def plotFrame(t):
fig.clf()
ax=plotAx()
cplot=[]; gplot=[]; qplot=[]; bcplot=[]
for mat1,ax1 in zip(mat,ax):
#Time
fig.suptitle(plotter.num2time(t).strftime('%Y-%b-%d %H:%M'))
fig.subplots_adjust(bottom=.15,top=.85)
it=np.interp(t,mat1['t'],np.arange(0,len(mat1['t'])))
rho1=sw.pden(mat1['salt'][:,:,int(it)]*(1.-it%1)+mat1['salt'][:,:,int(it)+1]*(it%1),
mat1['temp'][:,:,int(it)]*(1.-it%1)+mat1['temp'][:,:,int(it)+1]*(it%1),
0.0*mat1['temp'][:,:,int(it)]*(1.-it%1)+0.0*mat1['temp'][:,:,int(it)+1]*(it%1) )
salt1=mat1['salt'][:,:,int(it)]*(1.-it%1)+mat1['salt'][:,:,int(it)+1]*(it%1)
it=np.interp(t,mat0['t'],np.arange(0,len(mat0['t'])))
rho0=sw.pden(mat0['salt'][:,:,int(it)]*(1.-it%1)+mat0['salt'][:,:,int(it)+1]*(it%1),
mat0['temp'][:,:,int(it)]*(1.-it%1)+mat0['temp'][:,:,int(it)+1]*(it%1),
0.0*mat0['temp'][:,:,int(it)]*(1.-it%1)+0.0*mat0['temp'][:,:,int(it)+1]*(it%1) )
salt0=mat0['salt'][:,:,int(it)]*(1.-it%1)+mat0['salt'][:,:,int(it)+1]*(it%1)
#print([np.nanmax(rho1-rho0),np.nanmin(rho1-rho0)])
cplot1=ax1.contourf(mat1['lon'],mat1['lat'],rho1-rho0,[tick1 for tick1 in np.arange(-5.0,5.01,.25) if np.abs(tick1)>1e-8],cmap=cmap,extend='both')
bcplot1=ax1.contour(mat1['lon'],mat1['lat'],salt1,levels=[31.5],colors='k',linewidth=1)
it=np.interp(t,mat1['t'],np.arange(0,len(mat1['t'])))
u1=mat1['u'][:,:,int(it)]*(1.-it%1)+mat1['u'][:,:,int(it)+1]*(it%1)
v1=mat1['v'][:,:,int(it)]*(1.-it%1)+mat1['v'][:,:,int(it)+1]*(it%1)
it=np.interp(t,mat0['t'],np.arange(0,len(mat0['t'])))
u0=mat0['u'][:,:,int(it)]*(1.-it%1)+mat0['u'][:,:,int(it)+1]*(it%1)
v0=mat0['v'][:,:,int(it)]*(1.-it%1)+mat0['v'][:,:,int(it)+1]*(it%1)
qplot1=plotter.add_uv2d(ax1,mat1['lon'],mat1['lat'],(u1-u0)*2,(v1-v0)*2)
#print([np.nanmin(u1-u0),np.nanmax(u1-u0),np.nanmin(v1-v0),np.nanmax(v1-v0)])
tLim1=3.*int((t-2)/3)+np.array([2.,5.])
obsll=[(lon1,lat1) for (lon1,lat1,type1,t1) in zip(obs['lon'],obs['lat'],obs['type'],obs['t']) if type1==6 and tLim1[0]<=t1<=tLim1[1]]
lon1,lat1=zip(*obsll)
gplot1=ax1.plot(lon1,lat1,'.',color=(1.,.55,0.),markersize=2,fillstyle='full')
#Colorbar
fig.subplots_adjust(right=.8)
cax=fig.add_axes([.82,.15,.02,.7])
cbar=fig.colorbar(cplot1,cax=cax,orientation='vertical',spacing='proportional')
cbar.set_ticks([tick1 for tick1 in np.arange(-5.0,5.01,1.)])
cbar.formatter=ticker.FuncFormatter(lambda x,pos:'{:.1f}'.format(x))
cbar.update_ticks()
cbar.set_label(r'Density difference [$\mathrm{kg m^{-3}}$]')
cplot.append(cplot1)
gplot.append(gplot1)
qplot.append(qplot1)
bcplot.append(bcplot1)
#plt.tight_layout()
return cplot,qplot,gplot,bcplot
def plotFrame(t):
fig.clf()
ax=plotAx()
cplot=[]; gplot=[]; bcplot=[]
for model1,ax1 in zip(model,ax):
#Time
fig.suptitle(plotter.num2time(t).strftime('%Y-%b-%d %H:%M'))
fig.subplots_adjust(bottom=0.15,top=.9,right=.85)
it=np.interp(t,model1.t,np.arange(0,len(model1.t)))
salt1=model1.salt[:,:,int(it)]*(1.-it%1)+model1.salt[:,:,int(it)+1]*(it%1)
temp1=model1.temp[:,:,int(it)]*(1.-it%1)+model1.temp[:,:,int(it)+1]*(it%1)
z1=model1.z[:,:,int(it)]*(1.-it%1)+model1.z[:,:,int(it)+1]*(it%1)
rho1=sw.pden(salt1,temp1,-z1,0.0*z1 )
rho1=rho1-1e3
z2,rho2=plotter.z_interp(z1,rho1,np.array([-300.,0]))
print([np.nanmax(rho2),np.nanmin(rho2)])
cplot1=ax1.contourf(np.reshape(model1.lon[:,0],(-1,1))+np.zeros(np.shape(z2)),-z2,rho2,[tick1 for tick1 in np.arange(18.,28.01,.5)],cmap=cmap,extend='neither')
bcplot1=ax1.contour(model1.lon,-z1,salt1,levels=[31.5],colors='k',linewidths=.5,linestyles='-')
bcplot.append(bcplot1)
bcplot2=ax1.contour(model1.lon,-z1,rho1,levels=[26.5],linestyles='--',colors='k',linewidths=.5)
bcplot.append(bcplot2)
#Coast
h=-z1[:,0]; h[np.isnan(h)]=3.
h=np.concatenate(([10e3],h,[10e3]))
hlon=np.concatenate(([-135.],model1.lon[:,0],[-120.]))
p=patch.Polygon(np.column_stack((hlon,h)),facecolor=(.5,.6,.5),edgecolor=None,closed=True)
ax1.add_patch(p)
tLim1=3.*int((t-2)/3.)+np.array([2.,5.])
obsll=[(lon1,z1) for (lon1,z1,type1,t1) in zip(obs['lon'],obs['z'],obs['type'],obs['t']) if type1==6 and tLim1[0]<=t1<=tLim1[1]]
lon1,z1=zip(*obsll)
gplot1=ax1.plot([np.min(lon1),np.min(lon1),np.max(lon1),np.max(lon1)],
[np.min(z1),np.max(z1),np.max(z1),np.min(z1)],':',
color=(.5,.5,.5),linewidth=1.)
#Colorbar
cax=fig.add_axes([.855,.15,.02,.75])
cbar=fig.colorbar(cplot1,cax=cax,orientation='vertical',spacing='vertical')
cbar.set_ticks([tick1 for tick1 in np.arange(18.0,28.01,1.)])
cbar.formatter=ticker.FuncFormatter(lambda x,pos:'{:.0f}'.format(x))
cbar.update_ticks()
cbar.set_label(r'Density-$10^3$ [$\mathrm{kg m^{-3}}$]')
cplot.append(cplot1)
gplot.append(gplot1)
#plt.tight_layout()
return cplot,gplot,bcplot
def plotFrame(t):
fig.clf()
ax=plotAx()
cplot=[]; gplot=[]; qplot=[]
for mat1,ax1 in zip(mat,ax):
#Time
fig.suptitle(plotter.num2time(t).strftime('%Y-%b-%d %H:%M'))
it=np.interp(t,mat1['t'],np.arange(0,len(mat1['t'])))
vort1=mat1['vort'][:,:,int(it)]*(1.-it%1)+mat1['vort'][:,:,int(it)+1]*(it%1)
cplot1=ax1.contourf(mat1['lon'],mat1['lat'],vort1,[tick1 for tick1 in np.arange(-1.4e-4,1.401e-4,.2e-4) if np.abs(tick1)>1e-8],cmap=cmap,extend='both')
u1=mat1['u'][:,:,int(it)]*(1.-it%1)+mat1['u'][:,:,int(it)+1]*(it%1)
v1=mat1['v'][:,:,int(it)]*(1.-it%1)+mat1['v'][:,:,int(it)+1]*(it%1)
qplot1=plotter.add_uv2d(ax1,mat1['lon'],mat1['lat'],u1,v1)
tLim1=3.*int((t-2)/3)+np.array([2.,5.])
obsll=[(lon1,lat1) for (lon1,lat1,type1,t1) in zip(obs['lon'],obs['lat'],obs['type'],obs['t']) if type1==6 and tLim1[0]<=t1<=tLim1[1]]
lon1,lat1=zip(*obsll)
gplot1=ax1.plot(lon1,lat1,'.',color=(1.,.55,0.),markersize=5,fillstyle='full')
#Colorbar
fig.subplots_adjust(right=.8)
cax=fig.add_axes([.82,.15,.02,.7])
cbar=fig.colorbar(cplot1,cax=cax,orientation='vertical',spacing='proportional')
cbar.set_ticks([tick1 for tick1 in np.arange(-1.4e-4,1.401e-4,.2e-4)])
cbar.formatter=ticker.FuncFormatter(lambda x,pos:'{:.1f}'.format(x*1e4))
cbar.update_ticks()
cbar.set_label(r'Rel. vorticity [$10^{-4}\,\mathrm{s^{-1}}$]')
cplot.append(cplot1)
gplot.append(gplot1)
qplot.append(qplot1)
#plt.tight_layout()
return cplot,qplot,gplot
for mat1 in mat:
mat1.t = mat1.t - 366
mat1.slope.t = mat1.slope.t - 366
ttick = np.arange(2392, 2413.01, 3) + plotter.time2num(
datetime.datetime(2005, 1, 1))
#%% Figure
ax = fig.add_subplot(1, 1, 1)
#x
ax.set_xlim(ttick[[0, -1]])
ax.xaxis.set_major_locator(ticker.FixedLocator(ttick))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(1))
ax.xaxis.set_major_formatter(
ticker.FuncFormatter(lambda x, pos: plotter.num2time(x).strftime('%m/%d')))
ax.set_xlabel('2011')
#y
ax.set_ylim(0, 225)
ax.yaxis.set_major_locator(ticker.MultipleLocator(25))
ax.set_ylabel(r'Enstrophy [$\mathrm{m^2 s^{-2}}$]')
#Grid
ax.grid(color=(.7, .7, .7), linestyle='--')
#%%
markers = ['*', 'o', 'x', None]
colors = ['m', 'r', 'g', 'b']
labels = ['Surface', 'Glider', 'Combined', 'No DA']
linewidths = [1, 1, 1, 1]
def dateFormatter(x, pos):
date = plotter.num2time(x).strftime('%m/%d')
return date
def plotFrame(ax):
cplot = []
qplot = []
bcplot = []
for ax1, t in zip(ax, mat1['t']):
#Time
fig.subplots_adjust(bottom=.15, top=.85)
it = np.interp(t, mat1['t'], np.arange(0, len(mat1['t'])))
it2 = np.minimum(int(it) + 1, len(mat1['t']) - 1)
print([it, it2])
salt1 = mat1['salt'][:, :, int(it)] * (
1. - it % 1) + mat1['salt'][:, :, it2] * (it % 1)
#print([np.nanmax(rho1),np.nanmin(rho1)])
cplot1 = ax1.contourf(mat1['lon'],
mat1['lat'],
salt1,
[tick1 for tick1 in np.arange(24., 33.01, .5)],
cmap=cmap,
extend='min')
bcplot1 = ax1.contour(mat1['lon'],
mat1['lat'],
salt1,
levels=[31.5],
colors='k',
linewidth=1)
it = np.interp(t, mat1['t'], np.arange(0, len(mat1['t'])))
u1 = mat1['u'][:, :, int(it)] * (
1. - it % 1) + mat1['u'][:, :, it2] * (it % 1)
v1 = mat1['v'][:, :, int(it)] * (
1. - it % 1) + mat1['v'][:, :, it2] * (it % 1)
qplot1 = plotter.add_uv2d(ax1, mat1['lon'], mat1['lat'], u1, v1)
#print([np.nanmin(u1-u0),np.nanmax(u1-u0),np.nanmin(v1-v0),np.nanmax(v1-v0)])
#Add glider
obsll = [(lon1, lat1)
for (lon1, lat1, type1,
t1) in zip(obs['lon'], obs['lat'], obs['type'], obs['t'])
if type1 == 6]
lon1, lat1 = zip(*obsll)
gplot1 = ax1.plot(lon1,
lat1,
'.',
color=(1., .55, 0.),
markersize=2,
fillstyle='full')
ax1.set_title(plotter.num2time(t).strftime('%m/%d/%y'))
#Colorbar
fig.subplots_adjust(right=.8)
cax = fig.add_axes([.82, .15, .02, .7])
cbar = fig.colorbar(cplot1,
cax=cax,
orientation='vertical',
spacing='proportional')
cbar.set_ticks([tick1 for tick1 in np.arange(24.0, 33.01, 1.)])
cbar.formatter = ticker.FuncFormatter(
lambda x, pos: '{:.0f}'.format(x))
cbar.update_ticks()
cbar.set_label(r'Salinity [$\mathrm{ppt}$]')
cplot.append(cplot1)
qplot.append(qplot1)
bcplot.append(bcplot1)
#plt.tight_layout()
return cplot, qplot, bcplot
mat.t = mat.t
dateRef = datetime.datetime(2005, 1, 1).toordinal()
ax = []
for i1 in np.arange(0, 4):
ax1 = fig.add_subplot(2, 2, i1 + 1)
ax1.set_xlim(2392 + dateRef, 2413 + dateRef)
ax1.grid(color=(.7, .7, .7), linestyle=':', linewidth=.5)
#ax1.set_ylim(0,6)
if i1 >= 0:
ax1.set_xlabel('2011')
ax1.xaxis.set_major_locator(
ticker.FixedLocator(np.arange(2392, 2434.1, 3) + dateRef))
ax1.xaxis.set_major_formatter(
ticker.FuncFormatter(
lambda x, pos: plotter.num2time(x).strftime('%m/%d')))
else:
ax1.xaxis.set_major_formatter(ticker.NullFormatter())
if i1 == 4:
ax1.set_axis_off()
ax.append(ax1)
#%% Differences of the whole period
def rms(x):
return np.sqrt(np.nanmean(x * x))
print('sst')
for val1 in mat.sst.rms:
def plotFrame(t):
fig.clf()
ax = plotAx()
cplot = []
gplot = []
qplot = []
bcplot = []
level1 = levelList[0]
for mat1, ax1, title1 in zip(mat, ax, titleList):
#Time
fig.suptitle(plotter.num2time(t).strftime('%Y-%b-%d %H:%M'))
fig.subplots_adjust()
inCon = level1 == mat1.contours
it = np.interp(t, mat1.t, np.arange(0, len(mat1.t)))
it1 = np.minimum(int(it) + 1, len(mat1.t) - 1)
z0 = mat0.z[:, :, inCon, int(it)] * (
1 - it % 1) + mat0.z[:, :, inCon, it1] * (it % 1)
z1 = mat1.z[:, :, inCon, int(it)] * (
1 - it % 1) + mat1.z[:, :, inCon, it1] * (it % 1)
z0 = np.squeeze(z0)
z1 = np.squeeze(z1)
mask0 = np.where(np.isnan(z0), np.ones(np.shape(z0)),
np.zeros(np.shape(z0)))
mask1 = np.where(np.isnan(z1 - z0), np.ones(np.shape(z1)),
np.zeros(np.shape(z1)))
print(
[np.nanpercentile(z1 - z0, 2.5),
np.nanpercentile(z1 - z0, 97.5)])
cplot1 = ax1.contourf(
mat1.lon,
mat1.lat,
z1 - z0, [
tick1
for tick1 in np.arange(-40.0, 40.01, 5.0) if np.abs(tick1) > 1
],
cmap=cmap,
extend='both')
if level1 <= 1024.5:
bcplot1 = ax1.contour(mat1.lon,
mat1.lat,
z1,
levels=np.arange(-200, 0.1, 10.),
colors='k',
linewidth=.5)
else:
bcplot1 = ax1.contour(mat1.lon,
mat1.lat,
z1,
levels=np.arange(-2000, 0.1, 25.),
colors='k',
linewidth=.5)
ax1.set_title(title1)
bcplot2 = ax1.contourf(mat1.lon,
mat1.lat,
mask1,
levels=[-.5, .5, 1],
cmap=cgrey,
vmin=0.5,
vmax=1,
alpha=.5)
tLim1 = 3. * int((t - 2) / 3) + np.array([2., 5.])
obsll = [(lon1, lat1)
for (lon1, lat1, type1,
t1) in zip(obs['lon'], obs['lat'], obs['type'], obs['t'])
if type1 == 6 and tLim1[0] <= t1 <= tLim1[1]]
lon1, lat1 = zip(*obsll)
gplot1 = ax1.plot(lon1,
lat1,
'.',
color=(1., .55, 0.),
markersize=2,
fillstyle='full')
#Colorbar
fig.subplots_adjust(right=.8)
cax = fig.add_axes([.8, .1, .02, .8])
cbar = fig.colorbar(cplot1,
cax=cax,
orientation='vertical',
spacing='proportional')
cbar.set_ticks([tick1 for tick1 in np.arange(-40.0, 40.1, 10.)])
cbar.formatter = ticker.FuncFormatter(
lambda x, pos: '{:.1f}'.format(x))
cbar.update_ticks()
cbar.set_label(r'Depth change [$\mathrm{m}$]')
cplot.append(cplot1)
gplot.append(gplot1)
bcplot.append(bcplot1)
#plt.tight_layout()
return cplot, gplot, bcplot
