-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi Peter,
You might have a look at Python with Numpy/Scipy/matplotlib. Processed data according to your needs may be observed interactively with matplotlib and numpy/scipy do a good job at offline analysis. You'd have to process your data again and again anyway whenever you want to check something else. happy hacking Johannes On 17.07.2014 11:52, Peter A. Bigot wrote: > Thanks for the recommendations. > > I should clarify that I am a software engineer, not a signals > engineer, and my recurring need to visualize time-series data is > often satisfied without having to invoke DSP. An example of the > sort of thing I frequently want to do is to interactively explore > data collected from multiple wireless sensors (e.g., six months of > temperature and humidity data collected at 1-minute intervals). > Technically signals, but simple shifts, scales, and basic windowed > statistics are more useful than FFTs and complex filters. > > Sometimes I do need DSP techniques to extract the data from > third-party wireless transmissions, hence my current dabbling with > GNU Radio, but it's the data not the extraction process that's the > primary focus. For example, the reason I'm using GNU Radio is my > need to demodulate packets from a WS-2080 Weather Station and some > other 433 MHz OOK sensors. Yes, I've tried rtl433 and > rtlsdr-433m-sensor; the signal I'm capturing is too noisy or I > don't have frequency/bandwidth/filter settings right. The specific > use case that introduced my question about analysis tools is my > desire to interactively identify regions of interest from wideband > captures and then re-play that data repeatedly through various > processing chains, tweaking parameters until I get something that > reliably produces the underlying data. > > @mossman: The GSoC project is very close to what I'd want for > DSP-oriented analysis. If it existed it'd probably handle the > motivating example above. It's too domain-specific for > generalized time-series visualization, though, so I'd still have an > unmet need. > > @marcus.mueller: Thanks for the details. My experience is that a > metered stream/dataflow-oriented architecture is simply unsuited to > the sort of offline analysis I'm trying to do. The ability to jump > forwards and backwards in time is crucial, as is the ability to > decouple the signal rate from the data processing rate. Example: > Qt Time Raster schedules its updates based on wall clock not sample > time, so speeding up or slowing down the rate of data through the > system changes the displayed images, and running unthrottled drops > all the information. > > @dan.cajacob: pandas reminds me a lot of R. The intro video showed > it'd be good for CLI-based data manipulation, but my initial need > is to explore data graphically. > > @mdammer: kst-plot's web site shows some promising graphs, and it > built cleanly (though it doesn't obey CMAKE_INSTALL_PREFIX), but > I've been unable to locate examples and documentation that would > allow me to evaluate its capabilities quickly. > > @madengr: Lack of source code for baudline and its focus on DSP > knocks it out of contention for my general needs. > > On 07/16/2014 09:52 AM, Peter A. Bigot wrote: >> The sort of capabilities I'm looking for include: Read >> time-series data from files of different formats (some too large >> to fit in physical memory). Display the data, optionally >> applying linear transformations. Interactively pan and zoom. >> Jump forwards and backwards among time-registered events. >> Enable/disable/time-shift data overlays. Export selected data to >> new files. Calculate and display statistics and other non-linear >> transformations of selected data. > > A rough course towards the tool I imagine would be: > > * Collect/develop a suite of Qt/C++ widgets for graphical data > display and manipulation that are not sensitive to the processing > rate, don't have a unidirectional concept of time, can be accessed > from Python, and can be combined to build something with the > capabilities listed above. > > * Use a command-line interface like pandas/R to display original > files, extract regions of interest, apply transformations, and > repeat until satori. > > * Use GNU Radio Companion to glue components together to form > domain-specific analysis applications. > > That's a lot of yak shaving just to get a reliable OOK packet > extractor, so it probably won't happen. > > Thanks again for the suggestions. > > Peter > > _______________________________________________ Discuss-gnuradio > mailing list Discuss-gnuradio@gnu.org > https://lists.gnu.org/mailman/listinfo/discuss-gnuradio > -----BEGIN PGP SIGNATURE----- Version: GnuPG v1 Comment: Using GnuPG with Thunderbird - http://www.enigmail.net/ iQIcBAEBAgAGBQJTx6dJAAoJEO7fmkDsqywMQSgQAIEM6ujO7XUGXlKSiH0EFBAt 7zUBbERcjIdNCv4/15kuH/sjNTfk9tUhu5aIK8M3FyRKyC3kIBkDLJBiZhMdxQ14 sHldxKpt2kkKW6wYXLHfAV2qqauWM1lTfB9VYwjbtj8Wej55OwA6JUR6jtHS8F3O yZ+0obljFsChLSV8Y2DEHl66Of9SnyUciKIhBCt6MF4v48WeVwbkSeo04Ff31abE f3VlNcoNubug20boz8xMTVjanIei47b8zD1HDkroDaJikOWoboL/zdDnYJbfWiSY L16x5GjovOOvnw3ASkIKqO4iea4mqbvEiPu3OV1qHYzhb1TsVa32evMy/b8tO2HX CRcYs6lzs0YOiNDmUl2QUvP+Uaz81MLKmbk2EeA5MDpeLcvpAbjrd0bPkaL0DVRO fPwIReIFJuRri74d4O54nyNYQgONhl++J+K+tKLFmZ36UHFeDhTZ+odiLf+qN7vU ZujT0fANAww+hMZO4R4QZCUyDvcXthuwvaGY4T0nEerAv4Pu5jlCKKJOZKze3gzb kUoMNvn1pN2vNglihIaU4cNQauO24Lx0MoNOHED9Ar/le7QctYmiFp9oCSmokKSO JLheZsslvN86wWVQ6uFWRpa1+hOrG/JX1Ayxm9qoRmBtoV2L6c2dTDvZrasnnGlf pUAk1sdiqba9+dpZdkDQ =M0RI -----END PGP SIGNATURE----- _______________________________________________ Discuss-gnuradio mailing list Discuss-gnuradio@gnu.org https://lists.gnu.org/mailman/listinfo/discuss-gnuradio