def analytic_phase(x, t=None, subint=None):
""" gets the phase from an amazing variety of signals
http://en.wikipedia.org/wiki/Analytic_signal
subinterval idea is not debugged and is probably unnecessary
may shorten data?
"""
from scipy.fftpack import hilbert
from pyfusion.utils import fix2pi_skips
from numpy import zeros, arctan2
# this subinterval idea does not seem necessary and is not debugged
if subint != None:
subint=powerof2(subint)
nsubints = int(len(x)/subint)
phs = zeros([nsubints, subint])
for i in range(nsubints):
xsub = x[i*subint:(i+1)*subint]
phs[i,:] = arctan2(xsub, hilbert(xsub))
phi = phs.flatten()
else:
y=hilbert(x) # use hilbert twice just to remove DC (lazy)
phi = arctan2(y, hilbert(y))
return(fix2pi_skips(phi, sign='+'))
def analytic_phase(x, t=None, subint=None):
""" gets the phase from an amazing variety of signals
http://en.wikipedia.org/wiki/Analytic_signal
subinterval idea is not debugged and is probably unnecessary
may shorten data?
"""
from scipy.fftpack import hilbert
from pyfusion.utils import fix2pi_skips
from numpy import zeros, arctan2
# this subinterval idea does not seem necessary and is not debugged
if subint != None:
subint=powerof2(subint)
nsubints = int(len(x)/subint)
phs = zeros([nsubints, subint])
for i in range(nsubints):
xsub = x[i*subint:(i+1)*subint]
phs[i,:] = arctan2(xsub, hilbert(xsub))
phi = phs.flatten()
else:
y=hilbert(x) # use hilbert twice just to remove DC (lazy)
phi = arctan2(y, hilbert(y))
return(fix2pi_skips(phi, sign='+'))
diag_name = 'MP'
dev=pyfusion.getDevice("LHD")
data=dev.acq.getdata(27233,diag_name)
#data.plot_signals()
# extract the phi DIrectly from the cfg file
Phi = np.array([2*np.pi/360*float(pyfusion.config.get
('Diagnostic:{cn}'.
format(cn=c.name),
'Coords_reduced')
.split(',')[0])
for c in data.channels])
pl.subplot(121)
pl.plot(Phi, linestyle='steps')
Phi_circ = fix2pi_skips(np.append(Phi, Phi[0]), around=0)
dp = np.diff(Phi_circ)
pl.plot(dp, linestyle='steps')
pl.figure()
pl.subplot(122)
phases = []
for N in range(-5, 5):
ph = modtwopi(N*dp, offset=0)
phases.append(ph)
pl.plot(phases[-1], label='N={N}'.format(N=N))
pl.legend()
pl.show(block=0)
# fake up a clusters file
clinds = [[c] for c in np.arange(len(phases))]
subset = phases
