def plot_AMV_generals(lat,lon,amvpattern,vscale=1):
"""
Customized AMV Plot for Generals Presentation (for consistent plotting)
Parameters
----------
lat : TYPE
DESCRIPTION.
lon : TYPE
DESCRIPTION.
amvpattern : [lon x alt]
DESCRIPTION.
vscale : INT
Amt of times to scale AMV pattern by
Returns
-------
None.
"""
bbox = [-80,0 ,0,65]
# Set up plot params
plt.style.use('default')
cmap = cmocean.cm.balance
cints = np.arange(-.55,.60,.05)
cintslb = np.arange(-.50,.6,.1)
# Make the plot
fig,ax = plt.subplots(1,1,figsize=(5,5),subplot_kw={"projection":ccrs.PlateCarree()})
ax,cb = viz.plot_AMV_spatial(amvpattern.T*vscale,lon,lat,bbox,cmap,cint=cints,ax=ax,fmt="%.2f",returncbar=True,
fontsize=8)
cb.set_ticks(cintslb)
return fig,ax,cb
#% Make AMV Spatial Plots
cmap = cmocean.cm.balance
cmap.set_bad(color='yellow')
#cint = np.arange(-1,1.1,0.1)
#clab = cint
fig, axs = plt.subplots(1,
4,
figsize=(12, 1.5),
subplot_kw={'projection': ccrs.PlateCarree()})
for mode in range(4):
varin = np.transpose(amvpat[mode], (1, 0))
viz.plot_AMV_spatial(varin,
lonr,
latr,
bbm,
cmap,
pcolor=0,
ax=axs[mode])
axs[mode].set_title("MLD %s" % modelname[mode], fontsize=12)
#plt.suptitle("AMV Pattern | Forcing: %s; fscale: %ix" % (forcingname[funiform],fscale),ha='center')
#fig.tight_layout(rect=[0, 0.03, .75, .95])
outname = outpath + 'AMVpattern_%s_allmodels.png' % (expid)
plt.savefig(outname, bbox_inches="tight", dpi=200)
#%Make AMV Time Plots
xlm = [24, 240]
ylm = [-0.5, 0.5]
#xtk = np.arange(xlm[0],xlm[1]+20,20)
fig, axs = plt.subplots(1, 4, figsize=(12, 1.5))
for mode in range(4):
amvload = np.load("%sAMV_Region_%s.npz"%(outpathdat,expid),allow_pickle=True)
amvsp15 = amvload['amvpat_region'].item()[region][model] # Contains [region][model]
amvid15 = amvload['amvidx_region'].item()[region][model]
#%% Make the plots
i = 6
mult=1
fig,ax = plt.subplots(1,1,figsize=(5,5),subplot_kw={"projection":ccrs.PlateCarree()})
#ax = viz.init_map(bbox_NA,ax=ax)
#pcm = ax.contourf(lonr,latr,amvsp[i].T,levels=cints,cmap=cmap)
#fig.colorbar(pcm,ax=ax,fraction=0.05)
ax,cb = viz.plot_AMV_spatial(amvsp15.T*mult,lonr,latr,bbox_NA,cmap,cint=cints,ax=ax,fmt="%.2f",returncbar=True)
cb.set_ticks(cintslb)
ax.set_title("AMV Pattern (NHFLXSTD)")
plt.savefig(outpathfig+"AMV_Spatial_Pattern_%s_%s_runid%s.png"%(modelfname[model],"NHFLXSTD","203"))
for i in range(5):
if i == 1:
mult= 10
else:
mult = 1
fig,ax = plt.subplots(1,1,figsize=(5,5),subplot_kw={"projection":ccrs.PlateCarree()})
#ax = viz.init_map(bbox_NA,ax=ax)
#pcm = ax.contourf(lonr,latr,amvsp[i].T,levels=cints,cmap=cmap)
cint = np.arange(-1, 1.1, 0.1)
#clab = cint
fig, axs = plt.subplots(1,
5,
figsize=(15, 1.5),
subplot_kw={'projection': ccrs.PlateCarree()})
for rid in range(nruns):
print("Plotting for run %s" % runids[rid])
varplot = invar[rid, :, :].T
viz.plot_AMV_spatial(varplot,
lonr,
latr,
bbox,
cmap,
pcolor=0,
cint=cint,
ax=axs[rid],
fmt="%.1f")
axs[rid].set_title("run%s" % runids[rid], fontsize=12)
outname = outpathfig + 'AMVpattern_runcomparison_%s.png' % (testid)
plt.savefig(outname, bbox_inches="tight", dpi=200)
# Plot autocorrelation for each forcing
xtk = np.arange(0, 39, 3)
for r in range(nregions):
for modid in range(4):
fig, ax = plt.subplots(1, 1, figsize=(6, 4))
accesm = cesmauto[r]
#clab = np.arange(-0.50,0.60,0.10)
#cint = np.arange(-1,1.2,0.2)
#cint = np.arange(-2,2.5,0.5)
#cint = np.arange(-1,)
#cint = np.arange(-2,2,0.2)
#clab = cint
for mode in hvarmode:
print(mode)
fig,ax = plt.subplots(1,1,figsize=(3,1.5))
plt.style.use("ggplot")
varin = np.transpose(regr_meth2[mode],(1,0))
plt.subplot(1,4,mode+1)
viz.plot_AMV_spatial(varin,lon,lat,bbox,cmap,pcolor=0)
#viz.plot_AMV_spatial(varin,lon,lat,mbbox,cmap,cint,clab)
#plt.title("AMV Spatial Pattern \n Model %s" % hvarnames[mode],fontsize=10)
plt.title("Model %s" % hvarnames[mode],fontsize=12)
outname = outpath+'AMVpattern_funiform%i_hvar%i_run%s.png' % (funiform,mode,runid)
plt.savefig(outname, bbox_inches="tight",dpi=200)
#%% Plot AMV FFor HADLISST
startyr = 1900
# Same plot, but for HadlISST
cmap = cmocean.cm.balance
#cint = np.arange(-3.5,3.25,0.25)
cint = np.arange(-0.8,1.0,0.2)
amvpat = amvsp[funiform]
for region in range(4):
#% Make AMV Spatial Plots
cmap = cmocean.cm.balance
cmap.set_bad(color='yellow')
fig,axs = plt.subplots(1,4,figsize=(12,1.5),subplot_kw={'projection':ccrs.PlateCarree()})
for mode in range(4):
print("Now on mode %i region %i f %i"% (mode,region,f))
varin = np.transpose(amvpat[region][mode],(1,0))*vscale
#viz.plot_AMV_spatial(varin,lonr,latr,bbox,cmap,cint=cint,clab=clabs,pcolor=0,ax=axs[mode],fmt="%.1f",)
viz.plot_AMV_spatial(varin,lonr,latr,bbox,cmap,cint=cint,labels=False,pcolor=0,ax=axs[mode],fmt="%.1f",)
#axs[mode].set_title("MLD %s" % modelname[mode],fontsize=12)
axs[mode].set_title("%s" % modelname[mode],fontsize=12)
outname = outpathfig+'%s_AMVpattern_%s_allmodels_vscale%i.png' % (regions[region],expid,vscale)
plt.savefig(outname, bbox_inches="tight",dpi=200)
#%Make AMV Time Plots
xlm = [24,240]
ylm = [-0.5,0.5]
#xtk = np.arange(xlm[0],xlm[1]+20,20)
fig,axs = plt.subplots(1,4,figsize=(12,1.5))
for mode in range(4):
#bboxes = (bbox_SP,bbox_ST,bbox_TR,bbox_NA)
regions = ("SPG","STG","TRO","NAT")
bboxes = (bbox_SP,bbox_ST,bbox_TR,bbox_NA)
#% Make AMV Spatial Plots
cmap = cmocean.cm.balance
cmap.set_bad(color='yellow')
cint = np.arange(-.5,.6,0.1)
#clab = cint
fig,axs = plt.subplots(1,1,figsize=(6,4),subplot_kw={'projection':ccrs.PlateCarree()})
plt.style.use('ggplot')
plotbbox = [-100,10,-5,80]
varin = h_regr.T
viz.plot_AMV_spatial(varin,hlon,hlat,plotbbox,cmap,cint=cint,pcolor=0,ax=axs)
axs.set_title("HadISST AMV SST Pattern (%s to %s)" % (startyr,hyr[0,-1]),fontsize=14)
scolors = ["black","cornflowerblue","crimson","gold"]
# Add region plots
ax = axs
lwb = 1.5
ax,l4 = viz.plot_box(bbox_NA,ax=ax,color=scolors[0],return_line=True,leglab='NAT',linewidth=lwb,linestyle="solid")
ax,l2 = viz.plot_box(bbox_ST,ax=ax,color=scolors[2],return_line=True,leglab='STG',linewidth=lwb)
ax,l1 = viz.plot_box(bbox_SP,ax=ax,color=scolors[1],return_line=True,leglab='SPG',linewidth=lwb,linestyle='dashed')
ax,l3 = viz.plot_box(bbox_TR,ax=ax,color=scolors[3],return_line=True,leglab='TRO',linewidth=lwb,linestyle='dashed')
leg = ax.legend([l1,l2,l3,l4],labels=regions,ncol=4,bbox_to_anchor=(0, -0.1),loc='upper left')
#leg(fancybox=True,shadow=True)