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")
# setup mercator map projection (-80 to +80).
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)
# 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.
im = m.imshow(topodat,cm.jet)
m.drawcoastlines()
m.drawcountries()
m.drawstates()
m.fillcontinents()
# draw parallels
m.drawparallels(circles,labels=[1,1,1,1])
# draw meridians
m.drawmeridians(meridians,labels=[1,1,1,1])
title('Mercator',y=1.1)
print 'plotting Mercator example, close plot window to proceed ...'
show()
# setup transverse mercator basemap.
m = Basemap(170.,-45,10.,45.,\
resolution='c',area_thresh=10000.,projection='tmerc',\
lat_0=0.,lon_0=-90.)
xsize = rcParams['figure.figsize'][0]
fig=figure(figsize=(xsize/m.aspect,xsize))
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)
# 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.
im = m.imshow(topodat, cm.jet)
m.drawcoastlines()
m.drawcountries()
m.drawstates()
m.fillcontinents()
# draw parallels
m.drawparallels(circles, labels=[1, 1, 1, 1])
# draw meridians
m.drawmeridians(meridians, labels=[1, 1, 1, 1])
title('Mercator', y=1.1)
print 'plotting Mercator example, close plot window to proceed ...'
show()
# setup transverse mercator basemap.
m = Basemap(170.,-45,10.,45.,\
resolution='c',area_thresh=10000.,projection='tmerc',\
lat_0=0.,lon_0=-90.)
xsize = rcParams['figure.figsize'][0]
fig = figure(figsize=(xsize / m.aspect, xsize))
lon, lat = self.baseMap(0.0, y, inverse=True)
return "%g" % lat
m = Basemap(-180.,-80.,180.,80.,\
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.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)
# define grid (nx x ny regularly spaced native projection grid)
nx = len(lons)
ny = int(80. * len(lats) / 90.)
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))
fig.add_axes([0.1, 0.1, 0.8, 0.8])
im = imshow(topodat,
cm.jet,
extent=(m.llcrnrx, m.urcrnrx, m.llcrnry, m.urcrnry),
origin='lower')
ax = gca() # get current axis instance
m.drawcoastlines(ax)
m.drawcountries(ax)
m.drawstates(ax)
m.fillcontinents(ax)
# draw parallels
m.drawparallels(ax, circles)
# draw meridians
m.drawmeridians(ax, meridians)
ax.set_xticks([]) # no ticks
ax.set_yticks([])
title('Mercator')
print 'plotting Mercator example, close plot window to proceed ...'
show()
m = Basemap(-145.5,1.,-2.566,46.352,\
resolution='c',area_thresh=10000.,projection='lcc',\
lat_1=50.,lon_0=-107.)
# define grid (nx x ny regularly spaced native projection grid)
meridians = arange(10., 360., delon)
npanel = 0
# plots of the US.
projs = ['lcc', 'aeqd', 'aea', 'laea', 'eqdc', 'stere']
fig = figure(figsize=(8, 12))
for proj in projs:
m = Basemap(width=width,height=height,
resolution='c',projection=proj,\
lat_0=lat_0,lon_0=lon_0)
npanel = npanel + 1
fig.add_subplot(3, 2, npanel)
# setup figure with same aspect ratio as map.
m.drawcoastlines()
m.drawcountries()
m.fillcontinents()
m.drawstates()
m.drawparallels(circles)
m.drawmeridians(meridians)
title('proj = ' + proj + ' centered on %sW, %sN' % (lon_0, lat_0),
fontsize=10)
proj = 'omerc'
delat = 10.
circles = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
delon = 10.
meridians = arange(10., 360., delon)
lat_1 = 40
lat_2 = 55
lon_1 = -120
lon_2 = -140
fontsize = 14
#Do the necessary processing for each analysis
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()
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 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")
meridians = arange(10.,360.,delon)
npanel = 0
# plots of the US.
projs = ['lcc','aeqd','aea','laea','eqdc','stere']
fig = figure(figsize=(8,12))
for proj in projs:
m = Basemap(width=width,height=height,
resolution='c',projection=proj,\
lat_0=lat_0,lon_0=lon_0)
npanel = npanel + 1
subplot(3,2,npanel)
# setup figure with same aspect ratio as map.
m.drawcoastlines()
m.drawcountries()
m.fillcontinents()
m.drawstates()
m.drawparallels(circles)
m.drawmeridians(meridians)
title('proj = '+proj+' centered on %sW, %sN' % (lon_0,lat_0),fontsize=10)
show()
proj = 'omerc'
delat = 10.
circles = arange(0.,90.+delat,delat).tolist()+\
arange(-delat,-90.-delat,-delat).tolist()
delon = 10.
meridians = arange(10.,360.,delon)
lat_1 = 40; lat_2 = 55
lon_1 = -120; lon_2 = -140
lat_0 = 47.5 ; lon_0 = -130
fig = figure()
x_bm,y_bm = ps2.to_basemap_xy(m2, x_grid / cm_per_m, y_grid / cm_per_m) #Radius factor used in all of the analyses R = 4.32 heights_cress = oban.analyze_grid(data.heights, x_grid, y_grid, data.x, data.y, oban.cressman_weights, R) contours = N.arange(5300., 6000., 60.0) parallels = N.arange(25., 60.0, 10.0) meridians = N.arange(-120., -60.0, 10.0) ##m2.drawstates() ##m2.drawcountries() ##m2.drawcoastlines() ##m2.drawparallels(parallels, labels = [1,1,0,0]) ##m2.drawmeridians(meridians, labels = [0,0,1,1]) ob_x, ob_y = ps2.to_basemap_xy(m2, data.x / cm_per_m, data.y / cm_per_m) #m2.plot(ob_x, ob_y, 'bx') #m2.plot(x_bm, y_bm, 'g.') for name in M.cm.cmapnames: f = P.figure() m2.drawstates() m2.drawcountries() m2.drawcoastlines() m2.drawparallels(parallels, labels = [1,1,0,0]) m2.drawmeridians(meridians, labels = [0,0,1,1]) c = m2.contour(x_bm, y_bm, heights_cress, contours, cmap=M.cm.get_cmap(name)) P.title(name) #P.clabel(c) P.show()
