m.drawmapboundary(fill_color='white',color='dimgrey',linewidth=0.7)
cs = m.contourf(x,y,var,limit,extend='both')
cs1 = m.contourf(x,y,pvar,colors='None',hatches=['....'])
if varnames[v] == 'Z30': # the interval is 250 m
cs2 = m.contour(x,y,climoq,np.arange(21900,23500,250),
colors='k',linewidths=1.5,zorder=10)
if varnames[v] == 'RNET':
m.drawcoastlines(color='darkgray',linewidth=0.3)
m.fillcontinents(color='dimgrey')
else:
m.drawcoastlines(color='dimgray',linewidth=0.8)
if varnames[v] == 'T2M':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
elif varnames[v] == 'Z500':
cmap = ncm.cmap('nrl_sirkes')
cs.set_cmap(cmap)
elif varnames[v] == 'Z30':
cmap = ncm.cmap('nrl_sirkes')
cs.set_cmap(cmap)
elif varnames[v] == 'SLP':
cmap = ncm.cmap('nrl_sirkes')
cs.set_cmap(cmap)
elif varnames[v] == 'U10' or varnames[v] == 'U300':
cmap = ncm.cmap('temp_diff_18lev')
cs.set_cmap(cmap)
cs.set_cmap(cmap)
elif varnames[v] == 'SWE':
var, lons_cyclic = shiftgrid(180., var, lons_cyclic, start=False)
lon2d, lat2d = np.meshgrid(lons_cyclic, lat)
x, y = m(lon2d, lat2d)
pvar, lons_cyclic = addcyclic(pvar, lon)
pvar, lons_cyclic = shiftgrid(180., pvar, lons_cyclic, start=False)
m.drawmapboundary(fill_color='white', color='dimgrey', linewidth=0.7)
cs = m.contourf(x, y, var, limit, extend='max', norm=norm)
cs1 = m.contourf(x, y, pvar, colors='None', hatches=['....'])
m.drawcoastlines(color='dimgrey', linewidth=0.6)
if varnamesn[v] == 'T2M':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
elif varnamesn[v] == 'T925':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
elif varnamesn[v] == 'T850':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
### Add experiment text to subplot
if any([v == 0, v == 2, v == 4]):
ax.annotate(r'\textbf{%s}' % varnamesn[v],
xy=(0, 0),
xytext=(-0.14, 0.5),
textcoords='axes fraction',
color='k',
climoq,lons_cyclic = addcyclic(climo[i], lon)
climoq,lons_cyclic = shiftgrid(180.,climoq,lons_cyclic,start=False)
m.drawmapboundary(fill_color='white',color='dimgray',linewidth=0.7)
cs = m.contourf(x,y,var,limit,extend='both')
cs1 = m.contourf(x,y,pvar,colors='None',hatches=['....'],
linewidths=0.4)
if varnames[v] == 'Z30': # the interval is 250 m
cs2 = m.contour(x,y,climoq,np.arange(21900,23500,250),
colors='k',linewidths=1.5,zorder=10)
m.drawcoastlines(color='dimgray',linewidth=0.8)
if varnames[v] == 'T2M':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
elif varnames[v] == 'SLP':
cmap = cmocean.cm.balance
cs.set_cmap(cmap)
elif varnames[v] == 'Z500':
cmap = cmocean.cm.balance
cs.set_cmap(cmap)
elif varnames[v] == 'Z30':
cmap = cmocean.cm.balance
cs.set_cmap(cmap)
elif varnames[v] == 'U10' or varnames[v] == 'U300' or varnames[v] == 'U500':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
elif varnames[v] == 'SWE':
cmap = cmap = cmocean.cm.balance
ax.spines['bottom'].set_color('dimgrey')
ax.spines['left'].set_linewidth(2)
ax.spines['bottom'].set_linewidth(2)
ax.tick_params('both', length=4, width=2, which='major', color='dimgrey')
if r < 2:
ax.spines['bottom'].set_color('w')
ax.tick_params('x', length=0, width=0, which='major', color='w')
plt.plot([0] * len(corrvar[r]),
linewidth=2,
color='dimgrey',
linestyle='--')
color = iter(
ncm.cmap('MPL_gnuplot2')(np.linspace(0, 0.8, len(corrvar[r]))))
for i in range(len(corrvar[r])):
c = next(color)
plt.plot(corrvar[r][i],
linewidth=1.5,
color=c,
alpha=1,
label=r'\textbf{%s}' % varnames[i],
linestyle='-',
marker='o',
markersize=3)
if r == 1:
plt.ylabel(r'\textbf{Pattern Correlation [R]}',
color='dimgrey',
fontsize=13)
plt.gca().invert_yaxis()
plt.yscale('log', nonposy='clip')
plt.ylabel(r'\textbf{Pressure (hPa)}',
color='dimgrey',
fontsize=15,
labelpad=1)
xlabels = [r'Sep', r'Oct', r'Nov', r'Dec', r'Jan', r'Feb', r'Mar', r'Apr']
plt.xticks(np.arange(0, 212, 30), xlabels, fontsize=8)
plt.yticks(zscale, map(str, zscale), ha='right', fontsize=8)
plt.minorticks_off()
plt.xlim([30, 210])
plt.ylim([1000, 10])
cmap = ncm.cmap('temp_diff_18lev')
cs.set_cmap(cmap)
cbar_ax = fig.add_axes([0.312, 0.1, 0.4, 0.03])
cbar = fig.colorbar(cs,
cax=cbar_ax,
orientation='horizontal',
extend='max',
extendfrac=0.07,
drawedges=False)
cbar.outline.set_edgecolor('dimgrey')
cbar.set_label(r'\textbf{m/s}', fontsize=11, color='dimgray')
cbar.set_ticks(barlim)
cbar.set_ticklabels(list(map(str, barlim)))
cbar.ax.tick_params(axis='x', size=.01)
m.drawmapboundary(fill_color='k')
m.drawcoastlines(color='k', linewidth=0.4)
### Colorbar limits
barlim = np.arange(0, 31, 5)
### Make the plot continuous
var, lons_cyclic = addcyclic(var, lons)
var, lons_cyclic = shiftgrid(180., var, lons_cyclic, start=False)
lon2d, lat2d = np.meshgrid(lons_cyclic, lats)
x, y = m(lon2d, lat2d)
cs = plt.contourf(x, y, var, np.arange(-1.8, 31.1, 1), extend='max')
cmap = ncm.cmap('MPL_gnuplot')
cs.set_cmap(cmap)
t = plt.annotate(r'\textbf{%s}' % yearsqq[i],
textcoords='axes fraction',
xy=(0, 0),
xytext=(0.34, 1.03),
fontsize=50,
color='w',
alpha=0.6)
t1 = plt.annotate(r'\textbf{GRAPHIC}: Zachary Labe (@ZLabe)',
textcoords='axes fraction',
xy=(0, 0),
xytext=(0.02, -0.167),
fontsize=4.5,
color='w',
anomalies = slp - meanslp
yr = np.where(years == 2012)[0][0]
springanom = np.nanmean(anomalies[:, 3:6, :, :], axis=1)
summeranom = np.nanmean(anomalies[:, 6:9, :, :], axis=1)
### Plot figure
plt.rc('text', usetex=True)
plt.rc('font', **{'family': 'sans-serif', 'sans-serif': ['Avant Garde']})
fig = plt.figure()
barlim = np.arange(-10, 12, 2)
values = np.arange(-10, 10.1, 0.5)
cmap = ncm.cmap('testcmap')
ax1 = plt.subplot(611)
plt.contourf(anomalies[yr, 3, :, :], values, cmap=cmap, extend='both')
ax1.spines['top'].set_color('darkgrey')
ax1.spines['right'].set_color('darkgrey')
ax1.spines['bottom'].set_color('darkgrey')
ax1.spines['left'].set_color('darkgrey')
plt.setp(ax1.get_yticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
ax1.xaxis.set_tick_params(size=0)
ax1.yaxis.set_tick_params(size=0)
plt.grid(color='darkgrey')
ax1.yaxis.grid(False)
parallels = np.arange(50, 86, 5)
meridians = np.arange(-180, 180, 30)
m.drawparallels(parallels,
labels=[False, False, False, False],
linewidth=0.0,
color='w')
par = m.drawmeridians(meridians,
labels=[True, True, False, False],
linewidth=0.0,
fontsize=4,
color='w')
setcolor(par, 'darkgrey')
### Set colormap
cmap2 = cmocean.cm.balance
cmap2 = ncm.cmap('BlRe')
cs2.set_cmap(cmap2)
cbar = m.colorbar(cs2,
drawedges=False,
location='bottom',
pad=0.14,
size=0.1)
ticks = np.arange(0, 8, 1)
cbar.set_ticks(barlim)
cbar.set_ticklabels(list(map(str, barlim)))
cbar.set_label(
r'\textbf{SEA SURFACE TEMPERATURE ANOMALIES [\textbf{$\bf{^\circ}$C}]}',
fontsize=14,
color='w')
cbar.ax.tick_params(axis='x', size=.0001)
for t in x[m][1]:
t.set_color(color)
m.drawparallels(parallels,
labels=[False, False, False, False],
linewidth=0.2,
fontsize=4)
mer = m.drawmeridians(meridians,
labels=[False, False, True, True],
linewidth=0.2,
fontsize=4)
setcolor(mer, 'k')
values = np.arange(-1, 1.1, 0.1)
cs = m.contourf(x, y, var, values, extend='both')
cmap = ncm.cmap('BrownBlue12')
cs.set_cmap(cmap)
cbar = plt.colorbar(cs,
orientation='horizontal',
extend='both',
extendfrac=0.06,
pad=0.05,
drawedges=True)
cbar.set_ticks(np.arange(-1, 2, 1))
cbar.set_ticklabels(map(str, np.arange(-1, 2, 1)))
cbar.set_label(r'\textbf{Difference (m)}', fontsize=8, color='k', labelpad=1)
cbar.ax.tick_params(labelsize=8)
plt.savefig(directoryfigure + 'seasonalcycle_lens.png', dpi=300)
#m = Basemap(projection='robin',lon_0=0,resolution='l')
m = Basemap(projection='ortho',lon_0=300,lat_0=-25,resolution='l')
var = sit[9] - sit2[9]
m.drawmapboundary(fill_color='white')
m.drawcoastlines(color='dimgrey',linewidth=0.3)
parallels = np.arange(-90,90,30)
meridians = np.arange(-180,180,60)
m.drawparallels(parallels,labels=[True,True,True,True],
linewidth=0.3,color='k',fontsize=6)
m.drawmeridians(meridians,labels=[True,True,True,True],
linewidth=0.3,color='k',fontsize=6)
m.drawlsmask(land_color='darkgrey',ocean_color='mintcream')
cs = m.contourf(lons,lats,var,80,latlon=True,extend='both')
cs1 = m.contour(lons,lats,var,50,linewidths=0.2,colors='darkgrey',
linestyles='-',latlon=True)
cmap = ncm.cmap('GMT_ocean')
cs.set_cmap(cmap)
cbar = plt.colorbar(cs,extend='both')
#cbar.set_label(r'\textbf{SIT}')
#ticks = np.arange(0,8,1)
#cbar.set_ticks(ticks)
#cbar.set_ticklabels(map(str,ticks))
plt.savefig(directoryfigure + 'testss_sstf.png',dpi=300)
print 'Completed: Script done!'
style = 'polar'
if style == 'ortho':
m = Basemap(projection='ortho',lon_0=-90,
lat_0=70,resolution='l',round=True)
elif style == 'polar':
m = Basemap(projection='npstere',boundinglat=56,lon_0=270,
resolution='l',round =True)
m.drawmapboundary(fill_color='darkgrey',linewidth=0.7)
m.drawcoastlines(color='darkgrey',linewidth=0.2)
m.drawlsmask(land_color='dimgrey',ocean_color='mintcream')
#### Plot filled contours
x,y = m(x1,y1)
diff[np.isnan(diff)]=0.0
csm=plt.get_cmap(ncm.cmap('NCV_blu_red'),16)
norm = c.BoundaryNorm(np.arange(-4,4.5,0.5),csm.N)
cs = m.hexbin(x,y,C=diff,vmin = -4,vmax = 4,cmap=csm,norm=norm)
barlim = np.arange(-4,5,1)
m.fillcontinents(color='dimgrey')
ax.annotate(r'\textbf{%s}' % yearsq[i],xy=(0,0),xytext=(0.865,0.90),
textcoords='axes fraction',color='k',fontsize=11,
rotation=320,ha='center',va='center')
cbar_ax = fig.add_axes([0.313,0.12,0.4,0.03])
cbar = fig.colorbar(cs,cax=cbar_ax,orientation='horizontal',
extend='both',extendfrac=0.07,drawedges=False)
cbar.set_ticks(barlim)
cbar.set_ticklabels(list(map(str,barlim)))
cs1 = m.contourf(x,
y,
pvalue_onq,
colors='None',
hatches=['....'],
linewidths=0.4)
ax1.annotate(r'\textbf{ON}',
xy=(0, 0),
xytext=(0.35, 1.05),
xycoords='axes fraction',
fontsize=25,
color='dimgrey',
rotation=0)
cmap = ncm.cmap('precip4_diff_19lev')
cs.set_cmap(cmap)
###########################################################################
ax2 = plt.subplot(132)
m = Basemap(projection='ortho',
lon_0=0,
lat_0=89,
resolution='l',
area_thresh=10000.)
var, lons_cyclic = addcyclic(diff_dj, lon)
var, lons_cyclic = shiftgrid(180., var, lons_cyclic, start=False)
lon2d, lat2d = np.meshgrid(lons_cyclic, lat)
def make_animation(fig, frames, outputname):
ani = animation.FuncAnimation(fig,
animate,
frames,
interval=0.01,
blit=False,
init_func=initial,
repeat=False)
# ani.save(outputname, writer=animation.FFMpegWriter(fps=4))
ani.save(outputname, writer='imagemagick')
plt.close(fig)
return ani
######################################### Run the Code #############
a = xr.open_dataset('sst_anom_mhws.nc')
a1 = a.sel(time=slice('2010-06-26', '2010-07-29'))
import nclcmaps
cmap1 = nclcmaps.cmap('sunshine_9lev')
ds = a1 * 1
varname = 'sstanom'
cartopy_projection = ccrs.Orthographic(central_latitude=0.0,
central_longitude=75.0)
min_value = 0.00
max_value = 0.8
N = 11
cmap1 = cmap1
fig, ax = make_figure(cartopy_projection)
make_animation(fig, frames=ds.time.size, outputname='output.gif')
new_lon = np.linspace(lon[0], lon[-1], len(lon) * new_res, endpoint=True)
new_lat = np.linspace(lat[0], lat[-1], len(lat) * new_res, endpoint=True)
dset_30_days.load()
new_lon, new_lat, matm = regrid(dset_30_days.sum('time')['trmm'].data, lon, lat, new_lon, new_lat)
lons, lats = np.meshgrid(new_lon, new_lat)
sys.path.append(os.path.join(os.environ['HOME'], 'pythonlibs'))
import nclcmaps as ncm
cmap = ncm.cmap('GMT_drywet')
proj = ccrs.PlateCarree()
f, ax = plt.subplots(figsize=(10, 8), subplot_kw=dict(projection=proj))
ax.set_extent([domain['lonmin'], domain['lonmax'], domain['latmin'], domain['latmax']])
ax.add_feature(cfeature.GSHHSFeature(scale='full', levels=[1,2,3,4]))
im = ax.contourf(lons, lats, matm, levels=np.arange(0, round_down(matm.max(), 20), 20), cmap=cmap, extend='max', transform=proj)
c = ax.contour(lons, lats, matm, levels=np.arange(0, round_down(matm.max(), 20), 20), color='k', linewidths=0.5, transform=proj)
cb = plt.colorbar(im, shrink=0.8)
x, y = prj(lons, lats)
ll_lon, ll_lat = prj(min(x), min(y), inverse=True)
ur_lon, ur_lat = prj(max(x), max(y), inverse=True)
return Basemap(projection='stere', lat_0=lat_0, lon_0=lon_0,
llcrnrlon=ll_lon, llcrnrlat=ll_lat,
urcrnrlon=ur_lon, urcrnrlat=ur_lat, round=True,
resolution='l')
m = polar_stere(lonmin,lonmax,latmin,latmax)
m.drawcoastlines(color = 'r',linewidth=1.4)
m.drawmapboundary(color='k')
m.drawlsmask(land_color='k',ocean_color='k')
cs = m.contourf(lon,lat,ice[:,:],np.arange(20,100.01,1),extend='min',latlon=True)
cmap = ncm.cmap('MPL_YlGnBu')
cmap = cmocean.cm.ice
cs.set_cmap(cmap)
m.fillcontinents(color='k')
cbar = m.colorbar(cs,location='right',pad = 0.2)
cbar.outline.set_edgecolor('k')
barlim = np.arange(20,101,10)
cbar.set_ticks(barlim)
cbar.set_ticklabels(list(map(str,barlim)))
cbar.set_label(r'\textbf{Concentration (\%)}',fontsize=13,
alpha=0.6)
cbar.ax.tick_params(axis='y', size=.01)
fig.suptitle(r'\textbf{ARCTIC SEA ICE -- %s}' % titletime,
m4.drawmapboundary(fill_color='white',color='dimgray',linewidth=0.7)
m4.drawmapboundary(fill_color='white',color='dimgray',linewidth=0.7)
m4.drawcoastlines(color='darkgrey',linewidth=0.1)
parallels = np.arange(-90,90,30)
meridians = np.arange(-180,180,60)
#m.drawparallels(parallels,labels=[True,True,True,True],
# linewidth=0.1,color='k',fontsize=6)
#m.drawmeridians(meridians,labels=[True,True,True,True],
# linewidth=0.1,color='k',fontsize=6)
#m4.drawlsmask(land_color='dimgray',ocean_color='mintcream')
cs = m4.contourf(x,y,var,limdiff,extend='both')
cs1 = m4.contour(x,y,var,barlimdiff,linewidths=0.1,colors='darkgrey',
linestyles='-')
cmap = ncm.cmap('amwg_blueyellowred')
cs.set_cmap(cmap)
cbar = m4.colorbar(cs,location='bottom',pad = 0.2,extend='max',
drawedges=False)
ticks = barlimdiff
labels = list(map(str,barlimdiff))
cbar.set_ticks(ticks)
cbar.set_ticklabels(labels)
cbar.set_label(r'\textbf{Difference [m]}',fontsize=11,color='dimgray')
cbar.ax.tick_params(axis='x', size=.01)
m4.fillcontinents(color='dimgray')
plt.annotate(r'\textbf{HIT}',xy=(-0.82,1.1),
xycoords='axes fraction',color='dimgray',fontsize=30,alpha=1)
plt.annotate(r'\textbf{CIT--HIT}',xy=(0.2,1.1),
varns[:] = var
ncfile.close()
print '*Completed: Created netCDF4 File!'
sncn = regrid(lat1,lon1,lat2,lon2,snc,years)
netcdfPiomas(lat2,lon2,sncn,directorydata1)
### Plot figure
plt.rc('text',usetex=True)
plt.rc('font',**{'family':'sans-serif','sans-serif':['Avant Garde']})
fig = plt.figure()
ax = plt.subplot(111)
cmap = ncm.cmap('MPL_PuRd')
sncn[np.where(sncn==0.0)] = np.nan
var = sncn[-2,3,:,:]*100.
m = Basemap(projection='npstere',boundinglat=66,lon_0=270,
resolution='l',round =True)
m.drawmapboundary(fill_color='white')
m.drawcoastlines(color='k',linewidth=0.3)
parallels = np.arange(50,90,10)
meridians = np.arange(-180,180,30)
m.drawparallels(parallels,labels=[False,False,False,False],
linewidth=0.3,color='k',fontsize=6)
m.drawmeridians(meridians,labels=[True,True,False,False],
linewidth=0.3,color='k',fontsize=6)
ncfile.close()
print('*Completed: Created netCDF4 File!')
sicn = regrid(lat1, lon1, lat2, lon2, sic, years)
netcdfPiomas(lat2, lon2, sicn, directorydata1)
### Plot figure
plt.rc('text', usetex=True)
plt.rc('font', **{'family': 'sans-serif', 'sans-serif': ['Avant Garde']})
fig = plt.figure()
ax = plt.subplot(111)
cmap = ncm.cmap('MPL_cubehelix')
sicn[np.where(sicn == 0.0)] = np.nan
var = sicn[-2, 3, :, :]
m = Basemap(projection='npstere',
boundinglat=55,
lon_0=270,
resolution='l',
round=True)
m.drawmapboundary(fill_color='white')
m.drawcoastlines(color='k', linewidth=0.3)
parallels = np.arange(50, 90, 10)
meridians = np.arange(-180, 180, 30)
m.drawparallels(parallels,
def hov_diagram(lon,
y,
contour_data,
levels,
col="testcmap",
ax=None,
rng=None,
step=60,
ew=False,
norm=False,
extend='both',
vmin=None,
vmax=None):
"""Draw hovmoller diagrams (time vs lat)
Inputs:
lon, y = x and y axes respectively. lon is usually longitude, y is time,
contour_data = data to be plotted (lon x time)
levels = levels for the contour of the hovmoller diagram
[optional]
ax = an axis on a plot to draw the plot on
extend = Which side of the colorbar to extend: Must be one of 'both', 'min', 'max', 'neither'
ew = Add "E" or "W" tag to longitude axis
col = ncl colormap. By default test cmap
rng = minimum axis tick and maximum x axis tick (an array of 2 values)
defaults to None and choose the min and max of the longitudes passed
step = steps taken on longitde axis"""
l1 = np.min(lon)
l2 = np.max(lon)
if (extend not in ['both', 'min', 'max', 'neither']):
raise ValueError("hov_diagram: Unexpected value for extend")
X, Y = np.meshgrid(lon, y)
if (isinstance(col, str)):
cmap = ncm.cmap(col)
if (ax is not None):
CS = ax.contourf(X,
Y,
contour_data,
levels,
cmap=cmap,
extend=extend)
else:
CS = plt.contourf(X,
Y,
contour_data,
levels,
cmap=cmap,
extend=extend)
else:
if (ax is not None):
CS = ax.contourf(X,
Y,
contour_data,
levels,
colors=col,
extend=extend)
else:
CS = plt.contourf(X,
Y,
contour_data,
levels,
colors=col,
extend=extend)
if (ax is None):
ax = plt.gca()
ax.minorticks_on()
ax.tick_params(axis="both", which="both", direction="out")
ax.tick_params(axis="y", which="minor", left="off")
ax.tick_params(axis="both", which="both", top="off", right="off")
if (rng is None):
tck = np.arange(l1, l2, step)
else:
if (len(rng) == 2):
tck = np.arange(rng[0], rng[1], step)
else:
raise ValueError("Expected only a 2 value array for rng")
if (ew):
tck_lb = [str(np.int(np.abs(t))) + __get_EW__(t) for t in tck]
else:
tck_lb = [str(t) for t in tck]
ax.set_xticks(tck)
ax.set_xticklabels(tck_lb, fontsize=7)
return CS
anomalies = h7 - meanh7
yr = np.where(years == 2011)[0][0]
springanom = np.nanmean(anomalies[:, 3:6, :, :], axis=1)
summeranom = np.nanmean(anomalies[:, 6:9, :, :], axis=1)
### Plot figure
plt.rc('text', usetex=True)
plt.rc('font', **{'family': 'sans-serif', 'sans-serif': ['Avant Garde']})
fig = plt.figure()
values = np.arange(-100, 101, 5)
barlim = np.arange(-100, 101, 50)
cmap = ncm.cmap('BlueDarkRed18')
ax1 = plt.subplot(611)
plt.contourf(anomalies[yr, 3, :, :], values, cmap=cmap, extend='both')
ax1.spines['top'].set_color('darkgrey')
ax1.spines['right'].set_color('darkgrey')
ax1.spines['bottom'].set_color('darkgrey')
ax1.spines['left'].set_color('darkgrey')
plt.setp(ax1.get_yticklabels(), visible=False)
plt.setp(ax1.get_xticklabels(), visible=False)
ax1.xaxis.set_tick_params(size=0)
ax1.yaxis.set_tick_params(size=0)
plt.grid(color='darkgrey')
ax1.yaxis.grid(False)
def plot_contour_map(contour_data,
lats,
lons,
minlev,
maxlev,
levspace,
add_cyclic=False,
lat_lim=[-90, 90],
lon_lim=[0, 360],
proj="cyl",
drawgrids=None,
gridfont=10,
gridlat=[-90, 90],
gridlon=[0, 360],
center_lon=0,
drawls=False,
cmap="testcmap",
ax=None,
extend='both',
conf=None,
ms=0.1,
rs=3,
scatter=True):
"""Plot a contour map on a basemap imported from mpl_toolkits
contour_data - Data for contour map should be lat x lon
lats - latitude values
lons - longitude values
minlev - minimum contour level
maxlev - maximum contour level
levspace - spacing between contours
extend [optional] - Takes 4 values 'min', 'max', 'both', 'neither'. Used for the contour map. 'both' by default
add_cyclic [optional] - Add a cyclic point to the plot. Useful for full longitude ranges
proj [optional] - Projection of the map.
Takes only three possible values from the range of projections available in matplotlib ['hammer', 'robin', 'cyl'].
Rectangle region bounds are ignored for both hammer and robin. Only lat_0 is considered. Default is 'cyl'
drawgrids [optional] - Draw grids on the map at this spacing - a 2 element tuple. Is only used for non-cylindrical maps. Default None
gridfont [optional] - Fontsize of grid label
lat_lim [optional] - Limits for latitude [0, 360] by default. Must be a 2 value array-like
lon_lim [optional] - Limits for longitude [-90,90] by default. Must be a 2 value array-like
lonshift [optional] - Shift the longitude to match lon_0. This argument takes the amount by which to shift
drawls [Optional] - Toggles Landsea masks. Set to False by default
cmap[Optional] - ncl colormap to use. Default is testcmap, or a matplotlib map or a list of colors
ax [Optional] - which axis to draw upon
conf [Optional] - Draw a scatter plot of 1s and 0s signifiying confidence
levels"""
if (len(lat_lim) != 2) or (len(lon_lim) != 2):
raise ValueError("Only 2 values expected for axis limits")
# Data for the contour map
clevs = np.arange(minlev, maxlev + levspace / 2., levspace)
if (proj not in ('cyl', 'hammer', 'robin')):
raise ValueError(
"plot_contour_map: proj not in one of ['robin', 'hammer', cyl'")
if (proj == 'cyl'):
m = Basemap(projection = 'cyl', llcrnrlat = lat_lim[0], \
urcrnrlat = lat_lim[1], \
area_thresh = 10000,
llcrnrlon = lon_lim[0], # urcrnrlon = 360,
urcrnrlon = lon_lim[1],
resolution = 'l', suppress_ticks = False, ax = ax)
elif (proj == 'hammer' or proj == 'robin'):
m = Basemap(projection=proj,
area_thresh=10000,
lon_0=center_lon,
resolution='l',
suppress_ticks=True,
ax=ax)
m.drawcoastlines()
nlon = len(lons)
# If lsmask is required
if (drawls):
m.drawlsmask()
if (proj != 'cyl'):
# If central longitude is not zero or the central value of the longitude array, the longitude grid
# also has to be shifted to accomodate for the new grid structure
if (
lons[nlon / 2] != center_lon
): # which means we need to ensure central longitude is set to lat_0
lon_start = center_lon - 180
contour_data, lons = shiftgrid(lon_start, contour_data, lons)
# Addcyclic is applied after centering the logitude since it can break the code because of the monotonicity issue
if (add_cyclic):
contour_data, lons = addcyclic(contour_data, lons)
x, y = np.meshgrid(lons, lats)
x, y = m(x, y) # Project meshgrid onto map
if (drawgrids is not None):
if (len(drawgrids) != 2):
raise ValueError(
"plot_contour_map: Expected 2 values as tuple for drawgrids"
)
m.drawparallels(np.arange(gridlat[0], gridlat[1] + 1,
drawgrids[0]),
labels=[1, 0, 0, 0],
fontsize=gridfont)
m.drawmeridians(np.arange(gridlon[0], gridlon[1] + 1,
drawgrids[1]),
fontsize=gridfont)
else:
if (add_cyclic):
contour_data, lons = addcyclic(contour_data, lons)
x, y = np.meshgrid(lons, lats)
# contour_data = contour_data[:,lon_pos]
if (extend not in ['both', 'min', 'max', 'neither']):
raise ValueError(
"plot_contour_map: extend only takes 3 values - ['both', 'min', 'max']"
)
if (isinstance(cmap, str)):
cmap = ncm.cmap(cmap)
if (isinstance(cmap, str) or isinstance(cmap, mcl.ListedColormap)
or isinstance(cmap, mcl.LinearSegmentedColormap)):
cs = m.contourf(x, y, contour_data, clevs, cmap=cmap, extend=extend)
elif (isinstance(cmap, np.ndarray)):
cs = m.contourf(x, y, contour_data, clevs, colors=cmap, extend=extend)
else:
raise ValueError("Invalid Colormap provided")
# Hack for map limits. Note: there needs to be a better way or simply migrate to cartopy
if (proj != 'cyl'):
# Map projections for latitude
llcrnrlon, llcrnrlat = m(min(lons), lat_lim[0])
urcrnrlon, urcrnrlat = m(max(lons), lat_lim[1])
if (ax is None):
ax = plt.gca()
ax.set_ylim(llcrnrlat, urcrnrlat)
# Drawing map boundary with black background.
# Relies on resolution being a little off. Is an unavoidable hack. Need to find something better
m.drawmapboundary(fill_color='k')
# Hatching the plot with significance levels
if (conf is not None):
conf[~conf.mask] = ms
if (scatter):
m.scatter(x[::rs, ::rs],
y[::rs, ::rs],
conf[::rs, ::rs],
marker='.',
color='k',
edgecolor=None,
lw=0)
else:
m.contourf(x,
y,
conf,
n_levels=2,
hatches=[None, '\\\+///'],
colors='none',
extend='lower',
linecolor='grey')
return m, cs
var,
limit,
extend='both',
alpha=0.7,
antiliased=True)
cs1 = m.contourf(x, y, pvar, colors='None', hatches=['....'])
cs2 = m.contour(lon2c,
lat2c,
climo,
np.arange(-200, 201, 60),
colors='k',
linewidths=1.5,
latlon=True,
zorder=10)
cmap = ncm.cmap('nrl_sirkes')
cs.set_cmap(cmap)
m.drawcoastlines(color='dimgray', linewidth=0.8)
### Add experiment text to subplot
ax1.annotate(r'%s' % experiments[i],
xy=(0, 0),
xytext=(0.865, 0.90),
textcoords='axes fraction',
color='k',
fontsize=11,
rotation=320,
ha='center',
va='center')
# Make the plot continuous
barlim = np.arange(-5, 5.1, 2)
var, lons_cyclic = addcyclic(var, lons)
var, lons_cyclic = shiftgrid(180., var, lons_cyclic, start=False)
lon2d, lat2d = np.meshgrid(lons_cyclic, lats)
x, y = m(lon2d, lat2d)
cs = m.contourf(x, y, var[:, :], np.arange(-5, 5.1, 0.25), extend='both')
cs1 = m.contour(x,
y,
var[:, :],
np.arange(-5, 5.1, 0.25),
linewidths=0.2,
colors='k',
linestyles='-')
cmap = ncm.cmap('BlueWhiteOrangeRed')
cs.set_cmap(cmap)
cbar = m.colorbar(cs, location='right', pad='10%', drawedges=True)
cbar.set_ticks(barlim)
cbar.set_ticklabels(map(str, barlim))
cbar.ax.tick_params(axis='x', size=.1)
cbar.set_label(r'\textbf{degrees C}')
fig.suptitle(r'\textbf{925T anomalies - %s %s-%s}' % (months, year1, year2))
plt.savefig(directoryfigure + 'TAS/tas_%s_%s%s.png' % (months, year1, year2),
dpi=300)
'Completed: Script done!'
cs2 = plt.contour(lat,lev,climovar,np.arange(-20,101,5),
linewidths=0.6,colors='dimgrey')
plt.contourf(latq,levq,pvar,colors='None',hatches=['////'],
linewidth=5)
plt.gca().invert_yaxis()
plt.yscale('log',nonposy='clip')
plt.xlim([0,90])
plt.ylim([1000,10])
plt.xticks(np.arange(0,96,15),map(str,np.arange(0,91,15)),fontsize=8)
plt.yticks(zscale,map(str,zscale),ha='right',fontsize=8)
plt.minorticks_off()
if varnames[v] == 'U':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
elif varnames[v] == 'TEMP':
cmap = ncm.cmap('NCV_blu_red')
cs.set_cmap(cmap)
elif varnames[v] == 'GEOP':
cmap = cmocean.cm.balance
cs.set_cmap(cmap)
elif varnames[v] == 'V':
cmap = ncm.cmap('temp_diff_18lev')
cs.set_cmap(cmap)
elif varnames[v] == 'EGR':
cmap = cmocean.cm.curl
cs.set_cmap(cmap)
### Add experiment text to subplot
m.drawlsmask(land_color='darkgrey',ocean_color='mintcream')
### Adjust maximum limits
values = np.arange(-3,3.1,0.25)
### Plot filled contours
cs = m.contourf(x,y,var,
values,extend='both')
cs1 = m.contour(x,y,var,
values,linewidths=0.2,colors='darkgrey',
linestyles='-')
cs2 = ax.scatter(x,y,varscat,color='k',marker='.',alpha=0.5,
edgecolor='k',linewidth=0.2)
### Set colormap
cmap = ncm.cmap('temp_19lev')
cs.set_cmap(cmap)
cbar_ax = fig.add_axes([0.313,0.13,0.4,0.03])
cbar = fig.colorbar(cs,cax=cbar_ax,orientation='horizontal',
extend='both',extendfrac=0.07,drawedges=True)
cbar.set_ticks(np.arange(-3,4,1))
cbar.set_ticklabels(map(str,np.arange(-3,4,1)))
cbar.set_label(r'\textbf{Difference (meters)}')
plt.subplots_adjust(wspace=-0.28)
plt.subplots_adjust(hspace=0.15)
plt.subplots_adjust(bottom=0.2)
plt.subplots_adjust(top=0.87)