for i in range(nclusters):
cid = i+1
ax.axvline([-100],lw=5,color=regioncolors[i],label="Cluster %i, s = %.3f"%(cid,new_sbyclust[i]))
ax.legend(fontsize=10)
ax.set_xticks(np.arange(-.2,.6,.1))
ax.set_xlim([-.25,.6])
plt.savefig("%sCESM1PIC_%s_SilhouettePlot_k%s%i_%s.png"%(outfigpath,expname,kmode,ii,yearstr),dpi=200,bbox_inches='tight')
# Plot 2: the silhoutte value map
cmap="RdBu_r"
silmap = np.zeros(nlat5*nlon5)*np.nan
silmap[okpts] = s_in
silmap = silmap.reshape(nlat5,nlon5)
proj = ccrs.PlateCarree(central_longitude=180)
fig,ax = plt.subplots(1,1,subplot_kw={'projection':proj})
ax = viz.add_coast_grid(ax)
pcm=ax.pcolormesh(lon5,lat5,silmap,vmin=-.5,vmax=.5,cmap=cmap,transform=ccrs.PlateCarree())
ax.contour(lon5,lat5,silmap,levels=[0],colors='k',linewidths=0.75,linestyles=":",transform=ccrs.PlateCarree())
#ax.pcolormesh(lon5,lat5,silmap,vmin=-.5,vmax=.5,cmap=cmocean.cm.balance,transform=ccrs.PlateCarree())
fig.colorbar(pcm,ax=ax,fraction=0.025)
ax.set_title("Silhouette Values for CESM-PiC Clusters (Year %s) \n $s_{avg}$ = %.3f" % (yearstr,s_in.mean()))
plt.savefig("%sCESM1PIC_%s_SilhouetteMap_k%s%i_%s.png"%(outfigpath,expname,kmode,ii,yearstr),dpi=200,bbox_inches='tight')
# Plot 3: the clustering result
fig,ax = plt.subplots(1,1,subplot_kw={'projection':proj})
ax = viz.add_coast_grid(ax)
pcm=ax.pcolormesh(lon5,lat5,clusternew,cmap=cmapn,transform=ccrs.PlateCarree())
fig.colorbar(pcm,ax=ax,fraction=0.025)
ax.set_title("CESM-PiC Clusters (Year %s)" % (yearstr))
plt.savefig("%sCESM1PIC_%s_ClustersMap_k%s%i_%s.png"%(outfigpath,expname,kmode,ii,yearstr),dpi=200,bbox_inches='tight')
constrained_layout=True,
subplot_kw={'projection': ccrs.PlateCarree(central_longitude=0)})
for i in tqdm(range(12)):
ax = axs.flatten()[i]
im = loopmon[i]
blabel = [0, 0, 0, 0]
if i % 3 == 0:
blabel[0] = 1
if i > 8:
blabel[-1] = 1
# Add coastline, Month Title
ax = viz.add_coast_grid(ax, bboxplot, blabels=blabel)
ax.set_title(mons3[im])
# Get plotting variable
plotvar = rhovalues[imsk][plotmcf][plotlag, plotmon, :, :]
plotmsk = rmasks[plotmon, plotlag, :, :, plotmcf, imsk]
# Flip Longitude
lon1, plotvar1 = proc.lon360to180(lon, plotvar.T)
_, plotmsk1 = proc.lon360to180(lon, plotmsk.T)
#_,plotmsk1 = proc.lon360to180(lon,limask.T)
plotvar1 *= limask180
plotmsk1 *= limask180
pcm = ax.contourf(lon1,
proj = ccrs.PlateCarree(central_longitude=180)
fig, axs = plt.subplots(2,
1,
subplot_kw={'projection': proj},
figsize=(12, 6),
constrained_layout=True)
cint = np.arange(-vlm, vlm + cstep, cstep)
for i in range(2):
ax = axs[i]
blabel = [1, 0, 0, 0]
if i == 1:
blabel[-1] = 1
ax = viz.add_coast_grid(ax,
bbox=bboxplot,
fill_color='gray',
blabels=blabel)
ploteof = eofs[i][:, :, im, n]
pcm = ax.pcolormesh(lon,
lat,
ploteof,
transform=ccrs.PlateCarree(),
cmap='cmo.balance',
vmin=-vlm,
vmax=vlm)
cf = ax.contour(lon,
lat,
ploteof,
vlms = [0, 2]
cintsneg = np.arange(0, 1.2, .2)
cintspos = np.arange(1, 2.2, .2)
# Set up plot params
plt.style.use('default')
cmap = cmocean.cm.balance
# Next plot the results
fig, axs = plt.subplots(1,
2,
subplot_kw={'projection': ccrs.PlateCarree()},
figsize=(12, 4.5))
ax = axs[0]
ax = viz.add_coast_grid(ax, bbox=bboxplot)
pcm = ax.pcolormesh(lonr,
latr,
fullratio.T,
vmin=vlms[0],
vmax=vlms[-1],
cmap=cmap)
#pcm = ax.contourf(lonr,latr,fullratio.T,levels=cints,cmap=cmocean.cm.balance)
clp = ax.contour(lonr,
latr,
fullratio.T,
levels=cintspos,
colors="k",
linewidths=0.75)
ax.clabel(clp, fmt="%.1f")
cln = ax.contour(lonr,
invar = da['ts'].values
lon = da[lonname].values
lat = da[latname].values
times = da[tname].values
print("Data loaded in %.2fs" % (time.time() - st))
# Portion Below is taken from calc_ENSO_PIC.py VV ***********
eofall, pcall, varexpall = scm.calc_enso(invar, lon, lat, pcrem, bbox=bbox)
# Sanity Check
if debug:
im = 0
ip = 0
proj = ccrs.PlateCarree(central_longitude=180)
fig, ax = plt.subplots(1, 1, subplot_kw={'projection': proj})
ax = viz.add_coast_grid(ax, bbox=bbox)
pcm = ax.pcolormesh(lon,
lat,
eofall[:, :, im, ip],
vmin=-1,
vmax=1,
cmap='cmo.balance',
transform=ccrs.PlateCarree())
cb = fig.colorbar(pcm,
ax=ax,
orientation='horizontal',
fraction=0.055,
pad=0.1)
cb.set_label("SST Anomaly ($\degree C \sigma_{ENSO}^{-1}$)")
ax.set_title("EOF %i, Month %i\n Variance Explained: %.2f" %
(ip + 1, im + 1, varexpall[im, ip] * 100) + "%")
if i == 0: # Set labels for left
blabel[0] = 1
ax.text(-0.28,
0.35,
'42-member \n Stdev. \n (%s, \n Lag %i)' %
(months[imon], ilag + 1),
va='bottom',
ha='center',
rotation='horizontal',
rotation_mode='anchor',
transform=ax.transAxes,
fontsize=14)
ax = viz.add_coast_grid(ax,
bbox=bboxplot,
blabels=blabel,
fill_color='gray',
ignore_error=True)
lon1, plotvar1 = proc.lon360to180(lon, plotvar.T)
pcm = ax.contourf(lon1,
lat,
plotvar1.T,
levels=cints_all[i],
extend='both',
cmap=cmaps[i])
ax.set_title(plotnames_fancy[i])
fig.colorbar(pcm,
ax=ax,
fraction=0.045,
def make_figure():
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree())
ax = viz.add_coast_grid(ax)
return fig, ax
latf = 50
klon,klat = proc.find_latlon(lonf,latf,lon180,lat)
klon360,_ = proc.find_latlon(lonf+360,latf,lon,lat)
#%% Make some plots (Annual Heat Flux without the mask)
# -----------------------------------------------------
bboxplot = [-85,0,0,65]
proj = ccrs.PlateCarree()
fig,axs = plt.subplots(1,2,subplot_kw={'projection':proj})
clvls = np.arange(-40,41,1)
for i in range(2):
ax = axs[i]
ax = viz.add_coast_grid(ax,bbox=bboxplot)
plotvar = dunmask[i].mean(-1)
cf = ax.contourf(lon180,lat,plotvar.T,
levels=clvls,cmap=cmocean.cm.balance,transform=proj,
extend='both')
ax.contour(lon180,lat,plotvar.T,levels=[0,1],colors='k')
ax.set_title(mconfigs[i])
fig.colorbar(cf,ax=axs.flatten(),orientation='horizontal')
#%% Try to plot the cross and autocorrelation, monthly
# ----------------------------------------------------
model = 1
lagid = 1
proj = ccrs.PlateCarree()
lon180, NAO1 = proc.lon360to180(lon360, NAO1)
BOTHDJFM = NAO1[klon[:, None], klat[None, :], :].copy()
#%% Make input plot for Mixed layer Depth Range
invar = hclim.max(2) - hclim.min(2)
bbox = [-80, 0, 0, 80]
#cint = np.concatenate([np.arange(0,100,20),np.arange(100,1800,300)])
cint = [0, 25, 50, 100, 250, 500, 750, 1000, 1250, 1500]
cmap = cmocean.cm.dense
# Old Figsize was 5 x 4
fig, ax = plt.subplots(1,
1,
subplot_kw={'projection': ccrs.PlateCarree()},
figsize=(8, 5))
ax = viz.add_coast_grid(ax, bbox=bbox)
#ax = viz.init_map(bbox,ax=ax)
#pcm = ax.contourf(lonr,latr,invar.T,cint,cmap=cmap)
pcm = ax.pcolormesh(lonr, latr, invar.T, vmin=0, vmax=1500, cmap=cmap)
cl = ax.contour(lonr, latr, invar.T, cint, colors="k", linewidths=.75)
#cl = ax.contour(lonr,latr,invar.T,cint,colors="k",linewidths = 0.5)
ax.clabel(cl, fmt="%i", fontsize=9)
#ax.add_feature(cfeature.LAND,color='k')
#ax.set_title("$MLD_{max} - MLD_{min}$" + "\n 40-member Ensemble Average",fontsize=12)
ax.set_title("$MLD_{max} - MLD_{min}$" + "\n %s" % mconfig, fontsize=12)
plt.colorbar(pcm, ax=ax, orientation='horizontal', fraction=0.040, pad=0.10)
plt.savefig(outpath + "MLD_RangeDiff.png", dpi=200)
#%% MLD Maximum