def buildT2():
nyrs = 10
lat = pyg.regularlat(31)
lon = pyg.regularlon(60)
time = pyg.ModelTime365(values=np.arange(nyrs*365), \
units='days', startdate={'year':2011, 'month':1, 'day':1})
pres = pyg.Pres(np.arange(1000, 0, -50.))
z = 6.6 * pyg.log(1000. / pres)
ts1 = 2 * pyg.sin(2 * np.pi * time / 365.) + 4 * pyg.Var(
(time, ), values=np.random.randn(nyrs * 365))
ts1 = ts1.smooth('time', 20)
ts2 = -5 + 0.6 * time / 365. + 5 * pyg.Var(
(time, ), values=np.random.randn(nyrs * 365))
ts2 = ts2.smooth('time', 20)
T_c = 260. + 40. * pyg.exp(-(
(lat - 10 * np.sin(2 * np.pi * time / 365)) / 45.)**2)
T_wave = 0.05 * lat * pyg.sind(6 * lon - time) # * ts1
T_lapse = -5 * z
Tf = (T_lapse + T_c + T_wave).transpose('time', 'pres', 'lat', 'lon')
Tf.name = 'Temp'
U_c = 40 * pyg.sind(2 * lat)**2 * pyg.sin(2 * np.pi * z / 12)**2
U_wave = 0.08 * lat * pyg.sind(6 * lon - time)
U = (U_c + ts2 * U_wave).transpose('time', 'pres', 'lat', 'lon')
U.name = 'U'
return pyg.Dataset(
[Tf, U],
atts={
'history':
'Synthetic Temperature and Wind data generated by pygeode'
})
def buildT2():
nyrs = 10
lat = pyg.regularlat(31)
lon = pyg.regularlon(60)
time = pyg.ModelTime365(values=np.arange(nyrs*365), \
units='days', startdate={'year':2011, 'month':1, 'day':1})
pres = pyg.Pres(np.arange(1000, 0, -50.))
z = 6.6 * pyg.log(1000./pres)
ts1 = 2*pyg.sin(2*np.pi*time/365.) + 4*pyg.Var((time,), values=np.random.randn(nyrs*365))
ts1 = ts1.smooth('time', 20)
ts2 = -5 + 0.6*time/365. + 5*pyg.Var((time,), values=np.random.randn(nyrs*365))
ts2 = ts2.smooth('time', 20)
T_c = 260. + 40. * pyg.exp(-((lat - 10*np.sin(2*np.pi*time/365))/45.)**2)
T_wave = 0.05 * lat * pyg.sind(6*lon - time)# * ts1
T_lapse = -5*z
Tf = (T_lapse + T_c + T_wave).transpose('time', 'pres', 'lat', 'lon')
Tf.name = 'Temp'
U_c = 40 * pyg.sind(2*lat)**2 * pyg.sin(2*np.pi * z / 12)**2
U_wave = 0.08 * lat * pyg.sind(6*lon - time)
U = (U_c + ts2*U_wave).transpose('time', 'pres', 'lat', 'lon')
U.name = 'U'
return pyg.Dataset([Tf, U], atts={'history':'Synthetic Temperature and Wind data generated by pygeode'})
def buildT1():
lat = pyg.regularlat(31)
lon = pyg.regularlon(60)
T_c = 260. + 40. * pyg.exp(-(lat/45.)**2)
T_wave = 0.05 * lat * pyg.sind(6*lon)
T = T_c + T_wave
T.name = 'Temp'
T.units = 'K'
return pyg.Dataset([T], atts={'history':'Synthetic Temperature data generated by pygeode'})
def test_issue053(): import pygeode as pyg import numpy as np l = pyg.regularlat(30) t = pyg.ModelTime365(values=np.arange(100), units='days', startdate=dict(year=1, month=1)) v = pyg.Var((t, l), name='Test', values=np.ones((100, 30))) v.plotatts['scalefactor'] = 2. v.plotatts['plottitle'] = 'V' a = l * v b = t + v assert a.plotatts == v.plotatts assert b.plotatts == v.plotatts
def test_issue053():
import pygeode as pyg
import numpy as np
l = pyg.regularlat(30)
t = pyg.ModelTime365(values=np.arange(100),
units='days',
startdate=dict(year=1, month=1))
v = pyg.Var((t, l), name='Test', values=np.ones((100, 30)))
v.plotatts['scalefactor'] = 2.
v.plotatts['plottitle'] = 'V'
a = l * v
b = t + v
assert a.plotatts == v.plotatts
assert b.plotatts == v.plotatts
"""
Specify contour levels
=======================
Use :func:`clfdict()` to create a set of contour levels and contour lines to plot.
"""
import pygeode as pyg, numpy as np
import pylab as pyl
pyl.ioff()
lat = pyg.regularlat(60)
lon = pyg.regularlon(120)
z = pyg.sin(2 * np.pi * lat /
180.)**10 + pyg.cos(10 +
(2 * np.pi / 180.)**2 * lat * lon) * pyg.cos(
2 * np.pi * lat / 180.)
ax = pyg.plot.AxesWrapper()
contour_dict = pyg.clfdict(min=-1.2,
axes=ax,
cdelt=0.4,
ndiv=3,
nf=2,
nl=1,
extend='both',
cmap='RdGy')
pyg.vcontour(z, **contour_dict)
ax.setp(title='Using helper function to set up contour levels')
