def fsizewind(namefile):
# load data
data = np.loadtxt(namefile+"_1.txt",delimiter=";")
s = data[:,1] ; v = data[:,5]
# plot drop = f(size)
restrict = (s > 0)
dropl = ppplot.plot1d() ; dropl.f = v[restrict] ; dropl.x = s[restrict]
dropl.linestyle,dropl.marker,dropl.color,dropl.fmt = '','.','r',"%.1f"
dropl.xlabel = "Vortex size (m)" ; dropl.ylabel = r"Friction velocity (m s$^{-1}$)"
#dropl.logx= True ; dropl.logy = True
dropl.makeshow()
def fdropsize(namefile):
# load data
data = np.loadtxt(namefile+"_1.txt",delimiter=";")
s = data[:,1] ; d = data[:,2]
# plot drop = f(size)
restrict = (s > 0)
dropl = ppplot.plot1d() ; dropl.f = d[restrict] ; dropl.x = s[restrict]
dropl.linestyle,dropl.marker,dropl.color,dropl.fmt = '','.','r',"%.1f"
dropl.xlabel = "Vortex size (m)" ; dropl.ylabel = "Pressure drop (Pa)"
#dropl.logx= True ; dropl.logy = True
dropl.makeshow()
url = "https://raw.githubusercontent.com/aymeric-spiga/planetoplot/master/examples/ppplot/sounding.txt"
sounding = urllib.urlopen(url).read()
soundingfile = open('sounding.txt', 'w').write(sounding)
# and loaded using `numpy.loadtxt()`
# In[23]:
press, z_alt, temp, dew, hum, mix, wdir, wknot, thta, thte, thtv = np.loadtxt(
"sounding.txt", skiprows=8, unpack=True)
# before the variables can be easily displayed using `ppplot` through a one-line instruction
# In[24]:
ppplot.plot1d(f=temp).makeshow()
# A more elaborate plot can be obtained as well by setting more attributes for the `plot1d` class object
# In[25]:
sd = ppplot.plot1d()
sd.f = z_alt
sd.x = temp
sd.linestyle = '-'
sd.marker = '.'
sd.color = 'r'
sd.ycoeff = 1.e-3
sd.title = "A random terrestrial sounding"
sd.legend = "Fort Smith 00Z 26 Sep 2013"
sd.xlabel = "Temperature ($^{\circ}$C)"
lat = data[:, 0]
lon = data[:, 1]
ls = data[:, 2]
u = data[:, 3:15]
data = np.loadtxt("v.txt")
v = data[:, 3:15]
# computations
wind = u**2 + v**2
wind = np.sqrt(wind)
# get evolution over season
ind = np.where(lon == dalon)
# make a simple plot
pl = ppplot.plot1d()
pl.x = range(0, 360, 30)
pl.xlabel = "L$_s$ ($^{\circ}$)"
pl.ylabel = "Wind speed (m s$^{-1}$)"
pl.out = "png"
pl.filename = "lsdune"
pl.f = u[ind][:, dalt]
pl.legend = "WE component"
pl.make()
pl.f = v[ind][:, dalt]
pl.legend = "SN component"
pl.make()
pl.f = wind[ind][:, dalt]
#! /usr/bin/env python
from ppclass import pp
import planets
import ppplot
fi = "DRAG90days_DISSIP10000_year7_912791376_512_z5"
u,lon,lat,p,t = pp(file=fi+".nc",var="u",t=0,z=0,x="-180,180").getfd()
# index = acosphi*((omega*acosphi)+u) / (omega*a*a)
sindex = planets.Saturn.superrot(u=u,lat=lat)
pl = ppplot.plot1d()
pl.f = sindex*1000.
pl.x = lat
pl.ylabel = r'Local superrotation index $s = \mathcal{M}_u / \Omega a^2$ ($\times 10^{-3}$)'
pl.xmin = -10.
pl.xmax = 10.
pl.fmt = '%.0f'
pl.ymin = -30.
pl.ymax = 10.
pl.marker = ''
pl.xlabel = "Latitude (deg)"
pl.make()
ppplot.save(mode="png",filename=fi+"_superrot")
req.changetime = "mars_dayini"
#prof,xx,yy,zz,tt = req.getfd()
### MCD
z,tpot,q,u,v = np.loadtxt("input_sounding",skiprows=1,unpack=True)
r,cp,p,rho,t = np.loadtxt("input_therm",unpack=True)
hgt,tsurf = np.loadtxt("input_more",unpack=True)
q = 0.001*q
### PLOT
nnn=60
dd=10
ppplot.rainbow(cb="jet",num=1+(nnn/dd))
sdg = ppplot.plot1d()
sdg.f = z-hgt
sdg.x = q
sdg.x = t
sdg.legend = 'mcd'
sdg.marker = 's'
sdg.color = 'w'
sdg.make()
nnn=60
dd=10
ppplot.rainbow(cb="jet",num=nnn/dd)
ppp = ppplot.plot1d()
ppp.marker = '.'
r.xmin = -90.
r.xmax = 90.
r.colorbar = "spectral"
r.fmt = "%.0f"
r.swaplab = False
r.xlabel = "Latitude ($^{\circ}$N)"
r.ylabel = "Pressure (Pa)"
r.units = "m s$^{-1}$"
r.make()
ppplot.save(mode="png",filename="section",includedate=False)
ppplot.close()
###################################
ppplot.figuref(x=12,y=8)
##
r = ppplot.plot1d()
r.f = gmcbwind
r.x = gmcblat
r.marker = '.'
r.linestyle = ''
r.color = 'p'
r.legend = "Cassini ISS CB (GM11)"
r.make()
##
r = ppplot.plot1d()
r.f = gmmtwind
r.x = gmmtlat
r.marker = '.'
r.linestyle = ''
r.color = 'm'
r.legend = "Cassini ISS MT (GM11)"
dtlwr = pp(file=zefile,t=ttt,x=lon,y=lat,var="dtlwr").getf()
dtswr = pp(file=zefile,t=ttt,x=lon,y=lat,var="dtswr").getf()
geop = pp(file=zefile,t=ttt,x=lon,y=lat,var="geop").getf()
### COMPUTATIONS
refpres = pres[0] ; surftpot = temp[0] ; surfh = 0.
### -- tpot
tpot = temp*(refpres/pres)**(Venus.R()/Venus.cp)
### -- alt
#alt = Venus.H(T0=temp)*np.log(refpres/pres)
alt = geop / Venus.g
### -- rho
rho = pres / Venus.R() / temp
### CHECK WITH A PLOT
pl = ppplot.plot1d(f=alt,x=tpot).makeshow()
pl = ppplot.plot1d(f=alt,x=rho).makeshow()
pl = ppplot.plot1d(f=alt,x=temp).makeshow()
### OPEN FILES TO BE WRITTEN
sounding = open("input_sounding", "w")
additional = open("input_therm", "w")
more = open("input_more", "w")
hr = open("input_hr", "w")
### GET and WRITE SURFACE VALUES
sounding.write( "%10.2f%12.2f%12.2f\n" % (refpres/100.,surftpot,0.) )
more.write( "%10.2f%10.2f" % (surfh,surftpot) )
### GET and WRITE VERTICAL PROFILE
nz = len(pres)
wheremin = np.argmin(diff) + 8
pblh3[indt] = np.mean(geop[tt,wheremin,:,:]) / grav
## sometimes spurious values caused by GW
diff = 100.*np.abs(pblh3[indt]-pblh1[indt])/pblh1[indt]
if diff > 33.: pblh3[indt] = pblh1[indt]
pblh[indt] = np.mean([pblh1[indt],pblh2[indt],pblh3[indt]])
## remove small or negative values
pblh = pblh[pblh > 100.]
## compute mean height
altitude = np.mean(np.mean(np.mean(geop,axis=3),axis=2),axis=0)/grav
altitude = altitude[0:nz]
file1=open('pbl.txt','w')
for val in pblh:
file1.write("%8.3f\n"%(val))
file1.close()
pl = ppplot.plot1d() # plot of the boundary layer height time evolution
pl.f = pblh
pl.makeshow()
pl = ppplot.plot2d() # shade of the vertical eddy heat flux time evolution
pl.f = vehfmean
pl.y = altitude
pl.makeshow()
sounding = urllib.urlopen(url).read()
soundingfile = open('sounding.txt','w').write(sounding)
# and loaded using `numpy.loadtxt()`
# In[23]:
press,z_alt,temp,dew,hum,mix,wdir,wknot,thta,thte,thtv = np.loadtxt("sounding.txt",skiprows=8,unpack=True)
# before the variables can be easily displayed using `ppplot` through a one-line instruction
# In[24]:
ppplot.plot1d(f=temp).makeshow()
# A more elaborate plot can be obtained as well by setting more attributes for the `plot1d` class object
# In[25]:
sd = ppplot.plot1d()
sd.f = z_alt
sd.x = temp
sd.linestyle = '-'
sd.marker = '.'
sd.color = 'r'
sd.ycoeff = 1.e-3
sd.title = "A random terrestrial sounding"
sd.legend = "Fort Smith 00Z 26 Sep 2013"
#! /usr/bin/env python import numpy as np import ppplot as ppp phalf = 2.e5 transi = 3. transi = 2. press = np.logspace(6,0) pl=ppp.plot1d() pl.f = press pl.x = 0.5*(1+np.tanh(transi*np.log(press/phalf))) pl.fmt = "%2.e" pl.logy = True #pl.logx = True pl.invert = True pl.makeshow()
#! /usr/bin/env python
import ppplot
import numpy as np
# load data
# http://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html
p,z,t,dew,hum,mix,wdir,wknot,thta,thte,thtv \
= np.loadtxt("sounding.txt",skiprows=8,unpack=True)
# make a simple plot
sdg = ppplot.plot1d()
sdg.f = z
sdg.x = t
sdg.makeshow()
# Tweaking a little bit the plot
sdg.linestyle = '-'
sdg.marker = '.'
sdg.color = 'r'
sdg.ycoeff = 1.e-3
sdg.title = "A random terrestrial sounding"
sdg.legend = "Fort Smith 00Z 26 Sep 2013"
sdg.xlabel = "Temperature ($^{\circ}$C)"
sdg.ylabel = "Altitude (km)"
sdg.makeshow()
sdg.make()
ppplot.save(mode="png", filename="plot", res=50, includedate=False)
## method 3: convective motions
diff = np.abs(wmax[indt, 8:] - np.max(wmax[indt, :] / 3.))
wheremin = np.argmin(diff) + 8
pblh3[indt] = np.mean(geop[tt, wheremin, :, :]) / grav
## sometimes spurious values caused by GW
diff = 100. * np.abs(pblh3[indt] - pblh1[indt]) / pblh1[indt]
if diff > 33.: pblh3[indt] = pblh1[indt]
pblh[indt] = np.mean([pblh1[indt], pblh2[indt], pblh3[indt]])
## remove small or negative values
pblh = pblh[pblh > 100.]
## compute mean height
altitude = np.mean(np.mean(np.mean(geop, axis=3), axis=2), axis=0) / grav
altitude = altitude[0:nz]
file1 = open('pbl.txt', 'w')
for val in pblh:
file1.write("%8.3f\n" % (val))
file1.close()
pl = ppplot.plot1d() # plot of the boundary layer height time evolution
pl.f = pblh
pl.makeshow()
pl = ppplot.plot2d() # shade of the vertical eddy heat flux time evolution
pl.f = vehfmean
pl.y = altitude
pl.makeshow()
#! /usr/bin/env python
import ppplot
import numpy as np
# load data
# http://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html
p,z,t,dew,hum,mix,wdir,wknot,thta,thte,thtv \
= np.loadtxt("sounding.txt",skiprows=8,unpack=True)
# make a simple plot
sdg = ppplot.plot1d()
sdg.f = z
sdg.x = t
sdg.makeshow()
# Tweaking a little bit the plot
sdg.linestyle = '-'
sdg.marker = '.'
sdg.color = 'r'
sdg.ycoeff = 1.e-3
sdg.title = "A random terrestrial sounding"
sdg.legend = "Fort Smith 00Z 26 Sep 2013"
sdg.xlabel = "Temperature ($^{\circ}$C)"
sdg.ylabel = "Altitude (km)"
sdg.makeshow()
sdg.make()
ppplot.save(mode="png",filename="plot",res=50,includedate=False)
