def linearInterpolation(A,I,levels=[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000], status=None):
"""
Linear interpolation
to interpolate a field from some levels to another set of levels
Value below "surface" are masked
Input
A : array to interpolate
I : interpolation field (usually Pressure or depth) from TOP (level 0) to BOTTOM (last level), i.e P value going up with each level
levels : levels to interplate to (same units as I), default levels are:[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000]
I and levels must have same units
Output
array on new levels (levels)
Examples:
A=interpolate(A,I,levels=[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000])
"""
try:
nlev=len(levels) # Number of pressure levels
except:
nlev=1 # if only one level len(levels) would breaks
levels=[levels,]
order=A.getOrder()
A=A(order='z...')
I=I(order='z...')
sh=list(I.shape)
nsigma=sh[0] #number of sigma levels
sh[0]=nlev
t=MV2.zeros(sh,typecode=MV2.float32)
sh2=I[0].shape
prev=-1
for ilev in range(nlev): # loop through pressure levels
if status is not None:
prev=genutil.statusbar(ilev,nlev-1.,prev)
lev=levels[ilev] # get value for the level
Iabv=MV2.ones(sh2,MV2.float)
Aabv=-1*Iabv # Array on sigma level Above
Abel=-1*Iabv # Array on sigma level Below
Ibel=-1*Iabv # Pressure on sigma level Below
Iabv=-1*Iabv # Pressure on sigma level Above
Ieq=MV2.masked_equal(Iabv,-1) # Area where Pressure == levels
for i in range(1,nsigma): # loop from second sigma level to last one
a = MV2.greater_equal(I[i], lev) # Where is the pressure greater than lev
b = MV2.less_equal(I[i-1],lev) # Where is the pressure less than lev
# Now looks if the pressure level is in between the 2 sigma levels
# If yes, sets Iabv, Ibel and Aabv, Abel
a=MV2.logical_and(a,b)
Iabv=MV2.where(a,I[i],Iabv) # Pressure on sigma level Above
Aabv=MV2.where(a,A[i],Aabv) # Array on sigma level Above
Ibel=MV2.where(a,I[i-1],Ibel) # Pressure on sigma level Below
Abel=MV2.where(a,A[i-1],Abel) # Array on sigma level Below
Ieq= MV2.where(MV2.equal(I[i],lev),A[i],Ieq)
val=MV2.masked_where(MV2.equal(Ibel,-1.),numpy.ones(Ibel.shape)*lev) # set to missing value if no data below lev if there is
tl=(val-Ibel)/(Iabv-Ibel)*(Aabv-Abel)+Abel # Interpolation
if ((Ieq.mask is None) or (Ieq.mask is MV22.nomask)):
tl=Ieq
else:
tl=MV2.where(1-Ieq.mask,Ieq,tl)
t[ilev]=tl.astype(MV2.float32)
ax=A.getAxisList()
autobnds=cdms2.getAutoBounds()
cdms2.setAutoBounds('off')
lvl=cdms2.createAxis(MV2.array(levels).filled())
cdms2.setAutoBounds(autobnds)
try:
lvl.units=I.units
except:
pass
lvl.id='plev'
try:
t.units=I.units
except:
pass
ax[0]=lvl
t.setAxisList(ax)
t.id=A.id
for att in A.listattributes():
setattr(t,att,getattr(A,att))
return t(order=order)
def harmonic(data, k=3):
data = data.reorder('t...')
cdutil.setAxisTimeBoundsDaily(data.getTime())
axislist = data.getAxisList()
dataid = data.id
daily = True
monthly = False
timeAxis = axislist[0]
N = 365. #len(timeAxis)
# P = 10. # 10 year, yearly harmonic oscilation
# P = 10*12 # 10 year, monthly harmonic oscilation
# P = 10*365 # 10 year, daily harmonic oscilation
# if P > N:
# raise ValueError("P('%d') value should not exceed N(%d)" % (P,N))
if k > N/2:
raise ValueError("k value should not exceed (%d) i.e. N/2 value" % (N/2))
if len(timeAxis) > 366:
print 'found more than 1 year data.'
# y_t = dailyClimatology(data, action='sum')
else:
y_t = data
# end of if len(timeAxis) > 366:
Y_0 = cdutil.averager(data, axis='t', action='average', weights='equal')
# make memory free
del data
t = numpy.arange(1, N+1, dtype='float')
otheraxis = list(Y_0.shape)
ax_product = 1
for ax in otheraxis:
ax_product *= ax
otheraxis.insert(0,N)
t = t.repeat(ax_product).reshape(otheraxis)
angle = 2 * math.pi * t/N
Y_k = 0.
for i in range(1,k+1):
kangle = angle*i
A_k = (2./N) * cdutil.averager(y_t * numpy.cos(kangle), axis='t', action='sum')
B_k = (2./N) * cdutil.averager(y_t * numpy.sin(kangle), axis='t', action='sum')
C_k = MV2.sqrt((A_k*A_k) + (B_k*B_k))
# if A_k is positiv, then retain this phase_angle as it is.
# phase_angle should be in degrees
phase_angle = phase_arc_angle = MV2.arctan(B_k/A_k)
# if A_k is zero, then replace phase_angle with pi/2 else retain same
phase_angle = MV2.where(MV2.equal(A_k, 0.), math.pi/2.0, phase_arc_angle)
# if A_k is negative, then add pi with phase_angle (if it is <= pi )
condition1 = MV2.logical_and(MV2.less(A_k, 0.), MV2.less_equal(phase_arc_angle, math.pi))
phase_angle = MV2.where(condition1, phase_arc_angle+math.pi, phase_arc_angle)
# if A_k is negative, then subtract pi from phase_angle (if it is > pi )
condition2 = MV2.logical_and(MV2.less(A_k, 0.), MV2.greater(phase_arc_angle, math.pi))
condition3 = MV2.logical_or(condition1, condition2)
phase_angle = MV2.where(condition3, phase_arc_angle-math.pi, phase_arc_angle)
# make memory free
del phase_arc_angle
if daily and not monthly:
# subtract 15 days lag to adjust phase_angle w.r.t daily
print "Daily Subtraction"
phase_angle -= (15.*2*math.pi)/N
# end of if daily and not monthly:
phase_angle = numpy.array(phase_angle)
# phase_angle = numpy.tile(phase_angle, N).reshape(kangle.shape)
kangle = numpy.array(kangle)
Y_k += C_k * MV2.cos(kangle - phase_angle)
# end of for i in range(1,k+1):
# add mean to the sum of first k-th harmonic of data
Y_k += Y_0
# make memory free
del y_t, Y_0
sumOfMean_and_first_k_harmonic = cdms2.createVariable(Y_k, id=dataid)
sumOfMean_and_first_k_harmonic.setAxisList(axislist)
sumOfMean_and_first_k_harmonic.comments = 'sumOfMean_and_first_%d_harmonic' % k
# make memory free
del Y_k
# return result
return sumOfMean_and_first_k_harmonic
def logLinearInterpolation(A,P,levels=[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000],status=None):
"""
Log-linear interpolation
to convert a field from sigma levels to pressure levels
Value below surface are masked
Input
A : array on sigma levels
P : pressure field from TOP (level 0) to BOTTOM (last level)
levels : pressure levels to interplate to (same units as P), default levels are:[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000]
P and levels must have same units
Output
array on pressure levels (levels)
Examples:
A=logLinearInterpolation(A,P),levels=[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000])
"""
try:
nlev=len(levels) # Number of pressure levels
except:
nlev=1 # if only one level len(levels) would breaks
levels=[levels,]
order=A.getOrder()
A=A(order='z...')
P=P(order='z...')
sh=list(P.shape)
nsigma=sh[0] #number of sigma levels
sh[0]=nlev
t=MV2.zeros(sh,typecode=MV2.float32)
sh2=P[0].shape
prev=-1
for ilev in range(nlev): # loop through pressure levels
if status is not None:
prev=genutil.statusbar(ilev,nlev-1.,prev)
lev=levels[ilev] # get value for the level
Pabv=MV2.ones(sh2,MV2.float)
Aabv=-1*Pabv # Array on sigma level Above
Abel=-1*Pabv # Array on sigma level Below
Pbel=-1*Pabv # Pressure on sigma level Below
Pabv=-1*Pabv # Pressure on sigma level Above
Peq=MV2.masked_equal(Pabv,-1) # Area where Pressure == levels
for i in range(1,nsigma): # loop from second sigma level to last one
a=MV2.greater_equal(P[i], lev) # Where is the pressure greater than lev
b= MV2.less_equal(P[i-1],lev) # Where is the pressure less than lev
# Now looks if the pressure level is in between the 2 sigma levels
# If yes, sets Pabv, Pbel and Aabv, Abel
a=MV2.logical_and(a,b)
Pabv=MV2.where(a,P[i],Pabv) # Pressure on sigma level Above
Aabv=MV2.where(a,A[i],Aabv) # Array on sigma level Above
Pbel=MV2.where(a,P[i-1],Pbel) # Pressure on sigma level Below
Abel=MV2.where(a,A[i-1],Abel) # Array on sigma level Below
Peq= MV2.where(MV2.equal(P[i],lev),A[i],Peq)
val=MV2.masked_where(MV2.equal(Pbel,-1),numpy.ones(Pbel.shape)*lev) # set to missing value if no data below lev if there is
tl=MV2.log(val/Pbel)/MV2.log(Pabv/Pbel)*(Aabv-Abel)+Abel # Interpolation
if ((Peq.mask is None) or (Peq.mask is MV2.nomask)):
tl=Peq
else:
tl=MV2.where(1-Peq.mask,Peq,tl)
t[ilev]=tl.astype(MV2.float32)
ax=A.getAxisList()
autobnds=cdms2.getAutoBounds()
cdms2.setAutoBounds('off')
lvl=cdms2.createAxis(MV2.array(levels).filled())
cdms2.setAutoBounds(autobnds)
try:
lvl.units=P.units
except:
pass
lvl.id='plev'
try:
t.units=P.units
except:
pass
ax[0]=lvl
t.setAxisList(ax)
t.id=A.id
for att in A.listattributes():
setattr(t,att,getattr(A,att))
return t(order=order)
def linearInterpolation(A,
I,
levels=[
100000, 92500, 85000, 70000, 60000, 50000, 40000,
30000, 25000, 20000, 15000, 10000, 7000, 5000,
3000, 2000, 1000
],
status=None):
"""
Linear interpolation
to interpolate a field from some levels to another set of levels
Value below "surface" are masked
Input
A : array to interpolate
I : interpolation field (usually Pressure or depth) from TOP (level 0) to BOTTOM (last level), i.e P value going up with each level
levels : levels to interplate to (same units as I), default levels are:[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000]
I and levels must have same units
Output
array on new levels (levels)
Examples:
A=interpolate(A,I,levels=[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000])
"""
try:
nlev = len(levels) # Number of pressure levels
except:
nlev = 1 # if only one level len(levels) would breaks
levels = [
levels,
]
order = A.getOrder()
A = A(order='z...')
I = I(order='z...')
sh = list(I.shape)
nsigma = sh[0] #number of sigma levels
sh[0] = nlev
t = MV2.zeros(sh, typecode=MV2.float32)
sh2 = I[0].shape
prev = -1
for ilev in range(nlev): # loop through pressure levels
if status is not None:
prev = genutil.statusbar(ilev, nlev - 1., prev)
lev = levels[ilev] # get value for the level
Iabv = MV2.ones(sh2, MV2.float)
Aabv = -1 * Iabv # Array on sigma level Above
Abel = -1 * Iabv # Array on sigma level Below
Ibel = -1 * Iabv # Pressure on sigma level Below
Iabv = -1 * Iabv # Pressure on sigma level Above
Ieq = MV2.masked_equal(Iabv, -1) # Area where Pressure == levels
for i in range(1, nsigma): # loop from second sigma level to last one
a = MV2.greater_equal(
I[i], lev) # Where is the pressure greater than lev
b = MV2.less_equal(I[i - 1],
lev) # Where is the pressure less than lev
# Now looks if the pressure level is in between the 2 sigma levels
# If yes, sets Iabv, Ibel and Aabv, Abel
a = MV2.logical_and(a, b)
Iabv = MV2.where(a, I[i], Iabv) # Pressure on sigma level Above
Aabv = MV2.where(a, A[i], Aabv) # Array on sigma level Above
Ibel = MV2.where(a, I[i - 1],
Ibel) # Pressure on sigma level Below
Abel = MV2.where(a, A[i - 1], Abel) # Array on sigma level Below
Ieq = MV2.where(MV2.equal(I[i], lev), A[i], Ieq)
val = MV2.masked_where(
MV2.equal(Ibel, -1.),
numpy.ones(Ibel.shape) *
lev) # set to missing value if no data below lev if there is
tl = (val - Ibel) / (Iabv - Ibel) * (Aabv -
Abel) + Abel # Interpolation
if ((Ieq.mask is None) or (Ieq.mask is MV22.nomask)):
tl = Ieq
else:
tl = MV2.where(1 - Ieq.mask, Ieq, tl)
t[ilev] = tl.astype(MV2.float32)
ax = A.getAxisList()
autobnds = cdms2.getAutoBounds()
cdms2.setAutoBounds('off')
lvl = cdms2.createAxis(MV2.array(levels).filled())
cdms2.setAutoBounds(autobnds)
try:
lvl.units = I.units
except:
pass
lvl.id = 'plev'
try:
t.units = I.units
except:
pass
ax[0] = lvl
t.setAxisList(ax)
t.id = A.id
for att in A.listattributes():
setattr(t, att, getattr(A, att))
return t(order=order)
def logLinearInterpolation(A,
P,
levels=[
100000, 92500, 85000, 70000, 60000, 50000,
40000, 30000, 25000, 20000, 15000, 10000, 7000,
5000, 3000, 2000, 1000
],
status=None):
"""
Log-linear interpolation
to convert a field from sigma levels to pressure levels
Value below surface are masked
Input
A : array on sigma levels
P : pressure field from TOP (level 0) to BOTTOM (last level)
levels : pressure levels to interplate to (same units as P), default levels are:[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000]
P and levels must have same units
Output
array on pressure levels (levels)
Examples:
A=logLinearInterpolation(A,P),levels=[100000, 92500, 85000, 70000, 60000, 50000, 40000, 30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000])
"""
try:
nlev = len(levels) # Number of pressure levels
except:
nlev = 1 # if only one level len(levels) would breaks
levels = [
levels,
]
order = A.getOrder()
A = A(order='z...')
P = P(order='z...')
sh = list(P.shape)
nsigma = sh[0] #number of sigma levels
sh[0] = nlev
t = MV2.zeros(sh, typecode=MV2.float32)
sh2 = P[0].shape
prev = -1
for ilev in range(nlev): # loop through pressure levels
if status is not None:
prev = genutil.statusbar(ilev, nlev - 1., prev)
lev = levels[ilev] # get value for the level
Pabv = MV2.ones(sh2, MV2.float)
Aabv = -1 * Pabv # Array on sigma level Above
Abel = -1 * Pabv # Array on sigma level Below
Pbel = -1 * Pabv # Pressure on sigma level Below
Pabv = -1 * Pabv # Pressure on sigma level Above
Peq = MV2.masked_equal(Pabv, -1) # Area where Pressure == levels
for i in range(1, nsigma): # loop from second sigma level to last one
a = MV2.greater_equal(
P[i], lev) # Where is the pressure greater than lev
b = MV2.less_equal(P[i - 1],
lev) # Where is the pressure less than lev
# Now looks if the pressure level is in between the 2 sigma levels
# If yes, sets Pabv, Pbel and Aabv, Abel
a = MV2.logical_and(a, b)
Pabv = MV2.where(a, P[i], Pabv) # Pressure on sigma level Above
Aabv = MV2.where(a, A[i], Aabv) # Array on sigma level Above
Pbel = MV2.where(a, P[i - 1],
Pbel) # Pressure on sigma level Below
Abel = MV2.where(a, A[i - 1], Abel) # Array on sigma level Below
Peq = MV2.where(MV2.equal(P[i], lev), A[i], Peq)
val = MV2.masked_where(
MV2.equal(Pbel, -1),
numpy.ones(Pbel.shape) *
lev) # set to missing value if no data below lev if there is
tl = MV2.log(val / Pbel) / MV2.log(
Pabv / Pbel) * (Aabv - Abel) + Abel # Interpolation
if ((Peq.mask is None) or (Peq.mask is MV2.nomask)):
tl = Peq
else:
tl = MV2.where(1 - Peq.mask, Peq, tl)
t[ilev] = tl.astype(MV2.float32)
ax = A.getAxisList()
autobnds = cdms2.getAutoBounds()
cdms2.setAutoBounds('off')
lvl = cdms2.createAxis(MV2.array(levels).filled())
cdms2.setAutoBounds(autobnds)
try:
lvl.units = P.units
except:
pass
lvl.id = 'plev'
try:
t.units = P.units
except:
pass
ax[0] = lvl
t.setAxisList(ax)
t.id = A.id
for att in A.listattributes():
setattr(t, att, getattr(A, att))
return t(order=order)
def harmonic(data, k=3, time_type='daily', phase_shift=15):
"""
Inputs :
data : climatology data
k : Integer no to compute K th harmonic. By default it takes 3.
time_type : daily | monthly | full (time type of input climatology)
'daily' -> it returns 365 days harmonic,
'monthly' -> it returns 12 month harmonic,
'full' -> it retuns harmonic for full length of
input data.
phase_shift : Used to subtract 'phase_shift' days lag to adjust
phase_angle w.r.t daily or monthly. By default it takes
15 days lag to adjust phase_angle w.r.t daily data.
User can pass None disable this option.
Returns :
Returns "sum mean of mean and first K th harmonic" of input
climatology data.
Concept :
Earth science data consists of a strong seasonality component as
indicated by the cycles of repeated patterns in climate variables such
as air pressure, temperature and precipitation. The seasonality forms
the strongest signals in this data and in order to find other patterns,
the seasonality is removed by subtracting the monthly mean values of the
raw data for each month. However since the raw data like air temperature,
pressure, etc. are constantly being generated with the help of satellite
observations, the climate scientists usually use a moving reference base
interval of some years of raw data to calculate the mean in order to
generate the anomaly time series and study the changes with respect to
that.
Fourier series analysis decomposes a signal into an infinite series of
harmonic components. Each of these components is comprised initially of
a sine wave and a cosine wave of equal integer frequency. These two waves
are then combined into a single cosine wave, which has characteristic
amplitude (size of the wave) and phase angle (offset of the wave).
Convergence has been established for bounded piecewise continuous
functions on a closed interval, with special conditions at points of
discontinuity. Its convergence has been established for other conditions
as well, but these are not relevant to the analysis at hand.
Reference: Daniel S Wilks, 'Statistical Methods in the Atmospheric
Sciences' second Edition, page no(372-378).
Written By : Arulalan.T
Date : 16.05.2014
"""
data = data.reorder('t...')
cdutil.setAxisTimeBoundsDaily(data.getTime())
axislist = data.getAxisList()
timeAxis = axislist[0]
dataid = data.id
if time_type in ['daily']:
N = 365.0 # must be float
elif time_type[:3] in ['mon']:
N = 12.0 # must be float
elif time_type in ['full']:
N = float(len(timeAxis))
if k > N/2:
raise ValueError("k value should not exceed (%d) i.e. N/2 value" % (N/2))
if len(timeAxis) > 366:
print 'found more than 1 year data.'
raise ValueError("Kindly pass only climatology data")
else:
y_t = data
# end of if len(timeAxis) > 366:
Y_0 = cdutil.averager(data, axis='t', action='average', weights='equal')
# make memory free
del data
t = numpy.arange(1, N+1, dtype='float')
otheraxis = list(Y_0.shape)
ax_product = 1
for ax in otheraxis:
ax_product *= ax
otheraxis.insert(0,N)
t = t.repeat(ax_product).reshape(otheraxis)
angle = 2 * math.pi * t/N
Y_k = 0.
for i in range(1,k+1):
kangle = angle*i
A_k = (2./N) * cdutil.averager(y_t * numpy.cos(kangle), axis='t', action='sum')
B_k = (2./N) * cdutil.averager(y_t * numpy.sin(kangle), axis='t', action='sum')
C_k = MV2.sqrt((A_k*A_k) + (B_k*B_k))
# if A_k is positiv, then retain this phase_angle as it is.
# phase_angle should be in degrees
phase_angle = phase_arc_angle = MV2.arctan(B_k/A_k)
# if A_k is zero, then replace phase_angle with pi/2 else retain same
phase_angle = MV2.where(MV2.equal(A_k, 0.), math.pi/2.0, phase_arc_angle)
# if A_k is negative, then add pi with phase_angle (if it is <= pi )
condition1 = MV2.logical_and(MV2.less(A_k, 0.), MV2.less_equal(phase_arc_angle, math.pi))
phase_angle = MV2.where(condition1, phase_arc_angle+math.pi, phase_arc_angle)
# if A_k is negative, then subtract pi from phase_angle (if it is > pi )
condition2 = MV2.logical_and(MV2.less(A_k, 0.), MV2.greater(phase_arc_angle, math.pi))
condition3 = MV2.logical_or(condition1, condition2)
phase_angle = MV2.where(condition3, phase_arc_angle-math.pi, phase_arc_angle)
# make memory free
del phase_arc_angle
if phase_shift:
# subtract 15 days lag to adjust phase_angle w.r.t daily
phase_angle -= (phase_shift *2 * math.pi) / N
# end of if daily and not monthly:
phase_angle = numpy.array(phase_angle)
kangle = numpy.array(kangle)
Y_k += C_k * MV2.cos(kangle - phase_angle)
# end of for i in range(1,k+1):
# add mean to the sum of first k-th harmonic of data
Y_k += Y_0
# make memory free
del y_t, Y_0
sumOfMean_and_first_k_harmonic = cdms2.createVariable(Y_k, id=dataid)
sumOfMean_and_first_k_harmonic.setAxisList(axislist)
sumOfMean_and_first_k_harmonic.comments = 'sumOfMean_and_first_%d_harmonic' % k
# make memory free
del Y_k
# return result
return sumOfMean_and_first_k_harmonic
def linearInterpolation(A,
Idx,
levels=[
100000, 92500, 85000, 70000, 60000, 50000, 40000,
30000, 25000, 20000, 15000, 10000, 7000, 5000,
3000, 2000, 1000
],
status=None,
axis='z'):
"""
Linear interpolation to interpolate a field from some levels to another set of levels
Values below "surface" are masked.
:param A: array to interpolate
:type A:
:param I: interpolation field (usually Pressure or depth) from TOP (level 0) to BOTTOM (last level)
i.e P value going up with each level.
:type I:
:param levels: levels to interpolate to (same units as I).
Default levels:[100000, 92500, 85000, 70000, 60000, 50000, 40000,
30000, 25000, 20000, 15000, 10000, 7000, 5000, 3000, 2000, 1000]
:type levels:
:param axis: Axis over which to do the linear interpolation.
Can provide either an int representing axis index, or the axis name.
Default: 'z'.
:type axis: str or int
.. note::
I and levels must have same units
:returns: array on new levels (levels)
:Examples:
.. doctest:: vertical_linearInterpolation
>>> A=interpolate(A,I) # interpolates A over default levels
"""
try:
nlev = len(levels) # Number of pressure levels
except BaseException:
nlev = 1 # if only one level len(levels) would breaks
levels = [
levels,
]
order = A.getOrder()
A = A(order='%s...' % axis)
Idx = Idx(order='%s...' % axis)
sh = list(Idx.shape)
nsigma = sh[0] # number of sigma levels
sh[0] = nlev
t = MV2.zeros(sh, typecode=MV2.float32)
sh2 = Idx[0].shape
prev = -1
for ilev in range(nlev): # loop through pressure levels
if status is not None:
prev = genutil.statusbar(ilev, nlev - 1., prev)
lev = levels[ilev] # get value for the level
Iabv = MV2.ones(sh2, MV2.float)
Aabv = -1 * Iabv # Array on sigma level Above
Abel = -1 * Iabv # Array on sigma level Below
Ibel = -1 * Iabv # Pressure on sigma level Below
Iabv = -1 * Iabv # Pressure on sigma level Above
Ieq = MV2.masked_equal(Iabv, -1) # Area where Pressure == levels
for i in range(1, nsigma): # loop from second sigma level to last one
a = MV2.greater_equal(
Idx[i], lev) # Where is the pressure greater than lev
b = MV2.less_equal(Idx[i - 1],
lev) # Where is the pressure less than lev
# Now looks if the pressure level is in between the 2 sigma levels
# If yes, sets Iabv, Ibel and Aabv, Abel
a = MV2.logical_and(a, b)
Iabv = MV2.where(a, Idx[i], Iabv) # Pressure on sigma level Above
Aabv = MV2.where(a, A[i], Aabv) # Array on sigma level Above
Ibel = MV2.where(a, Idx[i - 1],
Ibel) # Pressure on sigma level Below
Abel = MV2.where(a, A[i - 1], Abel) # Array on sigma level Below
Ieq = MV2.where(MV2.equal(Idx[i], lev), A[i], Ieq)
val = MV2.masked_where(MV2.equal(Ibel, -1.),
numpy.ones(Ibel.shape) * lev)
# set to missing value if no data below lev if
# there is
tl = (val - Ibel) / (Iabv - Ibel) * \
(Aabv - Abel) + Abel # Interpolation
if ((Ieq.mask is None) or (Ieq.mask is MV2.nomask)):
tl = Ieq
else:
tl = MV2.where(1 - Ieq.mask, Ieq, tl)
t[ilev] = tl.astype(MV2.float32)
ax = A.getAxisList()
autobnds = cdms2.getAutoBounds()
cdms2.setAutoBounds('off')
lvl = cdms2.createAxis(MV2.array(levels).filled())
cdms2.setAutoBounds(autobnds)
try:
lvl.units = Idx.units
except BaseException:
pass
lvl.id = 'plev'
try:
t.units = Idx.units
except BaseException:
pass
ax[0] = lvl
t.setAxisList(ax)
t.id = A.id
for att in A.listattributes():
setattr(t, att, getattr(A, att))
return t(order=order)
