Python Basemap.drawparallels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 drawparallels [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 drawparallels [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 drawparallels [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 drawparallels [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 drawparallels [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 drawparallels [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 drawparallels [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()

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

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

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

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

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

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