WINDOW_LENGTH = 16384
WINDOW_SHIFT = 1 # years, delta in the sliding window analysis
MEANS = True # if True, compute conditional means, if False, compute conditional variance
WORKERS = 16
NUM_SURR = 100 # how many surrs will be used to evaluate
SURR_TYPE = 'AR' # MF, FT, AR
diff_ax = (0, 2) # means -> 0, 2, var -> 1, 8
mean_ax = (18, 22) # means -> -1, 1.5, var -> 9, 18
PLOT_PHASE = False
PHASE_ANALYSIS_YEAR = None # year of detailed analysis - phase and bins, or None
AMPLITUDE = True
## loading data
g = load_station_data('TG_STAID000027.txt', date(1834, 7, 28),
date(2014, 1, 1), ANOMALISE)
sg = SurrogateField()
if AMPLITUDE:
g_amp = load_station_data('TG_STAID000027.txt', date(1834, 7, 28),
date(2014, 1, 1), False)
sg_amp = SurrogateField()
print(
"[%s] Wavelet analysis in progress with %d year window shifted by %d year(s)..."
% (str(datetime.now()), WINDOW_LENGTH, WINDOW_SHIFT))
k0 = 6. # wavenumber of Morlet wavelet used in analysis
y = 365.25 # year in days
fourier_factor = (4 * np.pi) / (k0 + np.sqrt(2 + np.power(k0, 2)))
period = PERIOD * y # frequency of interest
s0 = period / fourier_factor # get scale
cond_means = np.zeros((8, ))
if NUM_SURR != 0:
surr_completed = 0
diffs = np.zeros((NUM_SURR, ))
mean_vars = np.zeros_like(diffs)
g_surrs.data = g.data[start_idx:end_idx].copy()
g_surrs.time = g.time[start_idx:end_idx].copy()
if np.all(np.isnan(g_surrs.data) == False):
# construct the job queue
jobQ = Queue()
resQ = Queue()
for i in range(NUM_SURR):
jobQ.put(1)
for i in range(WORKERS):
jobQ.put(None)
a = g_surrs.get_seasonality(DETREND=True)
sg = SurrogateField()
sg.copy_field(g_surrs)
if SURR_TYPE == 'AR':
sg.prepare_AR_surrogates()
workers = [
Process(target=_cond_difference_surrogates,
args=(sg, g_surrs, a, start_cut, jobQ, resQ))
for iota in range(WORKERS)
]
for w in workers:
w.start()
while surr_completed < NUM_SURR:
# get result
diff, meanVar = resQ.get()
diffs[surr_completed] = diff
mean_vars[surr_completed] = meanVar
