print len(lons_out), ' obs after thinning'
# transform lons and lats to map coordinates.
x, y = m(array(lons_out) / d2r, array(lats_out) / d2r)
# find just those points in map region.
xx = []
yy = []
for xi, yi in zip(x, y):
if (xi > m.llcrnrx and xi < m.urcrnrx) and (yi > m.llcrnry
and yi < m.urcrnry):
xx.append(xi)
yy.append(yi)
# plot them as filled circles on the map.
# first, create figure with same aspect ratio as map.
fig = m.createfigure()
# background color will be used for 'wet' areas.
fig.add_axes([0.1, 0.1, 0.8, 0.8], axisbg='aqua')
# use zorder=10 to make sure markers are drawn last.
# (otherwise they are covered up when continents are filled)
m.scatter(xx, yy, marker='o', c='k', s=25, zorder=10)
# draw coasts and fill continents.
m.drawcoastlines(linewidth=0.5)
m.fillcontinents(color='coral')
# draw parallels and meridians.
delat = 20.
circles = arange(0.,90.,delat).tolist()+\
arange(-delat,-90,-delat).tolist()
m.drawparallels(circles)
delon = 45.
meridians = arange(0, 360, delon)
mapfile = sys.argv[1]+'.lonlatT'
lonfile = sys.argv[1]+'.lon'
latfile = sys.argv[1]+'.lat'
color_num = int(sys.argv[2])
# load data
map=array(load(mapfile))
lons=array(load(lonfile))
lats=array(load(latfile))
map,lons = shiftgrid(180.,map,lons,start=False)
# Mollweide projection
m1 = Basemap(projection='moll',lon_0=0.5*(lons[0]+lons[-1]))
lons, lats = meshgrid(lons, lats)
fig1 = m1.createfigure()
x, y = m1(lons, lats)
cs = m1.contourf(x,y,map,color_num,cmap=cm.jet)
m1.drawparallels(arange(-90.,90.,20.),labels=[1,0,0,0])
m1.drawmeridians(arange(0.,420.,30.),labels=[0,0,0,1])
#title('Moll. proj:'+ sys.argv[1])
title(r'$>3\sigma\/ detections\/ composite\/ map:\/ skewness$')
#title(r'$>3\sigma\/ detections\/ composite\/ map:\/ kurtosis$')
colorbar();
savefig(sys.argv[1]+'-moll.png'); #savefig(sys.argv[1]+'-moll.eps')
savefig(sys.argv[1]+'-moll.jpg');
#show()
nob = nob + 1
print len(lons_out), ' obs after thinning'
# transform lons and lats to map coordinates.
x,y = m(array(lons_out)/d2r, array(lats_out)/d2r)
# find just those points in map region.
xx=[]
yy=[]
for xi,yi in zip(x,y):
if (xi>m.llcrnrx and xi<m.urcrnrx) and (yi>m.llcrnry and yi<m.urcrnry):
xx.append(xi)
yy.append(yi)
# plot them as filled circles on the map.
# first, create figure with same aspect ratio as map.
fig=m.createfigure()
# background color will be used for 'wet' areas.
fig.add_axes([0.1,0.1,0.8,0.8],axisbg='aqua')
# use zorder=10 to make sure markers are drawn last.
# (otherwise they are covered up when continents are filled)
m.scatter(xx,yy,marker='o',c='k',s=25,zorder=10)
# draw coasts and fill continents.
m.drawcoastlines(linewidth=0.5)
m.fillcontinents(color='coral')
# draw parallels and meridians.
delat = 20.
circles = arange(0.,90.,delat).tolist()+\
arange(-delat,-90,-delat).tolist()
m.drawparallels(circles)
delon = 45.
meridians = arange(0,360,delon)
from matplotlib.toolkits.basemap import Basemap
from pylab import *
# read in topo data (on a regular lat/lon grid)
etopo = array(load('etopo20data.gz'),'d')
lons = array(load('etopo20lons.gz'),'d')
lats = array(load('etopo20lats.gz'),'d')
# create Basemap instance for Orthographic (satellite view) projection.
lon_0 = float(raw_input('enter reference longitude (lon_0):'))
lat_0 = float(raw_input('enter reference latitude (lat_0):'))
fillcont = int(raw_input('fill continents? (1 for yes, 0 for no):'))
m = Basemap(projection='ortho',lon_0=lon_0,lat_0=lat_0)
# compute native map projection coordinates for lat/lon grid.
lons, lats = meshgrid(lons, lats)
x,y = m(lons,lats)
# create figure with same aspect ratio as map.
fig=m.createfigure().add_axes([0.05,0.05,0.9,0.9])
# make filled contour plot.
cs = m.contourf(x,y,etopo,30,cmap=cm.jet)
# draw coastlines.
m.drawcoastlines()
# draw a line around the map region.
m.drawmapboundary()
if fillcont:
m.fillcontinents()
# draw parallels and meridians.
m.drawparallels(arange(-90.,120.,30.))
m.drawmeridians(arange(0.,420.,60.))
title('Orthographic Map Centered on Lon=%s, Lat=%s' % (lon_0,lat_0))
show()
#palette.set_bad('aqua', 1.0)
# plot image over map with imshow.
#im = m.imshow(topodatm,palette,norm=colors.normalize(vmin=0.0,vmax=3000.0,clip=False))
#a=axes()
#subplots_adjust(left=None,right=None,top=None,bottom=None,wspace=0,hspace=0)
# Mollweide projection
lons, lats = meshgrid(lons, lats)
#m1 = Basemap(projection='moll',lon_0=0.5*(lons[0]+lons[-1]))
m1 = Basemap(projection='moll', lon_0=0)
delta = (maxv - minv) / color_num
levels = arange(minv - 1 * delta, maxv + 1 * delta, delta)
print(levels)
fig = m1.createfigure()
subplots_adjust(left=0, right=.99, top=0.99, bottom=0.1, wspace=0, hspace=0)
x, y = m1(lons, lats)
fig = figure(figsize=(12, 6), dpi=dpires)
#fig=figure(figsize=(4,2), dpi=dpires)
#print dpires
ax = gca()
#cs = m1.contourf(x,y,mapM,color_num,cmap=cm.jet)
#cs = m1.contourf(x,y,mapM,color_num,cmap=palette, norm = matplotlib.colors.normalize(vmin=minv, vmax=maxv, clip=False) )
#cs = m1.contourf(x,y,mapM,colors=None, cmap=palette, norm = matplotlib.colors.normalize(vmin=minv, vmax=maxv, clip=False) )
#cs = m1.contourf(x,y,mapM, color_num, cmap=palette, norm = matplotlib.colors.normalize(vmin=minv, vmax=maxv, clip=False), extend='min' )
#cs = m1.contourf(x,y,mapM, levels, cmap=palette, norm = matplotlib.colors.normalize(vmin=minv, vmax=maxv, clip=False) )
cs = m1.contourf(x, y, mapM, levels, cmap=palette)
from matplotlib.toolkits.basemap import Basemap
import pylab as p
# set up orthographic map projection with
# perspective of satellite looking down at 50N, 100W.
# use low resolution coastlines.
map = Basemap(projection='ortho', lat_0=50, lon_0=-100, resolution='l')
# set up figure.
fig = map.createfigure()
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines()
map.drawcountries()
map.fillcontinents(color='coral')
# draw the edge of the map projection region (the projection limb)
map.drawmapboundary()
# draw lat/lon grid lines every 30 degrees.
map.drawmeridians(p.arange(0, 360, 30))
map.drawparallels(p.arange(-90, 90, 30))
# lat/lon coordinates of five cities.
lats = [40.02, 34.00, 38.55, 48.25, 17.29]
lons = [-105.16, -119.40, -77.00, -114.21, -88.10]
cities = [
'Boulder, CO', 'Santa Cruz, CA', 'Washington, DC', 'Whitefish, MT',
'Belize City, Belize'
]
# compute the native map projection coordinates for cities.
x, y = map(lons, lats)
# plot filled circles at the locations of the cities.
map.plot(x, y, 'bo')
# plot the names of those five cities.
for name, xpt, ypt in zip(cities, x, y):
p.text(xpt + 50000, ypt + 50000, name)
from matplotlib.toolkits.basemap import Basemap
from pylab import *
# read in topo data (on a regular lat/lon grid)
etopo = array(load('etopo20data.gz'), 'd')
lons = array(load('etopo20lons.gz'), 'd')
lats = array(load('etopo20lats.gz'), 'd')
# create Basemap instance for Orthographic (satellite view) projection.
lon_0 = float(raw_input('enter reference longitude (lon_0):'))
lat_0 = float(raw_input('enter reference latitude (lat_0):'))
fillcont = int(raw_input('fill continents? (1 for yes, 0 for no):'))
m = Basemap(projection='ortho', lon_0=lon_0, lat_0=lat_0)
# compute native map projection coordinates for lat/lon grid.
lons, lats = meshgrid(lons, lats)
x, y = m(lons, lats)
# create figure with same aspect ratio as map.
fig = m.createfigure().add_axes([0.05, 0.05, 0.9, 0.9])
# make filled contour plot.
cs = m.contourf(x, y, etopo, 30, cmap=cm.jet)
# draw coastlines.
m.drawcoastlines()
# draw a line around the map region.
m.drawmapboundary()
if fillcont:
m.fillcontinents()
# draw parallels and meridians.
m.drawparallels(arange(-90., 120., 30.))
m.drawmeridians(arange(0., 420., 60.))
title('Orthographic Map Centered on Lon=%s, Lat=%s' % (lon_0, lat_0))
show()
latminout = 22.0
llcrnrlon = -125.0
urcrnrlon = -60.0
standardpar = 50.0
centerlon=-105.
# create Basemap instance for Lambert Conformal Conic projection.
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)
# create figure.
# mult ysize by 3/2 to take into account there will
# be three rows and two columns.
fig=m.createfigure(figsize=(8,(3./2.)*8))
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)
cs = m.contour(x,y,t2m[nt,:,:],clevs,colors='k')
cs = m.contourf(x,y,t2m[nt,:,:],clevs,cmap=cm.jet)
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],
from matplotlib.toolkits.basemap import Basemap
import pylab as p
# set up orthographic map projection with
# perspective of satellite looking down at 50N, 100W.
# use low resolution coastlines.
map = Basemap(projection='ortho',lat_0=50,lon_0=-100,resolution='l')
# set up figure.
fig=map.createfigure()
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines()
map.drawcountries()
map.fillcontinents(color='coral')
# draw the edge of the map projection region (the projection limb)
map.drawmapboundary()
# draw lat/lon grid lines every 30 degrees.
map.drawmeridians(p.arange(0,360,30))
map.drawparallels(p.arange(-90,90,30))
# lat/lon coordinates of five cities.
lats=[40.02,34.00,38.55,48.25,17.29]
lons=[-105.16,-119.40,-77.00,-114.21,-88.10]
cities=['Boulder, CO','Santa Cruz, CA',
'Washington, DC','Whitefish, MT','Belize City, Belize']
# compute the native map projection coordinates for cities.
x,y = map(lons,lats)
# plot filled circles at the locations of the cities.
map.plot(x,y,'bo')
# plot the names of those five cities.
for name,xpt,ypt in zip(cities,x,y):
p.text(xpt+50000,ypt+50000,name)
# make up some data on a regular lat/lon grid.
nlats = 73; nlons = 145; delta = 2.*p.pi/(nlons-1)
# create Basemap instance for Lambert Conformal Conic projection.
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)
# create figure.
# mult ysize by 3/2 to take into account there will
# be three rows and two columns.
fig = m.createfigure(figsize=(8, (3. / 2.) * 8))
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)
cs = m.contour(x, y, t2m[nt, :, :], clevs, colors='k')
cs = m.contourf(x, y, t2m[nt, :, :], clevs, cmap=cm.jet)
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],
