Let's imagine there is a LED. It blinks on and off with a period of 0.5 seconds.
So on second 0 => 0.5 it is on, from second 0.5 => 1 it is off, from second 1 =>1.5 it is on again.
Let's imagine I want to read that input from outside camera (say iphone camera).
What I do is:
1. Take input stream, make image out of it, scan the image for presence of certain number of white pixels, if it is there, the led is on, I write "1" to my file. If it is not there I write "0".
I read input stream twice a second. So generally speaking if everything goes well and my processing does not lag somewhere I get good results. But imagine if:
0 => 0.5 LED is ON
0.49 => my camera reads info as "1"
0.5 => 1.0 LED is OFF
0.99 => my camera reads info as "0"
1.0 => 1.5 LED is ON
1.51 => my camera lagged and reads it as "0"
So we have data corruption here.
Question is, how do I synchronise reading so it preferrably goes into the middle of this window, for larger margin of error.
Also imagine if I'm trying to do that 10 times per second. The window becomes even less.
What can I read on the topic? What can I do to make it more reliable?
One possible solution seems to be reading input 4 times a second and to use data based on groups of 2 inputs.
Sounds like you might want to read about ways of encoding timecode.
http://en.wikipedia.org/wiki/Timecode
LTC (audio signal): http://en.wikipedia.org/wiki/Linear_timecode
VITC (analogue video signal): http://en.wikipedia.org/wiki/Vertical_interval_timecode
Each of these transmits 80 bits of data at the chosen frame rate (say, 30fps). I’m not sure how you’d do it in your case.
Clearly, having a smaller window is more accurate. With LTC, as audio is often sampled at around 44kHz, it’s possible to get it almost exactly spot on.
If the iPhone camera can only take 2 photos per second, I wonder if you could try taking photos at a different interval (say, even 0.7 seconds), and somehow do the maths to work out if it should be on or off (as the LED is still alternating at 0.5s). Over a period of a few seconds, it might be the same as sampling it every 0.1 seconds? (I’m just pulling numbers out of the sky, but I imagine you could work out something like that)
Another thought: can you use the video from the camera instead of a sequence of photos? You might be able to get 30fps that way? (I’m not sure – haven’t looked into it) There might be improvements around this in iOS 6.0 too (something worth checking, if you’re a developer).
Related
I've been using oxyplot for a month now and I'm pretty happy with what it delivers. I'm getting data from an oscilloscope and, after a fast processing, I'm plotting it in real time to a graph.
However, if I compare my application CPU usage to the one provided by the oscilloscope manufacturer, I'm loading a lot more the CPU. Maybe they're using some gpu-based plotter, but I think I can reduce my CPU usage with some modifications.
I'm capturing 10.000 samples per second and adding it to a LineSeries. I'm not plotting all that data, I'm decimating it to a constant number of points, let's say 80 points for a 20 secs measure, so I have 4 points/sec while totally zoomed out and a bit more detail if I zoom in to a specific range.
With the aid of ReSharper, I've noticed that the application is calling a lot of times (I've 6 different plots) the IsValidPoint method (something like 400.000.000 times), which is taking a lot of time.
I think the problem is that, when I add new points to the series, it checks for every point if it is a valid point, instead of the added values only.
Also, it spends a lot of time in the MeasureText/DrawText method.
My question is: is there a way to override those methods and to adapt it to my needs? I'm adding 10.000 new values each second, but the first ones remain the same, so there's no need for re-validate them. Also, the text shown doesn't change.
Thank you in advance for any advice you can give me. Have a good day!
I've been looking for an answer everywhere and I was only able to find some bits and pieces. What I want to do is to load multiple mp3 files (kind of temporarily merge them) and then cut them into pieces using silence detection.
My understanding is that I can use Mp3FileReader for this but the questions are:
1. How do I read say 20 seconds of audio from an mp3 file? Do I need to read 20 times reader.WaveFormat.AverageBytesPerSecond? Or maybe keep on reading frames until the sum of Mp3Frame.SampleCount / Mp3Frame.SampleRate exceeds 20 seconds?
2. How do I actually detect the silence? I would look at an appropriate number of the consecutive samples to check if they are all below some threshold. But how do I access the samples regardless of them being 8 or 16bit, mono or stereo etc.? Can I directly decode an MP3 frame?
3. After I have detected silence at say sample 10465, how do I map it back to the mp3 frame index to perform the cutting without re-encoding?
Here's the approach I'd recommend (which does involve re-encoding)
Use AudioFileReader to get your MP3 as floating point samples directly in the Read method
Find an open source noise gate algorithm, port it to C#, and use that to detect silence (i.e. when noise gate is closed, you have silence. You'll want to tweak threshold and attack/release times)
Create a derived ISampleProvider that uses the noise gate, and in its Read method, does not return samples that are in silence
Either: Pass the output into WaveFileWriter to create a WAV File and and encode the WAV file to MP3
Or: use NAudio.Lame to encode directly without a WAV step. You'll probably need to go from SampleProvider back down to 16 bit WAV provider first
BEFORE READING BELOW: Mark's answer is far easier to implement, and you'll almost certainly be happy with the results. This answer is for those who are willing to spend an inordinate amount of time on it.
So with that said, cutting an MP3 file based on silence without re-encoding or full decoding is actually possible... Basically, you can look at each frame's side info and each granule's gain & huffman data to "estimate" the silence.
Find the silence
Copy all the frames from before the silence to a new file
now it gets tricky...
Pull the audio data from the frames after the silence, keeping track of which frame header goes with what audio data.
Start writing the second new file, but as you write out the frames, update the main_data_begin field so the bit reservoir is in sync with where the audio data really is.
MP3 is a compressed audio format. You can't just cut bits out and expect the remainder to still be a valid MP3 file. In fact, since it's a DCT-based transform, the bits are in the frequency domain instead of the time domain. There simply are no bits for sample 10465. There's a frame which contains sample 10465, and there's a set of bits describing all frequencies in that frame.
Plain cutting the audio at sample 10465 and continuing with some random other sample probably causes a discontinuity, which means the number of frequencies present in the resulting frame skyrockets. So that definitely means a full recode. The better way is to smooth the transition, but that's not a trivial operation. And the result is of course slightly different than the input, so it still means a recode.
I don't understand why you'd want to read 20 seconds of audio anyway. Where's that number coming from? You usually want to read everything.
Sound is a wave; it's entirely expected that it crosses zero. So being close to zero isn't special. For a 20 Hz wave (threshold of hearing), zero crossings happen 40 times per second, but each time you'll have multiple samples near zero. So you basically need multiple samples that are all close to zero, but on both sides. 5 6 7 isn't much for 16 bits sounds, but it might very well be part of a wave that will have a maximum at 10000. You really should check for at least 0.05 seconds to catch those 20 Hz sounds.
Since you detected silence in a 50 millisecond interval, you have a "position" that's approximately several hundred samples wide. With any bit of luck, there's a frame boundary in there. Cut there. Else it's time for reencoding.
In a game I've created Negamax works well for low depth searches but larger depth increases causes it to freeze. I thought about changing depth to type 'long' instead of 'integer' but not sure what else I can do. I know computation will take longer so it is possible it is calculating behind the scenes and I'm interpreting as freeze up. Any advice would be appreciated. In the game a player can only make 1 of 3 possible moves in a position and it is not like chess where there are large numbers of moves possible in anyone position and terminal position is difficult to reach.
Thanks
Daz
What counts as larger depth?
Remember that these trees grow exponentially, so if you have 3 options on the first choice, you have 9 when you're 2 deep, 59049 options to check when you're 10 deep, and so on. Another possible reason for things to slow down drastically is if you start using the page file; that is if you're storing your whole tree and suddenly run out of Ram once you get to a "larger" depth. You can probably hear that, or see the blinking hard drive light, if that's contributing.
Your best bet is to get some feedback; get it to print out a new number every x thousand options it checks, so that you can find out instead of guessing at whether it's still trying and how far it has to go. Once you know what it's doing and assuming it is just munching through, look into something like alpha-beta pruning to prevent the tree from growing as quickly.
We're building a GIS interface to display GPS track data, e.g. imagine the raw data set from a guy wandering around a neighborhood on a bike for an hour. A set of data like this with perhaps a new point recorded every 5 seconds, will be large and displaying it in a browser or a handheld device will be challenging. Also, displaying every single point is usually not necessary since a user can't visually resolve that much data anyway.
So for performance reasons we are looking for algorithms that are good at 'reducing' data like this so that the number of points being displayed is reduced significantly but in such a way that it doesn't risk data mis-interpretation. For example, if our fictional bike rider stops for a drink, we certainly don't want to draw 100 lat/lon points in a cluster around the 7-Eleven.
We are aware of clustering, which is good for when looking at a bunch of disconnected points, however what we need is something that applies to tracks as described above. Thanks.
A more scientific and perhaps more math heavy solution is to use the Ramer-Douglas-Peucker algorithm to generalize your path. I used it when I studied for my Master of Surveying so it's a proven thing. :-)
Giving your path and the minimum angle you can tolerate in your path, it simplifies the path by reducing the number of points.
Typically the best way of doing that is:
Determine the minimum number of screen pixels you want between GPS points displayed.
Determine the distance represented by each pixel in the current zoom level.
Multiply answer 1 by answer 2 to get the minimum distance between coordinates you want to display.
starting from the first coordinate in the journey path, read each next coordinate until you've reached the required minimum distance from the current point. Repeat.
Looking for some help with a Labview data collection program. If I could collect 2ms of data at 8kHz (gives 16 data points) per channel (I am collecting data on 4 analog channels with an National Instruments data acquisition board). The DAQ-MX collection task gives a 1D array of 4 waveforms.
If I don't display the data I can do all my computation time is about 2ms and it is OK if the processing loop lags a little behind the collection loop. Updating the chart in Labview's front panel introduces an unacceptable delay. We don't need to update the display very quickly probably at 5-10Hz would be sufficient. But I don't know how to set this up.
My current Labview VI has three parallel loops
A timed-loop for data collection
A loop for analysis and processing
A low priority loop for caching data to disk as a TDMS file
Data is passed from the collection loop to the other loops using a queue. Labview examples gave me some ideas but I am stuck.
Any suggestions, references, ideas would be appreciated.
Thanks
Azim
Follow Up Question
eaolson suggests that I re-sample the data for display purposes. The data coming from the DAQ-MX read is a one dimensional array of waveforms. So I would need to somehow build or concatenate the waveform data for each channel. And then re-sample the data before updating the front panel chart. I suppose the best approach would be to queue the data and in a display loop dequeue the stack build and re-sample the data based on screen resolution and then update the chart. Would there be any other approach. I will look on
(NI Labview Forum)[http://forums.ni.com/ni/board?board.id=170] for more information as suggetsted by eaolson.
Updates
changed acceptable update rate for graphs to 5-10Hz (thanks Underflow and eaolson)
disk cache loop is a low priority one (thanks eaolson)
Thanks for all the responses.
Your overall architecture description sounds solid, but... getting to 30Hz for any non-trivial graph is going to be challenging. Make sure you really need that rate before trying to make it happen. Optimizing to that level might take some time.
References that should be helpful:
You can defer panel updates. This keeps the front panel from refreshing until you're ready for it to do so, allowing you to buffer data in the background, and only draw it occasionally.
You should know about (a)synchronous display. This option allows some control over display rates.
There is some general advice available about speeding execution.
There is a (somewhat dated) report on execution speed on the LAVA forums. Googling around the LAVA forums is a great idea if you need to optimize your speed.
Television updates at about 30 Hz. Any more than that is faster than the human eye can see. 30 Hz should be at the maximum update rate you should consider for a display, not the starting point. Consider an update rate of 5-10 Hz.
LabVIEW charts append the most recent data to the historical data they store and display all the data at once. At 8 kHz, you're acquiring at least 8000 data points per channel per second. That means the array backing that graph has to continuously be resized to hold the new data. Also, even if your graph is 1000 pixels across, that means you're displaying 8 data points per screen pixel. There's not usually any reason to display any more than one data point per pixel. If you really need fast update rates, plot less data. Create an array to hold the historical data and plot only every Nth data point, where N is chosen so you're plotting, say, only a few hundred points.
Remember that your loops can run at different rates. It may be satisfactory to run the write-to-disk loop at a much lower frequency than the data collection rate, maybe every couple of seconds.
Avoid property nodes if you can. They run in the UI thread, which is slower than most other execution.
Other than that, it's really hard to offer a lot of substantial advice without seeing code or more specifics. Consider also asking your question at the NI LabVIEW forums. There are a lot of helpful people there.