2 seconds)
RED - Software not found (usually the longest from 5 - 15 seconds)
BLUE - Software found but not activated (usually from 3 - 9 seconds)
YELLOW - Server IP mismatch (usually from 1 - 3 seconds)
ORANGE - Server IP mismatch and wrong software type (usually 5 - 10 seconds)
PURPLE - Activation key incorrect (usually within 2 seconds)
BLACK - Domain returns 404 - No longer exists (usually within a second)
UNK - Connection failed (usually due to our load balancer -- VERY rare) (never countered this yet)
Now basically what happens is a cronJob will start the process by pulling the domain and product type. It will then cURL the domain and start cycling through the status colors above.
While this is happening we have an ajax page that is returning the results so we can keep an eye on the status. The major problem is the Time Remaining is so volatile that it does not do a good estimate. Here is the current math:
# Number of accounts between NOW and when started
$completedAccounts = floor($parseData[2]*($parseData[1]/100));
# Number of seconds between NOW and when started
$completedTime = strtotime("now") - strtotime("$hour:$minute:$second");
# Avg number of seconds per account
$avgPerCompleted = $completedTime / $completedAccounts;
# Total number of remaining accounts to be scanned
$remainingAccounts = $parseData[2] - $completedAccounts;
# The total of seconds remaining for all of the remaining accounts
$remainingSeconds = $remainingAccounts * $avgPerCompleted;
$remainingTime = format_time($remainingSeconds, ":");
I could create a count on all of the green, red, blue, etc... and do an average of how long each color does, then use that for the average time, although I don't believe that would give much better results.
With the difference in times that are so varied, any suggestions would be grateful?
Thanks,
Jeff
OK, I believe I have figured it out. I had to create a class so I could calculate a single regression over a period of time.
function calc() {
$n = count($this->mDatas);
$vSumXX = $vSumXY = $vSumX = $vSumY = 0;
//var_dump($this->mDatas);
$vCnt = 0; // for time-series, start at t=0<br />
foreach ($this->mDatas AS $vOne) {
if (is_array($vOne)) { // x,y pair<br />
list($x,$y) = $vOne;
} else { // time-series<br />
$x = $vCnt; $y = $vOne;
} // fi</p>
$vSumXY += $x*$y;
$vSumXX += $x*$x;
$vSumX += $x;
$vSumY += $y;
$vCnt++;
} // rof
$vTop = ($n*$vSumXY – $vSumX*$vSumY);
$vBottom = ($n*$vSumXX – $vSumX*$vSumX);
$a = $vBottom!=0?$vTop/$vBottom:0;
$b = ($vSumY – $a*$vSumX)/$n;
//var_dump($a,$b);
return array($a,$b);
}
I take each account and start building an array, for the amount of time it takes for each one. The array then runs through this calculation so it will build a x and y time sets. Finally I then run the array through the predict function.
/** given x, return the prediction y */
function calcpredict($x) {
list($a,$b) = $this->calc();
$y = $a*$x+$b;
return $y;
}
I put static values in so you could see the results:
$eachTime = array(7,1,.5,12,11,6,3,.24,.12,.28,2,1,14,8,4,1,.15,1,12,3,8,4,5,8,.3,.2,.4,.6,4,5);
$forecastProcess = new Linear($eachTime);
$forecastTime = $forecastProcess->calcpredict(5);
This overall system gives me about a .003 difference in 10 accounts and about 2.6 difference in 2700 accounts. Next will be to calculate the Accuracy.
Thanks for trying guys and gals