The way we know and love is the famous digitalWrite() function. (Spoiler: Want a faster digitalWrite? Download Here!) But even the Arduino Reference claims that it is not the most efficient. The Arduino functions do a lot of error checking to make sure the pin is configured right and has to map Arduino numbering to actual IO ports. I ran some tests to find out. The estimated CPU cycles is calculated from ½ the waveform period measured divided by the period of 16Mhz, since it takes two write operations to complete a full period in a waveform.
The 3 methods I tested were digitalWrite(pin, LOW); digitalWrite(pin, HIGH);CLR(PORTB, 0) ; SET(PORTB, 0);PORTB |= _BV(0); PORTB &= ~(_BV(0)); The macros used: #define CLR(x,y) (x&=(~(1<<y))) #define SET(x,y) (x|=(1<<y)) #define _BV(bit) (1 << (bit)) The results As you can see, digitalWrite takes around 56 cycles to complete, while direct Port addressing takes 2 cycles. Next I tested just flipping a pin. HomePage. Déjà 18659 visites sur cette page.
Nouveau : Une machine multi-outil facile à construire, low-cost et propulsée par Arduino, çà vous tente ? Bienvenue ! Soutenez le site www.mon-club-elec.fr ! Vous aimez le site www.mon-club-elec.fr ? Vous avez gagné du temps avec des codes trouvés sur ce site ? Paiement par compte Paypal ou par carte bancaire acceptés Vous pouvez donner dès 1€ ! En cours : portage de la librairie JavacvPro en version PyQt : Ma librairie JavacvPro : la "vision par ordinateur" avec OpenCV sous Processing pour tous ! Je viens de finaliser la version 0.4 de ma librairie JavacvPro qui implémente la librairie OpenCV 2.3.1 sous Processing, permettant de créer facilement des applications de reconnaissance visuelle et d'analyse d'image en temps réel sur un flux vidéo de webcam. HomePageEssentiel Pour aller droit à essentiel... Open Source: 2015 - Java/C++/Python/Android/Design Patterns. A successful Git branching model » nvie.com.
In this post I present the development model that I’ve introduced for some of my projects (both at work and private) about a year ago, and which has turned out to be very successful.
I’ve been meaning to write about it for a while now, but I’ve never really found the time to do so thoroughly, until now. I won’t talk about any of the projects’ details, merely about the branching strategy and release management. It focuses around Git as the tool for the versioning of all of our source code. (By the way, if you’re interested in Git, our company GitPrime provides some awesome realtime data analytics on software engineering performance.)
Why git? For a thorough discussion on the pros and cons of Git compared to centralized source code control systems, see the web. But with Git, these actions are extremely cheap and simple, and they are considered one of the core parts of your daily workflow, really. Enough about the tools, let’s head onto the development model. Category:Programming Tasks. Programming tasks are problems that may be solved through programming.
When such a task is defined, Rosetta Code users are encouraged to solve them using as many different languages as they know. The end goal is to demonstrate how the same task is accomplished in different languages. These are the Programming Tasks that have been defined and solved. Feel free to add solutions in languages not already included. The Category:Simple is a small subset with only "really simple" tasks, like "Hello World", and demonstrations of basic language-features. The Category:Draft Programming Tasks is a list of tasks, some of which are just awaiting more implementations before they can be promoted to tasks. Read the guidelines on creating new tasks. The following 850 pages are in this category, out of 850 total. Test expressions régulières.