# "area" : "50/-15/30/5", ## north/west/south/east
# "type" : "an",
# "class" : "e4",
# "format" : "netcdf",
# "padding" : "0",
# "target" : "test.nc"
# })
#==============================================================================
# load ERA-40 as g1 and ERA-Interim as g2
print("[%s] Loading data..." % (str(datetime.now())))
g1 = DataField()
g2 = DataField()
g1.load('Spain.ERA.58-01.nc', 't2m', 'ERA-40')
g2.load('Spain.ERA.01-13.nc', 't2m', 'ERA-40')
# concatenate
last = g1.time[-1]
idx = np.where(g2.time == last)[0] + 1
ndays = g1.time.shape[0] + g2.time[idx:].shape[0]
data = np.zeros((ndays, g1.lats.shape[0], g1.lons.shape[0]))
time = np.zeros((ndays, ))
data[:g1.time.shape[0], ...] = g1.data
data[g1.time.shape[0]:, ...] = g2.data[idx:]
time[:g1.time.shape[0]] = g1.time
time[g1.time.shape[0]:] = g2.time[idx:]
# "area" : "50/-15/30/5", ## north/west/south/east
# "type" : "an",
# "class" : "e4",
# "format" : "netcdf",
# "padding" : "0",
# "target" : "test.nc"
# })
#==============================================================================
# load ERA-40 as g1 and ERA-Interim as g2
print("[%s] Loading data..." % (str(datetime.now())))
g1 = DataField()
g2 = DataField()
g1.load('Spain.ERA.58-01.nc', 't2m', 'ERA-40')
g2.load('Spain.ERA.01-13.nc', 't2m', 'ERA-40')
# concatenate
last = g1.time[-1]
idx = np.where(g2.time == last)[0] + 1
ndays = g1.time.shape[0] + g2.time[idx:].shape[0]
data = np.zeros((ndays, g1.lats.shape[0], g1.lons.shape[0]))
time = np.zeros((ndays, ))
data[:g1.time.shape[0], ...] = g1.data
data[g1.time.shape[0]:, ...] = g2.data[idx:]
time[:g1.time.shape[0]] = g1.time
time[g1.time.shape[0]:] = g2.time[idx:]
cbar = plt.colorbar(format=r"%2.2f",
shrink=0.75,
ticks=np.arange(mi, ma + step, (ma - mi) / 8),
aspect=25,
drawedges=False)
cbar.set_label(cbar_label)
cbar_obj = plt.getp(cbar.ax.axes, 'yticklabels')
plt.setp(cbar_obj, fontsize=10, color=(.1, .1, .1))
if filename != None:
plt.savefig(filename)
else:
plt.show()
g = DataField()
g.load('tg_0.25deg_reg_v9.0.nc', 'tg')
means = True
daily = False
if means:
idx = 0
y = 1950
while idx < g.data.shape[0]:
idx2 = g.find_date_ndx(date(y, 1, 1))
render_geo_field(g.data[idx:idx2, ...], g.lats, g.lons, None, None,
False, 'Yearly mean temperature %s' % str(y),
'temperature [$^{\circ}C$]',
'imgs/temp_mean%s.png' % str(y))
y += 1
idx = idx2
#m.drawmeridians(np.arange(lons[0], lons[-1]+1, 10), dashes = [1,3], labels = [0,0,0,0], color = (.2, .2, .2),
#fontsize = 8.5)
plt.title(title)
cbar = plt.colorbar(format = r"%2.2f", shrink = 0.75, ticks = np.arange(mi, ma + step, (ma-mi)/8),
aspect = 25, drawedges = False)
cbar.set_label(cbar_label)
cbar_obj = plt.getp(cbar.ax.axes, 'yticklabels')
plt.setp(cbar_obj, fontsize = 10, color = (.1, .1, .1))
if filename != None:
plt.savefig(filename)
else:
plt.show()
g = DataField()
g.load('tg_0.25deg_reg_v9.0.nc', 'tg')
means = True
daily = False
if means:
idx = 0
y = 1950
while idx < g.data.shape[0]:
idx2 = g.find_date_ndx(date(y,1,1))
render_geo_field(g.data[idx:idx2, ...], g.lats, g.lons, None, None, False, 'Yearly mean temperature %s' % str(y), 'temperature [$^{\circ}C$]', 'imgs/temp_mean%s.png' % str(y))
y += 1
idx = idx2
if daily:
idx = g.find_date_ndx(date(2012,1,1))
for i in range(idx,idx+59):
