def xzCloudPlot(nest,time,plotTemp=True,plotRH=False):
nc = openWRF(nest)
Nx,Ny,Nz,longitude,_lats,_dx,_dy,x_nr,y_nr = getDimensions(nc)
heightground_x,heighthalf_xz = _getHeight(nc, time, Nx, -1, Nz, -1, y_nr)
print 'Model height: ' + str(heightground_x[x_nr])
theta = nc.variables['T'][time,:,y_nr,:] + T_base
P = nc.variables['P'][time,:,y_nr,:] + nc.variables['PB'][time,:,y_nr,:]
T = theta*(P/P_bot)**kappa # Temperatur i halvflatene (Kelvin)
rho = P/(R*T) #[kg/m3]
qcloud_xz = 1000.0*nc.variables['QCLOUD'][time,:,y_nr,:]*rho # regner om til g/m3
qrain_xz = 1000.0*nc.variables['QRAIN'][time,:,y_nr,:]*rho
qsnow_xz = 1000.0*nc.variables['QSNOW'][time,:,y_nr,:]*rho
plt.figure()
plt.set_cmap(cmap_red)
plt.axis([0,Nx-1,0.0,z_max])
print u'Cloud water red, snow blue, rain green ($g/m^3$)'
grid = np.reshape(np.tile(arange(Nx),Nz),(Nz,-1))
plt.contourf(grid, heighthalf_xz, qcloud_xz, alpha=0.9,levels=xz_cloudwater_levels, cmap=cmap_red)#
plt.colorbar()
plt.contourf(grid, heighthalf_xz, qrain_xz, alpha=0.6,levels=xz_rain_levels, cmap=cmap_green)#
plt.colorbar()
plt.contourf(grid, heighthalf_xz, qsnow_xz, alpha=0.6,levels=xz_snow_levels,cmap=cmap_blue)#
plt.colorbar()
if plotTemp:
temp_int = arange(-80.0,50.0,2.0)
cs = plt.contour(grid, heighthalf_xz, T-T_zero, temp_int,colors='black',linestyles='solid')#linewidths=4
plt.clabel(cs, inline=1, fmt='%1.0f', fontsize=12,colors='black')
if plotRH:
rh = _getRH(nc,time,-1,y_nr,T,P)
rh_int = arange(90.,111.,5.)
cs = plt.contour(grid, heighthalf_xz,rh , rh_int, colors='grey')
plt.clabel(cs, inline=1, fmt='%1.0f', fontsize=12, colors='grey')
plt.plot(arange(Nx),heightground_x,color='black')
plt.fill_between(arange(Nx),heightground_x,0,facecolor='lightgrey')
plt.xticks(np.arange(0,Nx,8),np.round(longitude[Ny/2,::8], 1), fontsize='small')
plt.yticks(np.arange(0,z_max,dz), fontsize='small')
plt.xlabel('Lengdegrad')
plt.ylabel(u'Høyde [m]')
plt.show()
plt.close()
def skewTPlot(nest, time):
"""
This is the method to use from the outside
nest: The nesting level of the nc-file from WRF
time: The time for which to plot
"""
nc = openWRF(nest)
_Nx, _Ny, _Nz, _longs, _lats, _dx, _dy, x, y = getDimensions(nc)
plt.figure()
_isotherms()
_isobars()
_dry_adiabats()
_moist_adiabats()
P = nc.variables['P'][time, :, y, x] + nc.variables['PB'][time, :, y, x]
_windbarbs(nc, time, y, x, P)
_temperature(nc, time, y, x, P)
_dewpoint(nc, time, y, x, P)
plt.axis([-40, 50, P_b, P_t])
plt.xlabel('Temperatur ($^{\circ}\! C$) ved 1000hPa')
xticks = np.arange(-40, 51, 5)
plt.xticks(xticks,
['' if tick % 10 != 0 else str(tick) for tick in xticks])
plt.ylabel('Trykk (hPa)')
yticks = np.arange(P_bot, P_t - 1, -10**4)
plt.yticks(yticks, yticks / 100)
sfcT = nc.variables['T2'][time, y, x] - T_zero
sfcP = nc.variables['PSFC'][time, y, x]
sfcW = nc.variables['Q2'][time, y, x]
sfcTd = td(e(sfcW, sfcP))
plt.suptitle('Bakketemp: %4.1f$^{\circ}\! C$ Duggpunkt: %3.1f$^{\circ}\! C$ Trykk: %5.1f hPa' % (sfcT,sfcTd,0.01*sfcP), \
fontsize=10, x = 0.5, y = 0.03)
plt.show()
plt.close()
def skewTPlot(nest,time):
"""
This is the method to use from the outside
nest: The nesting level of the nc-file from WRF
time: The time for which to plot
"""
nc = openWRF(nest)
_Nx,_Ny,_Nz,_longs,_lats,_dx,_dy,x,y = getDimensions(nc)
plt.figure()
_isotherms()
_isobars()
_dry_adiabats()
_moist_adiabats()
P = nc.variables['P'][time,:,y,x] + nc.variables['PB'][time,:,y,x]
_windbarbs(nc,time,y,x,P)
_temperature(nc,time,y,x,P)
_dewpoint(nc,time,y,x,P)
plt.axis([-40,50,P_b,P_t])
plt.xlabel('Temperatur ($^{\circ}\! C$) ved 1000hPa')
xticks = np.arange(-40,51,5)
plt.xticks(xticks,['' if tick%10!=0 else str(tick) for tick in xticks])
plt.ylabel('Trykk (hPa)')
yticks = np.arange(P_bot,P_t-1,-10**4)
plt.yticks(yticks,yticks/100)
sfcT = nc.variables['T2'][time,y,x]-T_zero
sfcP = nc.variables['PSFC'][time,y,x]
sfcW = nc.variables['Q2'][time,y,x]
sfcTd = td(e(sfcW,sfcP))
plt.suptitle('Bakketemp: %4.1f$^{\circ}\! C$ Duggpunkt: %3.1f$^{\circ}\! C$ Trykk: %5.1f hPa' % (sfcT,sfcTd,0.01*sfcP), \
fontsize=10, x = 0.5, y = 0.03)
plt.show()
plt.close()
import numpy as np
import cv2
form matplotlib import pyplot as plt
img=cv2.imread('fate_zero.jpg',0)
cv2.imshow("Fate Zero",img)
plt.imshow(img, cmap = 'gray', interpolation = 'bicubic')
plt.xticks([]), plt.yticks([])
plt.show()
key=cv2.waitKey(0) & 0xFF
if key == ord('k'):
cv2.imwrite('Fate Zero.jpeg',img)
cv2.destroyWindow("Fate Zero")
elif key == 27:
cv2.destroyWindow("Fate Zero")
def tzCloudPlot(nest, plotMetar=False, offset=0):
nc = openWRF(nest)
Nx, Ny, Nz, _longs, _lats, _dx, _dy, x_nr, y_nr = getDimensions(nc)
heightground_t, heighthalf_tz = _getHeight(nc, Nx, Ny, Nz, x_nr, y_nr)
T_tz = np.zeros((Nz, Nt))
qcloud_tz = np.zeros((Nz, Nt))
qice_tz = np.zeros((Nz, Nt))
qsnow_tz = np.zeros((Nz, Nt))
qrain_tz = np.zeros((Nz, Nt))
for t in arange(Nt):
theta = nc.variables['T'][t, :, y_nr, x_nr] + T_base
P = nc.variables['P'][t, :, y_nr,
x_nr] + nc.variables['PB'][t, :, y_nr, x_nr]
T_tz[:,
t] = theta * (P /
P_bot)**kappa # Temperatur i halvflatene (Kelvin)
rho = P[:] / (R * T_tz[:, t]) # regner om til g/m3
qcloud_tz[:,
t] = 1000.0 * nc.variables['QCLOUD'][t, :, y_nr, x_nr] * rho
qice_tz[:, t] = 1000.0 * nc.variables['QICE'][t, :, y_nr, x_nr] * rho
qsnow_tz[:, t] = 1000.0 * nc.variables['QSNOW'][t, :, y_nr, x_nr] * rho
qrain_tz[:, t] = 1000.0 * nc.variables['QRAIN'][t, :, y_nr, x_nr] * rho
for s in [u'Snø', 'Regn']:
plt.figure()
plt.axis([-offset, Nt - 1, 0.0, z_max])
grid = np.reshape(np.tile(arange(Nt), Nz), (Nz, -1))
if (s == u"Snø"):
var = qsnow_tz
cm = cmap_blue
levs = tz_snow_levels
else:
var = qrain_tz
cm = cmap_green
levs = tz_rain_levels
plt.contourf(grid,
heighthalf_tz,
qcloud_tz,
alpha=0.9,
levels=tz_cloudwater_levels,
cmap=cmap_red) #
plt.colorbar()
plt.contourf(grid, heighthalf_tz, var, alpha=0.6, levels=levs,
cmap=cm) #
plt.colorbar()
cs = plt.contour(grid,
heighthalf_tz,
T_tz - T_zero,
temp_int,
colors='black',
linestyles='solid')
plt.clabel(cs, inline=1, fmt='%1.0f', fontsize=12, colors='black')
plt.fill_between(arange(-offset, Nt),
heightground_t[0],
0,
facecolor='lightgrey')
if plotMetar:
_metar()
print s + ' ($g/m^3$)'
plt.xlabel('Timer etter ' + date + 'T00:00Z')
plt.ylabel(u'Høyde [m]')
plt.yticks(np.arange(0, z_max, dz), fontsize='small')
plt.show()
plt.close()
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax1.set_xlim(0, Nt - 1)
ax1.plot(np.sum(qcloud_tz, axis=0), color='black', label=u"skyvann")
ax1.plot(np.sum(qsnow_tz, axis=0), color='green', label=u"snø")
ax1.set_xlabel('Timer etter ' + date + 'T00:00Z')
ax1.set_ylabel(u'Skyvann og snø ($g/m^2$)')
ax2 = ax1.twinx()
ax2.plot(np.sum(qice_tz, axis=0), color='blue', label="is")
ax2.plot(np.sum(qrain_tz, axis=0), color='red', label="regn")
ax2.set_ylabel('Regn og is ($g/m^2$)')
ax1.set_xlim(0, Nt - 1)
ax1.legend(loc='upper left')
ax2.legend(loc='upper right')
plt.show()
plt.close()
def yzCloudPlot(nest, time, plotTemp=True, plotRH=False):
nc = openWRF(nest)
Nx, Ny, Nz, _longs, latitude, _dx, _dy, x_nr, y_nr = getDimensions(nc)
heightground_y, heighthalf_yz = _getHeight(nc, time, -1, Ny, Nz, x_nr, -1)
print 'Model height: ' + str(heightground_y[y_nr])
theta = nc.variables['T'][time, :, :, x_nr] + T_base
P = nc.variables['P'][time, :, :, x_nr] + nc.variables['PB'][time, :, :,
x_nr]
T = theta * (P / P_bot)**kappa # Temperatur i halvflatene (Kelvin)
rho = P / (R * T) #[kg/m3]
qcloud_yz = 1000.0 * nc.variables['QCLOUD'][
time, :, :, x_nr] * rho # regner om til g/m3
qrain_yz = 1000.0 * nc.variables['QRAIN'][time, :, :, x_nr] * rho
qsnow_yz = 1000.0 * nc.variables['QSNOW'][time, :, :, x_nr] * rho
plt.figure()
plt.set_cmap(cmap_red)
plt.axis([0, Ny - 1, 0.0, z_max])
print u'Cloud water red, snow blue, rain green ($g/m^3$)'
grid = np.reshape(np.tile(arange(Ny), Nz), (Nz, -1))
plt.contourf(grid,
heighthalf_yz,
qcloud_yz,
alpha=0.9,
levels=xz_cloudwater_levels,
cmap=cmap_red) #
plt.colorbar()
plt.contourf(grid,
heighthalf_yz,
qrain_yz,
alpha=0.6,
levels=xz_rain_levels,
cmap=cmap_green) #
plt.colorbar()
plt.contourf(grid,
heighthalf_yz,
qsnow_yz,
alpha=0.6,
levels=xz_snow_levels,
cmap=cmap_blue) #
plt.colorbar()
if plotTemp:
cs = plt.contour(grid,
heighthalf_yz,
T - T_zero,
temp_int,
colors='black',
linestyles='solid') #linewidths=4
plt.clabel(cs, inline=1, fmt='%1.0f', fontsize=12, colors='black')
if plotRH:
rh = _getRH(nc, time, x_nr, -1, T, P)
rh_int = arange(90., 111., 5.)
cs = plt.contour(grid, heighthalf_yz, rh, rh_int, colors='grey')
plt.clabel(cs, inline=1, fmt='%1.0f', fontsize=12, colors='grey')
plt.plot(arange(Ny), heightground_y, color='black')
plt.fill_between(arange(Ny), heightground_y, 0, facecolor='lightgrey')
plt.xticks(np.arange(0, Ny, 8),
np.round(latitude[::8, Nx / 2], 1),
fontsize='small')
plt.yticks(np.arange(0, z_max, dz), fontsize='small')
plt.xlabel('Breddegrad')
plt.ylabel(u'Høyde [m]')
plt.show()
plt.close()