def Es(T, method=None):
"""Computes saturated pressure in Pa given T in K, using the method:
1: Hyland-Wexler formulation, polynomial coeff (absolute norm)
2: Wexler formulation
3: Hyland-Wexler formulation, polynomial coeff (relative error norm)
4: classic Goff Gratch equation
5: 6.112*numpy.ma.exp(17.67*tempc/(tempc+243.5))
Default is method 1
Note: 1 and 2 use method 3 where T is not : 173.15 < T < 473.15
ref for 1, 2 and 3:
Piotr Flatau and al., Journal of Applied Met., Vol 31, Dec 1992 ( http://ams.allenpress.com/perlserv/?request=get-document&doi=10.1175%2F1520-0450(1992)031%3C1507%3APFTSVP%3E2.0.CO%3B2&ct=1 )
"""
if method is None:
method = 1
if method == 1:
## Put in C
x = T - 273.15
## Water vapor
c0 = 0.611220713E03
c1 = 0.443944344E02
c2 = 0.143195336E01
c3 = 0.263350515E-01
c4 = 0.310636053E-03
c5 = 0.185218710E-05
c6 = 0.103440324E-07
c7 = -0.468258100E-10
c8 = 0.466533033E-13
eswat = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x *
(c5 + x *
(c6 + x *
(c7 + x * c8)))))))
## ice
c0 = .611153246E03
c1 = .503261230E02
c2 = .188595709E01
c3 = .422115970E-01
c4 = .620376691E-03
c5 = .616082536E-05
c6 = .405172828E-07
c7 = .161492905E-09
c8 = .297886454E-12
esice = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x *
(c5 + x *
(c6 + x *
(c7 + x * c8)))))))
## Combine
es = MV2.where(MV2.less(T, 273.15), esice, eswat)
## Overwrite values outside valid range with method 2
mn, mx = genutil.minmax(T)
if mn < 173.16 or mx > 473.15:
es2 = Es(T, method=2)
es = MV2.where(MV2.less(T, 173.16), es2, es)
es = MV2.where(MV2.greater(T, 473.15), es2, es)
elif method == 2:
# over water
g0 = -0.29912729E4
g1 = -0.60170128E4
g2 = 0.1887643854E2
g3 = -0.28354721E-1
g4 = 0.17838301E-4
g5 = -0.84150417E-9
g6 = 0.44412543E-12
g7 = 0.2858487E1
# over ice
k0 = -0.58653696e4
k1 = 0.2224103300E2
k2 = 0.13749042E-1
k3 = -0.34031775E-4
k4 = 0.26967687E-7
k5 = 0.6918651
esice = (k0 + (k1 + k5 * MV2.log(T) +
(k2 + (k3 + k4 * T) * T) * T) * T) / T # over ice
eswat = (g0 + (g1 + (g2 + g7 * MV2.log(T) +
(g3 + (g4 + (g5 + g6 * T) * T) * T) * T) * T) *
T) / T**2 # over water
es = MV2.where(MV2.less(T, 273.15), esice, eswat)
es = MV2.exp(es)
elif method == 3:
## Put in C
x = T - 273.15
## Water vapor
c0 = 0.611213476E03
c1 = 0.444007856E02
c2 = 0.143064234E01
c3 = 0.264461437E-01
c4 = 0.305930558E-03
c5 = 0.196237241E-05
c6 = 0.892344772E-08
c7 = -0.373208410E-10
c8 = 0.209339997E-13
eswat = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x *
(c5 + x *
(c6 + x *
(c7 + x * c8)))))))
## ice
c0 = .611123516E03
c1 = .503109514E02
c2 = .1888369801E01
c3 = .420547422E-01
c4 = .614396778E-03
c5 = .602780717E-05
c6 = .387940929E-07
c7 = .149436277E-09
c8 = .262655803E-12
esice = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x *
(c5 + x *
(c6 + x *
(c7 + x * c8)))))))
## Combine
es = MV2.where(MV2.less(T, 273.15), esice, eswat)
## Overwrite values outside valid range with method 2
mn, mx = genutil.minmax(T)
if mn < 173.16 or mx > 473.15:
es2 = Es(T, method=2)
es = MV2.where(MV2.less(T, 173.16), es2, es)
es = MV2.where(MV2.greater(T, 473.15), es2, es)
elif method == 4:
est = 101324.6 #Pa
Ts = 373.16 / T
a = -7.90298
b = 5.02808
c = -1.3816E-7
d = 11.344
f = 8.1328E-3
h = -3.49149
maxexp = int(numpy.log10(numpy.finfo(numpy.float).max))
minexp = 1 - a
es = a * (Ts - 1.)
es = es + b * numpy.ma.log10(Ts)
A = d * (1. - Ts)
A = numpy.ma.masked_greater(A, maxexp)
A = numpy.ma.masked_less(A, minexp)
es = es + c * (numpy.ma.power(10, A) - 1.)
A = h * (Ts - 1.)
A = numpy.ma.masked_greater(A, maxexp)
A = numpy.ma.masked_less(A, minexp)
es = es + f * (numpy.ma.power(10, A) - 1.)
es = est * numpy.ma.power(10, es)
elif method == 5:
tempc = T - 273.15
es = 611.2 * numpy.ma.exp(17.67 * tempc / (tempc + 243.5))
return es
def Es(T, method=None):
"""Computes saturated pressure in Pa given T in K, using the method:
1: Hyland-Wexler formulation, polynomial coeff (absolute norm)
2: Wexler formulation
3: Hyland-Wexler formulation, polynomial coeff (relative error norm)
4: classic Goff Gratch equation
5: 6.112*numpy.ma.exp(17.67*tempc/(tempc+243.5))
Default is method 1
Note: 1 and 2 use method 3 where T is not : 173.15 < T < 473.15
ref for 1, 2 and 3:
Piotr Flatau and al., Journal of Applied Met., Vol 31, Dec 1992
( http://ams.allenpress.com/perlserv/?request=get-document&\
doi=10.1175%2F1520-0450(1992)031%3C1507%3APFTSVP%3E2.0.CO%3B2&ct=1 )
"""
if method is None:
method = 1
if method == 1:
# Put in C
x = T - 273.15
# Water vapor
c0 = 0.611220713e03
c1 = 0.443944344e02
c2 = 0.143195336e01
c3 = 0.263350515e-01
c4 = 0.310636053e-03
c5 = 0.185218710e-05
c6 = 0.103440324e-07
c7 = -0.468258100e-10
c8 = 0.466533033e-13
eswat = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x * (c5 + x * (c6 + x * (c7 + x * c8)))))))
# ice
c0 = 0.611153246e03
c1 = 0.503261230e02
c2 = 0.188595709e01
c3 = 0.422115970e-01
c4 = 0.620376691e-03
c5 = 0.616082536e-05
c6 = 0.405172828e-07
c7 = 0.161492905e-09
c8 = 0.297886454e-12
esice = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x * (c5 + x * (c6 + x * (c7 + x * c8)))))))
# Combine
es = MV2.where(MV2.less(T, 273.15), esice, eswat)
# Overwrite values outside valid range with method 2
mn, mx = genutil.minmax(T)
if mn < 173.16 or mx > 473.15:
es2 = Es(T, method=2)
es = MV2.where(MV2.less(T, 173.16), es2, es)
es = MV2.where(MV2.greater(T, 473.15), es2, es)
elif method == 2:
# over water
g0 = -0.29912729e4
g1 = -0.60170128e4
g2 = 0.1887643854e2
g3 = -0.28354721e-1
g4 = 0.17838301e-4
g5 = -0.84150417e-9
g6 = 0.44412543e-12
g7 = 0.2858487e1
# over ice
k0 = -0.58653696e4
k1 = 0.2224103300e2
k2 = 0.13749042e-1
k3 = -0.34031775e-4
k4 = 0.26967687e-7
k5 = 0.6918651
esice = (k0 + (k1 + k5 * MV2.log(T) + (k2 + (k3 + k4 * T) * T) * T) * T) / T # over ice
eswat = (
g0 + (g1 + (g2 + g7 * MV2.log(T) + (g3 + (g4 + (g5 + g6 * T) * T) * T) * T) * T) * T
) / T ** 2 # over water
es = MV2.where(MV2.less(T, 273.15), esice, eswat)
es = MV2.exp(es)
elif method == 3:
# Put in C
x = T - 273.15
# Water vapor
c0 = 0.611213476e03
c1 = 0.444007856e02
c2 = 0.143064234e01
c3 = 0.264461437e-01
c4 = 0.305930558e-03
c5 = 0.196237241e-05
c6 = 0.892344772e-08
c7 = -0.373208410e-10
c8 = 0.209339997e-13
eswat = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x * (c5 + x * (c6 + x * (c7 + x * c8)))))))
# ice
c0 = 0.611123516e03
c1 = 0.503109514e02
c2 = 0.1888369801e01
c3 = 0.420547422e-01
c4 = 0.614396778e-03
c5 = 0.602780717e-05
c6 = 0.387940929e-07
c7 = 0.149436277e-09
c8 = 0.262655803e-12
esice = c0 + x * (c1 + x * (c2 + x * (c3 + x * (c4 + x * (c5 + x * (c6 + x * (c7 + x * c8)))))))
# Combine
es = MV2.where(MV2.less(T, 273.15), esice, eswat)
# Overwrite values outside valid range with method 2
mn, mx = genutil.minmax(T)
if mn < 173.16 or mx > 473.15:
es2 = Es(T, method=2)
es = MV2.where(MV2.less(T, 173.16), es2, es)
es = MV2.where(MV2.greater(T, 473.15), es2, es)
elif method == 4:
est = 101324.6 # Pa
Ts = 373.16 / T
a = -7.90298
b = 5.02808
c = -1.3816e-7
d = 11.344
f = 8.1328e-3
h = -3.49149
maxexp = int(numpy.log10(numpy.finfo(numpy.float).max))
minexp = 1 - a
es = a * (Ts - 1.0)
es = es + b * numpy.ma.log10(Ts)
A = d * (1.0 - Ts)
A = numpy.ma.masked_greater(A, maxexp)
A = numpy.ma.masked_less(A, minexp)
es = es + c * (numpy.ma.power(10, A) - 1.0)
A = h * (Ts - 1.0)
A = numpy.ma.masked_greater(A, maxexp)
A = numpy.ma.masked_less(A, minexp)
es = es + f * (numpy.ma.power(10, A) - 1.0)
es = est * numpy.ma.power(10, es)
elif method == 5:
tempc = T - 273.15
es = 611.2 * numpy.ma.exp(17.67 * tempc / (tempc + 243.5))
return es
def testAxisConvert(self):
gm = vcs.create1d()
gm.yaxisconvert = "log10"
data = MV2.arange(10)
data_pow = MV2.power(10, data)
data_pow.id = "test"
self.x.plot(data_pow, gm, bg=self.bg)
self.checkImage("test_vcs_yaxisconvert_log10.png")
self.x.clear()
gm.flip = True
gm.yaxisconvert = "linear"
gm.xaxisconvert = "log10"
self.x.plot(data_pow, gm, bg=self.bg)
self.checkImage("test_vcs_xaxisconvert_log10_flip.png")
self.x.clear()
gm.flip = False
gm.xaxisconvert = "linear"
gm.yaxisconvert = "ln"
data_exp = MV2.exp(data)
data_exp.id = "test"
self.x.plot(data_exp, gm, bg=self.bg)
self.checkImage("test_vcs_yaxisconvert_ln.png")
self.x.clear()
gm.flip = False
gm.xaxisconvert = "area_wt"
gm.yaxisconvert = "linear"
data2 = self.clt("clt",
time=slice(0, 1),
longitude=slice(23, 24),
squeeze=1)
self.x.plot(data2, gm, bg=self.bg)
self.checkImage("test_vcs_xaxisconvert_areawt.png")
self.x.clear()
gm.flip = True
gm.yaxisconvert = "area_wt"
gm.xaxisconvert = "linear"
self.x.plot(data2, gm, bg=self.bg)
self.checkImage("test_vcs_yaxisconvert_areawt_flip.png")
self.x.clear()
gm.flip = False
gm.xaxisconvert = "log10"
gm.yaxisconvert = "ln"
self.x.plot(data_pow, data_exp, gm, bg=self.bg)
self.checkImage("test_vcs_axisconvert_log10_ln.png")
self.x.clear()
#gm.flip = True
data2[:] = MV2.power(10, MV2.arange(1, data2.shape[0] + 1))
data2 = data2[:10]
gm.xaxisconvert = "area_wt"
gm.yaxisconvert = "log10"
self.x.plot(data2, gm, bg=self.bg)
self.checkImage("test_vcs_axisconvert_area_log10.png")
self.x.clear()
gm.flip = True
gm.yaxisconvert = "area_wt"
gm.xaxisconvert = "log10"
self.x.plot(data2, gm, bg=self.bg)
self.checkImage("test_vcs_axisconvert_area_log10_flip.png")
self.x.clear()
gm.flip = False
gm.xaxisconvert = "area_wt"
gm.yaxisconvert = "log10"
data_axis = MV2.array(data2.getAxis(0)[:])
data_axis.id = "test"
self.x.plot(data_axis, data2, gm, bg=self.bg)
self.checkImage("test_vcs_axisconvert_area_log10_2arrays.png")
with self.assertRaises(RuntimeError):
self.x.clear()
gm.flip = True
self.x.plot(data_axis, data2, gm, bg=self.bg)
self.x.clear()
gm.flip = False
gm.xaxisconvert = "area_wt"
gm.yaxisconvert = "log10"
gm.xticlabels1 = {-90: "90S", -80: "80S", -70: "70S", -60: "60S"}
gm.xticlabels2 = {-85: "85S", -75: "75S", -65: "65S", -55: "55S"}
mtics = {}
def func(x):
mtics[x] = ""
map(func, range(-90, -40, 10))
gm.xmtics2 = mtics
mtics = {}
map(func, range(-85, -40, 10))
gm.xmtics1 = mtics
gm.yticlabels1 = {100: "hun"}
gm.yticlabels2 = {1000: "thou"}
gm.ymtics1 = {10: "", 1000: ""}
gm.ymtics2 = {10000: "", 1000: ""}
gm.list()
tmpl = vcs.createtemplate()
for num in ["1", "2"]:
for loc in ["x", "y"]:
for attr in ["mintic", "tic"]:
filled_attr = "{}{}{}".format(loc, attr, num)
print("PRIO FOR ATT:", filled_attr)
obj = getattr(tmpl, filled_attr)
obj.priority = 1
obj.list()
tmpl.xlabel1.priority = 1
tmpl.xlabel2.priority = 1
tmpl.ylabel1.priority = 1
tmpl.ylabel2.priority = 1
self.x.plot(data_axis, data2, gm, tmpl, bg=self.bg)
self.checkImage("test_vcs_axisconvert_area_log10_user_labels.png")
from vacumm.misc.grid.masking import erode_coast
from vacumm.misc.plot import savefigs, add_key
import MV2, numpy as N, matplotlib.pyplot as P
# Champs initial
xx, yy = N.indices((50, 100), 'f')
x0 = y0 = 25
dxy = 30
var = MV2.exp(-((xx - x0)**2 + (yy - y0)**2) / dxy**2)
# Masques
# - reference
mask = var.filled() > .9
mask[:, 50:] = True
mask[15:35, 65:85] = False
# - variable
var[:] = MV2.masked_greater(var, .8)
var[:, 50:] = MV2.masked
# Erode
vare = erode_coast(var, mask)
# Plots
P.figure(figsize=(6, 9))
P.subplots_adjust(hspace=.2)
P.subplot(311)
P.pcolormesh(var.asma())
P.title('Original variable')
add_key(1, color='w')
P.subplot(312)
P.pcolormesh(mask)
from vacumm.misc.grid.masking import erode_coast
from vacumm.misc.plot import savefigs, add_key
import MV2, numpy as N, matplotlib.pyplot as P
# Champs initial
xx, yy = N.indices((50, 100), 'f')
x0 = y0 = 25
dxy = 30
var = MV2.exp(-((xx-x0)**2+(yy-y0)**2)/dxy**2)
# Masques
# - reference
mask = var.filled()>.9
mask[:, 50:] = True
mask[15:35, 65:85] = False
# - variable
var[:] = MV2.masked_greater(var, .8)
var[:, 50:] = MV2.masked
# Erode
vare = erode_coast(var, mask)
# Plots
P.figure(figsize=(6, 9))
P.subplots_adjust(hspace=.2)
P.subplot(311)
P.pcolormesh(var.asma())
P.title('Original variable') ; add_key(1, color='w')
P.subplot(312)
P.pcolormesh(mask)
P.title('Reference mask') ; add_key(2, color='w')
