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• Revisiting Nosefart and Discovering GME

  30 mai 2011, par Multimedia Mike — Game Hacking

  I found the following screenshot buried deep in an old directory structure of mine :

  
  
  

  I tried to recall how this screenshot came to exist. Had I actually created a functional KDE frontend to Nosefart yet neglected to release it ? I think it’s more likely that I used some designer tool (possibly KDevelop) to prototype a frontend. This would have been sometime in 2000.

  However, this screenshot prompted me to revisit Nosefart.

  Nosefart Background
  Nosefart is a program that can play Nintendo Sound Format (NSF) files. NSF files are files containing components that were surgically separated from Nintendo Entertainment System (NES) ROM dumps. These components contain the music playback engines for various games. An NSF player is a stripped down emulation system that can simulate the NES6502 CPU along with the custom hardware (2 square waves, 1 triangle wave, 1 noise generator, and 1 limited digital channel).

  Nosefart was written by Matt Conte and eventually imported into a Sourceforge project, though it has not seen any development since then. The distribution contains standalone command line players for Linux and DOS, a GTK frontend for the Linux command line version, and plugins for Winamp, XMMS, and CL-Amp.

  The Sourceforge project page notes that Nosefart is also part of XBMC. Let the record show that Nosefart is also incorporated into xine (I did that in 2002, I think).

  Upgrading the API
  When I tried running the command line version of Nosefart under Linux, I hit hard against the legacy audio API : OSS. Remember that ?

  In fairly short order, I was able to upgrade the CL program to use PulseAudio. The program is not especially sophisticated. It’s a single-threaded affair which checks for a keypress, processes an audio frame, and sends the frame out to the OSS file interface. All that was needed was to rewrite open_hardware() and close_hardware() for PA and then replace the write statement in play(). The only quirk that stood out is that including <pulse/pulseaudio.h> is insufficient for programming PA’s simple API. <pulse/simple.h> must be included separately.

  For extra credit, I adapted the program to ALSA. The program uses the most simplistic audio output API possible — just keep filling a buffer and sending it out to the DAC.

  Discovering GME
  I’m not sure what to do with the the program now since, during my research to attempt to bring Nosefart up to date, I became aware of a software library named Game Music Emu, or GME. It’s a pure C++ library that can essentially play any classic video game format you can possible name. Wow. A lot can happen in 10 years when you’re not paying attention.

  It’s such a well-written library that I didn’t need any tutorial or documentation to come up to speed. Just a quick read of the main gme.h header library enabled me in short order to whip up a quick C program that could play NSF and SPC files. Path of least resistance : Client program asks library to open a hardcoded file, synthesize 10 seconds of audio, and dump it into a file ; ask the FLAC command line program to transcode raw data to .flac file ; use ffplay to verify the results.

  I might develop some other uses for this library.

• Make better marketing decisions with attribution modeling

  19 décembre 2017, par InnoCraft — Community, Plugins

  Do you suspect some traffic sources are not getting the rewards they deserve ? Do you want to know how much credit each of your marketing channel actually gets ?

  When you look at which referrers contribute the most to your goal conversions or purchases, Piwik shows you only the referrer of the last visit. However, in reality, a visitor often visits a website multiple times from different referrers before they convert a goal. Giving all credit to the referrer of the last visit ignores all other referrers that contributed to a conversion as well.

  You can now push your marketing analysis to the next level with attribution modeling and finally discover the true value of all your marketing channels. As a result, you will be able to shift your marketing efforts and spending accordingly to maximize your success and stop wasting resources. In marketing, studying this data is called attribution modeling.

  Get the true value of your referrers

  Attribution is a premium feature that you can easily purchase from the Piwik marketplace.

  Once installed, you will be able to :

  • identify valuable referrers that you did not see before
  • invest in potential new partners
  • attribute a new level of conversion
  • make this work very easily by filling just a couple of form information

  Identify valuable referrers that you did not see before

  You probably have hundreds or even thousands of different sources listed within the referrer reports. We also guess that you have the feeling that it is always the same referrers which are credited of conversions.
  Guess what, those data are probably biased or at least are not telling you the whole story.
  Why ? Because by default, Piwik only attributes all credit to the last referrer.

  

  It is likely that many non credited sources played a role in the conversion process as well as people often visit your website several times before converting and they may come from different referrers.

  This is exactly where attribution modeling comes into play. With attribution modeling, you can decide which touchpoint you want to study. For example, you can choose to give credit to all the referrers a single visitor came from each time the user visits your website, and not only look at the last one. Without this feature, chances are, that you have spent too much money and / or efforts on the wrong referrer channels in the past because many referrers that contributed to conversions were ignored. Based on the insights you get by applying different attribution models, you can make better decisions on where to shift your marketing spending and efforts.

  Invest in potential new partners

  Once you apply different attribution models, you will find out that you need to consider a new list of referrers which you before either over- or under-estimated in terms of how much they contributed to your conversions. You probably did not identify those sources before because Piwik shows only the last referrer before a conversion. But you can now also look at what these newly discovered referrers are saying about your company, looking for any advertising programs they may offer, getting in contact with the owner of the website, and more.

  Apply up to 6 different attribution models

  By default, Piwik is attributing the conversion to the last referrer only. With attribution modeling you can analyze 6 different models :

  • Last Interaction : the conversion is attributed to the last referrer, even if it is a direct access.
  • Last Non-Direct : the conversion is attributed to the last referrer, but not in the case of a direct access.
  • First Interaction : the conversion is attributed to the first referrer which brought you the visit.
  • Linear : whatever the number of referrers which brought you the conversion, they will all get the same value.
  • Position Based : first and last referrer will be attributed 40% each the conversion value, the remaining 60% is divided between the rest of the referrers.
  • Time Decay : this attribution model means that the closer to the date of the conversion is, the more your last referrers will get credit.

  Those attribution models will enable you to analyze all your referrers deeply and increase your conversions.

  Let’s look at an example where we are comparing two models : “last interaction” and “first interaction”. Our goal is to identify whether some referrers that we are currently considering as less important, are finally playing a serious role in the total amount of conversions :

  

  Comparing Last Interaction model to First Interaction model

  Here it is interesting to observe that the website www.hongkiat.com is bringing almost 90% conversion more with the first interaction model rather than the last one.

  As a result we can look at this website and take the following actions :

  • have a look at the message on this website
  • look at opportunities to change the message
  • look at opportunities to display extra marketing messages
  • get in contact with the owner to identify any other communication opportunities

  The Multi Channel Attribution report

  Attribution modeling in Piwik does not require you to add any tracking code. The only thing you need is to install the plugin and let the magic happen.
  Simple as pie is the word you should keep in mind for this feature. Once installed, you will find the report within the goal section, just above the goals you created :

  

  The Multi Attribution menu

  There you can select the attribution model you would like to apply or compare.

  Attribution modeling is not just about playing with a new report. It is above all an opportunity to increase the number of conversions by identifying referrers that you may have not recognized as valuable in the past. To grow your business, it is crucial to identify the most (and least) successful channels correctly so you can spend your time and money wisely.

  Learn more about Multi Channel Conversion Attribution

• Back on the Salty Track

  12 juin 2011, par Multimedia Mike — General

  After I posted about my initial encounter and frustration with Google’s Native Client (NaCl) SDK and took a deep breath, I realized that I achieved an important proof of concept— I successfully played music using the NaCl SDK audio output interface. Then I started taking a closer read through the (C-based set of) header files and realized I might be able to make a go of it after all. I had much better luck this time and managed to create a proper Native Client interface that allows for controlling playback, presenting metadata, and toggling individual voices (a fascinating tool for studying classic game music).

  I haven’t bothered to post the actual plugin because, really, what’s the point ? I started with NaCl SDK 0.3 which requires Chrome 12, which means terribly limited reach, even among Chrome users. At least, that was true when I restarted this little project. Chrome 12 was formally released this past week. Chrome development really does move at breakneck pace.

  Anyway, here is a static screenshot of what the plugin currently looks like :

  
  
  

  Not pretty, but it does the job.

  Dev Journal
  Various notes based on this outing :

  • Portability : I tested my plugin using Chrome 12 on 64-bit Windows, Mac, and Linux. Mac and Linux both work ; Windows does not.
  • Build System : SDK 0.3 is still lacking in its ability to compile .cpp files (instead of .cc files) ; necessary because libgme is C++ using .cpp files. This requires some build system modification.
  • Getting the interfaces : This is where I got tripped up the first time around. get_browser_interface() from their example actually refers to a parameter passed in through the PPP_InitializeModule() function. The SDK’s template generator renames this to get_browser().
  • Debugging : I feel unstoppable once I have a printf() mechanism available to me during development. To that end, console.log() from JavaScript outputs to Chrome’s built-in JavaScript console log while putting printf() statements in the actual NaCl plugin causes the messages to show up in /.xsession-errors on Linux/X.
  • Size Matters : The binaries generated with the NaCl 0.3 SDK are ridiculously huge. The basic "Hello World" example in C compiles to binaries that are 6.7 MB and 7.8 MB for the 32- and 64-bit builds, respectively. This made me apprehensive to build a full version of SaltyGME that contains all the bells and whistles offered by the library. However, all of the GME code compiled into the binary adds very little size. Curiously, the C++ version of "Hello World" only ranges from 1.8-2.0 MB for 32- and 64-bit. Is there some kind of C tax happening here ? Note that running ’strip’ on the resulting .nexe files (they’re ELF files, after all) brings the sizes down into the C++ range, but at the cost of causing them to not work (more specifically, not even load).
  • No Messaging : The NaCl SDK is supposed to have a messaging interface which allows the NaCl plugin to send asynchronous messages up to the hosting page. When I try to instantiate it, I get a NULL. I’m stuck with the alternative of polling from the JavaScript side to, e.g., determine when a song has finished loading via the network.

  That’s all I can think of for now. I may work on this a little more (I’d like to at least see some audio visualization). Maybe Google will enable NaCl per default sometime around Chrome 21 and this program will be ready for prime time by then.

  See Also :

  • My first attempt at this same project