def plot_interpolated_data(outfile, data): #{{{2
'''Plot interpolated data before and after writing to file
outfile: name of the output file
data: interpolated array
'''
fig = plt.figure(figsize=(15, 6))
fig.clf()
pcol(sq(llc.flat(data[6, :, :])), cmap='viridis')
# pcol(llc.flat(t_new2[6,:,:]),cmap='viridis')
plt.xlabel('Latitude [$\degree$]', fontsize=14)
plt.ylabel('Longitude [$\degree$]', fontsize=14)
cbar = plt.colorbar()
fid = open(outfile, 'r')
v_new2 = np.fromfile(fid, np.float32)
fid.close()
v_new2 = np.reshape(v_new2, (12, 1170, 90))
v_new2.byteswap(True)
fig = plt.figure(figsize=(15, 6))
fig.clf()
pcol(sq(llc.flat(v_new2[6, :, :])), cmap='viridis')
plt.xlabel('Latitude [$\degree$]', fontsize=14)
plt.ylabel('Longitude [$\degree$]', fontsize=14)
cbar = plt.colorbar()
plt.show()
# #llc.pcol(xg,yg,xc,m,edgecolors='k',facecolor='none') #d[0,:,:])
# #llc.pcol(xg,yg,sq(d[3,:,:]*hf[0,:,:]),m,vmax=4.,edgecolors='k',facecolor='none') #d[0,:,:])
# llc.pcol(xg,yg,sq(d[3,:,:]*hf[0,:,:]),m,vmax=4) #,edgecolors='k',facecolor='none')
# #llc.pcol(xg,yg,sq(d[1,:,:]*hf[0,:,:]),m) #d[0,:,:])
# m.drawmapboundary()
# #m.drawcoastlines(color='k')
# #m.fillcontinents(color='w')
# plt.colorbar(orientation='horizontal')
# #plt.colorbar()
# plt.show()
# sys.exit('bye bye')
vind, vmax = 3, 6
#vind,vmax =4, 1
#vind,vmax =0, 1000
tmp = sq(xc)
fig = plt.figure()
m1 = Basemap(projection='cyl', lon_0=10., resolution='l')
m2 = Basemap(projection='npaeqd', lon_0=0., boundinglat=60, resolution='l')
m3 = Basemap(projection='spaeqd', lon_0=180., boundinglat=-50, resolution='l')
refdate = 1
for i in range(len(iter)):
if len(iter) == 1: tmp = sq(d[vind, :, :])
else: tmp = sq(d[i, vind, :, :])
daysSinceRefDate = iter[i] / 3
yearsSinceRefDate = daysSinceRefDate / 365
monthsSinceRefDate = round(np.mod(daysSinceRefDate, 365) / (365. / 12.))
mydate = "%04i/%02i" % (refdate + yearsSinceRefDate, monthsSinceRefDate)
print "iteration[%i] = %i, %s" % (i, iter[i], mydate)
else:
cfac = 1.
zdir = 1.
pfac = 1e-6 * cfac
psiw = overturningw(d3z[4,...],rac)
#psit = overturning(dl[1,...],dyg)
psir,zl = overturning(dl[0,...],dl[1,...],dl[2,...],dl[3,...],dxg,dyg)
yl = np.tile(yg[:3*nx,0].reshape((1,3*nx)),(nl,1))
zlmsk = np.where(zl,1,0)
levs = np.linspace(-30,20,26)
fig, ax = plt.subplots(3,1,sharex=True,sharey=False,squeeze=True,figsize=(8,10))
csf=np.copy(ax)
csf[0]=ax[0].contourf(yg[:3*nx,0],rf[:-1]*cfac*zdir,sq(psiw)*pfac*zdir,
levels=levs,extend='both')
csf[1]=ax[1].contourf(yg[:3*nx,0],dlr[:-1,0,0],sq(psir)*pfac,
levels=levs,extend='both')
#csf[2]=ax[2].pcolormesh(yg[:,0],dlt,sq(psit)*pfac)
csf[2]=ax[2].contourf(yl[:,:3*nx],np.array(zl[:,:3*nx])*cfac,
sq(psir*zlmsk)*pfac,
levels=levs, extend='both')
ax[0].set_title('%s: MOC (Sv) at timestep %i'%(myrun,myiter[0]))
ax[-1].set_xlabel('latitude (degN)')
ax[1].set_ylim(dlr.max(), dlr.min())
ylab=('depth (m)','$\sigma_{2}$ in kg/m$^3$',
'$\sigma_{2}$ remapped to depth (m)')
for k,b in enumerate(ax):
b.set_ylabel(ylab[k])
# csf[k].set_clim([-30,20])
ub = np.concatenate((ubf[0], ubf[1], vbf[3][:, ::-1].transpose(),
vbf[4][:, ::-1].transpose()),
axis=-1)
psib = np.cumsum(np.ma.masked_array(ub, ub == 0.), axis=0)
return psib
msku, mskv = atlantic_mask(msku, mskv)
psi = overturning(d[-2, :, :, :] * msku, d[-1, :, :, :] * mskv, dxg, dyg, drf)
psib = barostream(d[-2, :, :, :], d[-1, :, :, :], dxg, dyg, drf)
fig = plt.figure()
fig.clf()
plt.pcolormesh(yg[:270, 0], zc,
sq(psi) * 1e-6)
#plt.clim([-10,10])
plt.colorbar(orientation='horizontal')
plt.title("%s, %04i: overturning stream function (Sv)" % (mydir, myyear))
fig = plt.figure()
fig.clf()
plt.pcolormesh(sq(psib) * 1e-6)
plt.colorbar(orientation='horizontal')
plt.title("%s, %04i: overturning stream function (Sv)" % (mydir, myyear))
plt.show()
# sys.exit('bye bye')
#d3=rdmds('diag3Dm',iter)
i = 0
for i in range(1):
uu = np.mean(f[:, 0, :, :], axis=0)
vv = np.mean(f[:, 1, :, :], axis=0)
# uu = np.mean(d3[:,2,1,:,:],axis=0)
# vv = np.mean(d3[:,3,1,:,:],axis=0)
# uu = np.ma.masked_array(uu,hf[0,:,:]<=0.0)
# vv = np.ma.masked_array(vv,hf[0,:,:]<=0.0)
spd = np.sqrt(uu * uu + vv * vv)
u, v = Basemap.rotate_vector(m, uu * cs - vv * sn, uu * sn + vv * cs, xc,
yc)
fig.clf()
lh = llc.pcol(xg, yg, sq(wspd[i, :, :] * hf[0, :, :]), m)
m.drawcoastlines(color='k')
di = 1
q = m.quiver(xc[::di, ::di],
yc[::di, ::di],
u[::di, ::di],
v[::di, ::di],
latlon=True,
scale=200,
pivot='mid',
edgecolor='none',
headaxislength=5)
# pivot = 'mid',units = 'x', edgecolor = 'none',headaxislength = 5)
plt.show()