def collection():
global gps_times,lats,lons,alts
global lati,loni,alti
global lastlen
global tmin,tmax,dt
global counts,tbins#,weights
global yourThread
with dataLock: # Wait for lock on current thread
gps_times,lats,lons,alts = get_data(opts.gps_file,filetype='gps')
lati,loni,alti = interp_pos(gps_times.gps[:,0],lats,lons,alts)
currlen = gps_times.shape[0]
if currlen == lastlen:
sleep(POOL_TIME)
elif currlen > lastlen:
lastlen = currlen
tmin,tmax = gps_times.gps.min(),gps_times.gps.max()
# Create weights array for check of GPS data when user queries server
counts,tbins = np.histogram(gps_times.gps,bins=int((tmax-tmin)/dt))
# Start the next thread
yourThread = threading.Timer(POOL_TIME, collection, ())
yourThread.start()
def collection():
global gps_times, lats, lons, alts
global lati, loni, alti
global lastlen
global tmin, tmax, dt
global counts, tbins #,weights
global yourThread
with dataLock: # Wait for lock on current thread
gps_times, lats, lons, alts = get_data(opts.gps_file,
filetype='gps')
lati, loni, alti = interp_pos(gps_times.gps[:, 0], lats, lons,
alts)
currlen = gps_times.shape[0]
if currlen == lastlen:
sleep(POOL_TIME)
elif currlen > lastlen:
lastlen = currlen
tmin, tmax = gps_times.gps.min(), gps_times.gps.max()
# Create weights array for check of GPS data when user queries server
counts, tbins = np.histogram(gps_times.gps,
bins=int((tmax - tmin) / dt))
# Start the next thread
yourThread = threading.Timer(POOL_TIME, collection, ())
yourThread.start()
global yourThread
# Create your thread
yourThread = threading.Timer(POOL_TIME, collection, ())
yourThread.start()
# Initiate
initialize()
# When you kill Flask (SIGTERM), clear the trigger for the next thread
atexit.register(interrupt)
# Return app with get function
return app
# Global variables
gps_times, lats, lons, alts = get_data(opts.gps_file, filetype='gps')
print gps_times.shape, lats.shape, lons.shape, alts.shape
lati, loni, alti = interp_pos(gps_times.gps[:, 0], lats, lons, alts)
# Get current number of GPS data points for monitoring of opts.gps_file
lastlen = gps_times.shape[0]
tmin, tmax = gps_times.gps.min(), gps_times.gps.max()
# Create weights array for check of GPS data when user queries server
dt = opts.dt
counts, tbins = np.histogram(gps_times.gps, bins=int((tmax - tmin) / dt))
# Create Lock object to access variables on an individual thread
dataLock = threading.Lock()
# Thread handler
o = optparse.OptionParser()
o.set_description("Queries ground station server for interpolated GPS position")
o.add_option("--spec_file", type=str, help="Accumulated file for plotting")
o.add_option("--freq", type=float, default=137.5, help="Peak frequency to look for in data")
o.add_option("--width", type=int, default=500, help="Number of channels to include in spectrum analysis")
opts, args = o.parse_args(sys.argv[1:])
fmin, fmax = int(opts.freq) - 1, int(opts.freq) + 1 # MHz; for plotting
time_range = 200
rmswindow = 10
start_ind = 0
# Get initial data from Signal Hound
spec_times, spec_raw, freqs, freq_chan = get_data(opts.spec_file, filetype="sh", freq=opts.freq, width=opts.width)
print spec_times.shape, spec_raw.shape, freqs.shape
freq_chan = np.where(np.abs(freqs - opts.freq).min() == np.abs(freqs - opts.freq))[0]
print "\nReading %s..." % opts.spec_file
print "Frequency plotting: %.3f" % freqs[freq_chan]
# freqs -= 0.005
# print freqs.shape,spec_raw.shape
if spec_times.shape[0] == 0: # Ensure data in inFile
print "Invalid data: array with zero dimension\nExiting...\n"
sys.exit()
# Initialize plotting figure
fig = plt.figure(figsize=(16, 9), dpi=80, facecolor="w", edgecolor="w")
# mng = plt.get_current_fig_manager() # Make figure full screen
fig.suptitle("ECHO Realtime Spectrum: %s" % opts.spec_file, fontsize=16)
global yourThread
# Create your thread
yourThread = threading.Timer(POOL_TIME, collection, ())
yourThread.start()
# Initiate
initialize()
# When you kill Flask (SIGTERM), clear the trigger for the next thread
atexit.register(interrupt)
# Return app with get function
return app
# Global variables
gps_times,lats,lons,alts = get_data(opts.gps_file,filetype='gps')
print gps_times.shape,lats.shape,lons.shape,alts.shape
lati,loni,alti = interp_pos(gps_times.gps[:,0],lats,lons,alts)
# Get current number of GPS data points for monitoring of opts.gps_file
lastlen = gps_times.shape[0]
tmin,tmax = gps_times.gps.min(),gps_times.gps.max()
# Create weights array for check of GPS data when user queries server
dt = opts.dt
counts,tbins = np.histogram(gps_times.gps,bins=int((tmax-tmin)/dt))
# Create Lock object to access variables on an individual thread
dataLock = threading.Lock()
# Thread handler
default=137.5,
help='Peak frequency to look for in data')
o.add_option('--width',
type=int,
default=500,
help='Number of channels to include in spectrum analysis')
opts, args = o.parse_args(sys.argv[1:])
fmin, fmax = int(opts.freq) - 1, int(opts.freq) + 1 # MHz; for plotting
time_range = 200
rmswindow = 10
start_ind = 0
# Get initial data from Signal Hound
spec_times, spec_raw, freqs, freq_chan = get_data(opts.spec_file,
filetype='sh',
freq=opts.freq,
width=opts.width)
print spec_times.shape, spec_raw.shape, freqs.shape
freq_chan = np.where(
np.abs(freqs - opts.freq).min() == np.abs(freqs - opts.freq))[0]
print '\nReading %s...' % opts.spec_file
print 'Frequency plotting: %.3f' % freqs[freq_chan]
#freqs -= 0.005
#print freqs.shape,spec_raw.shape
if spec_times.shape[0] == 0: # Ensure data in inFile
print 'Invalid data: array with zero dimension\nExiting...\n'
sys.exit()
# Initialize plotting figure
fig = plt.figure(figsize=(16, 9), dpi=80, facecolor='w', edgecolor='w')
#mng = plt.get_current_fig_manager() # Make figure full screen
