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)
