def plot_map(data, rlon=None, rlat=None, use_pcolor=0, **keywords):
""" display the data in a map
keywords: dict which can include the following keywords minv=0.0, maxv=0.0, dv=0.0,
show_map=0, map_proj='cyl', show_lat=0, show_lon=0, lat_0=0.0, lon_0=0.0,
minlat=-90.0, maxlat=90.0, minlon=0.0, maxlon=360.0, use_log=0, level=level
"""
minv = 0.0
if ('minv' in keywords):
minv = keywords['minv']
maxv = 0.0
if ('maxv' in keywords):
maxv = keywords['maxv']
dv = 0.0
if ('dv' in keywords):
dv = keywords['dv']
if ('dv' in keywords):
dv = keywords['dv']
if (maxv > minv):
rlvl = arange(minv, maxv + dv, dv)
rlvl[0] = -999.0
rlvl[size(rlvl) - 1] = 999.
stitle = ""
add_str = ""
if ('title' in keywords):
add_str = keywords['title']
add_str = add_str.strip()
stitle = stitle + ' ' + add_str
if ('unit' in keywords):
add_str = keywords['unit']
add_str = add_str.strip()
stitle = stitle + '(' + add_str + ')'
cbar_vert = 1
if ('cbar_vert' in keywords):
cbar_vert = keywords['cbar_vert']
if (cbar_vert == 1):
orientation = 'vertical'
else:
orientation = 'horizontal'
show_lat = 1
if ('show_lat' in keywords):
show_lat = keywords['show_lat']
show_lon = 1
if ('show_lon' in keywords):
show_lon = keywords['show_lon']
nlon, nlat = shape(data)
vals = array(data)
map_proj = 'cyl'
if ('map_proj' in keywords):
map_proj = keywords['map_proj']
lat_0 = 0.0
if ('lat_0' in keywords):
lat_0 = keywords['lat_0']
minlat = -90.0
maxlat = 90.0
if ('minlat' in keywords):
minlat = keywords['minlat']
if ('maxlat' in keywords):
maxlat = keywords['maxlat']
if (rlat == None):
dlat = (maxlat - minlat) / nlat
rlat = arange(minlat, maxlat, dlat)
minlon = -180
maxlon = 180.0
if ('minlon' in keywords):
minlon = keywords['minlon']
if ('maxlon' in keywords):
maxlon = keywords['maxlon']
if (rlon == None):
dlon = (maxlon - minlon) / nlon
rlon = arange(minlon, maxlon, dlon)
lon_0 = 0
do_bdr = 0
if ('do_bdr' in keywords):
do_bdr = keywords['do_bdr']
if ('lon_0' in keywords):
lon_0 = keywords['lon_0']
boundinglat = 45
if ('boundinglat' in keywords):
boundinglat = keywords['boundinglat']
if (map_proj == 'npstere' or map_proj == 'spstere'):
m = Basemap(projection=map_proj, lon_0=lon_0, boundinglat=boundinglat)
elif (map_proj == 'ortho'):
m = Basemap(projection=map_proj, lon_0=lon_0, lat_0=lat_0)
else:
if (maxlon - minlon > 180):
m=Basemap(llcrnrlon=minlon, llcrnrlat=minlat, \
urcrnrlon=maxlon, urcrnrlat=maxlat,projection=map_proj, lon_0=lon_0, lat_0=lat_0, resolution='l')
else:
m=Basemap(llcrnrlon=minlon, llcrnrlat=minlat, \
urcrnrlon=maxlon, urcrnrlat=maxlat,projection=map_proj, lon_0=lon_0, lat_0=lat_0, resolution='i')
if (rlon[-1] < rlon[0] + 360.0):
rlon = resize(rlon, nlon + 1)
rlon[-1] = rlon[0] + 360.0
vals = squeeze(vals)
vals = resize(vals, [nlon + 1, nlat])
x, y = m(*meshgrid(rlon, rlat))
cmap = cm.Paired
if ('cmap' in keywords):
print 'cmap included'
cmap = keywords['cmap']
m.drawcoastlines(color='k', linewidth=0.5)
if (maxv > minv):
if (use_pcolor == 1):
cs0 = m.pcolormesh(x,
y,
transpose(vals),
shading='flat',
vmin=minv,
vmax=maxv,
cmap=cmap)
# cs0=m.imshow(x, y, transpose(vals), shading='flat', vmin=minv, vmax=maxv, cmap=cmap)
else:
cs0 = m.contourf(x, y, transpose(vals), rlvl, cmap=cmap)
else:
if (use_pcolor == 1):
cs0 = m.pcolor(x, y, transpose(vals), shading='flat', cmap=cmap)
else:
cs0 = m.contourf(x, y, transpose(vals), cmap=cmap)
# info(m.drawcoastlines)
# m.drawcountries(color=white)
m.drawmapboundary()
if (show_lat == 1):
if (maxlat - minlat >= 90):
m.drawparallels(arange(minlat, maxlat + 30.0, 30.),
labels=[1, 0, 0, 0],
color='grey')
else:
m.drawparallels(arange(minlat, maxlat + 5.0, 5.),
labels=[1, 0, 0, 0],
color='grey')
if (show_lon == 1):
if (maxlon - minlon >= 180):
m.drawmeridians(arange(minlon, maxlon + 60, 60.),
labels=[0, 0, 0, 1],
color='grey')
else:
m.drawmeridians(arange(minlon, maxlon + 10, 10.),
labels=[0, 0, 0, 1],
color='grey')
title(stitle)
show_colorbar = 1
if ('cb' in keywords):
show_colorbar = keywords['cb']
if (show_colorbar == 1):
colorbar(orientation=orientation, extend='both')
if (do_bdr == 1):
lvl = arange(max(vals.flat))
print shape(x), shape(y), shape(vals)
# cs2=m.contour(x[0:-1,:], y[0:-1,:], transpose(vals), lvl, colors='k', linewidth=0.5)
return m
lats[-1] = latsin[-1]+0.5*delon
lons, lats = meshgrid(lons, lats)
# setup of basemap ('lcc' = lambert conformal conic).
# use major and minor sphere radii from WGS84 ellipsoid.
m = Basemap(llcrnrlon=-145.5,llcrnrlat=1.,urcrnrlon=-2.566,urcrnrlat=46.352,\
resolution='l',area_thresh=1000.,projection='lcc',\
lat_1=50.,lon_0=-107.)
fig=m.createfigure()
ax = fig.add_axes([0.1,0.1,0.7,0.7],axisbg='aqua')
# make topodat a masked array, masking values lower than sea level.
topodat = where(topoin < 0.,1.e10,topoin)
topodat = ma.masked_values(topodat, 1.e10)
# make a pcolor plot.
x, y = m(lons, lats)
p = m.pcolor(x,y,topodat,shading='flat',cmap=cm.jet)
clim(-4000.,3000.) # adjust colormap.
cax = axes([0.875, 0.1, 0.05, 0.7]) # setup colorbar axes
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
# plot blue dot on boulder, colorado and label it as such.
xpt,ypt = m(-104.237,40.125)
m.plot([xpt],[ypt],'bo')
text(xpt+100000,ypt+100000,'Boulder')
# draw coastlines and political boundaries.
m.drawcoastlines()
#m.drawcountries()
#m.drawstates()
# draw parallels and meridians.
# label on left, right and bottom of map.
parallels = arange(0.,80,20.)
tlon = N.concatenate((tlon,tlon+360),1)
tlat = N.concatenate((tlat,tlat),1)
temp = MA.concatenate((temp,temp),1)
tlon = tlon-360.
pl.figure(figsize=(8.5,11))
pl.subplot(2,1,1)
# subplot 1 just shows POP grid cells.
map = Basemap(projection='merc', lat_ts=20, llcrnrlon=-180, \
urcrnrlon=180, llcrnrlat=-84, urcrnrlat=84, resolution='c')
map.drawcoastlines()
map.fillcontinents(color='white')
x, y = map(tlon,tlat)
im = map.pcolor(x,y,MA.masked_array(N.zeros(temp.shape,'f'), temp.mask),\
shading='faceted',cmap=pl.cm.cool,vmin=0,vmax=0)
# disclaimer: these are not really the grid cells because of the
# way pcolor interprets the x and y args.
pl.title('(A) CCSM POP Grid Cells')
# subplot 2 is a contour plot of surface temperature from the
# CCSM ocean model.
pl.subplot(2,1,2)
map.drawcoastlines()
map.fillcontinents(color='white')
CS1 = map.contourf(x,y,temp,15)
CS2 = map.contour(x,y,temp,15,colors='black',linewidths=0.5)
pl.title('(B) Surface Temp contours on POP Grid')
pl.show()
tlon = N.concatenate((tlon, tlon + 360), 1)
tlat = N.concatenate((tlat, tlat), 1)
temp = MA.concatenate((temp, temp), 1)
tlon = tlon - 360.
pl.figure(figsize=(8.5, 11))
pl.subplot(2, 1, 1)
# subplot 1 just shows POP grid cells.
map = Basemap(projection='merc', lat_ts=20, llcrnrlon=-180, \
urcrnrlon=180, llcrnrlat=-84, urcrnrlat=84, resolution='c')
map.drawcoastlines()
map.fillcontinents(color='white')
x, y = map(tlon, tlat)
im = map.pcolor(x,y,MA.masked_array(N.zeros(temp.shape,'f'), temp.mask),\
shading='faceted',cmap=pl.cm.cool,vmin=0,vmax=0)
# disclaimer: these are not really the grid cells because of the
# way pcolor interprets the x and y args.
pl.title('(A) CCSM POP Grid Cells')
# subplot 2 is a contour plot of surface temperature from the
# CCSM ocean model.
pl.subplot(2, 1, 2)
map.drawcoastlines()
map.fillcontinents(color='white')
CS1 = map.contourf(x, y, temp, 15)
CS2 = map.contour(x, y, temp, 15, colors='black', linewidths=0.5)
pl.title('(B) Surface Temp contours on POP Grid')
pl.show()
m = Basemap(llcrnrlon=llcrnrlon,llcrnrlat=llcrnrlat,
urcrnrlon=urcrnrlon,urcrnrlat=urcrnrlat,
rsphere=6371200.,
resolution='l',area_thresh=5000.,projection='lcc',
lat_1=standardpar,lon_0=centerlon)
x, y = m(lons, lats)
# setup figure size so each panel will have same aspect ratio as map.
xsize = rcParams['figure.figsize'][0]
ysize = (3./2.)*m.aspect*xsize
fig=figure(figsize=(xsize,ysize))
yoffset = (m.urcrnry-m.llcrnry)/30.
for npanel,fcsthr in enumerate(arange(0,72,12)):
nt = fcsthrs.index(fcsthr)
ax = fig.add_subplot(320+npanel+1)
# make a pcolor plot.
p = m.pcolor(x,y,t2m[nt,:,:],shading='flat',cmap=cm.jet)
clim(t2min,t2max) # fix color range to be the same for all panels
m.drawcoastlines()
m.drawstates()
m.drawcountries()
m.drawparallels(arange(25,75,20),labels=[1,0,0,0],fontsize=8,fontstyle='oblique')
m.drawmeridians(arange(-140,0,20),labels=[0,0,0,1],fontsize=8,yoffset=yoffset,fontstyle='oblique')
# panel title
title(repr(fcsthr)+'-h forecast valid '+verifdates[nt],fontsize=12)
# figure title
figtext(0.5,0.95,u"2-m temp (\N{DEGREE SIGN}K) forecasts from %s"%verifdates[0],horizontalalignment='center',fontsize=14)
# a single colorbar.
cax = axes([0.25, 0.03, 0.5, 0.025])
colorbar(tickfmt='%d', cax=cax, orientation='horizontal')
show()
hgt,x,y = m.transform_scalar(hgt,lons,lats,nx,ny,returnxy=True)
fig = figure(figsize=(8,8))
plots = ['contour','pcolor']
#plots = ['contour','imshow']
for np,plot in enumerate(plots):
fig.add_subplot(1,2,np+1)
ax = gca()
# plot data.
print plot+' plot ...'
if plot == 'pcolor':
m.pcolor(x,y,hgt,shading='flat')
elif plot == 'imshow':
im = m.imshow(hgt)
elif plot == 'contour':
levels, colls = m.contour(x,y,hgt,15,linewidths=0.5,colors='k')
levels, colls = m.contourf(x,y,hgt,15,cmap=cm.jet,colors=None)
# set size of plot to match aspect ratio of map.
l,b,w,h = ax.get_position()
b = 0.5 - 0.5*w*m.aspect; h = w*m.aspect
ax.set_position([l,b,w,h])
# draw map.
m.drawcoastlines()
# draw parallels
hgt, x, y = m.transform_scalar(hgt, lons, lats, nx, ny, returnxy=True)
fig = figure(figsize=(8, 8))
plots = ['contour', 'pcolor']
#plots = ['contour','imshow']
for np, plot in enumerate(plots):
fig.add_subplot(1, 2, np + 1)
ax = gca()
# plot data.
print plot + ' plot ...'
if plot == 'pcolor':
m.pcolor(x, y, hgt, shading='flat')
elif plot == 'imshow':
im = m.imshow(hgt)
elif plot == 'contour':
levels, colls = m.contour(x, y, hgt, 15, linewidths=0.5, colors='k')
levels, colls = m.contourf(x, y, hgt, 15, cmap=cm.jet, colors=None)
# set size of plot to match aspect ratio of map.
l, b, w, h = ax.get_position()
b = 0.5 - 0.5 * w * m.aspect
h = w * m.aspect
ax.set_position([l, b, w, h])
# draw map.
m.drawcoastlines()
resolution='l',
area_thresh=5000.,
projection='lcc',
lat_1=standardpar,
lon_0=centerlon)
x, y = m(lons, lats)
# setup figure size so each panel will have same aspect ratio as map.
xsize = rcParams['figure.figsize'][0]
ysize = (3. / 2.) * m.aspect * xsize
fig = figure(figsize=(xsize, ysize))
yoffset = (m.urcrnry - m.llcrnry) / 30.
for npanel, fcsthr in enumerate(arange(0, 72, 12)):
nt = fcsthrs.index(fcsthr)
ax = fig.add_subplot(320 + npanel + 1)
# make a pcolor plot.
p = m.pcolor(x, y, t2m[nt, :, :], shading='flat', cmap=cm.jet)
clim(t2min, t2max) # fix color range to be the same for all panels
m.drawcoastlines()
m.drawstates()
m.drawcountries()
m.drawparallels(arange(25, 75, 20),
labels=[1, 0, 0, 0],
fontsize=8,
fontstyle='oblique')
m.drawmeridians(arange(-140, 0, 20),
labels=[0, 0, 0, 1],
fontsize=8,
yoffset=yoffset,
fontstyle='oblique')
# panel title
title(repr(fcsthr) + '-h forecast valid ' + verifdates[nt], fontsize=12)
