示例#1
0
 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__()
示例#2
0
 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__()
示例#3
0
 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)
示例#4
0
文件: tests.py 项目: dpretty/pyfusion
 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)