g_working.data,
1,
False,
wavelet_analysis.morlet,
dj=0,
s0=s0,
j1=0,
k0=k0) # perform wavelet
phase = np.arctan2(np.imag(wave),
np.real(wave)) # get phases from oscillatory modes
start_cut = date(start_year + cnt * WINDOW_SHIFT, sm, sd)
idx = g_working.get_data_of_precise_length(WINDOW_LENGTH, start_cut,
None, True) # 16k or 13462
print 'data ', g.get_date_from_ndx(
start_idx), ' - ', g.get_date_from_ndx(end_idx)
print 'cut from ', start_cut, ' to ', g_working.get_date_from_ndx(-1)
last_mid_year = date.fromordinal(g_working.time[WINDOW_LENGTH /
2]).year
phase = phase[0, idx[0]:idx[1]]
phase_bins = get_equidistant_bins() # equidistant bins
for i in range(cond_means.shape[0]
): # get conditional means for current phase range
ndx = ((phase >= phase_bins[i]) & (phase <= phase_bins[i + 1]))
if MEANS:
cond_means[i] = np.mean(g_working.data[ndx])
else:
cond_means[i] = np.var(g_working.data[ndx], ddof=1)
difference_data.append(cond_means.max() -
cond_means.min()) # append difference to list
meanvar_data.append(np.mean(cond_means))
else:
_, _, idx = g.get_data_of_precise_length(WINDOW_LENGTH, date.fromordinal(g.time[4*y]), None, False)
first_mid_year = date.fromordinal(g.time[idx[0]+WINDOW_LENGTH/2]).year
while end_idx < g.data.shape[0]:
# data
g_working.data = g.data[start_idx : end_idx].copy()
g_working.time = g.time[start_idx : end_idx].copy()
if np.all(np.isnan(g_working.data) == False):
wave, _, _, _ = wavelet_analysis.continous_wavelet(g_working.data, 1, False, wavelet_analysis.morlet, dj = 0, s0 = s0, j1 = 0, k0 = k0) # perform wavelet
phase = np.arctan2(np.imag(wave), np.real(wave)) # get phases from oscillatory modes
start_cut = date(start_year+cnt*WINDOW_SHIFT, sm, sd)
idx = g_working.get_data_of_precise_length(WINDOW_LENGTH, start_cut, None, True) # 16k or 13462
print 'data ', g.get_date_from_ndx(start_idx), ' - ', g.get_date_from_ndx(end_idx)
print 'cut from ', start_cut, ' to ', g_working.get_date_from_ndx(-1)
last_mid_year = date.fromordinal(g_working.time[WINDOW_LENGTH/2]).year
phase = phase[0, idx[0] : idx[1]]
phase_bins = get_equidistant_bins() # equidistant bins
for i in range(cond_means.shape[0]): # get conditional means for current phase range
ndx = ((phase >= phase_bins[i]) & (phase <= phase_bins[i+1]))
if MEANS:
cond_means[i] = np.mean(g_working.data[ndx])
else:
cond_means[i] = np.var(g_working.data[ndx], ddof = 1)
difference_data.append(cond_means.max() - cond_means.min()) # append difference to list
meanvar_data.append(np.mean(cond_means))
else:
difference_data.append(np.nan)
meanvar_data.append(np.nan)
wave, _, _, _ = wavelet_analysis.continous_wavelet(
g_working_amp.data, 1, False, wavelet_analysis.morlet, dj=0, s0=s0_amp, j1=0, k0=k0
) # perform wavelet
amplitude = np.sqrt(np.power(np.real(wave), 2) + np.power(np.imag(wave), 2))
amplitude = amplitude[0, :]
phase_amp = np.arctan2(np.imag(wave), np.real(wave))
phase_amp = phase_amp[0, :]
reconstruction = amplitude * np.cos(phase_amp)
fit_x = np.vstack([reconstruction, np.ones(reconstruction.shape[0])]).T
m, c = np.linalg.lstsq(fit_x, g_working_amp.data)[0]
amplitude = m * amplitude + c
start_cut = date(start_year + cnt * WINDOW_SHIFT, sm, sd)
idx = g_working.get_data_of_precise_length(WINDOW_LENGTH, start_cut, None, True)
print "data ", g.get_date_from_ndx(start_idx), " - ", g.get_date_from_ndx(end_idx)
print "cut from ", start_cut, " to ", g_working.get_date_from_ndx(-1)
# last_mid_year = date.fromordinal(g_working.time[WINDOW_LENGTH/2]).year
last_mid_year += 1
print last_mid_year
phase = phase[0, idx[0] : idx[1]]
if AMPLITUDE:
amplitude = amplitude[idx[0] : idx[1]]
if PLOT_PHASE and BEGIN:
phase_till = date(start_year + (cnt + 1) * WINDOW_SHIFT, sm, sd)
ndx = g_working.find_date_ndx(phase_till)
if ndx != None and cnt < 125:
phase_total.append(phase[:ndx])
else:
phase_total.append(phase)
if PLOT_PHASE and not BEGIN:
ndx = g_working.find_date_ndx(last_day)
if SEASON == None:
cond_means = np.zeros((BINS, 2, 1))
else:
cond_means = np.zeros((BINS, 2, 2))
else:
cond_means = np.zeros((BINS, 2, 2))
def get_equidistant_bins(num):
return np.array(np.linspace(-np.pi, np.pi, num+1))
# start_cut = date(1958,1,1)
start_cut = date(1962,1,1)
l = 17532
if STATIONS == None:
g_data.data, g_data.time, idx = g.get_data_of_precise_length(l, start_cut, None, False)
print g_data.get_date_from_ndx(0), g_data.get_date_from_ndx(-1)
phase = phase[0, idx[0] : idx[1]]
if AMPLITUDE:
amplitude = amplitude[idx[0] : idx[1]]
else:
for i in range(len(STATIONS)):
locals()['g_data' + str(i)].data, locals()['g_data' + str(i)].time, idx = locals()['g' + str(i)].get_data_of_precise_length('16k', start_cut, None, False)
locals()['phase' + str(i)] = locals()['phase' + str(i)][0, idx[0] : idx[1]]
if AMPLITUDE:
locals()['amplitude' + str(i)] = locals()['amplitude' + str(i)][idx[0] : idx[1]]
phase_bins = get_equidistant_bins(BINS)
mons = {0: 'J', 1: 'F', 2: 'M', 3: 'A', 4: 'M', 5: 'J', 6: 'J', 7: 'A', 8: 'S', 9: 'O', 10: 'N', 11: 'D'}
if SEASON != None:
idx = 0
for se in SEASON:
