def __init__(self, tag, field='Br', precision='Float32', avg=False):
"""
:param tag: if you specify a pattern, it tries to read the corresponding
files and stack them.
:type tag: str
:param field: nature of the radial spectra. Possible choices are
'Bt' or 'Bp'
:type field: str
:param precision: single or double precision (default single, i.e. 'Float32')
:type precision: str
:param avg: when set to True, display time averaged quantities
:type avg: bool
"""
logFiles = scanDir('log.*')
if len(logFiles) != 0:
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
self.n_r_max = int(self.n_r_max)
self.n_r_ic_max = int(self.n_r_ic_max)
else:
n_r_max = 'n_r_max ?\n'
self.n_r_max = int(input(str1))
n_r_ic_max = 'n_r_ic_max ?\n'
self.n_r_ic_max = int(input(str1))
str1 = 'Aspect ratio ?\n'
self.radratio = float(input(str1))
self.n_r_tot = self.n_r_max+self.n_r_ic_max
self.ricb = self.radratio/(1.-self.radratio)
self.rcmb = 1./(1.-self.radratio)
outerCoreGrid = chebgrid(self.n_r_max-1, self.rcmb, self.ricb)
n_r_ic_tot = 2*self.n_r_ic_max-1
innerCoreGrid = chebgrid(n_r_ic_tot-1, self.ricb, -self.ricb)
self.radius = np.zeros((self.n_r_tot-1), dtype=precision)
self.radius[:self.n_r_max] = outerCoreGrid
self.radius[self.n_r_max-1:] = innerCoreGrid[:self.n_r_ic_max]
pattern = 'r%s' % field +'Spec'
files = scanDir('%s.%s' % (pattern, tag))
# Read the rB[rp]Spec.TAG files (stack them)
data = []
for k, file in enumerate(files):
print('Reading %s' % file)
f = npfile(file, endian='B')
while 1:
try:
data.append(f.fort_read(precision))
except TypeError:
break
data = np.array(data, dtype=precision)
# Time (every two lines only)
self.time = data[::2, 0]
# Poloidal/Toroidal energy for all radii for the 6 first spherical harmonic
# degrees
self.e_pol = np.zeros((len(self.time), self.n_r_tot-1, 6), dtype=precision)
self.e_pol_axi = np.zeros_like(self.e_pol)
self.e_pol[:, :, 0] = data[::2, 1:self.n_r_tot]
self.e_pol[:, :, 1] = data[::2, self.n_r_tot-1:2*(self.n_r_tot-1)]
self.e_pol[:, :, 2] = data[::2, 2*(self.n_r_tot-1):3*(self.n_r_tot-1)]
self.e_pol[:, :, 3] = data[::2, 3*(self.n_r_tot-1):4*(self.n_r_tot-1)]
self.e_pol[:, :, 4] = data[::2, 4*(self.n_r_tot-1):5*(self.n_r_tot-1)]
self.e_pol[:, :, 5] = data[::2, 5*(self.n_r_tot-1):6*(self.n_r_tot-1)]
self.e_pol_axi[:, :, 0] = data[1::2, 1:self.n_r_tot]
self.e_pol_axi[:, :, 1] = data[1::2, self.n_r_tot-1:2*(self.n_r_tot-1)]
self.e_pol_axi[:, :, 2] = data[1::2, 2*(self.n_r_tot-1):3*(self.n_r_tot-1)]
self.e_pol_axi[:, :, 3] = data[1::2, 3*(self.n_r_tot-1):4*(self.n_r_tot-1)]
self.e_pol_axi[:, :, 4] = data[1::2, 4*(self.n_r_tot-1):5*(self.n_r_tot-1)]
self.e_pol_axi[:, :, 5] = data[1::2, 5*(self.n_r_tot-1):6*(self.n_r_tot-1)]
if avg:
self.plotAvg()
def __init__(self, tag, field='Br', precision=np.float32, avg=False):
"""
:param tag: if you specify a pattern, it tries to read the corresponding
files and stack them.
:type tag: str
:param field: nature of the radial spectra. Possible choices are
'Bt' or 'Bp'
:type field: str
:param precision: single or double precision (default single, i.e.
np.float32)
:type precision: str
:param avg: when set to True, display time averaged quantities
:type avg: bool
"""
logFiles = scanDir('log.*')
if len(logFiles) != 0:
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
self.n_r_max = int(self.n_r_max)
self.n_r_ic_max = int(self.n_r_ic_max)
else:
n_r_max = 'n_r_max ?\n'
self.n_r_max = int(input(str1))
n_r_ic_max = 'n_r_ic_max ?\n'
self.n_r_ic_max = int(input(str1))
str1 = 'Aspect ratio ?\n'
self.radratio = float(input(str1))
self.n_r_tot = self.n_r_max + self.n_r_ic_max
self.ricb = self.radratio / (1. - self.radratio)
self.rcmb = 1. / (1. - self.radratio)
outerCoreGrid = chebgrid(self.n_r_max - 1, self.rcmb, self.ricb)
n_r_ic_tot = 2 * self.n_r_ic_max - 1
innerCoreGrid = chebgrid(n_r_ic_tot - 1, self.ricb, -self.ricb)
self.radius = np.zeros((self.n_r_tot - 1), dtype=precision)
self.radius[:self.n_r_max] = outerCoreGrid
self.radius[self.n_r_max - 1:] = innerCoreGrid[:self.n_r_ic_max]
pattern = 'r{}'.format(field) + 'Spec'
files = scanDir('{}.{}'.format(pattern, tag))
# Read the rB[rp]Spec.TAG files (stack them)
data = []
for k, file in enumerate(files):
print('Reading {}'.format(file))
f = npfile(file, endian='B')
while 1:
try:
data.append(f.fort_read(precision))
except TypeError:
break
data = np.array(data, dtype=precision)
# Time (every two lines only)
self.time = data[::2, 0]
# Poloidal/Toroidal energy for all radii for the 6 first spherical harmonic
# degrees
self.e_pol = np.zeros((len(self.time), self.n_r_tot - 1, 6),
dtype=precision)
self.e_pol_axi = np.zeros_like(self.e_pol)
self.e_pol[:, :, 0] = data[::2, 1:self.n_r_tot]
self.e_pol[:, :, 1] = data[::2,
self.n_r_tot - 1:2 * (self.n_r_tot - 1)]
self.e_pol[:, :,
2] = data[::2,
2 * (self.n_r_tot - 1):3 * (self.n_r_tot - 1)]
self.e_pol[:, :,
3] = data[::2,
3 * (self.n_r_tot - 1):4 * (self.n_r_tot - 1)]
self.e_pol[:, :,
4] = data[::2,
4 * (self.n_r_tot - 1):5 * (self.n_r_tot - 1)]
self.e_pol[:, :,
5] = data[::2,
5 * (self.n_r_tot - 1):6 * (self.n_r_tot - 1)]
self.e_pol_axi[:, :, 0] = data[1::2, 1:self.n_r_tot]
self.e_pol_axi[:, :, 1] = data[1::2,
self.n_r_tot - 1:2 * (self.n_r_tot - 1)]
self.e_pol_axi[:, :,
2] = data[1::2,
2 * (self.n_r_tot - 1):3 * (self.n_r_tot - 1)]
self.e_pol_axi[:, :,
3] = data[1::2,
3 * (self.n_r_tot - 1):4 * (self.n_r_tot - 1)]
self.e_pol_axi[:, :,
4] = data[1::2,
4 * (self.n_r_tot - 1):5 * (self.n_r_tot - 1)]
self.e_pol_axi[:, :,
5] = data[1::2,
5 * (self.n_r_tot - 1):6 * (self.n_r_tot - 1)]
if avg:
self.plotAvg()
def __init__(self, iplot=False, angle=10, pickleName='thHeat.pickle'):
"""
:param iplot: a boolean to toggle the plots on/off
:type iplot: bool
:param angle: the integration angle in degrees
:type angle: float
:pickleName: calculations a
"""
angle = angle * np.pi / 180
if os.path.exists('tInitAvg'):
file = open('tInitAvg', 'r')
tstart = float(file.readline())
file.close()
logFiles = scanDir('log.*')
tags = []
for lg in logFiles:
nml = MagicSetup(quiet=True, nml=lg)
if nml.start_time > tstart:
if os.path.exists('bLayersR.%s' % nml.tag):
tags.append(nml.tag)
if len(tags) == 0:
tags = [nml.tag]
print('Only 1 tag: %s' % tags)
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
a = AvgField()
self.nuss = a.nuss
else:
logFiles = scanDir('log.*')
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
if not os.path.exists(pickleName):
# reading ATmov
k = 0
for tag in tags:
file = 'ATmov.%s' % tag
if os.path.exists(file):
if k == 0:
m = Movie(file=file, iplot=False)
print(file)
else:
m += Movie(file=file, iplot=False)
print(file)
k += 1
# reading AHF_mov
kk = 0
for tag in tags:
file = 'AHF_mov.%s' % tag
if os.path.exists(file):
if kk == 0:
m1 = Movie(file=file, iplot=False)
print(file)
else:
m1 += Movie(file=file, iplot=False)
print(file)
kk += 1
self.tempmean = m.data[0, ...].mean(axis=0)
self.tempstd = m.data[0, ...].std(axis=0)
self.colat = m.theta
if kk > 0: # i.e. at least one AHF_mov file has been found
self.fluxmean = m1.data[0, ...].mean(axis=0)
self.fluxstd = m1.data[0, ...].std(axis=0)
else:
self.fluxmean = rderavg(self.tempmean, eta=self.radratio,
exclude=False, spectral=False)
self.fluxstd = rderavg(self.tempstd, eta=self.radratio,
exclude=False, spectral=False)
# Pickle saving
file = open(pickleName, 'wb')
pickle.dump([self.colat, self.tempmean, self.tempstd,\
self.fluxmean, self.fluxstd], file)
file.close()
else:
file = open(pickleName, 'r')
dat = pickle.load(file)
if len(dat) == 5:
self.colat, self.tempmean, self.tempstd, \
self.fluxmean, self.fluxstd = dat
else:
self.colat, self.tempmean, self.fluxmean = dat
self.fluxstd = np.zeros_like(self.fluxmean)
self.tempstd = np.zeros_like(self.fluxmean)
file.close()
self.ri = self.radratio/(1.-self.radratio)
self.ro = 1./(1.-self.radratio)
self.ntheta, self.nr = self.tempmean.shape
self.radius = chebgrid(self.nr-1, self.ro, self.ri)
th2D = np.zeros((self.ntheta, self.nr), dtype=self.radius.dtype)
#self.colat = np.linspace(0., np.pi, self.ntheta)
for i in range(self.ntheta):
th2D[i, :] = self.colat[i]
self.temprmmean = 0.5*simps(self.tempmean*np.sin(th2D), th2D, axis=0)
self.temprmstd = 0.5*simps(self.tempstd*np.sin(th2D), th2D, axis=0)
sinTh = np.sin(self.colat)
d1 = matder(self.nr-1, self.ro, self.ri)
# Conducting temperature profile (Boussinesq only!)
self.tcond = self.ri*self.ro/self.radius-self.ri+self.temprmmean[0]
self.fcond = -self.ri*self.ro/self.radius**2
self.nusstopmean = self.fluxmean[:, 0] / self.fcond[0]
self.nussbotmean = self.fluxmean[:, -1] / self.fcond[-1]
self.nusstopstd = self.fluxstd[:, 0] / self.fcond[0]
self.nussbotstd = self.fluxstd[:, -1] / self.fcond[-1]
# Close to the equator
mask2D = (th2D>=np.pi/2.-angle/2.)*(th2D<=np.pi/2+angle/2.)
mask = (self.colat>=np.pi/2.-angle/2.)*(self.colat<=np.pi/2+angle/2.)
fac = 1./simps(sinTh[mask], self.colat[mask])
self.nussBotEq = fac*simps(self.nussbotmean[mask]*sinTh[mask], self.colat[mask])
self.nussTopEq = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
self.tempEqmean = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
tempC = self.tempstd.copy()
tempC[~mask2D] = 0.
self.tempEqstd = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
dtempEq = np.dot(d1, self.tempEqmean)
self.betaEq = dtempEq[self.nr/2]
# 45\deg inclination
mask2D = (th2D>=np.pi/4.-angle/2.)*(th2D<=np.pi/4+angle/2.)
mask = (self.colat>=np.pi/4.-angle/2.)*(self.colat<=np.pi/4+angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBot45NH = fac*simps(self.nussbotmean[mask]*sinTh[mask], self.colat[mask])
nussTop45NH = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
temp45NH = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
mask2D = (th2D>=3.*np.pi/4.-angle/2.)*(th2D<=3.*np.pi/4+angle/2.)
mask = (self.colat>=3.*np.pi/4.-angle/2.)*(self.colat<=3.*np.pi/4+angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBot45SH = fac*simps(self.nussbotmean[mask]*sinTh[mask], self.colat[mask])
nussTop45SH = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
temp45SH = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
self.nussTop45 = 0.5*(nussTop45NH+nussTop45SH)
self.nussBot45 = 0.5*(nussBot45NH+nussBot45SH)
self.temp45 = 0.5*(temp45NH+temp45SH)
dtemp45 = np.dot(d1, self.temp45)
self.beta45 = dtemp45[self.nr/2]
# Polar regions
mask2D = (th2D<=angle/2.)
mask = (self.colat<=angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBotPoNH = fac*simps(self.nussbotmean[mask]*sinTh[mask], self.colat[mask])
nussTopPoNH = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
tempPolNHmean = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
tempC = self.tempstd.copy()
tempC[~mask2D] = 0.
tempPolNHstd = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
mask2D = (th2D>=np.pi-angle/2.)
mask = (self.colat>=np.pi-angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBotPoSH = fac*simps(self.nussbotmean[mask]*sinTh[mask], self.colat[mask])
nussTopPoSH = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
tempPolSHmean = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
tempC = self.tempstd.copy()
tempC[~mask2D] = 0.
tempPolSHstd = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
self.nussBotPo = 0.5*(nussBotPoNH+nussBotPoSH)
self.nussTopPo = 0.5*(nussTopPoNH+nussTopPoSH)
self.tempPolmean = 0.5*(tempPolNHmean+tempPolSHmean)
self.tempPolstd= 0.5*(tempPolNHstd+tempPolSHstd)
dtempPol = np.dot(d1, self.tempPolmean)
self.betaPol = dtempPol[self.nr/2]
# Inside and outside TC
angleTC = np.arcsin(self.ri/self.ro)
mask2D = (th2D<=angleTC)
mask = (self.colat<=angleTC)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussITC_NH = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
mask2D = (th2D>=np.pi-angleTC)
mask = (self.colat>=np.pi-angleTC)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussITC_SH = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
self.nussITC = 0.5*(nussITC_NH+nussITC_SH)
mask2D = (th2D>=angleTC)*(th2D<=np.pi-angleTC)
mask = (self.colat>=angleTC)*(self.colat<=np.pi-angleTC)
fac = 1./simps(sinTh[mask], self.colat[mask])
self.nussOTC = fac*simps(self.nusstopmean[mask]*sinTh[mask], self.colat[mask])
if iplot:
self.plot()
print(self)
def __init__(self, iplot=False, angle=10, pickleName='thHeat.pickle'):
"""
:param iplot: a boolean to toggle the plots on/off
:type iplot: bool
:param angle: the integration angle in degrees
:type angle: float
:pickleName: calculations a
"""
angle = angle * np.pi / 180
if os.path.exists('tInitAvg'):
file = open('tInitAvg', 'r')
tstart = float(file.readline())
file.close()
logFiles = scanDir('log.*')
tags = []
for lg in logFiles:
nml = MagicSetup(quiet=True, nml=lg)
if nml.start_time > tstart:
if os.path.exists('bLayersR.%s' % nml.tag):
tags.append(nml.tag)
if len(tags) == 0:
tags = [nml.tag]
print('Only 1 tag: %s' % tags)
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
a = AvgField()
self.nuss = a.nuss
else:
logFiles = scanDir('log.*')
MagicSetup.__init__(self, quiet=True, nml=logFiles[-1])
if not os.path.exists(pickleName):
# reading ATmov
k = 0
for tag in tags:
file = 'ATmov.%s' % tag
if os.path.exists(file):
if k == 0:
m = Movie(file=file, iplot=False)
print(file)
else:
m += Movie(file=file, iplot=False)
print(file)
k += 1
# reading AHF_mov
kk = 0
for tag in tags:
file = 'AHF_mov.%s' % tag
if os.path.exists(file):
if kk == 0:
m1 = Movie(file=file, iplot=False)
print(file)
else:
m1 += Movie(file=file, iplot=False)
print(file)
kk += 1
self.tempmean = m.data.mean(axis=0)
self.colat = m.theta
if kk > 0: # i.e. at least one AHF_mov file has been found
self.flux = m1.data.mean(axis=0)
else:
self.flux = rderavg(self.tempmean, eta=self.radratio,
exclude=False, spectral=False)
# Pickle saving
file = open(pickleName, 'wb')
pickle.dump([self.colat, self.tempmean, self.flux], file)
file.close()
else:
file = open(pickleName, 'r')
self.colat, self.tempmean, self.flux = pickle.load(file)
file.close()
self.ri = self.radratio/(1.-self.radratio)
self.ro = 1./(1.-self.radratio)
self.ntheta, self.nr = self.tempmean.shape
self.radius = chebgrid(self.nr-1, self.ro, self.ri)
th2D = np.zeros((self.ntheta, self.nr), dtype=self.radius.dtype)
#self.colat = np.linspace(0., np.pi, self.ntheta)
for i in range(self.ntheta):
th2D[i, :] = self.colat[i]
self.temprm = 0.5*simps(self.tempmean*np.sin(th2D), th2D, axis=0)
sinTh = np.sin(self.colat)
d1 = matder(self.nr-1, self.ro, self.ri)
# Conducting temperature profile (Boussinesq only!)
self.tcond = self.ri*self.ro/self.radius-self.ri+self.temprm[0]
self.fcond = -self.ri*self.ro/self.radius**2
self.nusstop = self.flux[:, 0] / self.fcond[0]
self.nussbot = self.flux[:, -1] / self.fcond[-1]
# Close to the equator
mask2D = (th2D>=np.pi/2.-angle/2.)*(th2D<=np.pi/2+angle/2.)
mask = (self.colat>=np.pi/2.-angle/2.)*(self.colat<=np.pi/2+angle/2.)
fac = 1./simps(sinTh[mask], self.colat[mask])
self.nussBotEq = fac*simps(self.nussbot[mask]*sinTh[mask], self.colat[mask])
self.nussTopEq = fac*simps(self.nusstop[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
self.tempEq = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
dtempEq = np.dot(d1, self.tempEq)
self.betaEq = dtempEq[self.nr/2]
# 45\deg inclination
mask2D = (th2D>=np.pi/4.-angle/2.)*(th2D<=np.pi/4+angle/2.)
mask = (self.colat>=np.pi/4.-angle/2.)*(self.colat<=np.pi/4+angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBot45NH = fac*simps(self.nussbot[mask]*sinTh[mask], self.colat[mask])
nussTop45NH = fac*simps(self.nusstop[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
temp45NH = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
mask2D = (th2D>=3.*np.pi/4.-angle/2.)*(th2D<=3.*np.pi/4+angle/2.)
mask = (self.colat>=3.*np.pi/4.-angle/2.)*(self.colat<=3.*np.pi/4+angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBot45SH = fac*simps(self.nussbot[mask]*sinTh[mask], self.colat[mask])
nussTop45SH = fac*simps(self.nusstop[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
temp45SH = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
self.nussTop45 = 0.5*(nussTop45NH+nussTop45SH)
self.nussBot45 = 0.5*(nussBot45NH+nussBot45SH)
self.temp45 = 0.5*(temp45NH+temp45SH)
dtemp45 = np.dot(d1, self.temp45)
self.beta45 = dtemp45[self.nr/2]
# Polar regions
mask2D = (th2D<=angle/2.)
mask = (self.colat<=angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBotPoNH = fac*simps(self.nussbot[mask]*sinTh[mask], self.colat[mask])
nussTopPoNH = fac*simps(self.nusstop[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
tempPolNH = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
mask2D = (th2D>=np.pi-angle/2.)
mask = (self.colat>=np.pi-angle/2.)
fac = 1./simps(np.sin(self.colat[mask]), self.colat[mask])
nussBotPoSH = fac*simps(self.nussbot[mask]*sinTh[mask], self.colat[mask])
nussTopPoSH = fac*simps(self.nusstop[mask]*sinTh[mask], self.colat[mask])
sinC = sinTh.copy()
sinC[~mask] = 0.
fac = 1./simps(sinC, self.colat)
tempC = self.tempmean.copy()
tempC[~mask2D] = 0.
tempPolSH = fac*simps(tempC*np.sin(th2D), th2D, axis=0)
self.nussBotPo = 0.5*(nussBotPoNH+nussBotPoSH)
self.nussTopPo = 0.5*(nussTopPoNH+nussTopPoSH)
self.tempPol = 0.5*(tempPolNH+tempPolSH)
dtempPol = np.dot(d1, self.tempPol)
self.betaPol = dtempPol[self.nr/2]
if iplot:
self.plot()
print(self)
