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  • Is there a way to formerly define a time interval for configuring a process?

    - by gshauger
    Horrible worded question...I know. I'm working on an application that processes data for the previous day. The problem is that I know the customer is going to eventually ask to it for every hour or some other arbitrary time interval. I know that languages such as Java or SQL have masks for defining dates. Well what about a way to define a time interval? Let me ask it this way. If someone asked you to create a configurable piece of software how would you allow the user to specify the time intervals?

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  • how can we count the time interval of the animation in cocos2d ?

    - by srikanth rongali
    Hi, I am doing my program in cocos2d. I am using NSDate to get the current time of the start of animation. And I know my animation takes 3 seconds. So I can get the time at completion of animation by using NSInterval and using the previous time and animation time. But, if If the animation time interval is not fixed how can I calculate the time interval of the animation and time at the completion of the animation ? I am animating a sprite. Please help how can I make it. Thank You.

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  • Mouse Wheel Scroll - How can I capture the time interval between start and stop of scrolling?

    - by Rahat
    Is there any way to capture the time interval between mouse wheel scroll start and stop? Actually I want to capture the interval between the scrolling start and stop when I very quickly scroll the mouse wheel. I have already looked at MouseWheel event but it don't fulfill my requirement. In senes that it always gives a value of Delta 120 or -120 but i want to call a function depending on the speed of the mouse scroll for example when i scroll the mouse normally i want to perform function 1 and when i scrolled the mouse very quickly i want to perform the function 2. In other words is there any way to distinguish between the mouse scroll high and normal speed. Any advice will be appreciated.

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  • SqlCE Flush Interval - Will the default setting lead to corruption?

    - by NormD
    SqlCE has a parameter set on the Connect String called Flush Interval. It is defined as: The interval time (in seconds) before all committed transactions are flushed to disk. If not specified, the default value is 10. I thought that a committed transaction, by definition, is a transaction that has been flushed to disk, specifically the database file. If a transaction is only stored in RAM then cannot the transaction be easily lost? I thought that transactions were first written to a log file and then applied to the database file itself, so perhaps this parameter could mean the time to wait until the transaction log is applied to the database file? I would have thought that this parameter should be 0.

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  • Why does mpstat show different values when I use the interval setting?

    - by Abe
    Here's the output I get when I run mpstat: $mpstat Linux 3.2.0-30-generic (my-laptop-C650) 09/17/2012 _x86_64_ (2 CPU) 05:32:01 PM CPU %usr %nice %sys %iowait %irq %soft %steal %guest %idle 05:32:01 PM all 9.16 0.08 2.69 2.00 0.00 0.04 0.00 0.00 86.02 And here's what I get when I run it with a one-second interval: $mpstat 1 05:31:51 PM CPU %usr %nice %sys %iowait %irq %soft %steal %guest %idle 05:31:52 PM all 1.52 0.00 1.01 0.00 0.00 0.00 0.00 0.00 97.47 05:31:53 PM all 2.04 0.00 1.02 0.00 0.00 0.00 0.00 0.00 96.94 05:31:54 PM all 1.50 0.00 1.50 0.00 0.00 0.00 0.00 0.00 97.00 Why does the first process show the processor as 86% idle, and the second show it as ~97% idle? I've tried this in a bunch of different configurations, and it's not a real difference in CPU usage -- unless mpstat itself is making the difference. Which number should I trust?

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  • Apache+FastCGI Timeout Error: "has failed to remain running for 30 seconds given 3 attempts, its restart interval has been backed off to 600 seconds"

    - by Sadjad Fouladi
    I've recently installed mod_fastcgi and Apache 2.2. I have a simple cgi script as below (test.fcgi): #!/bin/sh echo sadjad But when I invoke 'mysite.com/test.fcgi' I see "Internal Server Error" after a short period of time. The error.log file shows this error message: [Tue Jan 31 22:23:57 2006] [warn] FastCGI: (dynamic) server "~/public_html/oaduluth/dispatch.fcgi" has failed to remain running for 30 seconds given 3 attempts, its restart interval has been backed off to 600 seconds This is my .htaccess file: AddHandler fastcgi-script .fcgi RewriteEngine On RewriteCond %{REQUEST_FILENAME} !-f RewriteRule ^(.*)$ django.fcgi/$1 [QSA,L] What could the problem be? Is it my .htaccess file?

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  • Why my Ldirectord check multiple times on read server every interval?

    - by garconcn
    I have a Ldirectord server and two real servers. My ldirectord used to check the request page on real server once in every interval, but now I found that it check four times. I have monitored the log on both real servers, they have the same problem. Here is my ldirectord configuration: checktimeout=10 checkinterval=5 autoreload=yes logfile="/var/log/ldirectord.log" quiescent=no virtual=192.168.1.100:80 fallback=127.0.0.1:80 real=192.168.1.10:80 gate real=192.168.1.20:80 gate service=http request="lb.html" receive="still alive" scheduler=sh persistent=60 protocol=tcp checktype=negotiate Ldirectord will connect to each real server once every 5 seconds (checkinterval) and request 192.168.0.10:80/test.html (real/request). The access log in real server: 192.168.1.100 - - [13/Jun/2012:10:36:44 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:44 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:44 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:44 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:49 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:49 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:49 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:49 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:54 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:54 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:54 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805" 192.168.1.100 - - [13/Jun/2012:10:36:54 -0700] "GET /lb.html HTTP/1.1" 200 12 "-" "libwww-perl/5.805"

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  • Under what conditions will sendmail try to immediately resend a message instead of waiting for the standard requeue interval?

    - by Mike B
    CentOS 5.8 | Sendmail 8.14.4 I used to think that if SendMail experienced a temporary (400-class) error during delivery, it would place the message in a deferred queue (e.g. /var/spool/mqueue) and retry an hour later. For the most part, that appears to be the case. But every now and then, I'll notice log entries like this (email/domains renamed to protect the innocent :-) ) : Dec 5 01:43:03 foobox-out sendmail [11078]: qBE3l7js123022: to=<[email protected]>, delay=00:00:00, xdelay=00:00:00, mailer=relay, pri=124588, relay=exbox.foo.com. [10.10.10.10], dsn=4.0.0, stat=Deferred: 421 4.3.2 The maximum number of concurrent connections has exceeded a limit, closing transmission channel Dec 5 01:53:34 foobox-out sendmail [12763]: qBE3l7js123022: to=<[email protected]>, delay=00:10:31, xdelay=00:00:00, mailer=relay, pri=214588, relay=exbox.foo.com., dsn=4.0.0, stat=Deferred: 452 4.3.1 Insufficient system resources Dec 5 02:53:35 foobox-out sendmail [23255]: qBE3l7js123022: to=<[email protected]>, delay=01:10:32, xdelay=00:00:01, mailer=relay, pri=304588, relay=exbox.foo.com. [10.10.10.10], dsn=2.0.0, stat=Sent (<[email protected]> Queued mail for delivery) Why did Sendmail try again just 10 minutes after the first attempt and then wait another hour before trying again? If this is expected behavior, what scenarios will cause this faster requeue interval to occur?

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  • jQuery CSS Property Monitoring Plug-in updated

    - by Rick Strahl
    A few weeks back I had talked about the need to watch properties of an object and be able to take action when certain values changed. The need for this arose out of wanting to build generic components that could 'attach' themselves to other objects. One example is a drop shadow - if I add a shadow behavior to an object I want the shadow to be pinned to that object so when that object moves I also want the shadow to move with it, or when the panel is hidden the shadow should hide with it - automatically without having to explicitly hook up monitoring code to the panel. For example, in my shadow plug-in I can now do something like this (where el is the element that has the shadow attached and sh is the shadow): if (!exists) // if shadow was created el.watch("left,top,width,height,display", function() { if (el.is(":visible")) $(this).shadow(opt); // redraw else sh.hide(); }, 100, "_shadowMove"); The code now monitors several properties and if any of them change the provided function is called. So when the target object is moved or hidden or resized the watcher function is called and the shadow can be redrawn or hidden in the case of visibility going away. So if you run any of the following code: $("#box") .shadow() .draggable({ handle: ".blockheader" }); // drag around the box - shadow should follow // hide the box - shadow should disappear with box setTimeout(function() { $("#box").hide(); }, 4000); // show the box - shadow should come back too setTimeout(function() { $("#box").show(); }, 8000); This can be very handy functionality when you're dealing with objects or operations that you need to track generically and there are no native events for them. For example, with a generic shadow object that attaches itself to any another element there's no way that I know of to track whether the object has been moved or hidden either via some UI operation (like dragging) or via code. While some UI operations like jQuery.ui.draggable would allow events to fire when the mouse is moved nothing of the sort exists if you modify locations in code. Even tracking the object in drag mode this is hardly generic behavior - a generic shadow implementation can't know when dragging is hooked up. So the watcher provides an alternative that basically gives an Observer like pattern that notifies you when something you're interested in changes. In the watcher hookup code (in the shadow() plugin) above  a check is made if the object is visible and if it is the shadow is redrawn. Otherwise the shadow is hidden. The first parameter is a list of CSS properties to be monitored followed by the function that is called. The function called receives this as the element that's been changed and receives two parameters: The array of watched objects with their current values, plus an index to the object that caused the change function to fire. How does it work When I wrote it about this last time I started out with a simple timer that would poll for changes at a fixed interval with setInterval(). A few folks commented that there are is a DOM API - DOMAttrmodified in Mozilla and propertychange in IE that allow notification whenever any property changes which is much more efficient and smooth than the setInterval approach I used previously. On browser that support these events (FireFox and IE basically - WebKit has the DOMAttrModified event but it doesn't appear to work) the shadow effect is instant - no 'drag behind' of the shadow. Running on a browser that doesn't support still uses setInterval() and the shadow movement is slightly delayed which looks sloppy. There are a few additional changes to this code - it also supports monitoring multiple CSS properties now so a single object can monitor a host of CSS properties rather than one object per property which is easier to work with. For display purposes position, bounds and visibility will be common properties that are to be watched. Here's what the new version looks like: $.fn.watch = function (props, func, interval, id) { /// <summary> /// Allows you to monitor changes in a specific /// CSS property of an element by polling the value. /// when the value changes a function is called. /// The function called is called in the context /// of the selected element (ie. this) /// </summary> /// <param name="prop" type="String">CSS Properties to watch sep. by commas</param> /// <param name="func" type="Function"> /// Function called when the value has changed. /// </param> /// <param name="interval" type="Number"> /// Optional interval for browsers that don't support DOMAttrModified or propertychange events. /// Determines the interval used for setInterval calls. /// </param> /// <param name="id" type="String">A unique ID that identifies this watch instance on this element</param> /// <returns type="jQuery" /> if (!interval) interval = 200; if (!id) id = "_watcher"; return this.each(function () { var _t = this; var el$ = $(this); var fnc = function () { __watcher.call(_t, id) }; var itId = null; var data = { id: id, props: props.split(","), func: func, vals: [props.split(",").length], fnc: fnc, origProps: props, interval: interval }; $.each(data.props, function (i) { data.vals[i] = el$.css(data.props[i]); }); el$.data(id, data); hookChange(el$, id, data.fnc); }); function hookChange(el$, id, fnc) { el$.each(function () { var el = $(this); if (typeof (el.get(0).onpropertychange) == "object") el.bind("propertychange." + id, fnc); else if ($.browser.mozilla) el.bind("DOMAttrModified." + id, fnc); else itId = setInterval(fnc, interval); }); } function __watcher(id) { var el$ = $(this); var w = el$.data(id); if (!w) return; var _t = this; if (!w.func) return; // must unbind or else unwanted recursion may occur el$.unwatch(id); var changed = false; var i = 0; for (i; i < w.props.length; i++) { var newVal = el$.css(w.props[i]); if (w.vals[i] != newVal) { w.vals[i] = newVal; changed = true; break; } } if (changed) w.func.call(_t, w, i); // rebind event hookChange(el$, id, w.fnc); } } $.fn.unwatch = function (id) { this.each(function () { var el = $(this); var fnc = el.data(id).fnc; try { if (typeof (this.onpropertychange) == "object") el.unbind("propertychange." + id, fnc); else if ($.browser.mozilla) el.unbind("DOMAttrModified." + id, fnc); else clearInterval(id); } // ignore if element was already unbound catch (e) { } }); return this; } There are basically two jQuery functions - watch and unwatch. jQuery.fn.watch(props,func,interval,id) Starts watching an element for changes in the properties specified. props The CSS properties that are to be watched for changes. If any of the specified properties changes the function specified in the second parameter is fired. func (watchData,index) The function fired in response to a changed property. Receives this as the element changed and object that represents the watched properties and their respective values. The first parameter is passed in this structure:    { id: itId, props: [], func: func, vals: [] }; A second parameter is the index of the changed property so data.props[i] or data.vals[i] gets the property value that has changed. interval The interval for setInterval() for those browsers that don't support property watching in the DOM. In milliseconds. id An optional id that identifies this watcher. Required only if multiple watchers might be hooked up to the same element. The default is _watcher if not specified. jQuery.fn.unwatch(id) Unhooks watching of the element by disconnecting the event handlers. id Optional watcher id that was specified in the call to watch. This value can be omitted to use the default value of _watcher. You can also grab the latest version of the  code for this plug-in as well as the shadow in the full library at: http://www.west-wind.com:8080/svn/jquery/trunk/jQueryControls/Resources/ww.jquery.js watcher has no other dependencies although it lives in this larger library. The shadow plug-in depends on watcher.© Rick Strahl, West Wind Technologies, 2005-2011

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  • How to stop the targets generated by schedule:@selector(target:) interval:timeInterval ?

    - by srikanth rongali
    I am using [self schedule:@selector(target:) interval:timeInterval]; for generating bullets in shooting game in cocos2d. In target: I called method targetGenerate to generate for bullet. The enemy generates these bullets. After the player won or enemy won the game the bullets should stop. But, I could not make them stop. I used flags for this. But they did either work. If I set flag1 = 1; for game won. I am using [self schedule:@selector(update:)]; for updating the bullet position to know it hits the player or not ? And I tried like this -(id)init { if( (self = [super init]) ) { //code for enemy [self schedule:@selector(target:) interval:timeInterval]; [self schedule:@selector(update:)]; }return self; } -(void)target:(ccTime)dt { if(flag != 1) [self targetGenerate]; } -(void)targetGenerate { //code for the bullet to generate; CCSprite *bullet = … } -(void)update:(ccTime)dt { //code for to know intersection of bullet and player } But it was not working. How can I make the bullets to disappear after player won the game or enemy won the game ? Thank you.

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  • Python Turtle Graphics, how to plot functions over an interval?

    - by TheDragonAce
    I need to plot a function over a specified interval. The function is f1, which is shown below in the code, and the interval is [-7, -3]; [-1, 1]; [3, 7] with a step of .01. When I execute the program, nothing is drawn. Any ideas? import turtle from math import sqrt wn = turtle.Screen() wn.bgcolor("white") wn.title("Plotting") mypen = turtle.Turtle() mypen.shape("classic") mypen.color("black") mypen.speed(10) while True: try: def f1(x): return 2 * sqrt((-abs(abs(x)-1)) * abs(3 - abs(x))/((abs(x)-1)*(3-abs(x)))) * \ (1 + abs(abs(x)-3)/(abs(x)-3))*sqrt(1-(x/7)**2)+(5+0.97*(abs(x-0.5)+abs(x+0.5))-\ 3*(abs(x-0.75)+abs(x+0.75)))*(1+abs(1-abs(x))/(1-abs(x))) mypen.penup() step=.01 startf11=-7 stopf11=-3 startf12=-1 stopf12=1 startf13=3 stopf13=7 def f11 (startf11,stopf11,step): rc=[] y = f1(startf11) while y<=stopf11: rc.append(startf11) #y+=step mypen.setpos(f1(startf11)*25,y*25) mypen.dot() def f12 (startf12,stopf12,step): rc=[] y = f1(startf12) while y<=stopf12: rc.append(startf12) #y+=step mypen.setpos(f1(startf12)*25, y*25) mypen.dot() def f13 (startf13,stopf13,step): rc=[] y = f1(startf13) while y<=stopf13: rc.append(startf13) #y+=step mypen.setpos(f1(startf13)*25, y*25) mypen.dot() f11(startf11,stopf11,step) f12(startf12,stopf12,step) f13(startf13,stopf13,step) except ZeroDivisionError: continue

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  • Framework 4 Features: Support for Timed Jobs

    - by Anthony Shorten
    One of the new features of the Oracle Utilities Application Framework V4 is the ability for the batch framework to support Timed Batch. Traditionally batch is associated with set processing in the background in a fixed time frame. For example, billing customers. Over the last few versions their has been functionality required by the products required a more monitoring style batch process. The monitor is a batch process that looks for specific business events based upon record status or other pieces of data. For example, the framework contains a fact monitor (F1-FCTRN) that can be configured to look for specific status's or other conditions. The batch process then uses the instructions on the object to determine what to do. To support monitor style processing, you need to run the process regularly a number of times a day (for example, every ten minutes). Traditional batch could support this but it was not as optimal as expected (if you are a site using the old Workflow subsystem, you understand what I mean). The Batch framework was extended to add additional facilities to support times (and continuous batch which is another new feature for another blog entry). The new facilities include: The batch control now defines the job as Timed or Not Timed. Non-Timed batch are traditional batch jobs. The timer interval (the interval between executions) can be specified The timer can be made active or inactive. Only active timers are executed. Setting the Timer Active to inactive will stop the job at the next time interval. Setting the Timer Active to Active will start the execution of the timed job. You can specify the credentials, language to view the messages and an email address to send the a summary of the execution to. The email address is optional and requires an email server to be specified in the relevant feature configuration. You can specify the thread limits and commit intervals to be sued for the multiple executions. Once a timer job is defined it will be executed automatically by the Business Application Server process if the DEFAULT threadpool is active. This threadpool can be started using the online batch daemon (for non-production) or externally using the threadpoolworker utility. At that time any batch process with the Timer Active set to Active and Batch Control Type of Timed will begin executing. As Timed jobs are executed automatically then they do not appear in any external schedule or are managed by an external scheduler (except via the DEFAULT threadpool itself of course). Now, if the job has no work to do as the timer interval is being reached then that instance of the job is stopped and the next instance started at the timer interval. If there is still work to complete when the interval interval is reached, the instance will continue processing till the work is complete, then the instance will be stopped and the next instance scheduled for the next timer interval. One of the key ways of optimizing this processing is to set the timer interval correctly for the expected workload. This is an interesting new feature of the batch framework and we anticipate it will come in handy for specific business situations with the monitor processes.

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  • Taming Hopping Windows

    - by Roman Schindlauer
    At first glance, hopping windows seem fairly innocuous and obvious. They organize events into windows with a simple periodic definition: the windows have some duration d (e.g. a window covers 5 second time intervals), an interval or period p (e.g. a new window starts every 2 seconds) and an alignment a (e.g. one of those windows starts at 12:00 PM on March 15, 2012 UTC). var wins = xs     .HoppingWindow(TimeSpan.FromSeconds(5),                    TimeSpan.FromSeconds(2),                    new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc)); Logically, there is a window with start time a + np and end time a + np + d for every integer n. That’s a lot of windows. So why doesn’t the following query (always) blow up? var query = wins.Select(win => win.Count()); A few users have asked why StreamInsight doesn’t produce output for empty windows. Primarily it’s because there is an infinite number of empty windows! (Actually, StreamInsight uses DateTimeOffset.MaxValue to approximate “the end of time” and DateTimeOffset.MinValue to approximate “the beginning of time”, so the number of windows is lower in practice.) That was the good news. Now the bad news. Events also have duration. Consider the following simple input: var xs = this.Application                 .DefineEnumerable(() => new[]                     { EdgeEvent.CreateStart(DateTimeOffset.UtcNow, 0) })                 .ToStreamable(AdvanceTimeSettings.IncreasingStartTime); Because the event has no explicit end edge, it lasts until the end of time. So there are lots of non-empty windows if we apply a hopping window to that single event! For this reason, we need to be careful with hopping window queries in StreamInsight. Or we can switch to a custom implementation of hopping windows that doesn’t suffer from this shortcoming. The alternate window implementation produces output only when the input changes. We start by breaking up the timeline into non-overlapping intervals assigned to each window. In figure 1, six hopping windows (“Windows”) are assigned to six intervals (“Assignments”) in the timeline. Next we take input events (“Events”) and alter their lifetimes (“Altered Events”) so that they cover the intervals of the windows they intersect. In figure 1, you can see that the first event e1 intersects windows w1 and w2 so it is adjusted to cover assignments a1 and a2. Finally, we can use snapshot windows (“Snapshots”) to produce output for the hopping windows. Notice however that instead of having six windows generating output, we have only four. The first and second snapshots correspond to the first and second hopping windows. The remaining snapshots however cover two hopping windows each! While in this example we saved only two events, the savings can be more significant when the ratio of event duration to window duration is higher. Figure 1: Timeline The implementation of this strategy is straightforward. We need to set the start times of events to the start time of the interval assigned to the earliest window including the start time. Similarly, we need to modify the end times of events to the end time of the interval assigned to the latest window including the end time. The following snap-to-boundary function that rounds a timestamp value t down to the nearest value t' <= t such that t' is a + np for some integer n will be useful. For convenience, we will represent both DateTime and TimeSpan values using long ticks: static long SnapToBoundary(long t, long a, long p) {     return t - ((t - a) % p) - (t > a ? 0L : p); } How do we find the earliest window including the start time for an event? It’s the window following the last window that does not include the start time assuming that there are no gaps in the windows (i.e. duration < interval), and limitation of this solution. To find the end time of that antecedent window, we need to know the alignment of window ends: long e = a + (d % p); Using the window end alignment, we are finally ready to describe the start time selector: static long AdjustStartTime(long t, long e, long p) {     return SnapToBoundary(t, e, p) + p; } To find the latest window including the end time for an event, we look for the last window start time (non-inclusive): public static long AdjustEndTime(long t, long a, long d, long p) {     return SnapToBoundary(t - 1, a, p) + p + d; } Bringing it together, we can define the translation from events to ‘altered events’ as in Figure 1: public static IQStreamable<T> SnapToWindowIntervals<T>(IQStreamable<T> source, TimeSpan duration, TimeSpan interval, DateTime alignment) {     if (source == null) throw new ArgumentNullException("source");     // reason about DateTime and TimeSpan in ticks     long d = Math.Min(DateTime.MaxValue.Ticks, duration.Ticks);     long p = Math.Min(DateTime.MaxValue.Ticks, Math.Abs(interval.Ticks));     // set alignment to earliest possible window     var a = alignment.ToUniversalTime().Ticks % p;     // verify constraints of this solution     if (d <= 0L) { throw new ArgumentOutOfRangeException("duration"); }     if (p == 0L || p > d) { throw new ArgumentOutOfRangeException("interval"); }     // find the alignment of window ends     long e = a + (d % p);     return source.AlterEventLifetime(         evt => ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p)),         evt => ToDateTime(AdjustEndTime(evt.EndTime.ToUniversalTime().Ticks, a, d, p)) -             ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p))); } public static DateTime ToDateTime(long ticks) {     // just snap to min or max value rather than under/overflowing     return ticks < DateTime.MinValue.Ticks         ? new DateTime(DateTime.MinValue.Ticks, DateTimeKind.Utc)         : ticks > DateTime.MaxValue.Ticks         ? new DateTime(DateTime.MaxValue.Ticks, DateTimeKind.Utc)         : new DateTime(ticks, DateTimeKind.Utc); } Finally, we can describe our custom hopping window operator: public static IQWindowedStreamable<T> HoppingWindow2<T>(     IQStreamable<T> source,     TimeSpan duration,     TimeSpan interval,     DateTime alignment) {     if (source == null) { throw new ArgumentNullException("source"); }     return SnapToWindowIntervals(source, duration, interval, alignment).SnapshotWindow(); } By switching from HoppingWindow to HoppingWindow2 in the following example, the query returns quickly rather than gobbling resources and ultimately failing! public void Main() {     var start = new DateTimeOffset(new DateTime(2012, 6, 28), TimeSpan.Zero);     var duration = TimeSpan.FromSeconds(5);     var interval = TimeSpan.FromSeconds(2);     var alignment = new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc);     var events = this.Application.DefineEnumerable(() => new[]     {         EdgeEvent.CreateStart(start.AddSeconds(0), "e0"),         EdgeEvent.CreateStart(start.AddSeconds(1), "e1"),         EdgeEvent.CreateEnd(start.AddSeconds(1), start.AddSeconds(2), "e1"),         EdgeEvent.CreateStart(start.AddSeconds(3), "e2"),         EdgeEvent.CreateStart(start.AddSeconds(9), "e3"),         EdgeEvent.CreateEnd(start.AddSeconds(3), start.AddSeconds(10), "e2"),         EdgeEvent.CreateEnd(start.AddSeconds(9), start.AddSeconds(10), "e3"),     }).ToStreamable(AdvanceTimeSettings.IncreasingStartTime);     var adjustedEvents = SnapToWindowIntervals(events, duration, interval, alignment);     var query = from win in HoppingWindow2(events, duration, interval, alignment)                 select win.Count();     DisplayResults(adjustedEvents, "Adjusted Events");     DisplayResults(query, "Query"); } As you can see, instead of producing a massive number of windows for the open start edge e0, a single window is emitted from 12:00:15 AM until the end of time: Adjusted Events StartTime EndTime Payload 6/28/2012 12:00:01 AM 12/31/9999 11:59:59 PM e0 6/28/2012 12:00:03 AM 6/28/2012 12:00:07 AM e1 6/28/2012 12:00:05 AM 6/28/2012 12:00:15 AM e2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM e3 Query StartTime EndTime Payload 6/28/2012 12:00:01 AM 6/28/2012 12:00:03 AM 1 6/28/2012 12:00:03 AM 6/28/2012 12:00:05 AM 2 6/28/2012 12:00:05 AM 6/28/2012 12:00:07 AM 3 6/28/2012 12:00:07 AM 6/28/2012 12:00:11 AM 2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM 3 6/28/2012 12:00:15 AM 12/31/9999 11:59:59 PM 1 Regards, The StreamInsight Team

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  • Taming Hopping Windows

    - by Roman Schindlauer
    At first glance, hopping windows seem fairly innocuous and obvious. They organize events into windows with a simple periodic definition: the windows have some duration d (e.g. a window covers 5 second time intervals), an interval or period p (e.g. a new window starts every 2 seconds) and an alignment a (e.g. one of those windows starts at 12:00 PM on March 15, 2012 UTC). var wins = xs     .HoppingWindow(TimeSpan.FromSeconds(5),                    TimeSpan.FromSeconds(2),                    new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc)); Logically, there is a window with start time a + np and end time a + np + d for every integer n. That’s a lot of windows. So why doesn’t the following query (always) blow up? var query = wins.Select(win => win.Count()); A few users have asked why StreamInsight doesn’t produce output for empty windows. Primarily it’s because there is an infinite number of empty windows! (Actually, StreamInsight uses DateTimeOffset.MaxValue to approximate “the end of time” and DateTimeOffset.MinValue to approximate “the beginning of time”, so the number of windows is lower in practice.) That was the good news. Now the bad news. Events also have duration. Consider the following simple input: var xs = this.Application                 .DefineEnumerable(() => new[]                     { EdgeEvent.CreateStart(DateTimeOffset.UtcNow, 0) })                 .ToStreamable(AdvanceTimeSettings.IncreasingStartTime); Because the event has no explicit end edge, it lasts until the end of time. So there are lots of non-empty windows if we apply a hopping window to that single event! For this reason, we need to be careful with hopping window queries in StreamInsight. Or we can switch to a custom implementation of hopping windows that doesn’t suffer from this shortcoming. The alternate window implementation produces output only when the input changes. We start by breaking up the timeline into non-overlapping intervals assigned to each window. In figure 1, six hopping windows (“Windows”) are assigned to six intervals (“Assignments”) in the timeline. Next we take input events (“Events”) and alter their lifetimes (“Altered Events”) so that they cover the intervals of the windows they intersect. In figure 1, you can see that the first event e1 intersects windows w1 and w2 so it is adjusted to cover assignments a1 and a2. Finally, we can use snapshot windows (“Snapshots”) to produce output for the hopping windows. Notice however that instead of having six windows generating output, we have only four. The first and second snapshots correspond to the first and second hopping windows. The remaining snapshots however cover two hopping windows each! While in this example we saved only two events, the savings can be more significant when the ratio of event duration to window duration is higher. Figure 1: Timeline The implementation of this strategy is straightforward. We need to set the start times of events to the start time of the interval assigned to the earliest window including the start time. Similarly, we need to modify the end times of events to the end time of the interval assigned to the latest window including the end time. The following snap-to-boundary function that rounds a timestamp value t down to the nearest value t' <= t such that t' is a + np for some integer n will be useful. For convenience, we will represent both DateTime and TimeSpan values using long ticks: static long SnapToBoundary(long t, long a, long p) {     return t - ((t - a) % p) - (t > a ? 0L : p); } How do we find the earliest window including the start time for an event? It’s the window following the last window that does not include the start time assuming that there are no gaps in the windows (i.e. duration < interval), and limitation of this solution. To find the end time of that antecedent window, we need to know the alignment of window ends: long e = a + (d % p); Using the window end alignment, we are finally ready to describe the start time selector: static long AdjustStartTime(long t, long e, long p) {     return SnapToBoundary(t, e, p) + p; } To find the latest window including the end time for an event, we look for the last window start time (non-inclusive): public static long AdjustEndTime(long t, long a, long d, long p) {     return SnapToBoundary(t - 1, a, p) + p + d; } Bringing it together, we can define the translation from events to ‘altered events’ as in Figure 1: public static IQStreamable<T> SnapToWindowIntervals<T>(IQStreamable<T> source, TimeSpan duration, TimeSpan interval, DateTime alignment) {     if (source == null) throw new ArgumentNullException("source");     // reason about DateTime and TimeSpan in ticks     long d = Math.Min(DateTime.MaxValue.Ticks, duration.Ticks);     long p = Math.Min(DateTime.MaxValue.Ticks, Math.Abs(interval.Ticks));     // set alignment to earliest possible window     var a = alignment.ToUniversalTime().Ticks % p;     // verify constraints of this solution     if (d <= 0L) { throw new ArgumentOutOfRangeException("duration"); }     if (p == 0L || p > d) { throw new ArgumentOutOfRangeException("interval"); }     // find the alignment of window ends     long e = a + (d % p);     return source.AlterEventLifetime(         evt => ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p)),         evt => ToDateTime(AdjustEndTime(evt.EndTime.ToUniversalTime().Ticks, a, d, p)) -             ToDateTime(AdjustStartTime(evt.StartTime.ToUniversalTime().Ticks, e, p))); } public static DateTime ToDateTime(long ticks) {     // just snap to min or max value rather than under/overflowing     return ticks < DateTime.MinValue.Ticks         ? new DateTime(DateTime.MinValue.Ticks, DateTimeKind.Utc)         : ticks > DateTime.MaxValue.Ticks         ? new DateTime(DateTime.MaxValue.Ticks, DateTimeKind.Utc)         : new DateTime(ticks, DateTimeKind.Utc); } Finally, we can describe our custom hopping window operator: public static IQWindowedStreamable<T> HoppingWindow2<T>(     IQStreamable<T> source,     TimeSpan duration,     TimeSpan interval,     DateTime alignment) {     if (source == null) { throw new ArgumentNullException("source"); }     return SnapToWindowIntervals(source, duration, interval, alignment).SnapshotWindow(); } By switching from HoppingWindow to HoppingWindow2 in the following example, the query returns quickly rather than gobbling resources and ultimately failing! public void Main() {     var start = new DateTimeOffset(new DateTime(2012, 6, 28), TimeSpan.Zero);     var duration = TimeSpan.FromSeconds(5);     var interval = TimeSpan.FromSeconds(2);     var alignment = new DateTime(2012, 3, 15, 12, 0, 0, DateTimeKind.Utc);     var events = this.Application.DefineEnumerable(() => new[]     {         EdgeEvent.CreateStart(start.AddSeconds(0), "e0"),         EdgeEvent.CreateStart(start.AddSeconds(1), "e1"),         EdgeEvent.CreateEnd(start.AddSeconds(1), start.AddSeconds(2), "e1"),         EdgeEvent.CreateStart(start.AddSeconds(3), "e2"),         EdgeEvent.CreateStart(start.AddSeconds(9), "e3"),         EdgeEvent.CreateEnd(start.AddSeconds(3), start.AddSeconds(10), "e2"),         EdgeEvent.CreateEnd(start.AddSeconds(9), start.AddSeconds(10), "e3"),     }).ToStreamable(AdvanceTimeSettings.IncreasingStartTime);     var adjustedEvents = SnapToWindowIntervals(events, duration, interval, alignment);     var query = from win in HoppingWindow2(events, duration, interval, alignment)                 select win.Count();     DisplayResults(adjustedEvents, "Adjusted Events");     DisplayResults(query, "Query"); } As you can see, instead of producing a massive number of windows for the open start edge e0, a single window is emitted from 12:00:15 AM until the end of time: Adjusted Events StartTime EndTime Payload 6/28/2012 12:00:01 AM 12/31/9999 11:59:59 PM e0 6/28/2012 12:00:03 AM 6/28/2012 12:00:07 AM e1 6/28/2012 12:00:05 AM 6/28/2012 12:00:15 AM e2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM e3 Query StartTime EndTime Payload 6/28/2012 12:00:01 AM 6/28/2012 12:00:03 AM 1 6/28/2012 12:00:03 AM 6/28/2012 12:00:05 AM 2 6/28/2012 12:00:05 AM 6/28/2012 12:00:07 AM 3 6/28/2012 12:00:07 AM 6/28/2012 12:00:11 AM 2 6/28/2012 12:00:11 AM 6/28/2012 12:00:15 AM 3 6/28/2012 12:00:15 AM 12/31/9999 11:59:59 PM 1 Regards, The StreamInsight Team

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  • Partitioning Strategies for P6 Reporting Database

    - by Jeffrey McDaniel
    Prior to P6 Reporting Database version 3.2 sp1 range partitioning was used. This was applied only to the history tables. The ranges were defined during installation and additional ranges would need to be added once your date range entered the final defined range. As of P6 Reporting Database version 3.2 sp1, interval partitioning was implemented. Interval partitioning was applied to the existing History table as well as Slowly Changing Dimension tables. One of the major advantages of interval partitioning is there is no more manual addition of ranges. The interval partitioning will automatically create partitions for the defined interval when data is inserted into the table and it exceeds the existing partitions. In 3.2 sp1 there are steps on how to update your partitioning. For all versions after 3.2 sp1 interval partitioning is the only partitioning option used. When upgrading it is important to be aware of these changes. Here is a link with more information on partitioning -the types and the advantages. http://docs.oracle.com/cd/E11882_01/server.112/e25523/partition.htm

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  • How do I generate a random time interval and add it to a mysql datetime using php?

    - by KeenLearner
    I have many rows in mysql table with datetime's in the format of: 2008-12-08 04:16:51 etc I'd like to generate a random time interval of anywhere between 30 seconds, and 3 days and add them to the time above. a) how do I generate a random time between 30 and 3 days? b) how do I add this time to the date time format above? I imagine i need to do a loop to pull out all the info, do the math in php, and then update the row... Any ideas?

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  • how to stop a javascript loop for a particular interval of time?

    - by Harish
    i am using javascript for loop, to loop through a particular array and alert it's value. I want that after every alert it should stop for 30 seconds and then continue...till the end of loop. my code goes here.. for(var i=0; i<valArray.lenght; i++) { alert("The value ="+valArray[i]); //stop for 30seconds.. } i have used setTimeout() function, but it is not working...as loop end iterating but do not pause for 30seconds interval... is there any other way such as sleep function in PHP??

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  • A jQuery Plug-in to monitor Html Element CSS Changes

    - by Rick Strahl
    Here's a scenario I've run into on a few occasions: I need to be able to monitor certain CSS properties on an HTML element and know when that CSS element changes. The need for this arose out of wanting to build generic components that could 'attach' themselves to other objects and monitor changes on the ‘parent’ object so the dependent object can adjust itself accordingly. What I wanted to create is a jQuery plug-in that allows me to specify a list of CSS properties to monitor and have a function fire in response to any change to any of those CSS properties. The result are the .watch() and .unwatch() jQuery plug-ins. Here’s a simple example page of this plug-in that demonstrates tracking changes to an element being moved with draggable and closable behavior: http://www.west-wind.com/WestWindWebToolkit/samples/Ajax/jQueryPluginSamples/WatcherPlugin.htm Try it with different browsers – IE and FireFox use the DOM event handlers and Chrome, Safari and Opera use setInterval handlers to manage this behavior. It should work in all of them but all but IE and FireFox will show a bit of lag between the changes in the main element and the shadow. The relevant HTML for this example is this fragment of a main <div> (#notebox) and an element that is to mimic a shadow (#shadow). <div class="containercontent"> <div id="notebox" style="width: 200px; height: 150px;position: absolute; z-index: 20; padding: 20px; background-color: lightsteelblue;"> Go ahead drag me around and close me! </div> <div id="shadow" style="background-color: Gray; z-index: 19;position:absolute;display: none;"> </div> </div> The watcher plug in is then applied to the main <div> and shadow in sync with the following plug-in code: <script type="text/javascript"> $(document).ready(function () { var counter = 0; $("#notebox").watch("top,left,height,width,display,opacity", function (data, i) { var el = $(this); var sh = $("#shadow"); var propChanged = data.props[i]; var valChanged = data.vals[i]; counter++; showStatus("Prop: " + propChanged + " value: " + valChanged + " " + counter); var pos = el.position(); var w = el.outerWidth(); var h = el.outerHeight(); sh.css({ width: w, height: h, left: pos.left + 5, top: pos.top + 5, display: el.css("display"), opacity: el.css("opacity") }); }) .draggable() .closable() .css("left", 10); }); </script> When you run this page as you drag the #notebox element the #shadow element will maintain and stay pinned underneath the #notebox element effectively keeping the shadow attached to the main element. Likewise, if you hide or fadeOut() the #notebox element the shadow will also go away – show the #notebox element and the shadow also re-appears because we are assigning the display property from the parent on the shadow. Note we’re attaching the .watch() plug-in to the #notebox element and have it fire whenever top,left,height,width,opacity or display CSS properties are changed. The passed data element contains a props[] and vals[] array that holds the properties monitored and their current values. An index passed as the second parm tells you which property has changed and what its current value is (propChanged/valChanged in the code above). The rest of the watcher handler code then deals with figuring out the main element’s position and recalculating and setting the shadow’s position using the jQuery .css() function. Note that this is just an example to demonstrate the watch() behavior here – this is not the best way to create a shadow. If you’re interested in a more efficient and cleaner way to handle shadows with a plug-in check out the .shadow() plug-in in ww.jquery.js (code search for fn.shadow) which uses native CSS features when available but falls back to a tracked shadow element on browsers that don’t support it, which is how this watch() plug-in came about in the first place :-) How does it work? The plug-in works by letting the user specify a list of properties to monitor as a comma delimited string and a handler function: el.watch("top,left,height,width,display,opacity", function (data, i) {}, 100, id) You can also specify an interval (if no DOM event monitoring isn’t available in the browser) and an ID that identifies the event handler uniquely. The watch plug-in works by hooking up to DOMAttrModified in FireFox, to onPropertyChanged in Internet Explorer, or by using a timer with setInterval to handle the detection of changes for other browsers. Unfortunately WebKit doesn’t support DOMAttrModified consistently at the moment so Safari and Chrome currently have to use the slower setInterval mechanism. In response to a changed property (or a setInterval timer hit) a JavaScript handler is fired which then runs through all the properties monitored and determines if and which one has changed. The DOM events fire on all property/style changes so the intermediate plug-in handler filters only those hits we’re interested in. If one of our monitored properties has changed the specified event handler function is called along with a data object and an index that identifies the property that’s changed in the data.props/data.vals arrays. The jQuery plugin to implement this functionality looks like this: (function($){ $.fn.watch = function (props, func, interval, id) { /// <summary> /// Allows you to monitor changes in a specific /// CSS property of an element by polling the value. /// when the value changes a function is called. /// The function called is called in the context /// of the selected element (ie. this) /// </summary> /// <param name="prop" type="String">CSS Properties to watch sep. by commas</param> /// <param name="func" type="Function"> /// Function called when the value has changed. /// </param> /// <param name="interval" type="Number"> /// Optional interval for browsers that don't support DOMAttrModified or propertychange events. /// Determines the interval used for setInterval calls. /// </param> /// <param name="id" type="String">A unique ID that identifies this watch instance on this element</param> /// <returns type="jQuery" /> if (!interval) interval = 100; if (!id) id = "_watcher"; return this.each(function () { var _t = this; var el$ = $(this); var fnc = function () { __watcher.call(_t, id) }; var data = { id: id, props: props.split(","), vals: [props.split(",").length], func: func, fnc: fnc, origProps: props, interval: interval, intervalId: null }; // store initial props and values $.each(data.props, function (i) { data.vals[i] = el$.css(data.props[i]); }); el$.data(id, data); hookChange(el$, id, data); }); function hookChange(el$, id, data) { el$.each(function () { var el = $(this); if (typeof (el.get(0).onpropertychange) == "object") el.bind("propertychange." + id, data.fnc); else if ($.browser.mozilla) el.bind("DOMAttrModified." + id, data.fnc); else data.intervalId = setInterval(data.fnc, interval); }); } function __watcher(id) { var el$ = $(this); var w = el$.data(id); if (!w) return; var _t = this; if (!w.func) return; // must unbind or else unwanted recursion may occur el$.unwatch(id); var changed = false; var i = 0; for (i; i < w.props.length; i++) { var newVal = el$.css(w.props[i]); if (w.vals[i] != newVal) { w.vals[i] = newVal; changed = true; break; } } if (changed) w.func.call(_t, w, i); // rebind event hookChange(el$, id, w); } } $.fn.unwatch = function (id) { this.each(function () { var el = $(this); var data = el.data(id); try { if (typeof (this.onpropertychange) == "object") el.unbind("propertychange." + id, data.fnc); else if ($.browser.mozilla) el.unbind("DOMAttrModified." + id, data.fnc); else clearInterval(data.intervalId); } // ignore if element was already unbound catch (e) { } }); return this; } })(jQuery); Note that there’s a corresponding .unwatch() plug-in that can be used to stop monitoring properties. The ID parameter is optional both on watch() and unwatch() – a standard name is used if you don’t specify one, but it’s a good idea to use unique names for each element watched to avoid overlap in event ids especially if you’re monitoring many elements. The syntax is: $.fn.watch = function(props, func, interval, id) props A comma delimited list of CSS style properties that are to be watched for changes. If any of the specified properties changes the function specified in the second parameter is fired. func The function fired in response to a changed styles. Receives this as the element changed and an object parameter that represents the watched properties and their respective values. The first parameter is passed in this structure: { id: watcherId, props: [], vals: [], func: thisFunc, fnc: internalHandler, origProps: strPropertyListOnWatcher }; A second parameter is the index of the changed property so data.props[i] or data.vals[i] gets the property and changed value. interval The interval for setInterval() for those browsers that don't support property watching in the DOM. In milliseconds. id An optional id that identifies this watcher. Required only if multiple watchers might be hooked up to the same element. The default is _watcher if not specified. It’s been a Journey I started building this plug-in about two years ago and had to make many modifications to it in response to changes in jQuery and also in browser behaviors. I think the latest round of changes made should make this plug-in fairly future proof going forward (although I hope there will be better cross-browser change event notifications in the future). One of the big problems I ran into had to do with recursive change notifications – it looks like starting with jQuery 1.44 and later, jQuery internally modifies element properties on some calls to some .css()  property retrievals and things like outerHeight/Width(). In IE this would cause nasty lock up issues at times. In response to this I changed the code to unbind the events when the handler function is called and then rebind when it exits. This also makes user code less prone to stack overflow recursion as you can actually change properties on the base element. It also means though that if you change one of the monitors properties in the handler the watch() handler won’t fire in response – you need to resort to a setTimeout() call instead to force the code to run outside of the handler: $("#notebox") el.watch("top,left,height,width,display,opacity", function (data, i) { var el = $(this); … // this makes el changes work setTimeout(function () { el.css("top", 10) },10); }) Since I’ve built this component I’ve had a lot of good uses for it. The .shadow() fallback functionality is one of them. Resources The watch() plug-in is part of ww.jquery.js and the West Wind West Wind Web Toolkit. You’re free to use this code here or the code from the toolkit. West Wind Web Toolkit Latest version of ww.jquery.js (search for fn.watch) watch plug-in documentation © Rick Strahl, West Wind Technologies, 2005-2011Posted in ASP.NET  JavaScript  jQuery  

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  • Python/Biophysics- Trying to code a simple stochastic simulation!

    - by user359597
    Hey guys- I'm trying to figure out what to make of the following code- this is not the clear, intuitive python I've been learning. Was it written in C or something then wrapped in a python fxn? The code I wrote (not shown) is using the same math, but I couldn't figure out how to write a conditional loop. If anyone could explain/decipher/clean this up, I'd be really appreciative. I mean- is this 'good' python- or does it look funky? I'm brand new to this- but it's like the order of the fxns is messed up? I understand Gillespie's- I've successfully coded several simpler simulations. So in a nutshell- good code-(pythonic)? order? c? improvements? am i being an idiot? The code shown is the 'answer,' to the following question from a biophysics text (petri-net not shown and honestly not necessary to understand problem): "In a programming language of your choice, implement Gillespie’s First Reaction Algorithm to study the temporal behaviour of the reaction A---B in which the transition from A to B can only take place if another compound, C, is present, and where C dynamically interconverts with D, as modelled in the Petri-net below. Assume that there are 100 molecules of A, 1 of C, and no B or D present at the start of the reaction. Set kAB to 0.1 s-1 and both kCD and kDC to 1.0 s-1. Simulate the behaviour of the system over 100 s." def sim(): # Set the rate constants for all transitions kAB = 0.1 kCD = 1.0 kDC = 1.0 # Set up the initial state A = 100 B = 0 C = 1 D = 0 # Set the start and end times t = 0.0 tEnd = 100.0 print "Time\t", "Transition\t", "A\t", "B\t", "C\t", "D" # Compute the first interval transition, interval = transitionData(A, B, C, D, kAB, kCD, kDC) # Loop until the end time is exceded or no transition can fire any more while t <= tEnd and transition >= 0: print t, '\t', transition, '\t', A, '\t', B, '\t', C, '\t', D t += interval if transition == 0: A -= 1 B += 1 if transition == 1: C -= 1 D += 1 if transition == 2: C += 1 D -= 1 transition, interval = transitionData(A, B, C, D, kAB, kCD, kDC) def transitionData(A, B, C, D, kAB, kCD, kDC): """ Returns nTransition, the number of the firing transition (0: A->B, 1: C->D, 2: D->C), and interval, the interval between the time of the previous transition and that of the current one. """ RAB = kAB * A * C RCD = kCD * C RDC = kDC * D dt = [-1.0, -1.0, -1.0] if RAB > 0.0: dt[0] = -math.log(1.0 - random.random())/RAB if RCD > 0.0: dt[1] = -math.log(1.0 - random.random())/RCD if RDC > 0.0: dt[2] = -math.log(1.0 - random.random())/RDC interval = 1e36 transition = -1 for n in range(len(dt)): if dt[n] > 0.0 and dt[n] < interval: interval = dt[n] transition = n return transition, interval if __name__ == '__main__': sim()

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  • Python/Biomolecular Physics- Trying to code a simple stochastic simulation of a system exhibiting co

    - by user359597
    *edited 6/17/10 I'm trying to understand how to improve my code (make it more pythonic). Also, I'm interested in writing more intuitive 'conditionals' that would describe scenarios that are commonplace in biochemistry. The conditional criteria in the below program is explained in Answer #2, but I am not satisfied with it- it is correct, but isn't obvious and isn't easy to implement for more complicated conditional scenarios. Ideas welcome. Comments/criticisms welcome. First posting experience @ stackoverflow- please comment on etiquette if needed. The code generates a list of values that are the solution to the following exercise: "In a programming language of your choice, implement Gillespie’s First Reaction Algorithm to study the temporal behaviour of the reaction A---B in which the transition from A to B can only take place if another compound, C, is present, and where C dynamically interconverts with D, as modelled in the Petri-net below. Assume that there are 100 molecules of A, 1 of C, and no B or D present at the start of the reaction. Set kAB to 0.1 s-1 and both kCD and kDC to 1.0 s-1. Simulate the behaviour of the system over 100 s." def sim(): # Set the rate constants for all transitions kAB = 0.1 kCD = 1.0 kDC = 1.0 # Set up the initial state A = 100 B = 0 C = 1 D = 0 # Set the start and end times t = 0.0 tEnd = 100.0 print "Time\t", "Transition\t", "A\t", "B\t", "C\t", "D" # Compute the first interval transition, interval = transitionData(A, B, C, D, kAB, kCD, kDC) # Loop until the end time is exceded or no transition can fire any more while t <= tEnd and transition >= 0: print t, '\t', transition, '\t', A, '\t', B, '\t', C, '\t', D t += interval if transition == 0: A -= 1 B += 1 if transition == 1: C -= 1 D += 1 if transition == 2: C += 1 D -= 1 transition, interval = transitionData(A, B, C, D, kAB, kCD, kDC) def transitionData(A, B, C, D, kAB, kCD, kDC): """ Returns nTransition, the number of the firing transition (0: A->B, 1: C->D, 2: D->C), and interval, the interval between the time of the previous transition and that of the current one. """ RAB = kAB * A * C RCD = kCD * C RDC = kDC * D dt = [-1.0, -1.0, -1.0] if RAB > 0.0: dt[0] = -math.log(1.0 - random.random())/RAB if RCD > 0.0: dt[1] = -math.log(1.0 - random.random())/RCD if RDC > 0.0: dt[2] = -math.log(1.0 - random.random())/RDC interval = 1e36 transition = -1 for n in range(len(dt)): if dt[n] > 0.0 and dt[n] < interval: interval = dt[n] transition = n return transition, interval if __name__ == '__main__': sim()

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