None,
None,
'monthly',
anom=False)
pool = Pool(20)
net.wavelet(1, 'y', pool=pool, cut=1)
net.get_continuous_phase(pool=pool)
print "wavelet done"
net.get_phase_fluctuations(rewrite=True, pool=pool)
print "fluctuations done"
pool.close()
pool.join()
net.phase_fluctuations -= np.nanmean(net.phase_fluctuations, axis=0)
net.get_adjacency_matrix(net.phase_fluctuations,
method="L2",
pool=None,
use_queue=True,
num_workers=20)
net.save_net('networks/NCEP-SATannual-phase-fluctuations-adjmatL2.bin',
only_matrix=True)
print "L2 done"
## PHASE FLUCTUATIONS NETWORK correlation
print "Computing MI knn..."
net = ScaleSpecificNetwork(fname,
'air',
date(1950, 1, 1),
date(2016, 1, 1),
None,
None,
None,
# cPickle.dump({'mean_phase_diff' : np.mean(phase_diffs, axis = 0).flatten(),
# 'std_phase_diff' : np.std(phase_diffs, axis = 0, ddof = 1).flatten(),
# 'var_phase_diff' : np.var(phase_diffs, axis = 0, ddof = 1).flatten()}, f, protocol = cPickle.HIGHEST_PROTOCOL)
to_do = [['MIGAU', 8], ['MIGAU', 6]]
for do in to_do:
METHOD = do[0]
PERIOD = do[1]
print("computing for %d period using %s method" % (PERIOD, METHOD))
net = ScaleSpecificNetwork('/home/nikola/Work/phd/data/air.mon.mean.levels.nc', 'air',
date(1958,1,1), date(2014,1,1), None, None, 0, 'monthly', anom = True)
pool = Pool(WORKERS)
net.wavelet(PERIOD, get_amplitude = False, pool = pool)
print "wavelet on data done"
pool.close()
net.get_adjacency_matrix(net.phase, method = METHOD, pool = None, use_queue = True, num_workers = WORKERS)
print "estimating adjacency matrix done"
net.save_net('networks/NCEP-SATAsurface-phase-span-as-ERA-adjmat%s-scale%dyears.bin' % (METHOD, PERIOD), only_matrix = True)
# print phase_diffs.shape
# net.get_adjacency_matrix(phase_diffs, method = METHOD, pool = None, use_queue = True, num_workers = WORKERS)
# net.save_net('networks/NCEP-ERA-phase-diff-adjmat%s-scale%dyears.bin' % (METHOD, PERIOD), only_matrix = True)
# net.get_adjacency_matrix(net.phase, method = METHOD, pool = None, use_queue = True, num_workers = WORKERS)
# print "estimating adjacency matrix done"
# net.save_net('networks/ERA-SATAsurface-phase-adjmat%s-scale%dyears.bin' % (METHOD, PERIOD), only_matrix = True)
[-60, 0],
[40, 100],
level=0,
dataset="NCEP",
sampling="monthly",
anom=False,
)
surrs = SurrogateField()
a = net.get_seasonality(detrend=True)
surrs.copy_field(net)
net.return_seasonality(a[0], a[1], a[2])
pool = Pool(20)
net.wavelet(8, "y", cut=1, pool=pool)
net.get_adjacency_matrix(net.phase, method="MIEQQ", num_workers=0, pool=pool, use_queue=False)
pool.close()
pool.join()
data_adj_matrix = net.adjacency_matrix.copy()
surrs_adj_matrices = []
for i in range(NUM_SURR):
print("surr %d/%d computing..." % (i + 1, NUM_SURR))
pool = Pool(20)
surrs.construct_fourier_surrogates(pool=pool)
surrs.add_seasonality(a[0], a[1], a[2])
net.data = surrs.get_surr()
net.wavelet(8, "y", cut=1, pool=pool)
for scale in SCALES:
print("Computing networks using %s method..." % (method))
# phase
if method in ['MIEQQ', 'MIGAU', 'MPC']:
# net = ScaleSpecificNetwork(fname, 'air', date(1948,1,1), date(2016,1,1), None, None, level = 0, dataset = "NCEP",
# sampling = 'monthly', anom = False)
net = ScaleSpecificNetwork(fname, 't2m', date(1958,1,1), date(2014,1,1), None, None, level=None, pickled=True,
sampling='monthly', anom=False)
pool = Pool(NUM_WORKERS)
# net.get_hilbert_phase_amp(period = 90, width = 12, pool = pool, cut = 1)
net.wavelet(scale, period_unit='m', cut=2, pool=pool)
pool.close()
pool.join()
net.get_adjacency_matrix(net.phase, method = method, pool = None, use_queue = True, num_workers = NUM_WORKERS)
net.save_net('networks/ERA-SATsurface-scale%dmonths-phase-adjmat%s.bin' % (scale, method), only_matrix = True)
# amplitude
if method in ['MIEQQ', 'MIGAU', 'CORR']:
# net = ScaleSpecificNetwork(fname, 'air', date(1948,1,1), date(2016,1,1), None, None, level = 0, dataset = "NCEP",
# sampling = 'monthly', anom = False)
net = ScaleSpecificNetwork(fname, 't2m', date(1958,1,1), date(2014,1,1), None, None, level=None, pickled=True,
sampling='monthly', anom=False)
pool = Pool(NUM_WORKERS)
# net.get_hilbert_phase_amp(period = 90, width = 12, pool = pool, cut = 1)
net.wavelet(scale, period_unit='m', cut=2, pool=pool)
pool.close()
pool.join()
net.get_adjacency_matrix(net.amplitude, method = method, pool = None, use_queue = True, num_workers = NUM_WORKERS)
net.save_net('networks/ERA-SATsurface-scale%dmonths-amplitude-adjmat%s.bin' % (scale, method), only_matrix = True)
fname = '/home/nikola/Work/phd/data/air.mon.mean.sig995.nc'
# fname = "/Users/nikola/work-ui/data/air.mon.mean.sig995.nc"
## PHASE FLUCTUATIONS NETWORK L2 dist.
print "Computing L2 distance..."
net = ScaleSpecificNetwork(fname, 'air', date(1950,1,1), date(2016,1,1), None, None, None, 'monthly', anom = False)
pool = Pool(20)
net.wavelet(1, 'y', pool = pool, cut = 1)
net.get_continuous_phase(pool = pool)
print "wavelet done"
net.get_phase_fluctuations(rewrite = True, pool = pool)
print "fluctuations done"
pool.close()
pool.join()
net.phase_fluctuations -= np.nanmean(net.phase_fluctuations, axis = 0)
net.get_adjacency_matrix(net.phase_fluctuations, method = "L2", pool = None, use_queue = True, num_workers = 20)
net.save_net('networks/NCEP-SATannual-phase-fluctuations-adjmatL2.bin', only_matrix = True)
print "L2 done"
## PHASE FLUCTUATIONS NETWORK correlation
print "Computing MI knn..."
net = ScaleSpecificNetwork(fname, 'air', date(1950,1,1), date(2016,1,1), None, None, None, 'monthly', anom = False)
pool = Pool(20)
net.wavelet(1, 'y', pool = pool, cut = 1)
net.get_continuous_phase(pool = pool)
print "wavelet done"
net.get_phase_fluctuations(rewrite = True, pool = pool)
print "fluctuations done"
pool.close()
pool.join()
net.get_adjacency_matrix(net.phase_fluctuations, method = "CORR", pool = None, use_queue = True, num_workers = 20)
None,
level=0,
dataset="NCEP",
sampling='monthly',
anom=False)
surrs = SurrogateField()
a = net.get_seasonality(detrend=True)
surrs.copy_field(net)
net.return_seasonality(a[0], a[1], a[2])
pool = Pool(20)
net.wavelet(8, 'y', cut=1, pool=pool)
net.get_adjacency_matrix(net.phase,
method="MIEQQ",
num_workers=20,
pool=None,
use_queue=True)
pool.close()
pool.join()
data_adj_matrix = net.adjacency_matrix.copy()
surrs_adj_matrices = []
for i in range(NUM_SURR):
print("surr %d/%d computing..." % (i + 1, NUM_SURR))
pool = Pool(20)
surrs.construct_fourier_surrogates(pool=pool)
surrs.add_seasonality(a[0], a[1], a[2])
'/home/nikola/Work/phd/data/air.mon.mean.levels.nc',
'air',
date(1948, 1, 1),
date(2014, 1, 1),
None,
None,
0,
'monthly',
anom=False)
pool = Pool(WORKERS)
net.wavelet(PERIOD, get_amplitude=False, save_wavelet=True, pool=pool)
print "wavelet on data done"
pool.close()
net.get_adjacency_matrix(net.wave,
method=METHOD,
pool=None,
use_queue=True,
num_workers=WORKERS)
print "estimating adjacency matrix done"
net.save_net('networks/NCEP-SATsurface-wave-adjmat%s-scale%dyears.bin' %
(METHOD, PERIOD),
only_matrix=True)
print "computing SATA wavelet coherence..."
to_do = [['WCOH', 4], ['WCOH', 6], ['WCOH', 8], ['WCOH', 11], ['WCOH', 15]]
for do in to_do:
METHOD = do[0]
PERIOD = do[1]
print("computing for %d period using %s method" % (PERIOD, METHOD))
net = ScaleSpecificNetwork(
'/home/nikola/Work/phd/data/air.mon.mean.levels.nc',
import matplotlib.pyplot as plt
import numpy as np
methods = ['MIEQQ', 'MPC']
periods = [15, 11]
for METHOD in methods:
for PERIOD in periods:
net = ScaleSpecificNetwork('/home/nikola/Work/phd/data/air.mon.mean.levels.nc', 'air',
date(1948,1,1), date(2014,1,1), None, None, 0, 'monthly', anom = True)
pool = Pool(3)
net.wavelet(PERIOD, get_amplitude = False, pool = pool)
pool.close()
print "wavelet on data done"
net.get_adjacency_matrix(net.phase, method = METHOD, pool = None, use_queue = True, num_workers = 3)
print "estimating adjacency matrix done"
net.save_net('networks/NCEP-SATAsurface-adjmat%s-scale%dyears.bin' % (METHOD, PERIOD), only_matrix = True)
WORKERS = 10
print "computing SAT amplitude data networks..."
to_do = [['MIEQQ', 4], ['MIEQQ', 6], ['MIEQQ', 8], ['MIEQQ', 11], ['MIEQQ', 15],
['MIGAU', 4], ['MIGAU', 6], ['MIGAU', 8], ['MIGAU', 11], ['MIGAU', 15]]
for do in to_do:
METHOD = do[0]
PERIOD = do[1]
print("computing for %d period using %s method" % (PERIOD, METHOD))
net = ScaleSpecificNetwork('/home/nikola/Work/phd/data/air.mon.mean.levels.nc', 'air',
date(1948,1,1), date(2014,1,1), None, None, 0, 'monthly', anom = False)
pool = Pool(WORKERS)
'/home/nikola/Work/phd/data/air.mon.mean.levels.nc',
'air',
date(1948, 1, 1),
date(2014, 1, 1),
None,
None,
0,
'monthly',
anom=True)
pool = Pool(3)
net.wavelet(PERIOD, get_amplitude=False, pool=pool)
pool.close()
print "wavelet on data done"
net.get_adjacency_matrix(net.phase,
method=METHOD,
pool=None,
use_queue=True,
num_workers=3)
print "estimating adjacency matrix done"
net.save_net('networks/NCEP-SATAsurface-adjmat%s-scale%dyears.bin' %
(METHOD, PERIOD),
only_matrix=True)
WORKERS = 10
print "computing SAT amplitude data networks..."
to_do = [['MIEQQ', 4], ['MIEQQ', 6], ['MIEQQ', 8], ['MIEQQ',
11], ['MIEQQ', 15],
['MIGAU', 4], ['MIGAU', 6], ['MIGAU', 8], ['MIGAU', 11],
['MIGAU', 15]]
for do in to_do:
METHOD = do[0]
