itdaniher

If you're comfortable with Python or sqlite, it's pretty easy to dump the db to a text file.

Alternatively, we could build out functionality that distributes magnet links as a torrent, offering a 'decentralised' way of aggregating the work of other instances of magnetico.

On this note, I've had great luck with "whoosh" for fuzzy / advanced search. Example schema I use for magnet links at https://github.com/itdaniher/miracles-magnets/blob/master/magnet.py. Rgds!

FWIW I'd also like to see this enhancement landed. I see plenty of possibilities for an easy to embed ssh-based transport layer.

An application of this UI functionality might be supporting multiple simultaneous channel filters, so you can view multiple portions of the same signal simultaneously on different axes. I also found...

This gains additional value in the context of migrating from other tools, ie [Baudline](http://www.baudline.com/), which natively exports `RIFF (little-endian) data, WAVE audio, Microsoft PCM, 16 bit, stereo`

``` import scipy.io.wavfile import sys filename = sys.argv[1] fs1, y1 = scipy.io.wavfile.read(filename) assert y1.dtype.name == 'int16' stereo_to_complex = lambda a: a[0] + a[1]*1j y1 = y1/65536. y1 = stereo_to_complex(y1.T).astype('complex64') filename...

``` #0 0x0000000000000000 in ?? () #1 0x00005555555882dc in ngl_model_load_obj (fname=0x555555850a70 "../obj/c004.obj") at /home/user/frequensea/src/ngl.c:467 #2 0x00005555555676b3 in l_ngl_model_load_obj(lua_State*) () #3 0x000055555559bc7a in luaD_precall (L=0x555555843288, func=0x555555843580, nresults=1) at /home/user/frequensea/externals/lua/src/ldo.c:337 #4 0x00005555555b7de6...

OpenGL Renderer: GeForce GTX 960/PCIe/SSE2 OpenGL Version: 3.2.0 NVIDIA 375.39 Debian 9

@fdb I was too, it's possible I messed up with my gdb invocation.... In any case, I'll try again. Getting frequensea compiled wasn't too bad, and it looks like a...