Python Basemap.drawmeridians方法代码示例

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
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

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
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 

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
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")

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
	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")

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
	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")

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
# 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()

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
# 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()

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]

#.........这里部分代码省略.........
        elif N.size(rngs_idxs['lon']) == 1:
            zgrid = num.MLab.squeeze(data[ ritim[0]:ritim[-1]+1,
                                           rilat[0]:rilat[-1]+1, 
                                           rilon[0] ])
        else:
            raise ValueError, 'unrecognized configuration'


        #* Change zgrid for special case of a lat. vs. time contour 
        #  plot.  Calculate xgrid and ygrid:

        if keys_rngs_sizes_gt_1.count('time') and \
           keys_rngs_sizes_gt_1.count('lat'):
           zgrid = N.transpose(zgrid)

        xgrid, ygrid = pylab.meshgrid(x, y)
        

        #* Set contour levels:

        if plotkwds['levels'] == None:
            levels = nice_levels(zgrid)
        else:
            levels = plotkwds['levels']


        #- Plot (creating continents first if is a lat vs. lon plot)
        #  and write contour levels/color bar as appropriate:

        if keys_rngs_sizes_gt_1.count('lon') and \
           keys_rngs_sizes_gt_1.count('lat'):
            mapplot = Basemap(projection='cyl', resolution='l',
                              llcrnrlon=N.min(xgrid), llcrnrlat=N.min(ygrid),
                              urcrnrlon=N.max(xgrid), urcrnrlat=N.max(ygrid))
            mapplot.drawcoastlines()
            mapplot.drawmeridians(nice_levels(rngs['lon'], 
                                  approx_nlev=plotkwds['nlatlon']),
                                  labels=[1,0,0,1])
            mapplot.drawparallels(nice_levels(rngs['lat'],
                                  approx_nlev=plotkwds['nlatlon']),
                                  labels=[1,0,0,1])
            if plotkwds['filled']:
                plot = mapplot.contourf(xgrid, ygrid, zgrid, levels)
                pylab.colorbar(plot, orientation='horizontal', format='%g')
            else:
                plot = mapplot.contour(xgrid, ygrid, zgrid, levels)
                pylab.clabel(plot, inline=1, fontsize=10, fmt='%g')
        else:
            if plotkwds['filled']:
                plot = pylab.contourf(xgrid, ygrid, zgrid, levels)
                pylab.colorbar(plot, orientation='horizontal', format='%g')
            else:
                plot = pylab.contour(xgrid, ygrid, zgrid, levels)
                pylab.clabel(plot, inline=1, fontsize=10, fmt='%g')

    else:
        raise ValueError, 'unrecognized plottype'


    #- Add titling.  Lat vs. lon plots do not have axis labels because
    #  the map labels already make it clear, and for those plots the
    #  title also includes the time value:

    if keys_rngs_sizes_gt_1.count('lon') and \
       keys_rngs_sizes_gt_1.count('lat'):
        titlename = titlename + ' at ' \
                  + dimname['time'] + ' ' \
                  + str(rngs['time'][0]) + ' ' \
                  + dimunits['time']
        titlename = mpl_latex_script1(titlename)
        pylab.title(titlename)
    else: 
        titlename = mpl_latex_script1(titlename)
        xname = mpl_latex_script1(xname)
        yname = mpl_latex_script1(yname)
        pylab.xlabel(xname)
        pylab.ylabel(yname)
        pylab.title(titlename)


    #- Output plot to PNG file or screen.  The show command seems to
    #  have a problem on my Mac OS X, so save to a temporary file
    #  and use preview to view for fn == None and tmppreview set to
    #  True.  Note that the temporary file is not deleted by this 
    #  method:

    if plotkwds['fn'] == None:                       #+ Screen display
        if plotkwds['tmppreview'] and sys.platform == 'darwin':
            outputfn = tempfile.mkstemp('.png','qtcm_')
            pylab.savefig(outputfn[-1])
            os.system('open -a /Applications/Preview.app '+outputfn[-1])
        else:
            pylab.show()

    elif type(plotkwds['fn']) == type('a'):          #+ Write to file
        pylab.savefig(plotkwds['fn'])
        pylab.close(1)

    else:
        raise ValueError, 'cannot write to this type of file'

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
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.
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
fig.add_axes([0.1,0.1,0.75,0.75])
# plot image over map.

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
            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()

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
from matplotlib.toolkits.basemap import Basemap
import cPickle
from pylab import *
# read in topo data from pickle (on a regular lat/lon grid)
topodict = cPickle.load(open('etopo20.pickle','rb'))
etopo = topodict['data']; lons = topodict['lons']; lats = topodict['lats']
# create Basemap instance (global cylindrical equidistant is default)
m = Basemap(lons[0],lats[0],lons[-1],lats[-1])
# create figure with same aspect ratio as map.
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize,m.aspect*xsize))
fig.add_axes([0.1,0.1,0.8,0.8])
im = m.imshow(etopo)
# draw coastlines and fill continents.
m.drawcoastlines()
m.fillcontinents()
# draw parallels, label on bottom.
circles = arange(-90.,120.,30.)
m.drawparallels(circles,labels=[1,0,0,0])
# draw meridians, label on left.
meridians = arange(0.,390.,60.)
m.drawmeridians(meridians,labels=[0,0,0,1])
title('Cylindrical Equidistant')
show()

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
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()

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
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()

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
 #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:
    p.savefig('anim%03i'%nframe+'.png')

# 需要导入模块: from matplotlib.toolkits.basemap import Basemap [as 别名]
# 或者: from matplotlib.toolkits.basemap.Basemap import drawmeridians [as 别名]
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()