def __init__(self,
svd_data,
sv_list,
timebase,
min_dphase=-np.pi,
phase_pairs=None):
# NOTE I'd prefer not to duplicate info here which is in svd_data - should be able to refer to that, once sqlalchemy is hooked in
#self.topo_channels = svd_data.topo_channels
self.channels = svd_data.channels
#self.svs = sv_list
if len(sv_list) == 1:
self.a12 = 0
else:
# this ratio was inverted accidentally at first
self.a12 = svd_data.svs[sv_list[1]] / svd_data.svs[sv_list[0]]
self._binary_svs = list2bin(sv_list)
# peak frequency for fluctuation structure
self.timebase = timebase
self.freq, self.freq_elmt = peak_freq(svd_data.chronos[sv_list[0]],
self.timebase)
self.phase_pairs = phase_pairs
self.t0 = timebase[0]
# singular value filtered signals
self.signal = np.dot(
np.transpose(svd_data.topos[sv_list, :]),
np.dot(np.diag(svd_data.svs.take(sv_list)),
svd_data.chronos[sv_list, :]))
# phase differences between nearest neighbour channels
self.dphase = self._get_dphase(min_dphase=min_dphase)
self.p = np.sum(svd_data.svs.take(sv_list)**2) / svd_data.E
self.H = svd_data.H
self.E = svd_data.E
debug_(pyfusion.DEBUG, 4, key='FlucStruc')
super(FlucStruc, self).__init__()
def __init__(self, svd_data, sv_list, timebase, min_dphase = -np.pi, phase_pairs = None):
# NOTE I'd prefer not to duplicate info here which is in svd_data - should be able to refer to that, once sqlalchemy is hooked in
#self.topo_channels = svd_data.topo_channels
self.channels = svd_data.channels
#self.svs = sv_list
if len(sv_list) == 1:
self.a12 = 0
else:
# this ratio was inverted accidentally at first
self.a12 = svd_data.svs[sv_list[1]]/svd_data.svs[sv_list[0]]
self._binary_svs = list2bin(sv_list)
# peak frequency for fluctuation structure
self.timebase = timebase
self.freq, self.freq_elmt = peak_freq(svd_data.chronos[sv_list[0]], self.timebase)
self.phase_pairs = phase_pairs
self.t0 = timebase[0]
# singular value filtered signals
self.signal = np.dot(np.transpose(svd_data.topos[sv_list,:]),
np.dot(np.diag(svd_data.svs.take(sv_list)), svd_data.chronos[sv_list,:]))
# phase differences between nearest neighbour channels
self.dphase, self.fourier_values = self._get_dphase(min_dphase=min_dphase, get_fourier_value = 1)
self.p = np.sum(svd_data.svs.take(sv_list)**2)/svd_data.E
self.H = svd_data.H
self.E = svd_data.E
debug_(pyfusion.DEBUG, 4, key='FlucStruc')
super(FlucStruc, self).__init__()
def test_peak_freq(self):
timebase = Timebase(np.arange(0.0, 0.01, 1.e-6))
single_mode_signal = get_multimode_test_data(
channels=get_n_channels(1), timebase=timebase, modes=[mode_3])
p_f, p_f_elmt = peak_freq(single_mode_signal.signal[0],
single_mode_signal.timebase)
# Check that we get mode_3 frequency of 27.0 kHz (to 1 decimal place).
self.assertAlmostEqual(1.e-3 * p_f, 1.e-3 * mode_3['freq'], 1)
def test_peak_freq(self):
timebase = Timebase(np.arange(0.0,0.01, 1.e-6))
single_mode_signal = get_multimode_test_data(channels=get_n_channels(1),
timebase=timebase,
modes = [mode_3])
p_f, p_f_elmt = peak_freq(single_mode_signal.signal[0],
single_mode_signal.timebase)
# Check that we get mode_3 frequency of 27.0 kHz (to 1 decimal place).
self.assertAlmostEqual(1.e-3*p_f, 1.e-3*mode_3['freq'], 1)