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Cwind.py
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Cwind.py
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import h5py
from mpl_toolkits.basemap import Basemap # Import the map plotting interface.
import numpy as np
import matplotlib.pyplot as plt # Matplotlib is a scientific plotting package.
from matplotlib.pyplot import cm
from ipywidgets import *
from IPython.display import display
class Cwind:
def __init__(self):
x = h5py.File('./DATA/wind.h5')
self.rho = x['.']['rho'].value
self.u = x['.']['u'].value
self.v = x['.']['v'].value
self.w = x['.']['w'].value
x.close()
self.npn = 10
self.latn = 18
self.lonn = 36
self.month = ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
self.lats = 85.0 - np.arange(18)*10
self.lons = -175 + np.arange(36)*10
self.action = ToggleButtons(description='Plottype',options=['zonal-aver','lon-pres','lat-pres','lat-lon'],value='zonal-aver')
self.m_slider = IntSlider(description='Month',min=1, max=12, step=1, value=0)
self.lon_slider = IntSlider(description='Longitude',min=-175, max=175, step=10, value=-175)
self.lat_slider = IntSlider(description='Latitude ',min=-85, max=85, step=10, value=5)
self.pres_slider = IntSlider(description='Pressure ',min=100, max=1000, step=100, value=1000)
def plot_wind(self,action=ToggleButtons(),month=0,lon=0,lat=0,pres=0):
if action=='zonal-aver':
self.lat_slider.visible=False
self.lon_slider.visible=False
self.pres_slider.visible=False
elif action == 'lon-pres':
self.lat_slider.visible=True
self.lon_slider.visible=False
self.pres_slider.visible=False
elif action == 'lat-pres':
self.lat_slider.visible=False
self.lon_slider.visible=True
self.pres_slider.visible=False
elif action == 'lat-lon':
self.lat_slider.visible=False
self.lon_slider.visible=False
self.pres_slider.visible=True
else:
None
imonth = month-1
itake = (lon+175)/10
jtake = 17-(lat+85)/10
ktake = 10 - pres/100
# get the u wind in the center:
un = (self.u[imonth,:,:,:]+np.roll(self.u[imonth,:,:,:],1,axis=2))*0.5
vn = (self.v[imonth,:,0:self.latn,:]+self.v[imonth,:,1:self.latn+1,:])*0.5
# get the w-wind at the middle of the pressure layers:
grav=9.81
# initially winds are given on: 1000,950,850.....150,100 hPa
x = [0.0, 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5, 9.]
xinterp = np.arange(10) # 1000 ---> 100 hPa
wn=np.zeros((self.npn,self.latn,self.lonn))
for i in range(self.lonn):
for j in range(self.latn):
wn[:,j,i]=np.interp(xinterp,x,self.w[imonth,:,j,i])
for k in range(self.npn):
wn[k,:,:]/=(-self.rho[k]*grav)
speed = np.sqrt(un**2 + vn**2)
if action == 'lon-pres':
wrz = wn[:,jtake,:]
urz = un[:,jtake,:]
speedz = speed[:,jtake,:]
maxx = np.max(np.abs(urz))
maxy = np.max(np.abs(wrz))
Y,X = np.mgrid[ 1000:100:10j, -175:175:36j]
yv = wrz/maxy
xv = urz/maxx
plot1,ax = plt.subplots(figsize=(10,6))
plt.quiver(X, Y, xv, yv, # data
speedz, # colour the arrows based on this array
cmap=cm.rainbow, # colour map
headlength=7) # length of the arrows
ax.set_xlim(-180,180)
ax.set_ylim(1050,50)
ax.set_xlabel('Longitude (degrees)')
ax.set_ylabel('Pressure (hPa)')
if self.lats[jtake]> 0.:
ax.text(-170,150,'Latitude: %4iN'%(int(self.lats[jtake])))
else:
ax.text(-170,150,'Latitude: %4iS'%(-int(self.lats[jtake])))
ax.text(50,150,'Month: %s'%(self.month[imonth]))
ax.text(50,970,'Max w %6.3f m/s'%(maxy))
ax.text(-170,970,'Max u %6.0f m/s'%(maxx))
plt.title('Windfield (color: horizontal windspeed (m/s))')
plt.colorbar()
plt.show(plot1) # display the plot
elif action == 'lat-pres':
wrz = wn[:,:,itake]
vrz = vn[:,:,itake]
speedz = speed[:,:,itake]
maxx = np.max(np.abs(vrz))
maxy = np.max(np.abs(wrz))
Y,X = np.mgrid[ 1000:100:10j, 85:-85:18j]
yv = wrz/maxy
xv = vrz/maxx
plot1,ax = plt.subplots(figsize=(10,6))
plt.quiver(X, Y, xv, yv, # data
speedz, # colour the arrows based on this array
cmap=cm.rainbow, # colour map
headlength=5) # length of the arrows
ax.set_xlim(-90,90)
ax.set_ylim(1050,50)
ax.set_xlabel('Latitude (degrees)')
ax.set_ylabel('Pressure (hPa)')
if self.lons[itake]> 0.:
ax.text(-85,150,'Longtude: %4iE'%(int(self.lons[itake])))
else:
ax.text(-85,150,'Longitude: %4iW'%(-int(self.lons[itake])))
ax.text(30,150,'Month: %s'%(self.month[imonth]))
ax.text(30,970,'Max w %6.3f m/s'%(maxy))
ax.text(-85,970,'Max v %6.1f m/s'%(maxx))
plt.title('Windfield (color: horizontal windspeed (m/s))')
plt.colorbar()
plt.show(plot1) # display the plot
elif action=='zonal-aver':
# zonal average
wrz = wn[:,:,:].mean(axis=2)
vrz = vn[:,:,:].mean(axis=2)
speedz = speed[:,:,:].mean(axis=2)
maxx = np.max(np.abs(vrz))
maxy = np.max(np.abs(wrz))
y,x = np.mgrid[ 1000:100:10j, 85:-85:18j]
yv = wrz/maxy
xv = vrz/maxx
plot1,ax = plt.subplots(figsize=(10,6))
plt.quiver(x, y, xv, yv, # data
speedz, # colour the arrows based on this array
cmap=cm.rainbow, # colour map
headlength=5) # length of the arrows
#plt.streamplot(x, y, xv, yv, # data
# color=speedz, # array that determines the colour
# cmap=cm.rainbow, # colour map
# linewidth=2, # line thickness
# arrowstyle='->', # arrow style
# arrowsize=1.5) # arrow size
ax.set_xlim(-90,90)
ax.set_ylim(1050,50)
ax.set_xlabel('latitude (degrees)')
ax.set_ylabel('pressure (hPa)')
ax.text(-85,150,'zonal average')
ax.text(30,150,'month: %s'%(self.month[imonth]))
ax.text(30,970,'max w %6.3f m/s'%(maxy))
ax.text(-85,970,'max v %6.1f m/s'%(maxx))
plt.title('windfield (color: horizontal windspeed (m/s))')
plt.colorbar()
plt.show(plot1) # display the plot
elif action=='lat-lon':
# zonal average
urz = un[ktake,:,:]
vrz = vn[ktake,:,:]
speedz = speed[ktake,:,:]
maxx = np.max(np.abs(urz))
maxy = np.max(np.abs(vrz))
y,x = np.mgrid[ 85:-85:18j,-175:175:36j]
xv = urz/maxx
yv = vrz/maxy
plot1,ax = plt.subplots(figsize=(14,6))
m = Basemap(projection='cyl',llcrnrlat=-90,urcrnrlat=90,\
llcrnrlon=-180,urcrnrlon=180,resolution='c')
m.drawcoastlines()
#m.fillcontinents(color='coral',lake_color='aqua')
# draw parallels and meridians.
m.drawparallels(np.arange(-90.,91.,30.))
m.drawmeridians(np.arange(-180.,181.,60.))
#m.drawmapboundary(fill_color='aqua')
m.quiver(x, y, xv, yv, # data
speedz, # colour the arrows based on this array
cmap=cm.rainbow, # colour map
headlength=5) # length of the arrows
#plt.streamplot(x, y, xv, yv, # data
# color=speedz, # array that determines the colour
# cmap=cm.rainbow, # colour map
# linewidth=2, # line thickness
# arrowstyle='->', # arrow style
# arrowsize=1.5) # arrow size
#ax.set_xlabel('logitude (degrees)')
#ax.set_ylabel('latitude (degrees)')
#ax.text(-170,85,'Pressure: %4i hPa'%(1000-ktake*100))
#ax.text(50,85,'month: %s'%(self.month[m]))
#ax.text(-170,-85,'max u %6.1f m/s'%(maxx))
#ax.text(50,-85,'max v %6.1f m/s'%(maxy))
plt.title('windfield %4i hPa ; month: %s (color: horizontal windspeed (m/s))'%(1000-ktake*100, self.month[imonth]))
plt.colorbar()
plt.show(plot1) # display the plot
else:
None