def plt_gr(fign):
t = psi.time<=200
T = psi.time[t].copy()
# Fitting the growth curve
popt, pcov = curve_fit(exponential, T, crest_growth.psi, p0=(1, 1e-6, 1))
curve = exponential(T, *popt)
fig = plt.figure(num=fign,figsize=(8,5),facecolor='w')
ax = plt.gca()
ax.plot(T,crest_growth.psi/1000,'bo',mfc='b',markersize=10,label=ur'Crest $\psi$')
ax.plot(T,curve/1000,'k--',lw=4.5,label=ur'Exponential Fit')
ax.set_xlim(10.,200)
ax.set_xticks(range(10,200,15))
ax.tick_params(labelsize=22)
rstyle(ax)
ax.set_ylabel(ur"$\psi(y=900) \times 10^{3}$ (m$^{2}$ s$^{-1}$)",fontsize=25,fontweight='demibold')
ax.set_xlabel(ur'Time (days)',fontsize=30,fontweight='demibold')
ax.set_title(ur'Growth Rate $\sim$ %1.2f $\times 10^{-2}$ day$^{-1}$'%(popt[1]*100.),fontsize=25,fontweight='demibold')
ax.legend(numpoints=1,loc=0,prop={'size':25},frameon=False)
plt.draw()
plt.show(block=False)
return fig
def plt_energy(fign):
fig = plt.figure(num=fign,figsize=(8,5),facecolor='w')
ax = plt.gca()
ax.plot(energy.time,energy.potential,'k',lw=3.5,label='EPE')
ax.plot(energy.time,energy.kinetic_layer1,'r',lw=3.5,label='Layer 1 - EKE')
ax.plot(energy.time,energy.kinetic_layer2,'b',lw=3.5,label='Layer 2 - EKE')
ax.set_ylim(0,20)
ax.set_xlim(0,1210)
ax.set_yticks(np.arange(0,22.5,2.5))
ax.tick_params(labelsize=22)
rstyle(ax)
ax.set_ylabel('Nondimensionalized energy',fontsize=25,fontweight='demibold')
ax.set_xlabel(ur'Time (days)',fontsize=30,fontweight='demibold')
ax.legend(numpoints=1,loc=0,prop={'size':18},frameon=False)
# plt.draw()
# plt.show(block=False)
return fig
def plt_annual_WBCt(fign):
fig = plt.figure(num=fign,figsize=(8,5),facecolor='w')
ax = plt.gca()
argo = np.ones(soest_gs.latitude.shape[0])*np.nan
wind = np.ones(scow_gs.latitude.shape[0])*np.nan
d = py.find(soest_gs.depth == 1200)[0]
for i in xrange(argo.shape[0]):
gs = soestgs_annual_Ipsi[d,i,:]
good = py.find(~np.isnan(gs))
if len(good) > 0:
argo[i] = gs[good[0]]
del gs, good
for i in xrange(wind.shape[0]):
gs = scowgs_annual_psi[i,:]
good = py.find(~np.isnan(gs))
if len(good) > 0:
wind[i] = gs[good[0]]
del gs, good
ax.plot(soest_gs.latitude,argo,'b',lw=3.5,label='ARGO')
ax.plot(scow_gs.latitude,wind,'r',lw=3.5,label='Sverdrup - Ekman')
ax.legend(numpoints=1,loc=0,prop={'size':20},frameon=False)
ax.plot([-60,0],[0,0],'k--',lw=3.5)
ax.set_ylim(-40,40)
ax.set_xlim(-5,-50)
ax.set_yticks(range(-40,50,10))
ax.set_xticks(range(-50,0,5))
ax.tick_params(labelsize=18)
rstyle(ax)
labels = [ur'5$^{\circ}$S',ur'10$^{\circ}$S',ur'15$^{\circ}$S',ur'20$^{\circ}$S',
ur'25$^{\circ}$S',ur'30$^{\circ}$S',ur'35$^{\circ}$S',ur'40$^{\circ}$S',ur'45$^{\circ}$S',
ur'50$^{\circ}$S']
labels.reverse()
ax.set_xticklabels(labels)
ax.set_ylabel('Transport at X$_{w}$ (Sv)',fontsize=30,fontweight='demibold')
ax.set_xlabel(ur'Latitude',fontsize=30,fontweight='demibold')
plt.draw()
plt.show(block=False)
return fig
def plt_energy(fign):
fig = plt.figure(num=fign, figsize=(8, 5), facecolor='w')
ax = plt.gca()
ax.plot(energy.time, energy.potential, 'k', lw=3.5, label='EPE')
ax.plot(energy.time,
energy.kinetic_layer1,
'r',
lw=3.5,
label='Layer 1 - EKE')
ax.plot(energy.time,
energy.kinetic_layer2,
'b',
lw=3.5,
label='Layer 2 - EKE')
ax.set_ylim(0, 20)
ax.set_xlim(0, 1210)
ax.set_yticks(np.arange(0, 22.5, 2.5))
ax.tick_params(labelsize=22)
rstyle(ax)
ax.set_ylabel('Nondimensionalized energy',
fontsize=25,
fontweight='demibold')
ax.set_xlabel(ur'Time (days)', fontsize=30, fontweight='demibold')
ax.legend(numpoints=1, loc=0, prop={'size': 18}, frameon=False)
# plt.draw()
# plt.show(block=False)
return fig
def plt_psi_profile(fign):
# Line properties
colors = ['b', 'r', 'g', 'k', 'orange', 'm']
linestyles = ['solid', 'dashed', 'dashdot', 'dotted', 'dashed', 'solid']
linewidths = [3, 3.5, 3.5, 3.5, 3.5, 3.5, 3]
lat = np.arange(-15.625, -45.625, -5)
fig = plt.figure(num=fign, figsize=(5, 8), facecolor='w')
ax = plt.gca()
for i in xrange(lat.shape[0]):
isoest = np.abs(soest_gs.latitude - lat[i]).argmin()
psi = soestgs_annual_psi[:, isoest, :]
j = py.find(~np.isnan(psi[0, :]))[0]
psi = psi[:, j]
ax.plot(psi * 100,
soest_gs.depth,
color=colors[i],
linestyle=linestyles[i],
lw=linewidths[i],
label=ur'%1.1f$^{\circ}$ S' %
(np.abs(soest_gs.latitude[isoest])))
ax.plot([0, 0], [0, 2000], 'k', lw=5, zorder=1)
del psi
ax.set_ylim(2000, 0)
ax.set_xlim(-4, 10)
ax.set_yticks(range(0, 2200, 200))
ax.set_xticks(np.arange(-4, 12, 2))
ax.tick_params(labelsize=22)
rstyle(ax)
ax.set_ylabel('Depth (m)', fontsize=30, fontweight='demibold')
ax.set_xlabel(
ur'ARGO-derived $\bar{\psi}_{geostrophic} \times 10^{4}$ (m$^{2}$ s$^{-1}$)',
fontsize=18,
fontweight='demibold')
ax.legend(numpoints=1, loc=0, prop={'size': 18}, frameon=False)
# plt.draw()
# plt.show(block=False)
return fig
def plt_psi_profile(fign):
# Line properties
colors = ['b','r','g','k','orange','m']
linestyles = ['solid','dashed','dashdot',
'dotted','dashed','solid']
linewidths = [3,3.5,3.5,3.5,3.5,3.5,3]
lat = np.arange(-15.625,-45.625,-5)
fig = plt.figure(num=fign,figsize=(5,8),facecolor='w')
ax = plt.gca()
for i in xrange(lat.shape[0]):
isoest = np.abs(soest_gs.latitude - lat[i]).argmin()
psi = soestgs_annual_psi[:,isoest,:]
j = py.find(~np.isnan(psi[0,:]))[0]
psi = psi[:,j]
ax.plot(psi*100,soest_gs.depth,color=colors[i],linestyle=linestyles[i],
lw = linewidths[i],label=ur'%1.1f$^{\circ}$ S'%(np.abs(soest_gs.latitude[isoest])))
ax.plot([0,0],[0,2000],'k',lw=5,zorder=1)
del psi
ax.set_ylim(2000,0)
ax.set_xlim(-4,10)
ax.set_yticks(range(0,2200,200))
ax.set_xticks(np.arange(-4,12,2))
ax.tick_params(labelsize=22)
rstyle(ax)
ax.set_ylabel('Depth (m)',fontsize=30,fontweight='demibold')
ax.set_xlabel(ur'ARGO-derived $\bar{\psi}_{geostrophic} \times 10^{4}$ (m$^{2}$ s$^{-1}$)',fontsize=18,fontweight='demibold')
ax.legend(numpoints=1,loc=0,prop={'size':18},frameon=False)
# plt.draw()
# plt.show(block=False)
return fig
def plt_gr(fign):
t = psi.time <= 200
T = psi.time[t].copy()
# Fitting the growth curve
popt, pcov = curve_fit(exponential, T, crest_growth.psi, p0=(1, 1e-6, 1))
curve = exponential(T, *popt)
fig = plt.figure(num=fign, figsize=(8, 5), facecolor='w')
ax = plt.gca()
ax.plot(T,
crest_growth.psi / 1000,
'bo',
mfc='b',
markersize=10,
label=ur'Crest $\psi$')
ax.plot(T, curve / 1000, 'k--', lw=4.5, label=ur'Exponential Fit')
ax.set_xlim(10., 200)
ax.set_xticks(range(10, 200, 15))
ax.tick_params(labelsize=22)
rstyle(ax)
ax.set_ylabel(ur"$\psi(y=900) \times 10^{3}$ (m$^{2}$ s$^{-1}$)",
fontsize=25,
fontweight='demibold')
ax.set_xlabel(ur'Time (days)', fontsize=30, fontweight='demibold')
ax.set_title(ur'Growth Rate $\sim$ %1.2f $\times 10^{-2}$ day$^{-1}$' %
(popt[1] * 100.),
fontsize=25,
fontweight='demibold')
ax.legend(numpoints=1, loc=0, prop={'size': 25}, frameon=False)
plt.draw()
plt.show(block=False)
return fig
def plt_annual_WBCt(fign):
fig = plt.figure(num=fign, figsize=(8, 5), facecolor='w')
ax = plt.gca()
argo = np.ones(soest_gs.latitude.shape[0]) * np.nan
wind = np.ones(scow_gs.latitude.shape[0]) * np.nan
d = py.find(soest_gs.depth == 1200)[0]
for i in xrange(argo.shape[0]):
gs = soestgs_annual_Ipsi[d, i, :]
good = py.find(~np.isnan(gs))
if len(good) > 0:
argo[i] = gs[good[0]]
del gs, good
for i in xrange(wind.shape[0]):
gs = scowgs_annual_psi[i, :]
good = py.find(~np.isnan(gs))
if len(good) > 0:
wind[i] = gs[good[0]]
del gs, good
ax.plot(soest_gs.latitude, argo, 'b', lw=3.5, label='ARGO')
ax.plot(scow_gs.latitude, wind, 'r', lw=3.5, label='Sverdrup - Ekman')
ax.legend(numpoints=1, loc=0, prop={'size': 20}, frameon=False)
ax.plot([-60, 0], [0, 0], 'k--', lw=3.5)
ax.set_ylim(-40, 40)
ax.set_xlim(-5, -50)
ax.set_yticks(range(-40, 50, 10))
ax.set_xticks(range(-50, 0, 5))
ax.tick_params(labelsize=18)
rstyle(ax)
labels = [
ur'5$^{\circ}$S', ur'10$^{\circ}$S', ur'15$^{\circ}$S',
ur'20$^{\circ}$S', ur'25$^{\circ}$S', ur'30$^{\circ}$S',
ur'35$^{\circ}$S', ur'40$^{\circ}$S', ur'45$^{\circ}$S',
ur'50$^{\circ}$S'
]
labels.reverse()
ax.set_xticklabels(labels)
ax.set_ylabel('Transport at X$_{w}$ (Sv)',
fontsize=30,
fontweight='demibold')
ax.set_xlabel(ur'Latitude', fontsize=30, fontweight='demibold')
plt.draw()
plt.show(block=False)
return fig