def InvokeMap(coastfile='/media/sda4/map-data/aust-coast-noaa-2000000-1.dat',
lllon=80,
urlon=166,
lllat=-47,
urlat=-9,
draw_map=True):
global PYLIB_PATH
map = Basemap(projection='cyl',
llcrnrlon=lllon,
urcrnrlon=urlon,
llcrnrlat=lllat,
urcrnrlat=urlat,
#lat_ts=-35,
lat_0=-35,
lon_0=120,
resolution='l',
area_thresh=1000.)
try:
coast = p.load(coastfile)
coast = p.load(coastfile)
coast_x,coast_y = map(coast[:,0],coast[:,1])
p.plot(coast_x,coast_y,color='black')
except IOError:
map.drawcoastlines()
map.drawmapboundary()
map.drawmeridians(p.arange(0,360,10),labels=[0,0,1,0])
map.drawparallels(p.arange(-90,0,10),labels=[1,0,0,0])
return map
def doit():
map = Basemap(projection='lcc',
llcrnrlon=80,
urcrnrlon=160,
llcrnrlat=-50,
urcrnrlat=-8,
#lat_ts=-35,
lat_0=-35,
lon_0=120,
resolution='c',
area_thresh=1000.)
p.clf()
map.drawcoastlines()
# map.drawcountries()
# map.drawrivers()
map.drawmeridians(p.arange(0,360,10),labels=[0,0,1,0])
map.drawparallels(p.arange(-90,0,10),labels=[1,0,0,0])
traj=p.load('example_traj.dat')
coast=p.load('/media/sda4/map-data/aust-coast-noaa-2000000-1.dat')
traj_x,traj_y = map(traj[:,1],traj[:,0])
# coast_x,coast_y = map(coast[:,0],coast[:,1])
p.plot(traj_x,traj_y)
p.plot(coast_x,coast_y,color='black')
map.drawmapboundary()
p.show()
return map
def draw_graph_on_map(g, node2weight, node2pos, pic_title, pic_area=[-130,10,140,70], output_fname_prefix=None, need_draw_edge=0):
"""
2007-09-13
identity_pair_ls is a list of pairs of strains (ecotype id as in table ecotype)
2007-10-08
correct a bug in 4*diameter_ls, diameter_ls has to be converted to array first.
sqrt the node weight, 8 times the original weight
"""
import os, sys
sys.stderr.write("Drawing graph on a map ...\n")
import pylab, math
from matplotlib.toolkits.basemap import Basemap
pylab.clf()
fig = pylab.figure()
fig.add_axes([0.05,0.05,0.9,0.9]) #[left, bottom, width, height]
m = Basemap(llcrnrlon=pic_area[0],llcrnrlat=pic_area[1],urcrnrlon=pic_area[2],urcrnrlat=pic_area[3],\
resolution='l',projection='mill', ax=pylab.gca())
sys.stderr.write("\tDrawing nodes ...")
euc_coord1_ls = []
euc_coord2_ls = []
diameter_ls = []
for n in g.nodes():
lat, lon = node2pos[n]
euc_coord1, euc_coord2 = m(lon, lat) #longitude first, latitude 2nd
euc_coord1_ls.append(euc_coord1)
euc_coord2_ls.append(euc_coord2)
diameter_ls.append(math.sqrt(node2weight[n]))
import numpy
diameter_ls = numpy.array(diameter_ls)
m.scatter(euc_coord1_ls, euc_coord2_ls, 8*diameter_ls, marker='o', color='r', alpha=0.4, zorder=12, faceted=False)
sys.stderr.write("Done.\n")
if need_draw_edge:
sys.stderr.write("\tDrawing edges ...")
ax=pylab.gca()
for popid1, popid2, no_of_connections in g.edges():
lat1, lon1 = node2pos[popid1]
lat2, lon2 = node2pos[popid2]
x1, y1 = m(lon1, lat1)
x2, y2 = m(lon2, lat2)
ax.plot([x1,x2],[y1,y2], 'g', linewidth=math.log(no_of_connections+1)/2, alpha=0.2, zorder=10)
sys.stderr.write("Done.\n")
#m.drawcoastlines()
m.drawparallels(pylab.arange(-90,90,30), labels=[1,1,0,1])
m.drawmeridians(pylab.arange(-180,180,30), labels=[1,1,0,1])
m.fillcontinents()
m.drawcountries()
m.drawstates()
pylab.title(pic_title)
if output_fname_prefix:
pylab.savefig('%s.eps'%output_fname_prefix, dpi=600)
pylab.savefig('%s.svg'%output_fname_prefix, dpi=600)
pylab.savefig('%s.png'%output_fname_prefix, dpi=600)
del fig, m, pylab
sys.stderr.write("Done.\n")
def draw_clustered_strain_location(self, label_ls, weighted_pos_ls, diameter_ls, label_type, label_type2label_name, pic_area=[-180,-90,180,90], output_fname_prefix=None, label_name=None):
"""
2007-07-11
draw populations derived from connected_components of the strain network
#each pie denotes a population, with diameter proportional to the size of the population
#each pie labeled with the number of strains in that population
2007-07-13
use popid as label
2007-07-17
no parallels, no meridians
2007-08-29
copied from CreatePopulation.py
2007-09-11
add label name
2007-10-14
correct a bug in 5*diameter_ls. diameter_ls has to an array
"""
sys.stderr.write("Drawing population map...")
import pylab
from matplotlib.toolkits.basemap import Basemap
pylab.clf()
fig = pylab.figure()
fig.add_axes([0.05,0.05,0.9,0.9]) #[left, bottom, width, height]
m = Basemap(llcrnrlon=pic_area[0],llcrnrlat=pic_area[1],urcrnrlon=pic_area[2],urcrnrlat=pic_area[3],\
resolution='l',projection='mill')
euc_coord1_ls = []
euc_coord2_ls = []
ax=pylab.gca()
for i in range(len(weighted_pos_ls)):
lat, lon = weighted_pos_ls[i]
euc_coord1, euc_coord2 = m(lon, lat) #longitude first, latitude 2nd
euc_coord1_ls.append(euc_coord1)
euc_coord2_ls.append(euc_coord2)
ax.text(euc_coord1, euc_coord2, str(label_ls[i]), size=5, alpha=0.5, horizontalalignment='center', verticalalignment='center', zorder=12)
import numpy
diameter_ls = numpy.array(diameter_ls)
m.scatter(euc_coord1_ls, euc_coord2_ls, 5*diameter_ls, marker='o', color='r', alpha=0.3, zorder=10, faceted=False)
#m.drawcoastlines()
m.drawparallels(pylab.arange(-90,90,30), labels=[1,1,0,1]) #labels intersect the left, right, top bottom of the plot
m.drawmeridians(pylab.arange(-180,180,30), labels=[1,1,0,1])
m.fillcontinents()
m.drawcountries()
m.drawstates()
pylab.title("worldwide distribution of %s populations, labeled by %s"%(len(weighted_pos_ls), label_type2label_name[label_type]))
if output_fname_prefix:
pylab.savefig('%s_pop_map.eps'%output_fname_prefix, dpi=300)
pylab.savefig('%s_pop_map.svg'%output_fname_prefix, dpi=300)
pylab.savefig('%s_pop_map.png'%output_fname_prefix, dpi=300)
del m, pylab, Basemap
sys.stderr.write("Done.\n")
def DrawSiteNetwork(self,
g,
node_label2pos_counts,
pic_area=[-180, -90, 180, 90],
output_fname_prefix=None):
"""
2007-07-17
put ax.plot() right after Basemap() but after m.xxx() so that it'll zoom in
use 'g' in ax.plot(), otherwise, ax.plot() alternates all colors.
no parallels, no meridians
2007-08-29 copied from CreatePopulation.py and renamed from DrawStrainNetwork
"""
sys.stderr.write("Drawing Site Network...")
import pylab
from matplotlib.toolkits.basemap import Basemap
pylab.clf()
fig = pylab.figure()
fig.add_axes([0.05, 0.05, 0.9, 0.9]) #[left, bottom, width, height]
m = Basemap(llcrnrlon=pic_area[0],llcrnrlat=pic_area[1],urcrnrlon=pic_area[2],urcrnrlat=pic_area[3],\
resolution='l',projection='mill')
ax = pylab.gca()
for e in g.edges():
lat1, lon1 = node_label2pos_counts[e[0]][0]
lat2, lon2 = node_label2pos_counts[e[1]][0]
x1, y1 = m(lon1, lat1)
x2, y2 = m(lon2, lat2)
ax.plot([x1, x2], [y1, y2], 'g', alpha=0.5, zorder=12)
#m.drawcoastlines()
m.drawparallels(pylab.arange(-90, 90, 30), labels=[1, 1, 0, 1])
m.drawmeridians(pylab.arange(-180, 180, 30), labels=[1, 1, 0, 1])
m.fillcontinents()
m.drawcountries()
m.drawstates()
pylab.title("Network of strains")
if output_fname_prefix:
pylab.savefig('%s_site_network.eps' % output_fname_prefix, dpi=300)
pylab.savefig('%s_site_network.svg' % output_fname_prefix, dpi=300)
pylab.savefig('%s_site_network.png' % output_fname_prefix, dpi=300)
del m, pylab, Basemap
sys.stderr.write("Done.\n")
def DrawSiteNetwork(self, g, node_label2pos_counts,pic_area=[-180,-90,180,90], output_fname_prefix=None):
"""
2007-07-17
put ax.plot() right after Basemap() but after m.xxx() so that it'll zoom in
use 'g' in ax.plot(), otherwise, ax.plot() alternates all colors.
no parallels, no meridians
2007-08-29 copied from CreatePopulation.py and renamed from DrawStrainNetwork
"""
sys.stderr.write("Drawing Site Network...")
import pylab
from matplotlib.toolkits.basemap import Basemap
pylab.clf()
fig = pylab.figure()
fig.add_axes([0.05,0.05,0.9,0.9]) #[left, bottom, width, height]
m = Basemap(llcrnrlon=pic_area[0],llcrnrlat=pic_area[1],urcrnrlon=pic_area[2],urcrnrlat=pic_area[3],\
resolution='l',projection='mill')
ax=pylab.gca()
for e in g.edges():
lat1, lon1 = node_label2pos_counts[e[0]][0]
lat2, lon2 = node_label2pos_counts[e[1]][0]
x1, y1 = m(lon1, lat1)
x2, y2 = m(lon2, lat2)
ax.plot([x1,x2],[y1,y2], 'g', alpha=0.5, zorder=12)
#m.drawcoastlines()
m.drawparallels(pylab.arange(-90,90,30), labels=[1,1,0,1])
m.drawmeridians(pylab.arange(-180,180,30), labels=[1,1,0,1])
m.fillcontinents()
m.drawcountries()
m.drawstates()
pylab.title("Network of strains")
if output_fname_prefix:
pylab.savefig('%s_site_network.eps'%output_fname_prefix, dpi=300)
pylab.savefig('%s_site_network.svg'%output_fname_prefix, dpi=300)
pylab.savefig('%s_site_network.png'%output_fname_prefix, dpi=300)
del m, pylab, Basemap
sys.stderr.write("Done.\n")
fig = P.figure()
# panel 1
mnh = Basemap(lon_0=-105, boundinglat=20.0, resolution="c", area_thresh=10000.0, projection="nplaea")
xnh, ynh = mnh(lons, lats)
ax = fig.add_subplot(211)
CS = mnh.contour(xnh, ynh, hgt, 15, linewidths=0.5, colors="k")
CS = mnh.contourf(xnh, ynh, hgt, 15, cmap=P.cm.Spectral)
# colorbar on bottom.
l, b, w, h = ax.get_position()
cax = P.axes([l, b - 0.05, w, 0.025]) # setup colorbar axes
P.colorbar(cax=cax, orientation="horizontal", ticks=CS.levels[0::4]) # draw colorbar
P.axes(ax) # make the original axes current again
mnh.drawcoastlines(linewidth=0.5)
delat = 30.0
circles = P.arange(0.0, 90.0, delat).tolist() + P.arange(-delat, -90, -delat).tolist()
mnh.drawparallels(circles, labels=[1, 0, 0, 0])
delon = 45.0
meridians = P.arange(0, 360, delon)
mnh.drawmeridians(meridians, labels=[1, 0, 0, 1])
P.title("NH 500 hPa Height (cm.Spectral)")
# panel 2
msh = Basemap(lon_0=-105, boundinglat=-20.0, resolution="c", area_thresh=10000.0, projection="splaea")
xsh, ysh = msh(lons, lats)
ax = fig.add_subplot(212)
CS = msh.contour(xsh, ysh, hgt, 15, linewidths=0.5, colors="k")
CS = msh.contourf(xsh, ysh, hgt, 15, cmap=P.cm.Spectral)
# colorbar on bottom.
ax.apply_aspect()
l, b, w, h = ax.get_position()
cax = P.axes([l, b - 0.05, w, 0.025]) # setup colorbar axes
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.
fig=figure(figsize=(8,8))
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],
horizontalalignment='center',fontsize=14)
# a single colorbar.
cax = axes([0.1, 0.03, 0.8, 0.025])
colorbar(cax=cax, orientation='horizontal')
show()
# in which direction to depart for other points on earth and how far
# it will be to reach that destination.
# The specified point shows up as a red dot in the center of the map.
# This example shows how to use the width and height keywords
# to specify the map projection region (instead of specifying
# the lat/lon of the upper right and lower left corners).
# user enters the lon/lat of the point, and it's name
lon_0 = float(raw_input('input reference lon (degrees):'))
lat_0 = float(raw_input('input reference lat (degrees):'))
location = raw_input('name of location:')
# use these values to setup Basemap instance.
width = 28000000
m = Basemap(width=width,height=width,\
resolution='c',projection='aeqd',\
lat_0=lat_0,lon_0=lon_0)
# draw coasts and fill continents.
m.drawcoastlines(linewidth=0.5)
m.fillcontinents()
# 20 degree graticule.
m.drawparallels(arange(-80, 81, 20))
m.drawmeridians(arange(-180, 180, 20))
# draw a red dot at the center.
xpt, ypt = m(lon_0, lat_0)
m.plot([xpt], [ypt], 'ro')
# draw the title.
title('The World According to Garp in ' + location)
show()
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)
m.drawmeridians(meridians, labels=[1, 1, 1, 1])
title('Randomly Spaced Locations (Min Dist = %g km, %g points)' %
(rcrit, len(lons_out)),
y=1.075)
show()
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()
lats = P.arange(-90. + 0.5 * delta, 90., delta)
# define cylindrical equidistant projection.
m = Basemap(projection='cyl',
llcrnrlon=-180,
llcrnrlat=-90,
urcrnrlon=180,
urcrnrlat=90,
resolution='l')
# plot (unwarped) rgba image.
im = m.imshow(rgba)
# draw coastlines.
m.drawcoastlines(linewidth=0.5, color='0.5')
# draw lat/lon grid lines.
m.drawmeridians(P.arange(-180, 180, 60), labels=[0, 0, 0, 1], color='0.5')
m.drawparallels(P.arange(-90, 90, 30), labels=[1, 0, 0, 0], color='0.5')
P.title("Blue Marble image - native 'cyl' projection", fontsize=12)
P.show()
# define orthographic projection centered on North America.
m = Basemap(projection='ortho', lat_0=40, lon_0=40, resolution='l')
# transform to nx x ny regularly spaced native projection grid
# nx and ny chosen to have roughly the same horizontal res as original image.
dx = 2. * P.pi * m.rmajor / float(nlons)
nx = int((m.xmax - m.xmin) / dx) + 1
ny = int((m.ymax - m.ymin) / dx) + 1
rgba_warped = ma.zeros((ny, nx, 4), P.Float64)
# interpolate rgba values from proj='cyl' (geographic coords) to 'lcc'
# values outside of projection limb will be masked.
for k in range(4):
rgba_warped[:, :, k] = m.transform_scalar(rgba[:, :, k],
def add_text(rlon, rlat, txt, m=None, **keywords):
show_lat = 1
if ('show_lat' in keywords):
show_lat = keywords['show_lat']
rlon = array(rlon)
rlat = array(rlat)
show_lon = 1
if ('show_lon' in keywords):
show_lon = keywords['show_lon']
if (m == None):
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']
minlon = -180
maxlon = 180.0
if ('minlon' in keywords):
minlon = keywords['minlon']
if ('maxlon' in keywords):
maxlon = keywords['maxlon']
lon_0 = 0
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:
m=Basemap(llcrnrlon=minlon, llcrnrlat=minlat, \
urcrnrlon=maxlon, urcrnrlat=maxlat,projection=map_proj, lon_0=lon_0, lat_0=lat_0)
if (show_lat == 1):
m.drawparallels(arange(minlat, maxlat + 30.0, 30.),
labels=[1, 0, 0, 0])
if (show_lon == 1):
m.drawmeridians(arange(minlon, maxlon + 60, 60.),
labels=[0, 0, 0, 1])
x, y = m(rlon, rlat)
for i in range(size(rlon)):
text(x[i], y[i], txt[i], fontsize=10)
if ('title' in keywords):
stitle = keywords['title']
title(stitle)
return m
#latfile = s+'.lat'
#map=array(load(mapfile))
#lons=array(load(lonfile))
#lats=array(load(latfile))
#map,lons = shiftgrid(180,map,lons,start=False)
#subplots_adjust(left=0,right=.99,top=0.99,bottom=0.1,wspace=0,hspace=0)
#m2 = Basemap(projection='moll',lon_0=0.5*(lons[0]+lons[-1]))
#lons, lats = meshgrid(lons, lats)
#levels = arange(-36, 39, 0.2)
#x, y = m2(lons, lats)
#cs = m2.contourf(x,y,map,color_num,cmap=cm.hot)
# EXPERIMENTAL END
if mymeridians == '1':
m1.drawparallels(arange(-90., 90., DeltaLatitude),
labels=[1, 0, 0, 0],
fontsize=meridians_fontsize)
m1.drawmeridians(arange(0., 420., DeltaLongitude), labels=[0, 0, 0, 1])
# 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('>3$\sigma$ detections composite map: skewness')
#title('>3$\sigma$ detections composite map: kurtosis')
#rc('font',c=fgcolor)
#rc('lines', lw=2, c=fgcolor)
if mytitle != 'notitle':
title(mytitle, color=fgcolor, fontsize=meridians_fontsize)
if mycolorbar == 'moll':
# colorbar(tickfmt='%.1lf',)
def makeFigure(self):
"""
:todo: Uses pylab so may not be threadsafe.
"""
lon = self.grid.lon0 + N.arrayrange(self.grid.nlon) * self.grid.dlon
lat = self.grid.lat0 + N.arrayrange(self.grid.nlat) * self.grid.dlat
ll_lon, ll_lat = lon[0], lat[0]
ur_lon, ur_lat = lon[-1], lat[-1]
# Account for variable lat/lon axis ordering
#!TODO: Could we move this (along with the equivilent in render_imp.py into grid.py?
if self.grid.ilat < self.grid.ilon:
latLonOrdering = True
else:
latLonOrdering = False
if latLonOrdering:
var = self.grid.value
else:
var = MA.transpose(self.grid.value)
fig = p.figure()
map = Basemap(projection='cyl',
llcrnrlon=ll_lon,
llcrnrlat=ll_lat,
urcrnrlon=ur_lon,
urcrnrlat=ur_lat,
resolution='l')
## if self.grid.units:
## p.title("%s\n(%s)" % (self.grid.long_name, self.grid.units))
## else:
## p.title(self.grid.long_name)
p.title(self.grid.long_name)
if self.type == 'colour':
# transform_scalar doesn't support masked arrays so we must fill then replace the mask.
var_dat = map.transform_scalar(var.filled(1.0e20), lon, lat,
len(lon), len(lat))
var = MA.masked_values(var_dat, 1.0e20)
map.imshow(var,
cmap=self.cmap,
vmin=self.vmin,
vmax=self.vmax,
interpolation='nearest')
cbar = p.colorbar(orientation='horizontal', format='%.2g')
if self.grid.units:
cbar.ax.set_xlabel(self.grid.units)
else:
x, y = map(*p.meshgrid(lon, lat))
c = map.contour(x, y, var, 12, colors='black')
c.clabel(fontsize=8)
map.fillcontinents(color='#e0e0e0')
map.drawcoastlines(color='gray')
map.drawmeridians(p.arange(-180, 180, 30),
labels=[1, 0, 0, 1],
color='gray')
map.drawparallels(p.arange(-90, 90, 15),
labels=[1, 0, 0, 1],
color='gray')
# Wrap the caption
caption = word_wrap(self.caption, 80)
fig.text(0.1,
0.08,
caption,
fontsize=10,
horizontalalignment='left',
verticalalignment='top',
transform=fig.transFigure)
return fig
xx, yy = meshgrid(lon, lat)
m = Basemap(resolution='l',
lat_0=N.average(lat),
lon_0=N.average(lon),
llcrnrlon=min(lon),
llcrnrlat=min(lat),
urcrnrlon=max(lon),
urcrnrlat=max(lat))
levels = vcs.mkscale(genutil.minmax(composites))
m.contourf(lon, lat, composites[i], levels=levels, cmap=bwr)
clabel(m.contour(lon, lat, composites[i], levels=levels))
title("Phase %i/%i" (i + 1, 6))
m.drawcoastlines()
m.drawcountries()
m.fillcontinents(color='coral')
m.drawparallels(vcs.mkscale(genutil.minmax(lat)), labels=[1, 0, 0, 0])
m.drawmeridians(vcs.mkscale(genutil.minmax(lon)), labels=[0, 0, 0, 1])
figtext(
.5, 1.,
"\n%s [%s]" % ("El Nino phase composites\nSea surface temperature",
composites.units))
savefig(sys.argv[0].replace(".py", ".png"))
show()
# Fall back to vcs because we have it!
except:
# Plot 1 phase over two, then a time series
# TODO: we must do something nicer!!
import vcs, EzTemplate
x = vcs.init()
T = EzTemplate.Multi(rows=nrow,
m = Basemap(-135.,-20.,45.,-20.,
resolution='c',area_thresh=10000.,projection='laea',
lat_0=90.,lon_0=-90.)
cmap = cm.jet
fig = figure(figsize=(6,6))
ax = fig.add_axes([0.1, 0.1, 0.8, 0.8])
x,y = m(lons, lats)
cs = contour(x,y,hgt,15,linewidths=0.5,colors='k')
cs = contourf(x,y,hgt,15,cmap=cmap,colors=None)
# draw map.
m.drawcoastlines()
# draw parallels
delat = 30.
delon = 90.
circles = arange(10.,90.+delat,delat).tolist()
m.drawparallels(circles,labels=[0,0,1,1], fontsize=16)
# draw meridians
meridians = arange(0.,360.,delon)
m.drawmeridians(meridians,labels=[1,1,1,1],fontsize=16)
savefig('contour_small.png', dpi=50)
savefig('contour_large', dpi=120)
show()
def draw_clustered_strain_location(self,
label_ls,
weighted_pos_ls,
diameter_ls,
label_type,
label_type2label_name,
pic_area=[-180, -90, 180, 90],
output_fname_prefix=None,
label_name=None):
"""
2007-07-11
draw populations derived from connected_components of the strain network
#each pie denotes a population, with diameter proportional to the size of the population
#each pie labeled with the number of strains in that population
2007-07-13
use popid as label
2007-07-17
no parallels, no meridians
2007-08-29
copied from CreatePopulation.py
2007-09-11
add label name
2007-10-14
correct a bug in 5*diameter_ls. diameter_ls has to an array
"""
sys.stderr.write("Drawing population map...")
import pylab
from matplotlib.toolkits.basemap import Basemap
pylab.clf()
fig = pylab.figure()
fig.add_axes([0.05, 0.05, 0.9, 0.9]) #[left, bottom, width, height]
m = Basemap(llcrnrlon=pic_area[0],llcrnrlat=pic_area[1],urcrnrlon=pic_area[2],urcrnrlat=pic_area[3],\
resolution='l',projection='mill')
euc_coord1_ls = []
euc_coord2_ls = []
ax = pylab.gca()
for i in range(len(weighted_pos_ls)):
lat, lon = weighted_pos_ls[i]
euc_coord1, euc_coord2 = m(lon,
lat) #longitude first, latitude 2nd
euc_coord1_ls.append(euc_coord1)
euc_coord2_ls.append(euc_coord2)
ax.text(euc_coord1,
euc_coord2,
str(label_ls[i]),
size=5,
alpha=0.5,
horizontalalignment='center',
verticalalignment='center',
zorder=12)
import numpy
diameter_ls = numpy.array(diameter_ls)
m.scatter(euc_coord1_ls,
euc_coord2_ls,
5 * diameter_ls,
marker='o',
color='r',
alpha=0.3,
zorder=10,
faceted=False)
#m.drawcoastlines()
m.drawparallels(pylab.arange(-90, 90, 30), labels=[
1, 1, 0, 1
]) #labels intersect the left, right, top bottom of the plot
m.drawmeridians(pylab.arange(-180, 180, 30), labels=[1, 1, 0, 1])
m.fillcontinents()
m.drawcountries()
m.drawstates()
pylab.title("worldwide distribution of %s populations, labeled by %s" %
(len(weighted_pos_ls), label_type2label_name[label_type]))
if output_fname_prefix:
pylab.savefig('%s_pop_map.eps' % output_fname_prefix, dpi=300)
pylab.savefig('%s_pop_map.svg' % output_fname_prefix, dpi=300)
pylab.savefig('%s_pop_map.png' % output_fname_prefix, dpi=300)
del m, pylab, Basemap
sys.stderr.write("Done.\n")
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('>3$\sigma$ detections composite map: skewness')
title('>3$\sigma$ detections composite map: kurtosis')
colorbar();
savefig(sys.argv[1]+'-moll.png'); #savefig(sys.argv[1]+'-moll.eps')
# north polar projection.
m2 = Basemap(llcrnrlon=-45.,llcrnrlat=10.,urcrnrlon=135.,urcrnrlat=10., projection='stere', lat_0=90.,lon_0=0.,lat_ts=90.)
# resolution='c',area_thresh=10000.,
fig2 = m2.createfigure()
x, y = m2(lons, lats)
cs = m2.contourf(x,y,map,color_num,cmap=cm.jet)
m = Basemap(projection='stere',lon_0=lon_0,lat_0=90.,lat_ts=lat_0,\
llcrnrlat=latcorners[0],urcrnrlat=latcorners[2],\
llcrnrlon=loncorners[0],urcrnrlon=loncorners[2],\
rsphere=6371200.,resolution='l',area_thresh=10000)
# create figure
fig = pylab.figure(figsize=(6,8.5))
pylab.subplot(211)
ax = pylab.gca()
# draw coastlines, state and country boundaries, edge of map.
m.drawcoastlines()
m.drawstates()
m.drawcountries()
# draw parallels.
delat = 10.0
parallels = pylab.arange(0.,90,delat)
m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10)
# draw meridians
delon = 10.
meridians = pylab.arange(180.,360.,delon)
m.drawmeridians(meridians,labels=[0,0,0,1],fontsize=10)
ny = data.shape[0]; nx = data.shape[1]
lons, lats = m.makegrid(nx, ny) # get lat/lons of ny by nx evenly space grid.
x, y = m(lons, lats) # compute map proj coordinates.
# draw filled contours.
clevs = [0,1,2.5,5,7.5,10,15,20,30,40,50,70,100,150,200,250,300,400,500,600,750]
cs = m.contourf(x,y,data,clevs,cmap=cm.s3pcpn)
# new axis for colorbar.
l,b,w,h=ax.get_position()
cax = pylab.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
# draw colorbar.
pylab.colorbar(cs, cax, format='%g', ticks=clevs, drawedges=False)
urcrnrlon = llcrnrlon+(array.shape[1]-1)*coords[1]
urcrnrlat = coords[3]
llcrnrlat = urcrnrlat+(array.shape[0]-1)*coords[5]
# create Basemap instance.
m = Basemap(llcrnrlon=llcrnrlon,llcrnrlat=llcrnrlat,urcrnrlon=urcrnrlon,urcrnrlat=urcrnrlat,projection='cyl')
# create a figure, add an axes
# (leaving room for a colorbar).
fig = p.figure()
ax = fig.add_axes([0.1,0.1,0.75,0.75])
# plot image from DEM over map.
im = m.imshow(array,origin='upper')
# make a colorbar.
cax = p.axes([0.875, 0.1, 0.05, 0.75]) # setup colorbar axes.
p.colorbar(cax=cax) # draw colorbar
p.axes(ax) # make the original axes current again
# draw meridians and parallels.
m.drawmeridians(p.linspace(llcrnrlon+0.1,urcrnrlon-0.1,5),labels=[0,0,0,1],fmt='%4.2f')
m.drawparallels(p.linspace(llcrnrlat+0.1,urcrnrlat-0.1,5),labels=[1,0,0,0],fmt='%4.2f')
# plot county boundaries from
# http://edcftp.cr.usgs.gov/pub/data/nationalatlas/countyp020.tar.gz
shp_info = m.readshapefile('countyp020','counties',drawbounds=True,linewidth=1.0)
# plot some cities.
lons = [-105.22,-105.513,-105.316,-105.47]; lats = [39.76,39.801,39.633,39.41]
names = ['Golden','Central City','Evergreen','Bailey']
x,y = m(lons,lats)
m.plot(x,y,'ko')
for name,xx,yy in zip(names,x,y):
p.text(xx+0.01,yy+0.01,name)
p.title(gd.GetDescription()+' USGS DEM with county boundaries')
p.show()
def test_drawMap(self):
sys.stderr.write("Drawing graph on a map ...\n")
#import pdb
#pdb.set_trace()
import StockDB, Stock_250kDB #StockDB has to be setup otherwise, StockDB.Ecotype.table is None in getEcotypeInfo()
hostname = 'papaya.usc.edu'
dbname = 'stock_250k'
db_user = '******'
db_passwd = ''
drivername = 'mysql'
schema = None
db = Stock_250kDB.Stock_250kDB(drivername=drivername,
username=db_user,
password=db_passwd,
hostname=hostname,
database=dbname,
schema=schema)
#doesn't matter which database to connect as far as StockDB is imported
#db = StockDB.StockDB(drivername=drivername, username=db_user,
# password=db_passwd, hostname=hostname, database=dbname, schema=schema)
db.setup(create_tables=False)
from common import getEcotypeInfo
ecotype_info = getEcotypeInfo(db)
from matplotlib.toolkits.basemap import Basemap
#from mpl_toolkits.basemap import Basemap
import pylab
from matplotlib import rcParams
rcParams['font.size'] = 6
rcParams['legend.fontsize'] = 6
#rcParams['text.fontsize'] = 6 #deprecated. use font.size instead
rcParams['axes.labelsize'] = 4
rcParams['axes.titlesize'] = 8
rcParams['xtick.labelsize'] = 4
rcParams['ytick.labelsize'] = 4
pylab.clf()
#fig = pylab.figure()
#fig.add_axes([0.05,0.05,0.9,0.9]) #[left, bottom, width, height]
axe_map = pylab.axes([0.5, 0.02, 0.4, 0.8], frameon=False)
axe_map.set_title("Global Arabidopsis Ecotype Distribution")
axe_map.set_xlabel('ecotype is drawn as circles.')
axe_map.set_ylabel('strains')
pic_area = [-140, -40, 140, 70]
m = Basemap(llcrnrlon=pic_area[0],llcrnrlat=pic_area[1],urcrnrlon=pic_area[2],urcrnrlat=pic_area[3],\
resolution='l',projection='mill', ax=axe_map)
"""
llcrnrx = -self.rmajor
llcrnry = -self.rmajor
urcrnrx = -llcrnrx
urcrnry = -llcrnry
"""
#m.drawcoastlines()
#m.bluemarble()
m.drawparallels(pylab.arange(-90, 90, 30),
labels=[1, 1, 0, 1],
size=4,
linewidth=0.1)
m.drawmeridians(pylab.arange(-180, 180, 30),
labels=[1, 1, 0, 1],
size=4,
linewidth=0.1)
m.fillcontinents()
m.drawcountries(linewidth=0.1)
#m.drawstates()
#m.drawlsmask((0,255,0,255), (0,0,255,255), lakes=True)
#m.drawlsmask('coral','aqua',lakes=True)
print "xlim:", axe_map.get_xlim()
print "ylim:", axe_map.get_ylim()
xlim = axe_map.get_xlim()
ylim = axe_map.get_ylim()
"""
for strain_id in StrainID2PCAPosInfo.strain_id_ls:
img_y_pos = StrainID2PCAPosInfo.strain_id2img_y_pos[strain_id]
phenotype_row_index = phenData.row_id2row_index[strain_id]
phenotype = phenData.data_matrix[phenotype_row_index][phenotype_col_index]
ecotype_id = int(strain_id)
ecotype_obj = ecotype_info.ecotype_id2ecotype_obj.get(ecotype_id)
if ecotype_obj:
lat, lon = ecotype_obj.latitude, ecotype_obj.longitude
else:
sys.stderr.write("Warning: Ecotype %s not in ecotype_info (fetched from stock db).\n"%ecotype_id)
continue
if lat and lon:
x, y = m(lon, lat)
color = cmap(norm(phenotype))
ax.plot([0, x], [img_y_pos, y], linestyle='--', alpha=0.2, linewidth=0.2)
ax.scatter([x],[y], s=10, linewidth=0, facecolor=color) #, zorder=10)
"""
#pylab.title("Global Arabidopsis Ecotype Distribution")
output_fname_prefix = '/tmp/map'
print "ylim:", axe_map.get_ylim()
axe_map.set_xlim(xlim)
axe_map.set_ylim(ylim)
axe_chromosome = pylab.axes([0.05, 0.02, 0.8, 0.8], frameon=False)
axe_chromosome.set_title("chromosome")
#fix the two transformations before doing cross-axe drawings
axe_map.transData.freeze() # eval the lazy objects
axe_map.transAxes.freeze()
axe_chromosome.transData.freeze() # eval the lazy objects
axe_chromosome.transAxes.freeze()
no_of_ecotypes = 200
ecotype_id_ls = ecotype_info.ecotype_id2ecotype_obj.keys(
)[:no_of_ecotypes]
no_of_ecotypes_drawn = 0
for i in range(no_of_ecotypes):
ecotype_id = ecotype_id_ls[i]
y_pos = i / float(no_of_ecotypes)
#y_pos = i/float(no_of_ecotypes)*ylim[1]
ecotype_obj = ecotype_info.ecotype_id2ecotype_obj.get(ecotype_id)
if ecotype_obj:
lat, lon = ecotype_obj.latitude, ecotype_obj.longitude
else:
sys.stderr.write(
"Warning: Ecotype %s not in ecotype_info (fetched from stock db).\n"
% ecotype_id)
continue
if lat and lon:
x, y = m(lon, lat)
#axe_map.plot([0, x], [y_pos, y], linestyle='--', alpha=0.2, linewidth=0.2)
axe_map.set_xlim(xlim)
axe_map.set_ylim(ylim)
axe_map.scatter([x], [y],
s=5,
linewidth=0,
facecolor='r',
alpha=0.2,
zorder=10)
canvas_x, canvas_y = axe_map.transData.xy_tup((x, y))
axe_chromosome_xy = axe_chromosome.transData.inverse_xy_tup(
(canvas_x, canvas_y))
axe_chromosome.plot([0, axe_chromosome_xy[0]],
[y_pos, axe_chromosome_xy[1]],
linestyle='--',
alpha=0.2,
linewidth=0.2)
no_of_ecotypes_drawn += 1
#release two transformations
axe_map.transData.thaw() # eval the lazy objects
axe_map.transAxes.thaw()
axe_chromosome.transData.thaw() # eval the lazy objects
axe_chromosome.transAxes.thaw()
#set to the same x/y_lim before cross-axe drawing
axe_map.set_xlim(xlim)
axe_map.set_ylim(ylim)
axe_chromosome.set_xlim([0, 1])
axe_chromosome.set_ylim([0, 1])
if output_fname_prefix:
pylab.savefig('%s.png' % output_fname_prefix, dpi=600)
pylab.savefig('%s.svg' % output_fname_prefix)
sys.stderr.write("%s ecotypes drawn. Done.\n" % (no_of_ecotypes_drawn))
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
ax = fig.add_axes([0.1,0.1,0.75,0.75])
im = m.imshow(topoin,cm.jet)
cax = axes([0.875, 0.1, 0.05, 0.75])
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
m.drawcoastlines()
#m.drawcountries()
#m.drawstates()
#m.fillcontinents()
# draw parallels
delat = 30.
circles = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
m.drawparallels(circles,labels=[1,0,0,1])
# draw meridians
delon = 60.
meridians = arange(-180,180,delon)
m.drawmeridians(meridians,labels=[1,0,0,1])
title('Cylindrical Equidistant')
print 'plotting Cylindrical Equidistant example, close plot window to proceed ...'
show()
m = Basemap(-180.,-80.,180.,80.,\
resolution='c',area_thresh=10000.,projection='merc',\
lon_0=0.5*(lons[0]+lons[-1]),lat_ts=20.)
# transform to nx x ny regularly spaced native projection grid
nx = len(lons); ny = int(80.*len(lats)/90.)
topodat = m.transform_scalar(topoin,lons,lats,nx,ny)
xsize = rcParams['figure.figsize'][0]
lat_1=33,
lat_2=45,
lon_0=-95)
fig = p.figure(figsize=(8, m.aspect * 8))
fig.add_axes([0.1, 0.1, 0.8, 0.8])
# draw climate division boundaries.
shp_info = m.readshapefile('divisions', 'climdivs', drawbounds=True)
print shp_info
# make sure the shapefile has polygons (and not just lines).
if shp_info[1] != 5:
print 'warning: shapefile does not contain polygons'
# choose a color for each climate division (randomly).
colors = {}
divnames = []
print m.climdivs_info[0].keys()
for shapedict in m.climdivs_info:
divname = shapedict['ST'] + repr(shapedict['DIV'])
colors[divname] = (random.uniform(0, 1), random.uniform(0, 1),
random.uniform(0, 1))
divnames.append(divname)
# cycle through climate divnames, color each one.
for nshape, seg in enumerate(m.climdivs):
xx, yy = zip(*seg)
color = rgb2hex(colors[divnames[nshape]])
p.fill(xx, yy, color, edgecolor=color)
# draw meridians and parallels.
m.drawparallels(nx.arange(25, 65, 20), labels=[1, 0, 0, 0])
m.drawmeridians(nx.arange(-120, -40, 20), labels=[0, 0, 0, 1])
p.title('NCDC Climate Divisions')
p.show()
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
fig = Figure()
canvas = FigureCanvas(fig)
# create axes instance, leaving room for colorbar at bottom.
ax = fig.add_axes([0.125,0.175,0.75,0.75])
# create Basemap instance for Robinson projection.
# set 'ax' keyword so pylab won't be imported.
m = Basemap(projection='robin',lon_0=0.5*(lons[0]+lons[-1]),ax=ax)
# reset figure size to have same aspect ratio as map.
# fig will be 8 inches wide.
# (don't use createfigure, since that imports pylab).
fig.set_figsize_inches((8,m.aspect*8.))
# make filled contour plot.
x, y = m(*meshgrid(lons, lats))
cs = m.contourf(x,y,etopo,30,cmap=cm.jet)
# draw coastlines.
m.drawcoastlines()
# draw a line around the map region.
m.drawmapboundary()
# draw parallels and meridians.
m.drawparallels(nx.arange(-60.,90.,30.),labels=[1,0,0,0],fontsize=10)
m.drawmeridians(nx.arange(0.,420.,60.),labels=[0,0,0,1],fontsize=10)
# add a title.
ax.set_title('Robinson Projection')
# add a colorbar.
cax = fig.add_axes([0.125, 0.05, 0.75, 0.05],frameon=False)
fig.colorbar(cs, cax=cax, tickfmt='%d', orientation='horizontal',clabels=cs.levels[::3])
# save image (width 800 pixels with dpi=100 and fig width 8 inches).
canvas.print_figure('simpletest',dpi=100)
# done.
print 'image saved in simpletest.png'
nlons = rgba.shape[1]; nlats = rgba.shape[0]
delta = 360./float(nlons)
lons = P.arange(-180.+0.5*delta,180.,delta)
lats = P.arange(-90.+0.5*delta,90.,delta)
# create new figure
fig=P.figure()
# define cylindrical equidistant projection.
m = Basemap(projection='cyl',llcrnrlon=-180,llcrnrlat=-90,urcrnrlon=180,urcrnrlat=90,resolution='l')
# plot (unwarped) rgba image.
im = m.imshow(rgba)
# draw coastlines.
m.drawcoastlines(linewidth=0.5,color='0.5')
# draw lat/lon grid lines.
m.drawmeridians(P.arange(-180,180,60),labels=[0,0,0,1],color='0.5')
m.drawparallels(P.arange(-90,90,30),labels=[1,0,0,0],color='0.5')
P.title("Blue Marble image - native 'cyl' projection",fontsize=12)
print 'plot cylindrical map (no warping needed) ...'
# create new figure
fig=P.figure()
# define orthographic projection centered on North America.
m = Basemap(projection='ortho',lat_0=40,lon_0=40,resolution='l')
# transform to nx x ny regularly spaced native projection grid
# nx and ny chosen to have roughly the same horizontal res as original image.
dx = 2.*P.pi*m.rmajor/float(nlons)
nx = int((m.xmax-m.xmin)/dx)+1; ny = int((m.ymax-m.ymin)/dx)+1
rgba_warped = ma.zeros((ny,nx,4),P.Float64)
# interpolate rgba values from proj='cyl' (geographic coords) to 'lcc'
# values outside of projection limb will be masked.
for k in range(4):
from matplotlib.toolkits.basemap import Basemap
from pylab import title, show, arange
# create Basemap instance for Geostationary (satellite view) projection.
lon_0 = float(raw_input('enter reference longitude (lon_0):'))
h = float(raw_input('enter satellite height above equator in meters (satellite_height):'))
m = Basemap(projection='geos',lon_0=lon_0,satellite_height=h,rsphere=(6378137.00,6356752.3142),)
# plot land-sea mask.
rgba_land = (0,255,0,255) # land green.
rgba_ocean = (0,0,255,255) # ocean blue.
# lakes=True means plot inland lakes with ocean color.
m.drawlsmask(rgba_land, rgba_ocean, lakes=True)
# draw parallels and meridians.
m.drawparallels(arange(-90.,120.,30.))
m.drawmeridians(arange(0.,420.,60.))
m.drawmapboundary()
title('Geostationary Map Centered on Lon=%s, Satellite Height=%s' % (lon_0,h))
show()
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')
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines(linewidth=0.25)
map.drawcountries(linewidth=0.25)
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, 32.73, 38.55, 48.25, 17.29]
lons = [-105.16, -117.16, -77.00, -114.21, -88.10]
cities = [
'Boulder, CO', 'San Diego, 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, fontsize=9)
# make up some data on a regular lat/lon grid.
nlats = 73
# plot wind vectors over map.
#Q = m.quiver(x,y,urot,vrot,scale=500)
# plot wind vectors on projection grid (looks better).
# first, shift grid so it goes from -180 to 180 (instead of 0 to 360
# in longitude). Otherwise, interpolation is messed up.
ugrid,newlons = shiftgrid(180.,u[nt,:,:],longitudes,start=False)
vgrid,newlons = shiftgrid(180.,v[nt,:,:],longitudes,start=False)
# transform vectors to projection grid.
urot,vrot,xx,yy = m.transform_vector(ugrid,vgrid,newlons,latitudes,51,51,returnxy=True,masked=True)
# plot wind vectors over map.
Q = m.quiver(xx,yy,urot,vrot,scale=500)
# make quiver key.
qk = p.quiverkey(Q, 0.1, 0.1, 20, '20 m/s', labelpos='W')
# draw coastlines, parallels, meridians, title.
m.drawcoastlines(linewidth=1.5)
m.drawparallels(parallels)
m.drawmeridians(meridians)
p.title('SLP and Wind Vectors '+date)
if nt == 0: # plot colorbar on a separate axes (only for first frame)
cax = p.axes([l+w-0.05, b, 0.03, h]) # setup colorbar axes
fig.colorbar(CS,drawedges=True, cax=cax) # draw colorbar
cax.text(0.0,-0.05,'mb')
p.axes(ax) # reset current axes
p.draw() # draw the plot
# save first and last frame n1 times
# (so gif animation pauses at beginning and end)
if nframe == 0 or nt == slp.shape[0]-1:
for n in range(n1):
p.savefig('anim%03i'%nframe+'.png')
nframe = nframe + 1
else:
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')
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines(linewidth=0.25)
map.drawcountries(linewidth=0.25)
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=[40.02,32.73,38.55,48.25,17.29]
lons=[-105.16,-117.16,-77.00,-114.21,-88.10]
cities=['Boulder, CO','San Diego, 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,fontsize=9)
# make up some data on a regular lat/lon grid.
nlats = 73; nlons = 145; delta = 2.*p.pi/(nlons-1)
lats = (0.5*p.pi-delta*p.indices((nlats,nlons))[0,:,:])
lons = (delta*p.indices((nlats,nlons))[1,:,:])
resolution='c',area_thresh=10000.,projection='lcc',\
lat_1=50.,lon_0=-107.)
# transform to nx x ny regularly spaced native projection grid
nx = int((m.xmax-m.xmin)/40000.)+1; ny = int((m.ymax-m.ymin)/40000.)+1
topodat = m.transform_scalar(topoin,lons,lats,nx,ny)
# set up figure with same aspect ratio as map.
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
ax = fig.add_axes([0.1,0.1,0.7,0.7])
# plot image over map.
im = m.imshow(topodat,cm.jet)
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
m.drawcoastlines()
m.drawcountries()
m.drawstates()
#m.fillcontinents()
# draw parallels
delat = 20.
parallels = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
m.drawparallels(parallels,labels=[1,1,0,1]) # labels on left, right, bottom.
# draw meridians
delon = 30.
meridians = arange(10.,360.,delon)
m.drawmeridians(meridians,labels=[1,1,0,1]) # labels on left, right, bottom.
title('ETOPO Topography - Lambert Conformal Conic')
show()
# in which direction to depart for other points on earth and how far
# it will be to reach that destination.
# The specified point shows up as a red dot in the center of the map.
# This example shows how to use the width and height keywords
# to specify the map projection region (instead of specifying
# the lat/lon of the upper right and lower left corners).
# user enters the lon/lat of the point, and it's name
lon_0 = float(raw_input('input reference lon (degrees):'))
lat_0 = float(raw_input('input reference lat (degrees):'))
location = raw_input('name of location:')
# use these values to setup Basemap instance.
width = 28000000
m = Basemap(width=width,height=width,\
resolution='c',projection='aeqd',\
lat_0=lat_0,lon_0=lon_0)
# draw coasts and fill continents.
m.drawcoastlines(linewidth=0.5)
m.fillcontinents()
# 20 degree graticule.
m.drawparallels(arange(-80,81,20))
m.drawmeridians(arange(-180,180,20))
# draw a red dot at the center.
xpt, ypt = m(lon_0, lat_0)
m.plot([xpt],[ypt],'ro')
# draw the title.
title('The World According to Garp in '+location)
show()
res = 'i'
map = Basemap(projection=prj,
llcrnrlon=lonmin,
llcrnrlat=latmin,
urcrnrlon=lonmax,
urcrnrlat=latmax,
resolution=res)
map.plot(lon, lat, 'r-')
map.plot(lon, lat, 'k+')
fs = 10
pylab.text(115.9,-31.9, "Perth", fontsize=fs, ha='left', va='top')
pylab.text(114.1,-21.9, "Exmouth", fontsize=fs, ha='left', va='top')
pylab.text(118.5,-20.4, "Port Hedland", fontsize=fs, ha='left', va='top')
pylab.text(130.8,-12.6, "Darwin", fontsize=fs, ha='left', va='top')
pylab.text(145.75,-16.9, "Cairns", fontsize=fs, ha='right', va='top')
pylab.text(149.2,-21.2, "Mackay", fontsize=fs, ha='right', va='top')
pylab.text(153.0,-27.5, "Brisbane", fontsize=fs, ha='right', va='top')
pylab.text(153.1,-30.25, "Coffs Harbour", fontsize=fs, ha='right', va='top')
pylab.text(151.1,-33.9, "Sydney", fontsize=fs, ha='right', va='top')
pylab.text(150.5,-35.3, "Ulladulla", fontsize=fs, ha='right', va='top')
map.fillcontinents(color='0.9')
map.drawcoastlines()
map.drawparallels(parallel, label=[1,0,0,1], fontsize=8)
map.drawmeridians(meridian, label=[1,0,0,1], fontsize=8)
pylab.show()
pylab.savefig("N:\\cyclone\\sandpits\\carthur\\landfall\\gates.v0.2.png")
# Lambert Conformal map of lower 48 states.
m = Basemap(llcrnrlon=-119,llcrnrlat=22,urcrnrlon=-64,urcrnrlat=49,
projection='lcc',lat_1=33,lat_2=45,lon_0=-95)
fig=p.figure(figsize=(8,m.aspect*8))
fig.add_axes([0.1,0.1,0.8,0.8])
# draw climate division boundaries.
shp_info = m.readshapefile('divisions','climdivs',drawbounds=True)
print shp_info
# make sure the shapefile has polygons (and not just lines).
if shp_info[1] != 5:
print 'warning: shapefile does not contain polygons'
# choose a color for each climate division (randomly).
colors={}
divnames=[]
print m.climdivs_info[0].keys()
for shapedict in m.climdivs_info:
divname = shapedict['ST']+repr(shapedict['DIV'])
colors[divname] = (random.uniform(0,1),random.uniform(0,1),random.uniform(0,1))
divnames.append(divname)
# cycle through climate divnames, color each one.
for nshape,seg in enumerate(m.climdivs):
xx,yy = zip(*seg)
color = rgb2hex(colors[divnames[nshape]])
p.fill(xx,yy,color,edgecolor=color)
# draw meridians and parallels.
m.drawparallels(nx.arange(25,65,20),labels=[1,0,0,0])
m.drawmeridians(nx.arange(-120,-40,20),labels=[0,0,0,1])
p.title('NCDC Climate Divisions')
p.show()
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 Robinson projection.
m = Basemap(projection='robin', lon_0=0.5 * (lons[0] + lons[-1]))
# create figure with same aspect ratio as map.
fig = m.createfigure()
# make filled contour plot.
x, y = m(*meshgrid(lons, lats))
cs = m.contourf(x, y, etopo, 30, cmap=cm.jet)
# draw coastlines.
m.drawcoastlines()
# draw a line around the map region.
m.drawmapboundary()
# draw parallels and meridians.
m.drawparallels(arange(-60., 90., 30.), labels=[1, 0, 0, 0])
m.drawmeridians(arange(0., 420., 60.), labels=[0, 0, 0, 1])
# add a title.
title('Robinson Projection')
show()
def plot_track(rlon, rlat=None, m=None, **keywords):
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']
if (m is None):
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']
minlon = -180
maxlon = 180.0
if ('minlon' in keywords):
minlon = keywords['minlon']
if ('maxlon' in keywords):
maxlon = keywords['maxlon']
lon_0 = 0
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:
m = Basemap(llcrnrlon=minlon,
llcrnrlat=minlat,
urcrnrlon=maxlon,
urcrnrlat=maxlat,
projection=map_proj,
lon_0=lon_0,
lat_0=lat_0)
if (show_lat == 1):
m.drawparallels(arange(minlat, maxlat + 30.0, 30.),
labels=[1, 0, 0, 0])
if (show_lon == 1):
m.drawmeridians(arange(minlon, maxlon + 60, 60.),
labels=[0, 0, 0, 1])
sgn = 'o'
if ('sgn' in keywords):
sgn = keywords['sgn']
if ('color' in keywords):
print('I am here', size(rlon))
lcolor = keywords['color']
print(max(lcolor), min(lcolor))
if ('minv' in keywords):
vmin = keywords['minv']
else:
vmin = min(lcolor)
if ('maxv' in keywords):
vmax = keywords['maxv']
else:
vmax = max(lcolor)
cx = cm.jet
cx.set_over('r')
cx.set_under('w')
x, y = m(rlon, rlat)
if (len(rlon) < 100):
scatter(x,
y,
marker=sgn,
c=lcolor,
s=30.0,
color='w',
vmin=vmin,
vmax=vmax,
cmap=cx) # , markersize=11)
else:
scatter(x,
y,
marker=sgn,
c=lcolor,
s=26,
edgecolor='w',
vmin=vmin,
vmax=vmax,
cmap=cx) # , markersize=6)
cbar_vert = 1
if ('cbar_vert' in keywords):
cbar_vert = keywords['cbar_vert']
if (cbar_vert == 1):
orientation = 'vertical'
else:
orientation = 'horizontal'
show_colorbar = 0
if ('cb' in keywords):
show_colorbar = keywords['cb']
if (show_colorbar == 1):
colorbar(orientation=orientation)
# colorbar(cmap=cx)
m.drawcoastlines(color='k', linewidth=1.0)
m.drawmapboundary()
# m.drawcountries(color='k', linewidth=0.5)
if ('title' in keywords):
stitle = keywords['title']
title(stitle)
return m
fig = figure(figsize=(xsize, m.aspect * xsize))
ax = fig.add_axes([0.1, 0.1, 0.75, 0.75])
# plot image over map.
im = m.imshow(topoin, cm.jet)
cax = axes([0.875, 0.1, 0.05, 0.75]) # setup colorbar axes.
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
m.drawcoastlines()
#m.drawcountries()
#m.drawstates()
#m.fillcontinents()
# draw parallels
delat = 30.
circles = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
m.drawparallels(circles, labels=[1, 0, 0, 1])
# draw meridians
delon = 60.
meridians = arange(-180, 180, delon)
m.drawmeridians(meridians, labels=[1, 0, 0, 1])
title('Cylindrical Equidistant')
print 'plotting Cylindrical Equidistant example, close plot window to proceed ...'
show()
# setup miller cylindrical map projection.
m = Basemap(-180.,-90.,180.,90.,\
resolution='c',area_thresh=10000.,projection='mill')
# transform to nx x ny regularly spaced native projection grid
nx = len(lons)
ny = len(lats)
topodat = m.transform_scalar(topoin, lons, lats, nx, ny)
im = imshow(topoin,
cm.jet,
extent=(m.llcrnrx, m.urcrnrx, m.llcrnry, m.urcrnry),
origin='lower')
cax = axes([0.875, 0.1, 0.05, 0.75])
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
m.drawcoastlines(ax)
#m.drawcountries(ax)
#m.drawstates(ax)
#m.fillcontinents(ax)
# draw parallels
delat = 30.
circles = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
m.drawparallels(ax, circles)
# draw meridians
delon = 60.
lon1 = int(lons[0] / delon) * delon
lon2 = (int(lons[-1] / delon) + 1) * delon
meridians = arange(lon1, lon2, delon)
m.drawmeridians(ax, meridians)
ax.set_xticks([]) # no ticks
ax.set_yticks([])
title('Cylindrical Equidistant')
print 'plotting Cylindrical Equidistant example, close plot window to proceed ...'
show()
m = Basemap(lons[0],-80.,lons[-1],80.,\
resolution='c',area_thresh=10000.,projection='merc',\
lon_0=0.5*(lons[0]+lons[-1]),lat_ts=20.)
# 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)
m.drawmeridians(meridians,labels=[1,1,1,1])
title('Randomly Spaced Locations (Min Dist = %g km, %g points)'% (rcrit,len(lons_out)),y=1.075)
show()
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
fig.add_axes([0.1,0.1,0.8,0.8])
ax = gca() # get current axis instance
ax.update_datalim(((m.llcrnrx, m.llcrnry),(m.urcrnrx,m.urcrnry)))
ax.set_xlim((m.llcrnrx, m.urcrnrx))
ax.set_ylim((m.llcrnry, m.urcrnry))
m.drawcoastlines(ax)
m.drawcountries(ax)
m.drawstates(ax)
m.fillcontinents(ax)
# draw parallels
delat = 30.
circles = arange(0.,90.,delat).tolist()+\
arange(-delat,-90,-delat).tolist()
m.drawparallels(ax,circles)
# convert parallels to native map projection coordinates
nativeCoordCircles = m([0]*len(circles), circles)[1]
ax.set_yticks(nativeCoordCircles)
ax.yaxis.set_major_formatter(MercYAxisFormatter(m))
# draw meridians
delon = 60.
lon1 = int(m.llcrnrlon/delon)*delon
lon2 = (int(m.urcrnrlon/delon)+1)*delon
meridians = arange(lon1,lon2,delon)
m.drawmeridians(ax,meridians)
ax.set_xticks(meridians)
title('Mercator with Longitude and Latitude Labels')
print 'plotting Mercator Y-axis latitude ticks example, close plot window to proceed ...'
show()
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 Robinson projection.
m = Basemap(projection='robin',lon_0=0.5*(lons[0]+lons[-1]))
# create figure with same aspect ratio as map.
fig = m.createfigure()
# make filled contour plot.
x, y = m(*meshgrid(lons, lats))
cs = m.contourf(x,y,etopo,30,cmap=cm.jet)
# draw coastlines.
m.drawcoastlines()
# draw a line around the map region.
m.drawmapboundary()
# draw parallels and meridians.
m.drawparallels(arange(-60.,90.,30.),labels=[1,0,0,0])
m.drawmeridians(arange(0.,420.,60.),labels=[0,0,0,1])
# add a title.
title('Robinson Projection')
show()
res = 'i'
map = Basemap(projection=prj,
llcrnrlon=lonmin,
llcrnrlat=latmin,
urcrnrlon=lonmax,
urcrnrlat=latmax,
resolution=res)
map.plot(lon, lat, 'r-')
map.plot(lon, lat, 'k+')
fs = 10
pylab.text(115.9,-31.9, "Perth", fontsize=fs, ha='left', va='top')
pylab.text(114.1,-21.9, "Exmouth", fontsize=fs, ha='left', va='top')
pylab.text(118.5,-20.4, "Port Hedland", fontsize=fs, ha='left', va='top')
pylab.text(130.8,-12.6, "Darwin", fontsize=fs, ha='left', va='top')
pylab.text(145.75,-16.9, "Cairns", fontsize=fs, ha='right', va='top')
pylab.text(149.2,-21.2, "Mackay", fontsize=fs, ha='right', va='top')
pylab.text(153.0,-27.5, "Brisbane", fontsize=fs, ha='right', va='top')
pylab.text(153.1,-30.25, "Coffs Harbour", fontsize=fs, ha='right', va='top')
pylab.text(151.1,-33.9, "Sydney", fontsize=fs, ha='right', va='top')
pylab.text(150.5,-35.3, "Ulladulla", fontsize=fs, ha='right', va='top')
map.fillcontinents(color='0.9')
map.drawcoastlines()
map.drawparallels(parallel, label=[1,0,0,1], fontsize=8)
map.drawmeridians(meridian, label=[1,0,0,1], fontsize=8)
pylab.show()
pylab.savefig("N:\\cyclone\\sandpits\\carthur\\landfall\\gates.v0.2.png")
from matplotlib.toolkits.basemap import Basemap
from pylab import title, show, arange
# 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):'))
m = Basemap(projection='ortho', lon_0=lon_0, lat_0=lat_0)
# plot land-sea mask.
rgba_land = (0, 255, 0, 255) # land green.
rgba_ocean = (0, 0, 255, 255) # ocean blue.
# lakes=True means plot inland lakes with ocean color.
m.drawlsmask(rgba_land, rgba_ocean, lakes=True)
# draw parallels and meridians.
m.drawparallels(arange(-90., 120., 30.))
m.drawmeridians(arange(0., 420., 60.))
m.drawmapboundary()
title('Orthographic Map Centered on Lon=%s, Lat=%s' % (lon_0, lat_0))
show()
ax = fig.add_axes([0.1,0.1,0.7,0.7])
# make a filled contour plot.
x, y = m(lons, lats)
CS = m.contour(x,y,hgt,15,linewidths=0.5,colors='k')
CS = m.contourf(x,y,hgt,15,cmap=cm.jet)
l,b,w,h=ax.get_position()
cax = axes([l+w+0.075, b, 0.05, h]) # setup colorbar axes
colorbar(drawedges=True, cax=cax) # draw colorbar
axes(ax) # make the original axes current again
# draw coastlines and political boundaries.
m.drawcoastlines()
m.drawmapboundary()
m.fillcontinents()
# draw parallels and meridians.
parallels = arange(-60.,90,30.)
m.drawparallels(parallels,labels=[1,0,0,0])
meridians = arange(-360.,360.,30.)
m.drawmeridians(meridians)
title('Sinusoidal Filled Contour Demo')
print 'plotting with sinusoidal basemap ...'
# create new figure
fig=figure()
# setup of mollweide basemap
m = Basemap(resolution='c',projection='moll',lon_0=0)
ax = fig.add_axes([0.1,0.1,0.7,0.7])
# make a filled contour plot.
x, y = m(lons, lats)
CS = m.contour(x,y,hgt,15,linewidths=0.5,colors='k')
CS = m.contourf(x,y,hgt,15,cmap=cm.jet)
l,b,w,h=ax.get_position()
lon[0:-1] = tmp[:]
lon[-1] = tmp[0]+360
del tmp
f.close()
#--- Mapping information:
map = Basemap( projection='cyl', resolution='l'
, llcrnrlon=0, urcrnrlon=360
, llcrnrlat=-76.875, urcrnrlat=76.875
, lon_0=180, lat_0=0
)
map.drawmeridians(p.arange(0,361,45), labels=[0,0,0,1])
map.drawparallels(p.arange(-90,90,30), labels=[1,0,0,1])
map.drawcoastlines()
#--- Write out contour map and view using preview:
x, y = p.meshgrid(lon,lat)
CS = map.contourf(x, y, u1, cmap=p.cm.gray)
p.text( 0.5, -0.15, 'Longitude [deg]'
, horizontalalignment='center'
, verticalalignment='center'
, transform = p.gca().transAxes )
p.text( -0.11, 0.5, 'Latitude [deg]'
, rotation='vertical'
, horizontalalignment='center'
, verticalalignment='center'
fig=figure(figsize=(xsize,m.aspect*xsize))
ax = fig.add_axes([0.1,0.1,0.75,0.75])
# plot image over map.
im = m.imshow(topoin,cm.jet)
cax = axes([0.875, 0.1, 0.05, 0.75]) # setup colorbar axes.
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
m.drawcoastlines()
#m.drawcountries()
#m.drawstates()
#m.fillcontinents()
# draw parallels
delat = 30.
circles = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
m.drawparallels(circles,labels=[1,0,0,1])
# draw meridians
delon = 60.
meridians = arange(-180,180,delon)
m.drawmeridians(meridians,labels=[1,0,0,1])
title('Cylindrical Equidistant')
print 'plotting Cylindrical Equidistant example, close plot window to proceed ...'
show()
# setup miller cylindrical map projection.
m = Basemap(-180.,-90.,180.,90.,\
resolution='c',area_thresh=10000.,projection='mill')
# transform to nx x ny regularly spaced native projection grid
nx = len(lons); ny = len(lats)
topodat = m.transform_scalar(topoin,lons,lats,nx,ny)
# setup figure with same aspect ratio as map.
# define grid (nx x ny regularly spaced native projection grid)
nx = int((m.xmax-m.xmin)/40000.)+1; ny = int((m.ymax-m.ymin)/40000.)+1
lonsout, latsout = m.makegrid(nx,ny)
topodat = interp(topoin,lons,lats,lonsout,latsout)
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
ax = fig.add_axes([0.1,0.1,0.75,0.75])
im = imshow(topodat,cm.jet,extent=(m.xmin, m.xmax, m.ymin, m.ymax),origin='lower')
cax = axes([0.875, 0.1, 0.05, 0.75])
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
m.drawcoastlines(ax)
m.drawcountries(ax)
m.drawstates(ax)
#m.fillcontinents(ax)
# draw parallels
delat = 20.
parallels = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
m.drawparallels(ax,parallels)
# draw meridians
delon = 30.
meridians = arange(0.,360.,delon)
m.drawmeridians(ax,meridians)
ax.set_xticks([]) # no ticks
ax.set_yticks([])
title('ETOPO Topography - Lambert Conformal Conic')
show()
# read shapefile.
shp_info = m.readshapefile('huralll020','hurrtracks',drawbounds=False)
print shp_info
# find names of storms that reached Cat 4.
names = []
for shapedict in m.hurrtracks_info:
cat = shapedict['CATEGORY']
name = shapedict['NAME']
if cat in ['H4','H5'] and name not in names:
if name != 'NOT NAMED': names.append(name)
print names
print len(names)
# plot tracks of those storms.
for shapedict,shape in zip(m.hurrtracks_info,m.hurrtracks):
name = shapedict['NAME']
cat = shapedict['CATEGORY']
if name in names:
xx,yy = zip(*shape)
# show part of track where storm > Cat 4 as thick red.
if cat in ['H4','H5']:
p.plot(xx,yy,linewidth=1.5,color='r')
elif cat in ['H1','H2','H3']:
p.plot(xx,yy,color='k')
# draw coastlines, meridians and parallels.
m.drawcoastlines()
m.drawcountries()
m.drawparallels(p.arange(10,70,20),labels=[0,1,0,0])
m.drawmeridians(p.arange(-100,0,20),labels=[0,0,0,1])
p.title('Atlantic Hurricane Tracks (Storms Reaching Category 4)')
p.show()
topodat = interp(topoin, lons, lats, lonsout, latsout)
xsize = rcParams['figure.figsize'][0]
fig = figure(figsize=(xsize, m.aspect * xsize))
ax = fig.add_axes([0.1, 0.1, 0.75, 0.75])
im = imshow(topodat,
cm.jet,
extent=(m.xmin, m.xmax, m.ymin, m.ymax),
origin='lower')
cax = axes([0.875, 0.1, 0.05, 0.75])
colorbar(tickfmt='%d', cax=cax) # draw colorbar
axes(ax) # make the original axes current again
m.drawcoastlines(ax)
m.drawcountries(ax)
m.drawstates(ax)
#m.fillcontinents(ax)
# draw parallels
delat = 20.
parallels = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
m.drawparallels(ax, parallels)
# draw meridians
delon = 30.
meridians = arange(0., 360., delon)
m.drawmeridians(ax, meridians)
ax.set_xticks([]) # no ticks
ax.set_yticks([])
title('ETOPO Topography - Lambert Conformal Conic')
show()
def plot_track(rlon, rlat=None, m=None, **keywords):
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']
if (m == None):
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']
minlon = -180
maxlon = 180.0
if ('minlon' in keywords):
minlon = keywords['minlon']
if ('maxlon' in keywords):
maxlon = keywords['maxlon']
lon_0 = 0
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:
m=Basemap(llcrnrlon=minlon, llcrnrlat=minlat, \
urcrnrlon=maxlon, urcrnrlat=maxlat,projection=map_proj, lon_0=lon_0, lat_0=lat_0)
if (show_lat == 1):
m.drawparallels(arange(minlat, maxlat + 30.0, 30.),
labels=[1, 0, 0, 0])
if (show_lon == 1):
m.drawmeridians(arange(minlon, maxlon + 60, 60.),
labels=[0, 0, 0, 1])
sgn = '+'
if ('sgn' in keywords):
sgn = keywords['sgn']
if ('color' in keywords):
lcolor = keywords['color']
if (len(rlon) < 100):
m.plot(rlon, rlat, sgn, color=lcolor, markersize=11)
else:
m.plot(rlon, rlat, sgn, color=lcolor, markersize=6)
else:
m.plot(rlon, rlat, sgn)
m.drawcoastlines(color='w', linewidth=0.5)
m.drawmapboundary()
# m.drawcountries(color='k', linewidth=0.5)
if ('title' in keywords):
stitle = keywords['title']
title(stitle)
return m
contours = N.arange(5300., 6000., 60.0)
parallels = N.arange(25., 60.0, 10.0)
meridians = N.arange(-120., -60.0, 10.0)
fields = (cress1, cress2, cress3, cress_187, barnes_analyses[0],
barnes_analyses[1], barnes_analyses[2], barnes_3pass)
names = ('Cressman 1st Pass', 'Cressman 2nd Pass', 'Cressman 3rd Pass',
'Cressman R=1.87d', r'$\rm{Barnes} \gamma=1.0$',r'$\rm{Barnes} \gamma=0.4$',
r'$\rm{Barnes} \gamma=0.2$', r'$\rm{Barnes 3-pass} \gamma=1.0$')
filenames = ('cress1', 'cress2', 'cress3', 'cress187', 'barnes1', 'barnes2',
'barnes3', 'barnes3pass')
for field,name,filename in zip(fields, names, filenames):
f = P.figure()
bm_ps.drawstates()
bm_ps.drawcountries()
bm_ps.drawcoastlines()
bm_ps.drawparallels(parallels, labels = [1,1,0,0])
bm_ps.drawmeridians(meridians, labels = [0,0,1,1])
cp = bm_ps.contour(x_bm, y_bm, field, contours, cmap=colormap)
P.clabel(cp, fontsize=fontsize, fmt='%.1f')
f.text(0.5,0.95,name,horizontalalignment='center',fontsize=16)
if save_work:
P.savefig(filename + '.png', dpi = 300)
else:
P.show()
filename = 'cress12diff'
f = P.figure()
bm_ps.drawstates()
bm_ps.drawcountries()
bm_ps.drawcoastlines()
bm_ps.drawparallels(parallels, labels = [1,1,0,0])
# setup a mercator projection.
m = Basemap(-90.,30.,30.,60.,\
resolution='c',area_thresh=10000.,projection='merc',\
lat_ts=20.)
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
fig.add_axes([0.1,0.1,0.8,0.8])
ax = gca() # get current axis instance
ax.update_datalim(((m.llcrnrx, m.llcrnry),(m.urcrnrx,m.urcrnry)))
ax.set_xlim((m.llcrnrx, m.urcrnrx))
ax.set_ylim((m.llcrnry, m.urcrnry))
m.drawcoastlines(ax)
m.fillcontinents(ax)
# draw parallels
circles = [35,45,55]
m.drawparallels(ax,circles,labels=[1,1,0,1])
# draw meridians
meridians = [-90,-60,-30,0,30]
m.drawmeridians(ax,meridians,labels=[1,1,0,1])
# nylat, nylon are lat/lon of New York
nylat = 40.78
nylon = -73.98
# lonlat, lonlon are lat/lon of London.
lonlat = 51.53
lonlon = 0.08
# draw the great circle.
m.drawgreatcircle(ax,nylon,nylat,lonlon,lonlat,linewidth=2,color='b')
title('Great Circle from New York to London')
show()
nx = int((m.xmax-m.xmin)/40000.)+1; ny = int((m.ymax-m.ymin)/40000.)+1
topodat,x,y = m.transform_scalar(topoin,lons,lats,nx,ny,returnxy=True)
# create the figure.
fig=figure(figsize=(8,8))
# add an axes, leaving room for colorbar on the right.
ax = fig.add_axes([0.1,0.1,0.7,0.7])
# plot image over map with imshow.
im = m.imshow(topodat,cm.jet)
# setup colorbar axes instance.
l,b,w,h = ax.get_position()
cax = axes([l+w+0.075, b, 0.05, h])
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.)
m.drawparallels(parallels,labels=[1,1,0,1])
meridians = arange(10.,360.,30.)
m.drawmeridians(meridians,labels=[1,1,0,1])
# set title.
title('ETOPO Topography - Lambert Conformal Conic')
show()
nylat = 40.78
nylon = -73.98
# lonlat, lonlon are lat/lon of London.
lonlat = 51.53
lonlon = 0.08
# find 1000 points along the great circle.
#x,y = m.gcpoints(nylon,nylat,lonlon,lonlat,1000)
# draw the great circle.
#m.plot(x,y,linewidth=2)
# drawgreatcircle performs the previous 2 steps in one call.
m.drawgreatcircle(nylon, nylat, lonlon, lonlat, linewidth=2, color='b')
m.drawcoastlines()
m.fillcontinents()
# draw parallels
circles = arange(10, 90, 20)
m.drawparallels(circles, labels=[1, 1, 0, 1])
# draw meridians
meridians = arange(-180, 180, 30)
m.drawmeridians(meridians, labels=[1, 1, 0, 1])
title('Great Circle from New York to London (Mercator)')
show()
# setup a gnomonic projection.
m = Basemap(llcrnrlon=-100.,llcrnrlat=20.,urcrnrlon=20.,urcrnrlat=60.,\
resolution='c',area_thresh=10000.,projection='gnom',\
lat_0=40.,lon_0=-45.)
# make figure with aspect ratio that matches map region.
xsize = rcParams['figure.figsize'][0]
fig = figure(figsize=(xsize, m.aspect * xsize))
fig.add_axes([0.1, 0.1, 0.8, 0.8])
# nylat, nylon are lat/lon of New York
# setup a mercator projection.
m = Basemap(-90.,30.,30.,60.,\
resolution='c',area_thresh=10000.,projection='merc',\
lat_ts=20.)
xsize = rcParams['figure.figsize'][0]
fig = figure(figsize=(xsize, m.aspect * xsize))
fig.add_axes([0.1, 0.1, 0.8, 0.8])
ax = gca() # get current axis instance
ax.update_datalim(((m.llcrnrx, m.llcrnry), (m.urcrnrx, m.urcrnry)))
ax.set_xlim((m.llcrnrx, m.urcrnrx))
ax.set_ylim((m.llcrnry, m.urcrnry))
m.drawcoastlines(ax)
m.fillcontinents(ax)
# draw parallels
circles = [35, 45, 55]
m.drawparallels(ax, circles, labels=[1, 1, 0, 1])
# draw meridians
meridians = [-90, -60, -30, 0, 30]
m.drawmeridians(ax, meridians, labels=[1, 1, 0, 1])
# nylat, nylon are lat/lon of New York
nylat = 40.78
nylon = -73.98
# lonlat, lonlon are lat/lon of London.
lonlat = 51.53
lonlon = 0.08
# draw the great circle.
m.drawgreatcircle(ax, nylon, nylat, lonlon, lonlat, linewidth=2, color='b')
title('Great Circle from New York to London')
show()
lons = load('etopo20lons.gz')
lats = load('etopo20lats.gz')
# create figure.
fig = Figure()
canvas = FigureCanvas(fig)
# create axes instance, leaving room for colorbar at bottom.
ax = fig.add_axes([0.125,0.175,0.75,0.75])
# create Basemap instance for Robinson projection.
# set 'ax' keyword so pylab won't be imported.
m = Basemap(projection='robin',lon_0=0.5*(lons[0]+lons[-1]),ax=ax)
# make filled contour plot.
x, y = m(*meshgrid(lons, lats))
cs = m.contourf(x,y,etopo,30,cmap=cm.jet)
# draw coastlines.
m.drawcoastlines()
# draw a line around the map region.
m.drawmapboundary()
# draw parallels and meridians.
m.drawparallels(nx.arange(-60.,90.,30.),labels=[1,0,0,0],fontsize=10)
m.drawmeridians(nx.arange(0.,420.,60.),labels=[0,0,0,1],fontsize=10)
# add a title.
ax.set_title('Robinson Projection')
# add a colorbar.
l,b,w,h = ax.get_position()
cax = fig.add_axes([l, b-0.1, w, 0.03],frameon=False) # setup colorbar axes
fig.colorbar(cs, cax=cax, orientation='horizontal',ticks=cs.levels[::3])
# save image (width 800 pixels with dpi=100 and fig width 8 inches).
canvas.print_figure('simpletest',dpi=100)
# done.
print 'image saved in simpletest.png'
projection = 'sp' + proj
elif hem == 'North':
projection = 'np' + proj
# setup map projection
# centered on Australia (for SH) or US (for NH).
if proj == 'ortho':
m = Basemap(projection='ortho',
resolution='c',
area_thresh=10000.,
lat_0=lat_0,
lon_0=lon_0_ortho)
else:
m = Basemap(boundinglat=bounding_lat,lon_0=lon_0,\
resolution='c',area_thresh=10000.,projection=projection)
# compute native map projection coordinates for lat/lon grid.
x, y = m(*meshgrid(lons, lats))
ax = fig.add_subplot(2, 2, npanel)
# make filled contour plot.
cs = m.contourf(x, y, etopo, 20, cmap=cm.jet)
# draw coastlines.
m.drawcoastlines()
# draw parallels and meridians.
m.drawparallels(arange(-80., 90, 20.))
m.drawmeridians(arange(0., 360., 60.))
# draw boundary around map region.
m.drawmapboundary()
# draw title.
title(hem + ' Polar ' + projname, y=1.05, fontsize=12)
show()
#savefig('polarmap'+hem+'.eps')
