def Winds_hPa(U,V,P,pressurelevel):
# Calculates and creates a file with pressurelevel hPa winds
pressurelevel_pascal=pressurelevel*100.
U_hPa=cdu.logLinearInterpolation(U,P,levels=pressurelevel_pascal)
U_hPa.long_name=''.join(['U at ',str(pressurelevel),'hPa'])
U_hPa.id='U'
U_hPa.notes='U manipulated by cdutils.logLinearInterpolation'
V_hPa=cdu.logLinearInterpolation(V,P,levels=pressurelevel_pascal)
V_hPa.long_name=''.join(['V at ',str(pressurelevel),'hPa'])
V_hPa.notes='V manipulated by cdutils.logLinearInterpolation'
V_hPa.id='V'
return U_hPa,V_hPa
def testVert(self):
f = cdms2.open(
os.path.join(cdat_info.get_sampledata_path(), 'vertical.nc'))
Ps = f('PS')
U = f('U')
B = f('hybm')
A = f('hyam')
Po = f('variable_2')
P = cdutil.reconstructPressureFromHybrid(Ps, A, B, Po)
U2 = cdutil.logLinearInterpolation(U, P)
U2b = cdutil.logLinearInterpolation(U, P, axis='0')
self.assertTrue(numpy.ma.allclose(U2, U2b))
U2b = cdutil.logLinearInterpolation(U, P, axis='(lev)')
self.assertTrue(numpy.ma.allclose(U2, U2b))
def EIS_LTS(T,P,RELHUM):
#Calculates the Lower Tropospheric Stability (LTS) and Estimated Inversion Strenght (EIS)
Theta_700=cdu.logLinearInterpolation(T,P,levels=70000)*(1000./700.)**(2./7.)
Theta_700=cdu.averager(Theta_700,axis='z')
Theta_1000=cdu.logLinearInterpolation(T,P,levels=100000)
Theta_1000=cdu.averager(Theta_1000,axis='z')
LTS=Theta_700-Theta_1000
LTS.id='LTS'
LTS.long_name='Lower tropospheric stability'
LTS.units='K'
Theta_700.long_name='Potential temperature at 700hPa'
Theta_700.units='K'
Theta_1000.long_name='Potential temperature at 1000hPa'
Theta_1000.units='K'
# !!! Still need to develop EIS !!!
EIS=LTS
return LTS,EIS,Theta_700,Theta_1000
def Variable_hPa(var,P,pressurelevel):
# Calculates and creates a file with pressurelevel hPa winds
pressurelevel_pascal=pressurelevel*100.
var_hPa=cdu.logLinearInterpolation(var,P,levels=pressurelevel_pascal)
var_id=var.id
var_hPa.long_name=''.join([var_id,' at ',str(pressurelevel),'hPa'])
var_hPa.id=var_id
var_hPa.notes=''.join([var_id,' manipulated by cdutils.logLinearInterpolation'])
return var_hPa
#!/usr/bin/env python
# Adapted for numpy/ma/cdms2 by convertcdms.py
import cdutil
import cdms2 as cdms,vcs,sys,os
import vcs.test.support
bg = vcs.test.support.bg
f = cdms.open(os.path.join(cdms.__path__[0],'..','..','..','..','sample_data','vertical.nc'))
Ps=f('PS')
U=f('U')
B=f('hybm')
A=f('hyam')
Po=f('variable_2')
P=cdutil.reconstructPressureFromHybrid(Ps,A,B,Po)
U2=cdutil.logLinearInterpolation(U,P)
x=vcs.init()
x.plot(U2,bg=bg)
vcs.test.support.check_plot(x)
#!/usr/bin/env python
# Adapted for numpy/ma/cdms2 by convertcdms.py
import cdutil, cdat_info
import cdms2
import os
bg = 0
f = cdms2.open(os.path.join(cdat_info.get_sampledata_path(), 'vertical.nc'))
Ps = f('PS')
U = f('U')
B = f('hybm')
A = f('hyam')
Po = f('variable_2')
P = cdutil.reconstructPressureFromHybrid(Ps, A, B, Po)
U2 = cdutil.logLinearInterpolation(U, P)
#x=vcs.init()
#x.plot(U2,bg=bg)
#raw_input()
#!/usr/bin/env python
# Adapted for numpy/ma/cdms2 by convertcdms.py
import cdutil
import cdat_info
import numpy
import cdms2
import os
bg = 0
f = cdms2.open(os.path.join(cdat_info.get_sampledata_path(), 'vertical.nc'))
Ps = f('PS')
U = f('U')
B = f('hybm')
A = f('hyam')
Po = f('variable_2')
P = cdutil.reconstructPressureFromHybrid(Ps, A, B, Po)
U2 = cdutil.logLinearInterpolation(U, P)
U2b = cdutil.logLinearInterpolation(U, P, axis='0')
assert(numpy.ma.allclose(U2, U2b))
U2b = cdutil.logLinearInterpolation(U, P, axis='(lev)')
assert(numpy.ma.allclose(U2, U2b))
axes = v.getAxisList()
opened = False
for itim, tm in enumerate(tim): # loop over time
if ranks[itim] == myPe:
T = v(time=slice(itim, itim + 1))
Ps = fps('ps', time=slice(itim, itim + 1))
# create the pressure field
P = cdutil.reconstructPressureFromHybrid(Ps, A, B, Po)
# interpolate
print '[%d] Interpolating at time index %d' % (myPe, itim)
out = cdutil.logLinearInterpolation(T, P, levels)
out.info()
## print '[%d] Done!' % myPe
## sh=list(out.shape)
## sh.insert(0,1)
## out=MA.reshape(out,tuple(sh))
## t=tim.subAxis(itim,itim+1)
## xx=reltime(tim[itim],tim.units)
## t_new=xx.torel('days since 1800').value
## t[0]=t_new
## t.units='days since 1800'
## meta[0][0]=t
## levelsax=cdms.createAxis(levels/100.)
## levelsax.id='plev'
## levelsax.units='hPa'
## levelsax.designateLevel()
axes=v.getAxisList()
opened = False
for itim,tm in enumerate(tim): # loop over time
if ranks[itim] == myPe:
T=v(time=slice(itim,itim+1))
Ps=fps('ps',time=slice(itim,itim+1))
# create the pressure field
P=cdutil.reconstructPressureFromHybrid(Ps,A,B,Po)
# interpolate
print '[%d] Interpolating at time index %d' % (myPe, itim)
out=cdutil.logLinearInterpolation(T,P,levels)
out.info()
## print '[%d] Done!' % myPe
## sh=list(out.shape)
## sh.insert(0,1)
## out=MA.reshape(out,tuple(sh))
## t=tim.subAxis(itim,itim+1)
## xx=reltime(tim[itim],tim.units)
## t_new=xx.torel('days since 1800').value
## t[0]=t_new
## t.units='days since 1800'
## meta[0][0]=t
## levelsax=cdms.createAxis(levels/100.)
## levelsax.id='plev'
## levelsax.units='hPa'
## levelsax.designateLevel()