No, f_sample is the sampling rate. Remember: every "frequency domain" 1024-vector you've stored corresponds to 1024 time samples (hence my longish explanation of what happens to samples). 1024 time-domain samples take exactly 1024 sampling periods T_sample to capture, and T = 1/f.
Best regards, Marcus On 01.04.2017 15:47, Ellie White wrote: > > Hello Marcus – > > > > Thank you for the very helpful suggestions and clarifications – that > makes much more sense now! > > > > I just want to double check on one last thing, regarding your > statement that: > > > > t = N_samples / f_sample > > > > I think you indicated that N_samples is the number of samples read > from the file. I wanted to clarify what the value of f_sample is – is > that the size of the FFT (in my case 1024)? I apologize if I’m > missing something obvious here. > > > > Thanks again! > > > > Ellie > > > > *From:*Marcus Müller [mailto:marcus.muel...@ettus.com] > *Sent:* Friday, March 31, 2017 8:01 AM > *To:* Ellie White <orionnebul...@outlook.com>; discuss-gnuradio@gnu.org > *Subject:* Re: [Discuss-gnuradio] File sink question > > > > Hi Ellie, > > > > On 31.03.2017 02:52, Ellie White wrote: > > Thank you for the quick response. I guess I had been confused and > had set the sampling rate far too high! I think the right sampling > rate should be 2 MHz for the RTL-SDR dongle, based on what I’ve > seen online – does that sound more appropriate to you? > > Well, *you* are the one designing your signal processing application, > so you tell me what's appropriate for your /purpose/. But yes, the SDR > dongles can typically operate at such sampling rates. > > > > Regarding the rest of my question, if I am understanding this > correctly, the file sink stores data read in from the source (in > my case, the SDR dongle) as a 2d array, containing frequency and > time information. > > No, not at all! > The file sink just stores data. Just as it comes. Every stream > connection in GNU Radio really just transports numbers – and you're > storing only these numbers, in raw binary format, and nothing more! > > So, if I would run my flowgraph for some amount of time, I am > accumulating time samples in the destination file via the file > sink (each time sample containing 1024 values representing the > power of each frequency channel produced by the FFT block) – is > that correct? # > > So, what your flow graph does is it takes 1024-element vectors of the > complex input signal coming from your RTL-SDR (which then really are > just 1024 complex values in memory, each of which is a float32 real, > and a float32 imaginary part, directly after each other, in machine > format), subjects them to an FFT, which does something "logically" to > these vectors, but doesn't change the fact that they're still > 1024-vectors of complexes, then subjects these to a transformation > from complex values to magnitude squares, which changes them to > 1024-vectors of floats, and then just writes them to a file. > > That file will just contain floats. There's absolutely no indication > of time or frequency in these – just numbers. The fact that they're > 1024-vectors, of float32, with a special meaning, generated from a > signal with a specific sampling rate, is something that is not stored > in the file. Again: the file really just contains the raw numbers, one > after the other, with no dimensionality or annotations. > > > > To clarify a bit further, my aim is to make a plot of power vs. > time for one particular frequency channel using python. So I want > to be able to tell how many seconds of data I am looking at, > rather than how many time samples I am looking at. > > But that's trivial, because t = N_samples / f_sample !! > > I attached a plot to illustrate what I mean: right now, the x-axis > is labeled based on time samples (I think), > > Well, it's labeled with the index of the number numpy read. > > and I would like to label it with the corresponding time stamp > instead. > > So, generate an index vector with numpy, for example > > idx = numpy.linspace(0,len(samples_read_from_file)/f_sample, > len(samples_read_from_file)) > pyplot.plot(idx, samples_read_from_file) > > No magic involved! :) > > So the question is, how do I convert number of time samples into > an indication of time intervals? > > > > Hopefully this makes sense and isn’t too convoluted…let me know if > I need to clarify anything further or provide any other information. > > > > No, everything's fine so far. You're clearly entering the field of DSP > in a very cool way, and I'd say: go for it! > > Best regards, > Marcus >
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