Python load_monthly_data_general 예제들

예제 #1

파일: geo_data_bootstrap_analysis.py 프로젝트: vejmelkam/ndw-climate

        plt.title(pltnames[i])
        plt.colorbar()
        
    plt.savefig(file)

# <codecell>

# change to higher dir for loading to work
os.chdir('/home/martin/Projects/Climate/ndw-climate/')

# load up the monthly SLP geo-field
# print("[%s] Loading SLP geo field..." % (str(datetime.now())))
# gf = load_monthly_slp_all()

print("[%s] Loading SAT SH geo field..." % (str(datetime.now())))
gf = load_monthly_data_general('data/air.mon.mean.nc', 'air', date(1948, 1, 1), date(2012, 1, 1), None, None, [-89, 0], 0)

# load up the monthly SAT geo-field
# print("[%s] Loading SAT geo field..." % (str(datetime.now())))
# gf = load_monthly_sat_all()
print("[%s] Field loaded." % (str(datetime.now())))

# <codecell>

print gf.d.shape
print gf.lons[0], gf.lons[-1]
print gf.lats[0], gf.lats[-1]
print gf.d.shape[1] * gf.d.shape[2]

# <codecell>

예제 #2

파일: geo_data_bootstrap_analysis.py 프로젝트: Skye777/ndw-climate

        plt.colorbar()

    plt.savefig(file)


# <codecell>

# change to higher dir for loading to work
os.chdir('/home/martin/Projects/Climate/ndw-climate/')

# load up the monthly SLP geo-field
# print("[%s] Loading SLP geo field..." % (str(datetime.now())))
# gf = load_monthly_slp_all()

print("[%s] Loading SAT SH geo field..." % (str(datetime.now())))
gf = load_monthly_data_general('data/air.mon.mean.nc', 'air', date(1948, 1, 1),
                               date(2012, 1, 1), None, None, [-89, 0], 0)

# load up the monthly SAT geo-field
# print("[%s] Loading SAT geo field..." % (str(datetime.now())))
# gf = load_monthly_sat_all()
print("[%s] Field loaded." % (str(datetime.now())))

# <codecell>

print gf.d.shape
print gf.lons[0], gf.lons[-1]
print gf.lats[0], gf.lats[-1]
print gf.d.shape[1] * gf.d.shape[2]

# <codecell>

예제 #3

파일: geo_data_estimate_component_count.py 프로젝트: vejmelkam/ndw-climate

# <markdowncell>

# **Loading & filtering phase**
# 
# Now we must filter the data in frequency, the data loading has thus been moved here.

# <codecell>

os.chdir('/home/martin/Projects/ndw-climate/')

# load up the monthly SLP geo-field
print("[%s] Loading geo field..." % (str(datetime.now())))

gf = load_monthly_data_general("data/hgt.mon.mean.nc", "hgt",
                               date(1948, 1, 1), date(2012, 1, 1),
                               None, None, None, 5)


# load up the monthly SLP geo-field
if USE_MUVAR:
    print("[%s] Constructing F2 surrogate ..." % (str(datetime.now())))
    sgf = SurrGeoFieldAR()
    sgf.copy_field(gf)
    sgf.construct_fourier2_surrogates()
    sgf.d = sgf.sd.copy()

    # slide in fourier2 surrogate
    orig_gf = gf
    gf = sgf

예제 #4

파일: geo_data_estimate_component_count.py 프로젝트: Skye777/ndw-climate

np.random.seed()

# <markdowncell>

# **Loading & filtering phase**
#
# Now we must filter the data in frequency, the data loading has thus been moved here.

# <codecell>

os.chdir('/home/martin/Projects/ndw-climate/')

# load up the monthly SLP geo-field
print("[%s] Loading geo field..." % (str(datetime.now())))

gf = load_monthly_data_general("data/hgt.mon.mean.nc", "hgt", date(1948, 1, 1),
                               date(2012, 1, 1), None, None, None, 5)

# load up the monthly SLP geo-field
if USE_MUVAR:
    print("[%s] Constructing F2 surrogate ..." % (str(datetime.now())))
    sgf = SurrGeoFieldAR()
    sgf.copy_field(gf)
    sgf.construct_fourier2_surrogates()
    sgf.d = sgf.sd.copy()

    # slide in fourier2 surrogate
    orig_gf = gf
    gf = sgf

# load up the monthly SLP geo-field
print("[%s] Done loading, data hase shape %s." %