def __init__(self, pth, fname, num): filename = os.path.join(pth, fname) #open/parse the data: dta, stats = hgi.hhg_open_data(filename) print stats if dta == []: print 'exit' exit() window = gtk.Window() scr = window.get_screen() #do night detection and prepare long-term plot, if enough data: if len(dta)>5000: tme_ngt,acc_ngt,lgt_ngt,min_ngt,res_ngt, stats = hhg_nght_stats(dta) print stats #data should be loaded and analyzed, let's plot it: if (dta != False): fig = hplt.Hhg_nights_plot(scr.get_width()/80,8,80) if fig != False: nf = array((acc_ngt, lgt_ngt+100, min_ngt+200)).T nums = 0 if dta.dtype == hgi.desc_raw: xyz = array((dta.x, dta.y, dta.z)).T nums = str(sum(dta.d)) elif dta.dtype == hgi.desc_mv: xyz = array((dta.xm,dta.ym,dta.zm,dta.xv,dta.yv,dta.zv)).T fig.plot(dta.t,xyz,dta.l, tme_ngt,nf, nums, pth, (res_ngt*4)-20, num,) #otherwise prepare a raw plot: else: fig = hplt.Hhg_raw_plot(scr.get_width()/80,8,80) fig.plot(1, 3, dta.t, array((dta.x,dta.y,dta.z)).T, pth, num,'3D acceleration') fig.plot(2, 3, dta.t, array((dta.l)).T>>8, pth, num, 'ambient light') fig.plot(3, 3, dta.t, (array((dta.l)).T&0xFF)/2-30, pth, num, 'temperature') fig.draw_top_text( (('user: anonymous'),(stats )) ) # if selected, write data to binary file (so it can be used later): if fig.save_dta_file: print 'saving data to ' + fig.save_dta_file save(fig.save_dta_file, dta)
import pdb #check where to load from (default is the 1st HedgeHog's data): filename, scr = hhg_fopen.load('/media/HEDGEHOG/log000.HHG') #open/parse the data: dta, stats = hgi.hhg_open_data(filename) print stats if dta == []: exit() #do night detection and prepare long-term plot, if enough data: if len(dta)>5000: tme_ngt,acc_ngt,lgt_ngt,min_ngt,res_ngt, stats = hhg_nght_stats(dta) print stats #data should be loaded and analyzed, let's plot it: if (dta != False): fig = hplt.Hhg_nights_plot(scr.get_width()/80,8,80) if fig != False: nf = array((acc_ngt, lgt_ngt+100, min_ngt+200)).T nums = 0 if dta.dtype == hgi.desc_raw: xyz = array((dta.x, dta.y, dta.z)).T nums = str(sum(dta.d)) elif dta.dtype == hgi.desc_mv: xyz = array((dta.xm,dta.ym,dta.zm,dta.xv,dta.yv,dta.zv)).T fig.plot(dta.t,xyz,dta.l, tme_ngt,nf, (res_ngt*4)-20, nums)
if dta == []: exit() #shortcut to read the new npy files (have 7 cols): if len(dta[0]) == 7: fig = hplt.Hhg_raw_plot(scr.get_width() / 80, 8, 80) fig.plot(1, 3, dta.t, np.array((dta.x, dta.y, dta.z)).T, '3D acceleration') fig.plot(2, 3, dta.t, np.array((dta.e1)).T >> 8, 'ambient light') fig.plot(3, 3, dta.t, (np.array((dta.e1)).T & 0xFF) / 2 - 30, 'temperature') fig.show() exit(0) #do night detection and prepare long-term plot, if enough data: if len(dta) > 100000: tme_ngt, acc_ngt, lgt_ngt, min_ngt, res_ngt, stats = hhg_nght_stats(dta) print stats #data should be loaded and analyzed, let's plot it: if (dta != False): fig = hplt.Hhg_nights_plot(scr.get_width() / 80, 8, 80) if fig != False: nf = array((acc_ngt, lgt_ngt + 100, min_ngt + 200)).T nums = 0 if dta.dtype == hgi.desc_raw: xyz = array((dta.x, dta.y, dta.z)).T nums = str(sum(dta.d)) elif dta.dtype == hgi.desc_mv: xyz = array((dta.xm, dta.ym, dta.zm, dta.xv, dta.yv, dta.zv)).T fig.plot(dta.t, xyz, dta.l, tme_ngt, nf, (res_ngt * 4) - 20, nums)