SF.net SVN: matplotlib: [5197] trunk/toolkits/basemap/examples

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Revision: 5197
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=5197&view=rev
Author:   jswhit
Date:     2008-05-20 05:22:09 -0700 (Tue, 20 May 2008)

Log Message:
-----------
more examples updated to numpy/pyplot namespace

Modified Paths:
--------------
    trunk/toolkits/basemap/examples/ccsm_popgrid.py
    trunk/toolkits/basemap/examples/fillstates.py
    trunk/toolkits/basemap/examples/garp.py
    trunk/toolkits/basemap/examples/hurrtracks.py
    trunk/toolkits/basemap/examples/panelplot.py
    trunk/toolkits/basemap/examples/plot_tissot.py
    trunk/toolkits/basemap/examples/plotprecip.py
    trunk/toolkits/basemap/examples/plotsst.py
    trunk/toolkits/basemap/examples/pnganim.py
    trunk/toolkits/basemap/examples/polarmaps.py
    trunk/toolkits/basemap/examples/setwh.py
    trunk/toolkits/basemap/examples/show_colormaps.py
    trunk/toolkits/basemap/examples/testgdal.py

Modified: trunk/toolkits/basemap/examples/ccsm_popgrid.py
===================================================================

--- trunk/toolkits/basemap/examples/ccsm_popgrid.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/ccsm_popgrid.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -20,10 +20,10 @@
 
 POP grids are used extensively locally in oceanographic and ice models.
 """
-import pylab as pl
 from matplotlib import rcParams
-from numpy import ma as MA
-import numpy as N
+from numpy import ma 
+import numpy as np
+import matplotlib.pyplot as plt
 from mpl_toolkits.basemap import Basemap, NetCDFFile
 
 # read in data from netCDF file.
@@ -36,17 +36,17 @@
 fpin.close()
 
 # make longitudes monotonically increasing.
-tlon = N.where(N.greater_equal(tlon,min(tlon[:,0])),tlon-360,tlon)
+tlon = np.where(np.greater_equal(tlon,min(tlon[:,0])),tlon-360,tlon)
 
 # stack grids side-by-side (in longitiudinal direction), so
 # any range of longitudes may be plotted on a world map.
-tlon = N.concatenate((tlon,tlon+360),1)
-tlat = N.concatenate((tlat,tlat),1)
-temp = MA.concatenate((temp,temp),1)
+tlon = np.concatenate((tlon,tlon+360),1)
+tlat = np.concatenate((tlat,tlat),1)
+temp = ma.concatenate((temp,temp),1)
 tlon = tlon-360.
 
-pl.figure(figsize=(6,8))
-pl.subplot(2,1,1)
+plt.figure(figsize=(6,8))
+plt.subplot(2,1,1)
 # subplot 1 just shows POP grid cells.
 map = Basemap(projection='merc', lat_ts=20, llcrnrlon=-180, \
       urcrnrlon=180, llcrnrlat=-84, urcrnrlat=84, resolution='c')
@@ -55,22 +55,22 @@
 map.fillcontinents(color='white')
 
 x, y = map(tlon,tlat)
-im = map.pcolor(x,y,MA.masked_array(N.zeros(temp.shape,'f'), temp.mask),\
-                shading='faceted',cmap=pl.cm.cool,vmin=0,vmax=0)
+im = map.pcolor(x,y,ma.masked_array(np.zeros(temp.shape,'f'), temp.mask),\
+                shading='faceted',cmap=plt.cm.cool,vmin=0,vmax=0)
 # disclaimer:  these are not really the grid cells because of the
 # way pcolor interprets the x and y args.
-pl.title('(A) CCSM POP Grid Cells')
+plt.title('(A) CCSM POP Grid Cells')
 
 # subplot 2 is a contour plot of surface temperature from the
 # CCSM ocean model.
-pl.subplot(2,1,2)
+plt.subplot(2,1,2)
 map.drawcoastlines()
 map.fillcontinents(color='white')
 
 CS1 = map.contourf(x,y,temp,15)
 CS2 = map.contour(x,y,temp,15,colors='black',linewidths=0.5)
-pl.title('(B) Surface Temp contours on POP Grid')
+plt.title('(B) Surface Temp contours on POP Grid')
 
-pl.show()
-#pl.savefig('ccsm_popgrid.ps')
+plt.show()
+#plt.savefig('ccsm_popgrid.ps')
 

Modified: trunk/toolkits/basemap/examples/fillstates.py
===================================================================
--- trunk/toolkits/basemap/examples/fillstates.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/fillstates.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,5 +1,5 @@
-import pylab as p
-import numpy
+import numpy as np
+import matplotlib.pyplot as plt
 from mpl_toolkits.basemap import Basemap as Basemap
 from matplotlib.colors import rgb2hex
 from matplotlib.patches import Polygon
@@ -68,7 +68,7 @@
 # choose a color for each state based on population density.
 colors={}
 statenames=[]
-cmap = p.cm.hot # use 'hot' colormap
+cmap = plt.cm.hot # use 'hot' colormap
 vmin = 0; vmax = 450 # set range.
 print m.states_info[0].keys()
 for shapedict in m.states_info:
@@ -79,10 +79,10 @@
         # calling colormap with value between 0 and 1 returns
         # rgba value.  Invert color range (hot colors are high
         # population), take sqrt root to spread out colors more.
-        colors[statename] = cmap(1.-p.sqrt((pop-vmin)/(vmax-vmin)))[:3]
+        colors[statename] = cmap(1.-np.sqrt((pop-vmin)/(vmax-vmin)))[:3]
     statenames.append(statename)
 # cycle through state names, color each one.
-ax = p.gca() # get current axes instance
+ax = plt.gca() # get current axes instance
 for nshape,seg in enumerate(m.states):
     # skip DC and Puerto Rico.
     if statenames[nshape] not in ['District of Columbia','Puerto Rico']:
@@ -90,7 +90,7 @@
         poly = Polygon(seg,facecolor=color,edgecolor=color)
         ax.add_patch(poly)
 # draw meridians and parallels.
-m.drawparallels(numpy.arange(25,65,20),labels=[1,0,0,0])
-m.drawmeridians(numpy.arange(-120,-40,20),labels=[0,0,0,1])
-p.title('Filling State Polygons by Population Density')
-p.show()
+m.drawparallels(np.arange(25,65,20),labels=[1,0,0,0])
+m.drawmeridians(np.arange(-120,-40,20),labels=[0,0,0,1])
+plt.title('Filling State Polygons by Population Density')
+plt.show()

Modified: trunk/toolkits/basemap/examples/garp.py
===================================================================
--- trunk/toolkits/basemap/examples/garp.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/garp.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,5 +1,6 @@
 from mpl_toolkits.basemap import Basemap
-from pylab import title, show, arange, pi
+import numpy as np
+import matplotlib.pyplot as plt
 
 # the shortest route from the center of the map
 # to any other point is a straight line in the azimuthal
@@ -30,11 +31,11 @@
 m.drawcoastlines(linewidth=0.5)
 m.fillcontinents(color='coral',lake_color='aqua')
 # 20 degree graticule.
-m.drawparallels(arange(-80,81,20))
-m.drawmeridians(arange(-180,180,20))
+m.drawparallels(np.arange(-80,81,20))
+m.drawmeridians(np.arange(-180,180,20))
 # draw a black dot at the center.
 xpt, ypt = m(lon_0, lat_0)
 m.plot([xpt],[ypt],'ko') 
 # draw the title.
-title('The World According to Garp in '+location)
-show()
+plt.title('The World According to Garp in '+location)
+plt.show()

Modified: trunk/toolkits/basemap/examples/hurrtracks.py
===================================================================
--- trunk/toolkits/basemap/examples/hurrtracks.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/hurrtracks.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,16 +1,17 @@
 """
 draw Atlantic Hurricane Tracks for storms that reached Cat 4 or 5.
 part of the track for which storm is cat 4 or 5 is shown red.
-ESRI shapefile data from http://www.nationalatlas.gov/atlasftp.html
+ESRI shapefile data from http://www.nationalatlas.gov/atlasftplt.html
 """
-import pylab as p
+import numpy as np
+import matplotlib.pyplot as plt
 from mpl_toolkits.basemap import Basemap as Basemap
-# Lambert Conformal Conic map.
+# Lambert Conformal Conic maplt.
 m = Basemap(llcrnrlon=-100.,llcrnrlat=0.,urcrnrlon=-20.,urcrnrlat=57.,
             projection='lcc',lat_1=20.,lat_2=40.,lon_0=-60.,
             resolution ='l',area_thresh=1000.)
 # create figure.
-fig=p.figure()
+fig=plt.figure()
 # read shapefile.
 shp_info = m.readshapefile('huralll020','hurrtracks',drawbounds=False)
 print shp_info
@@ -32,15 +33,15 @@
         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')
+            plt.plot(xx,yy,linewidth=1.5,color='r')
         elif cat in ['H1','H2','H3']:
-            p.plot(xx,yy,color='k')
+            plt.plot(xx,yy,color='k')
 # draw coastlines, meridians and parallels.
 m.drawcoastlines()
 m.drawcountries()
 m.drawmapboundary(fill_color='#99ffff')
 m.fillcontinents(color='#cc9966',lake_color='#99ffff')
-m.drawparallels(p.arange(10,70,20),labels=[1,1,0,0])
-m.drawmeridians(p.arange(-100,0,20),labels=[0,0,0,1])
-p.title('Atlantic Hurricane Tracks (Storms Reaching Category 4, 1851-2004)')
-p.show()
+m.drawparallels(np.arange(10,70,20),labels=[1,1,0,0])
+m.drawmeridians(np.arange(-100,0,20),labels=[0,0,0,1])
+plt.title('Atlantic Hurricane Tracks (Storms Reaching Category 4, 1851-2004)')
+plt.show()

Modified: trunk/toolkits/basemap/examples/panelplot.py
===================================================================
--- trunk/toolkits/basemap/examples/panelplot.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/panelplot.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,14 +1,16 @@
 from mpl_toolkits.basemap import Basemap
 from matplotlib import rcParams
 from matplotlib.ticker import MultipleLocator
-import pylab as P
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.mlab as mlab
 
 
 # read in data on lat/lon grid.
-hgt  = P.load('500hgtdata.gz')
-lons = P.load('500hgtlons.gz')
-lats = P.load('500hgtlats.gz')
-lons, lats = P.meshgrid(lons, lats)
+hgt  = mlab.load('500hgtdata.gz')
+lons = mlab.load('500hgtlons.gz')
+lats = mlab.load('500hgtlats.gz')
+lons, lats = np.meshgrid(lons, lats)
 
 # Example to show how to make multi-panel plots.
 
@@ -18,29 +20,29 @@
 rcParams['figure.subplot.wspace'] = 0.5 # more width between subplots
 
 # create new figure
-fig=P.figure()
+fig=plt.figure()
 # panel 1
 mnh = Basemap(lon_0=-105,boundinglat=20.,
              resolution='c',area_thresh=10000.,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)
+CS = mnh.contourf(xnh,ynh,hgt,15,cmap=plt.cm.Spectral)
 # colorbar on bottom.
 pos = ax.get_position()
 l, b, w, h = pos.bounds
-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
+cax = plt.axes([l, b-0.05, w, 0.025]) # setup colorbar axes
+plt.colorbar(cax=cax, orientation='horizontal',ticks=CS.levels[0::4]) # draw colorbar
+plt.axes(ax)  # make the original axes current again
 mnh.drawcoastlines(linewidth=0.5)
 delat = 30.
-circles = P.arange(0.,90.,delat).tolist()+\
-          P.arange(-delat,-90,-delat).tolist()
+circles = np.arange(0.,90.,delat).tolist()+\
+          np.arange(-delat,-90,-delat).tolist()
 mnh.drawparallels(circles,labels=[1,0,0,0])
 delon = 45.
-meridians = P.arange(0,360,delon)
+meridians = np.arange(0,360,delon)
 mnh.drawmeridians(meridians,labels=[1,0,0,1])
-P.title('NH 500 hPa Height (cm.Spectral)')
+plt.title('NH 500 hPa Height (cm.Spectral)')
 
 # panel 2
 msh = Basemap(lon_0=-105,boundinglat=-20.,
@@ -48,17 +50,17 @@
 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)
+CS = msh.contourf(xsh,ysh,hgt,15,cmap=plt.cm.Spectral)
 # colorbar on bottom.
 pos = ax.get_position()
 l, b, w, h = pos.bounds
-cax = P.axes([l, b-0.05, w, 0.025]) # setup colorbar axes
-P.colorbar(cax=cax,orientation='horizontal',ticks=MultipleLocator(320)) # draw colorbar
-P.axes(ax)  # make the original axes current again
+cax = plt.axes([l, b-0.05, w, 0.025]) # setup colorbar axes
+plt.colorbar(cax=cax,orientation='horizontal',ticks=MultipleLocator(320)) # draw colorbar
+plt.axes(ax)  # make the original axes current again
 msh.drawcoastlines(linewidth=0.5)
 msh.drawparallels(circles,labels=[1,0,0,0])
 msh.drawmeridians(meridians,labels=[1,0,0,1])
-P.title('SH 500 hPa Height (cm.Spectral)')
+plt.title('SH 500 hPa Height (cm.Spectral)')
 
 # 2-panel plot, oriented horizontally, colorbar on right.
 
@@ -68,33 +70,33 @@
 rcParams['figure.subplot.top'] = 0.85
 
 # panel 1
-fig = P.figure()
+fig = plt.figure()
 ax = fig.add_subplot(121)
 CS = mnh.contour(xnh,ynh,hgt,15,linewidths=0.5,colors='k')
-CS = mnh.contourf(xnh,ynh,hgt,15,cmap=P.cm.RdBu)
+CS = mnh.contourf(xnh,ynh,hgt,15,cmap=plt.cm.RdBu)
 # colorbar on right
 pos = ax.get_position()
 l, b, w, h = pos.bounds
-cax = P.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
-P.colorbar(cax=cax, ticks=MultipleLocator(160), format='%4i') # draw colorbar
-P.axes(ax)  # make the original axes current again
+cax = plt.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
+plt.colorbar(cax=cax, ticks=MultipleLocator(160), format='%4i') # draw colorbar
+plt.axes(ax)  # make the original axes current again
 mnh.drawcoastlines(linewidth=0.5)
 mnh.drawparallels(circles,labels=[1,0,0,0])
 mnh.drawmeridians(meridians,labels=[1,0,0,1])
-P.title('NH 500 hPa Height (cm.RdBu)')
+plt.title('NH 500 hPa Height (cm.RdBu)')
 
 # panel 2
 ax = fig.add_subplot(122)
 CS = msh.contour(xsh,ysh,hgt,15,linewidths=0.5,colors='k')
-CS = msh.contourf(xsh,ysh,hgt,15,cmap=P.cm.RdBu)
+CS = msh.contourf(xsh,ysh,hgt,15,cmap=plt.cm.RdBu)
 # colorbar on right.
 pos = ax.get_position()
 l, b, w, h = pos.bounds
-cax = P.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
-P.colorbar(cax=cax, ticks=MultipleLocator(160), format='%4i') # draw colorbar
-P.axes(ax)  # make the original axes current again
+cax = plt.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
+plt.colorbar(cax=cax, ticks=MultipleLocator(160), format='%4i') # draw colorbar
+plt.axes(ax)  # make the original axes current again
 msh.drawcoastlines(linewidth=0.5)
 msh.drawparallels(circles,labels=[1,0,0,0])
 msh.drawmeridians(meridians,labels=[1,0,0,1])
-P.title('SH 500 hPa Height (cm.RdBu)')
-P.show()
+plt.title('SH 500 hPa Height (cm.RdBu)')
+plt.show()

Modified: trunk/toolkits/basemap/examples/plot_tissot.py
===================================================================
--- trunk/toolkits/basemap/examples/plot_tissot.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/plot_tissot.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,4 +1,5 @@
-import pylab as p
+import numpy as np
+import matplotlib.pyplot as plt
 from mpl_toolkits.basemap import Basemap as Basemap
 from matplotlib.patches import Polygon
 
@@ -13,44 +14,44 @@
 # adapted from http://www.perrygeo.net/wordpress/?p=4
 
 # create new figure
-fig=p.figure()
+fig=plt.figure()
 m = Basemap(llcrnrlon=-180,llcrnrlat=-80,urcrnrlon=180,urcrnrlat=80,
             projection='cyl')
 shp_info = m.readshapefile('tissot','tissot',drawbounds=True)
-ax = p.gca()
+ax = plt.gca()
 for nshape,seg in enumerate(m.tissot):
     poly = Polygon(seg,facecolor='green',zorder=10)
     ax.add_patch(poly)
 # draw meridians and parallels.
-m.drawparallels(p.arange(-90,91,30),labels=[1,0,0,0])
-m.drawmeridians(p.arange(-180,180,60),labels=[0,0,0,1])
+m.drawparallels(np.arange(-90,91,30),labels=[1,0,0,0])
+m.drawmeridians(np.arange(-180,180,60),labels=[0,0,0,1])
 m.drawcoastlines()
 m.fillcontinents()
-p.title('Tissot Diagram - Cylindrical Equal Area')
+plt.title('Tissot Diagram - Cylindrical Equal Area')
 print 'plot Cylindrical Equidistant Equal Area Tissot diagram ...'
 
 # create new figure
-fig=p.figure()
+fig=plt.figure()
 m = Basemap(llcrnrlon=-180,llcrnrlat=-70,urcrnrlon=180,urcrnrlat=70,
             projection='merc',lat_ts=20)
 shp_info = m.readshapefile('tissot','tissot',drawbounds=True)
-ax = p.gca()
+ax = plt.gca()
 for nshape,seg in enumerate(m.tissot):
     poly = Polygon(seg,facecolor='green',zorder=10)
     ax.add_patch(poly)
 # draw meridians and parallels.
-m.drawparallels(p.arange(-90,91,30),labels=[1,0,0,0])
-m.drawmeridians(p.arange(-180,180,60),labels=[0,0,0,1])
+m.drawparallels(np.arange(-90,91,30),labels=[1,0,0,0])
+m.drawmeridians(np.arange(-180,180,60),labels=[0,0,0,1])
 m.drawcoastlines()
 m.fillcontinents()
-p.title('Tissot Diagram - Mercator Conformal')
+plt.title('Tissot Diagram - Mercator Conformal')
 print 'plot Mercator Conformal Tissot diagram ...'
 
 # create new figure
-fig=p.figure()
+fig=plt.figure()
 m = Basemap(lon_0=-60,lat_0=45,projection='ortho')
 shp_info = m.readshapefile('tissot','tissot',drawbounds=False)
-ax = p.gca()
+ax = plt.gca()
 for nshape,seg in enumerate(m.tissot):
     xx,yy = zip(*seg)
     if max(xx) < 1.e20 and max(yy) < 1.e20:
@@ -58,42 +59,42 @@
         ax.add_patch(poly)
 m.drawcoastlines()
 m.fillcontinents()
-m.drawparallels(p.arange(-90,91,30))
-m.drawmeridians(p.arange(-180,180,30))
-p.title('Tissot Diagram - Orthographic')
+m.drawparallels(np.arange(-90,91,30))
+m.drawmeridians(np.arange(-180,180,30))
+plt.title('Tissot Diagram - Orthographic')
 m.drawmapboundary()
-p.gca().set_frame_on(True)
+plt.gca().set_frame_on(True)
 print 'plot Orthographic Tissot diagram ...'
 
 # create new figure
-fig=p.figure()
+fig=plt.figure()
 m = Basemap(lon_0=270,lat_0=90,boundinglat=10,projection='npstere')
 shp_info = m.readshapefile('tissot','tissot',drawbounds=True)
-ax = p.gca()
+ax = plt.gca()
 for nshape,seg in enumerate(m.tissot):
     poly = Polygon(seg,facecolor='green',zorder=10)
     ax.add_patch(poly)
 # draw meridians and parallels.
-m.drawparallels(p.arange(-90,91,30),labels=[1,0,0,0])
-m.drawmeridians(p.arange(-180,180,30),labels=[0,0,0,1])
+m.drawparallels(np.arange(-90,91,30),labels=[1,0,0,0])
+m.drawmeridians(np.arange(-180,180,30),labels=[0,0,0,1])
 m.drawcoastlines()
 m.fillcontinents()
-p.title('Tissot Diagram - North Polar Stereographic Conformal')
+plt.title('Tissot Diagram - North Polar Stereographic Conformal')
 print 'plot North Polar Stereographic Conformal Tissot diagram ...'
 
 # create new figure
-fig=p.figure()
+fig=plt.figure()
 m = Basemap(lon_0=270,lat_0=90,boundinglat=10,projection='nplaea')
 shp_info = m.readshapefile('tissot','tissot',drawbounds=True)
-ax = p.gca()
+ax = plt.gca()
 for nshape,seg in enumerate(m.tissot):
     poly = Polygon(seg,facecolor='green',zorder=10)
     ax.add_patch(poly)
 # draw meridians and parallels.
-m.drawparallels(p.arange(-90,91,30),labels=[1,0,0,0])
-m.drawmeridians(p.arange(-180,180,30),labels=[0,0,0,1])
+m.drawparallels(np.arange(-90,91,30),labels=[1,0,0,0])
+m.drawmeridians(np.arange(-180,180,30),labels=[0,0,0,1])
 m.drawcoastlines()
 m.fillcontinents()
-p.title('Tissot Diagram - North Polar Lambert Azimuthal Equal Area')
+plt.title('Tissot Diagram - North Polar Lambert Azimuthal Equal Area')
 print 'plot North Polar Lambert Azimuthal Equal Area Tissot diagram ...'
-p.show()
+plt.show()

Modified: trunk/toolkits/basemap/examples/plotprecip.py
===================================================================
--- trunk/toolkits/basemap/examples/plotprecip.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/plotprecip.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,5 +1,7 @@
 from mpl_toolkits.basemap import Basemap, cm, NetCDFFile
-import pylab, copy
+import numpy as np
+import matplotlib.pyplot as plt
+import copy
 from matplotlib import rcParams
 
 # make tick labels smaller
@@ -29,20 +31,20 @@
             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()
+fig = plt.figure(figsize=(6,8.5))
+plt.subplot(211)
+ax = plt.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)
+parallels = np.arange(0.,90,delat)
 m.drawparallels(parallels,labels=[1,0,0,0],fontsize=10)
 # draw meridians
 delon = 10.
-meridians = pylab.arange(180.,360.,delon)
+meridians = np.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.
@@ -53,15 +55,15 @@
 # new axis for colorbar.
 pos = ax.get_position()
 l, b, w, h = pos.bounds
-cax = pylab.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
+cax = plt.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
 # draw colorbar.
-pylab.colorbar(cs, cax, format='%g', ticks=clevs, drawedges=False) 
-pylab.axes(ax)  # make the original axes current again
+plt.colorbar(cs, cax, format='%g', ticks=clevs, drawedges=False) 
+plt.axes(ax)  # make the original axes current again
 # plot title
-pylab.title(plottitle+'- contourf',fontsize=10)
+plt.title(plottitle+'- contourf',fontsize=10)
 
-pylab.subplot(212)
-ax = pylab.gca()
+plt.subplot(212)
+ax = plt.gca()
 # draw coastlines, state and country boundaries, edge of map.
 m.drawcoastlines()
 m.drawstates()
@@ -79,15 +81,15 @@
 # new axis for colorbar.
 pos = ax.get_position()
 l, b, w, h = pos.bounds
-cax = pylab.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
+cax = plt.axes([l+w+0.025, b, 0.025, h]) # setup colorbar axes
 # using im2, not im (hack to prevent colors from being
 # too compressed at the low end on the colorbar - results
 # from highly nonuniform colormap)
-pylab.colorbar(im2, cax, format='%d') # draw colorbar
-pylab.axes(ax)  # make the original axes current again
+plt.colorbar(im2, cax, format='%d') # draw colorbar
+plt.axes(ax)  # make the original axes current again
 # reset colorbar tick labels (hack to get
-cax.set_yticks(pylab.linspace(0,1,len(clevs)))
+cax.set_yticks(np.linspace(0,1,len(clevs)))
 cax.set_yticklabels(['%g' % clev for clev in clevs])
 # plot title
-pylab.title(plottitle+' - imshow',fontsize=10)
-pylab.show() # display onscreen.
+plt.title(plottitle+' - imshow',fontsize=10)
+plt.show() # display onscreen.

Modified: trunk/toolkits/basemap/examples/plotsst.py
===================================================================
--- trunk/toolkits/basemap/examples/plotsst.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/plotsst.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,5 +1,7 @@
 from mpl_toolkits.basemap import Basemap, NetCDFFile
-import pylab, numpy, sys
+import numpy as np
+import matplotlib.pyplot as plt
+import sys
 # read in sea-surface temperature and ice data
 # can be a local file, a URL for a remote opendap dataset,
 # or (if PyNIO is installed) a GRIB or HDF file.
@@ -25,29 +27,29 @@
 delat = lats[1]-lats[0]
 lons = (lons - 0.5*delon).tolist()
 lons.append(lons[-1]+delon)
-lons = numpy.array(lons,numpy.float64)
+lons = np.array(lons,np.float64)
 lats = (lats - 0.5*delat).tolist()
 lats.append(lats[-1]+delat)
-lats = numpy.array(lats,numpy.float64)
+lats = np.array(lats,np.float64)
 # create Basemap instance for mollweide projection.
 # coastlines not used, so resolution set to None to skip
 # continent processing (this speeds things up a bit)
 #m = Basemap(projection='ortho',lon_0=-110,lat_0=20,resolution=None)
 m = Basemap(projection='moll',lon_0=lons.mean(),lat_0=0,resolution=None)
 # compute map projection coordinates of grid.
-x, y = m(*numpy.meshgrid(lons, lats))
+x, y = m(*np.meshgrid(lons, lats))
 # draw line around map projection limb.
 # color background of map projection region.
 # missing values over land will show up this color.
 m.drawmapboundary(fill_color='0.3')
 # plot ice, then with pcolor
-im1 = m.pcolor(x,y,sst,shading='flat',cmap=pylab.cm.jet)
-im2 = m.pcolor(x,y,ice,shading='flat',cmap=pylab.cm.gist_gray)
+im1 = m.pcolor(x,y,sst,shading='flat',cmap=plt.cm.jet)
+im2 = m.pcolor(x,y,ice,shading='flat',cmap=plt.cm.gist_gray)
 # draw parallels and meridians, but don't bother labelling them.
-m.drawparallels(numpy.arange(-90.,120.,30.))
-m.drawmeridians(numpy.arange(0.,420.,60.))
+m.drawparallels(np.arange(-90.,120.,30.))
+m.drawmeridians(np.arange(0.,420.,60.))
 # draw horizontal colorbar.
-pylab.colorbar(im1,orientation='horizontal')
+plt.colorbar(im1,orientation='horizontal')
 # display the plot with a title.
-pylab.title('SST and ICE analysis for %s'%date)
-pylab.show()
+plt.title('SST and ICE analysis for %s'%date)
+plt.show()

Modified: trunk/toolkits/basemap/examples/pnganim.py
===================================================================
--- trunk/toolkits/basemap/examples/pnganim.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/pnganim.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -4,8 +4,9 @@
 
 # reads data over http - needs an active internet connection.
 
-import numpy
-import pylab
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.mlab as mlab
 from numpy import ma
 import datetime, sys, time, subprocess
 from mpl_toolkits.basemap import Basemap, shiftgrid, NetCDFFile, num2date
@@ -62,40 +63,40 @@
 vin = vdata[ntime1:ntime2+1,0,:,:] 
 datelabels = dates[ntime1:ntime2+1]
 # add cyclic points
-slp = numpy.zeros((slpin.shape[0],slpin.shape[1],slpin.shape[2]+1),numpy.float64)
+slp = np.zeros((slpin.shape[0],slpin.shape[1],slpin.shape[2]+1),np.float64)
 slp[:,:,0:-1] = slpin; slp[:,:,-1] = slpin[:,:,0]
-u = numpy.zeros((uin.shape[0],uin.shape[1],uin.shape[2]+1),numpy.float64)
+u = np.zeros((uin.shape[0],uin.shape[1],uin.shape[2]+1),np.float64)
 u[:,:,0:-1] = uin; u[:,:,-1] = uin[:,:,0]
-v = numpy.zeros((vin.shape[0],vin.shape[1],vin.shape[2]+1),numpy.float64)
+v = np.zeros((vin.shape[0],vin.shape[1],vin.shape[2]+1),np.float64)
 v[:,:,0:-1] = vin; v[:,:,-1] = vin[:,:,0]
-longitudes.append(360.); longitudes = numpy.array(longitudes)
+longitudes.append(360.); longitudes = np.array(longitudes)
 # make 2-d grid of lons, lats
-lons, lats = numpy.meshgrid(longitudes,latitudes)
+lons, lats = np.meshgrid(longitudes,latitudes)
 print 'min/max slp,u,v'
 print slp.min(), slp.max()
 print uin.min(), uin.max()
 print vin.min(), vin.max()
 print 'dates'
 print datelabels
-# make orthographic basemapylab.
+# make orthographic basemaplt.
 m = Basemap(resolution='c',projection='ortho',lat_0=60.,lon_0=-60.)
-pylab.ion() # interactive mode on.
+plt.ion() # interactive mode on.
 uin = udata[ntime1:ntime2+1,0,:,:] 
 vin = vdata[ntime1:ntime2+1,0,:,:] 
 datelabels = dates[ntime1:ntime2+1]
-# make orthographic basemapylab.
+# make orthographic basemaplt.
 m = Basemap(resolution='c',projection='ortho',lat_0=60.,lon_0=-60.)
-pylab.ion() # interactive mode on.
+plt.ion() # interactive mode on.
 # create figure, add axes (leaving room for colorbar on right)
-fig = pylab.figure()
+fig = plt.figure()
 ax = fig.add_axes([0.1,0.1,0.7,0.7])
 # set desired contour levels.
-clevs = numpy.arange(960,1061,5)
+clevs = np.arange(960,1061,5)
 # compute native x,y coordinates of grid.
 x, y = m(lons, lats)
 # define parallels and meridians to draw.
-parallels = numpy.arange(-80.,90,20.)
-meridians = numpy.arange(0.,360.,20.)
+parallels = np.arange(-80.,90,20.)
+meridians = np.arange(0.,360.,20.)
 # number of repeated frames at beginning and end is n1.
 nframe = 0; n1 = 10
 pos = ax.get_position()
@@ -104,42 +105,42 @@
 # parallels, meridians and title.
 for nt,date in enumerate(datelabels[1:]):
     CS = m.contour(x,y,slp[nt,:,:],clevs,linewidths=0.5,colors='k',animated=True)
-    CS = m.contourf(x,y,slp[nt,:,:],clevs,cmap=pylab.cm.RdBu_r,animated=True)
+    CS = m.contourf(x,y,slp[nt,:,:],clevs,cmap=plt.cm.RdBu_r,animated=True)
     # plot wind vectors on lat/lon grid.
     # rotate wind vectors to map projection coordinates.
     #urot,vrot = m.rotate_vector(u[nt,:,:],v[nt,:,:],lons,lats)
-    # plot wind vectors over mapylab.
+    # plot wind vectors over maplt.
     #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 upylab.
+    # in longitude).  Otherwise, interpolation is messed uplt.
     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 mapylab.
+    # plot wind vectors over maplt.
     Q = m.quiver(xx,yy,urot,vrot,scale=500)
     # make quiver key.
-    qk = pylab.quiverkey(Q, 0.1, 0.1, 20, '20 m/s', labelpos='W')
+    qk = plt.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)
-    pylab.title('SLP and Wind Vectors '+date)
+    plt.title('SLP and Wind Vectors '+date)
     if nt == 0: # plot colorbar on a separate axes (only for first frame)
-        cax = pylab.axes([l+w-0.05, b, 0.03, h]) # setup colorbar axes
+        cax = plt.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')
-        pylab.axes(ax) # reset current axes
-    pylab.draw() # draw the plot
+        plt.axes(ax) # reset current axes
+    plt.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):
-           pylab.savefig('anim%03i'%nframe+'.png')
+           plt.savefig('anim%03i'%nframe+'.png')
            nframe = nframe + 1
     else:
-       pylab.savefig('anim%03i'%nframe+'.png')
+       plt.savefig('anim%03i'%nframe+'.png')
        nframe = nframe + 1
     ax.clear() # clear the axes for the next plot.
 

Modified: trunk/toolkits/basemap/examples/polarmaps.py
===================================================================
--- trunk/toolkits/basemap/examples/polarmaps.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/polarmaps.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -6,17 +6,18 @@
 # illustrates special-case polar-centric projections.
 
 from mpl_toolkits.basemap import Basemap
-from pylab import title, colorbar, show, axes, cm, load, arange, \
-                  figure, ravel, meshgrid
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.mlab as mlab
 
 # read in topo data (on a regular lat/lon grid)
 # longitudes go from 20 to 380.
-etopo = load('etopo20data.gz')
-lons = load('etopo20lons.gz')
-lats = load('etopo20lats.gz')
+etopo = mlab.load('etopo20data.gz')
+lons = mlab.load('etopo20lons.gz')
+lats = mlab.load('etopo20lats.gz')
 
 print 'min/max etopo20 data:'
-print min(ravel(etopo)),max(ravel(etopo))
+print etopo.min(),etopo.max()
 
 # these are the 4 polar projections
 projs = ['laea','stere','aeqd','ortho'] # short names
@@ -36,7 +37,7 @@
         lat_0 = 90.
         bounding_lat = 20.
     # loop over projections, one for each panel of the figure.
-    fig = figure(figsize=(8,8))
+    fig = plt.figure(figsize=(8,8))
     npanel = 0
     for proj,projname in zip(projs,projnames):
         npanel = npanel + 1
@@ -53,18 +54,18 @@
            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))
+        x,y = m(*np.meshgrid(lons,lats))
         ax = fig.add_subplot(2,2,npanel)
         # make filled contour plot.
-        cs = m.contourf(x,y,etopo,20,cmap=cm.jet)
+        cs = m.contourf(x,y,etopo,20,cmap=plt.cm.jet)
         # draw coastlines.
         m.drawcoastlines()
         # draw parallels and meridians.
-        m.drawparallels(arange(-80.,90,20.))
-        m.drawmeridians(arange(0.,360.,60.))
+        m.drawparallels(np.arange(-80.,90,20.))
+        m.drawmeridians(np.arange(0.,360.,60.))
         # draw boundary around map region.
         m.drawmapboundary()
         # draw title.
-        title(hem+' Polar '+projname,y=1.05,fontsize=12)
+        plt.title(hem+' Polar '+projname,y=1.05,fontsize=12)
         print 'plotting '+hem+' Polar '+projname+' basemap ...'
-show()
+plt.show()

Modified: trunk/toolkits/basemap/examples/setwh.py
===================================================================
--- trunk/toolkits/basemap/examples/setwh.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/setwh.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -2,7 +2,8 @@
 # to the Basemap constructor.
 
 from mpl_toolkits.basemap import Basemap
-from pylab import arange, show, title, figure
+import numpy as np
+import matplotlib.pyplot as plt
 
 # setup projection parameters
 lat_0 = 40.
@@ -10,14 +11,14 @@
 width = 6000000.
 height = 2.*width/3.
 delat = 25.
-circles = arange(0.,90.+delat,delat).tolist()+\
-          arange(-delat,-90.-delat,-delat).tolist()
+circles = np.arange(0.,90.+delat,delat).tolist()+\
+          np.arange(-delat,-90.-delat,-delat).tolist()
 delon = 30.
-meridians = arange(10.,360.,delon)
+meridians = np.arange(10.,360.,delon)
 npanel = 0
 # plots of the US.
 projs = ['lcc','aeqd','aea','laea','eqdc','stere']
-fig = figure(figsize=(7,7))
+fig = plt.figure(figsize=(7,7))
 for proj in projs:
     m = Basemap(width=width,height=height,
                 resolution='c',projection=proj,\
@@ -30,6 +31,6 @@
     m.drawstates()
     m.drawparallels(circles)
     m.drawmeridians(meridians)
-    title('proj = '+proj+' centered on %sW, %sN' % (lon_0,lat_0),fontsize=10)
+    plt.title('proj = '+proj+' centered on %sW, %sN' % (lon_0,lat_0),fontsize=10)
 
-show()
+plt.show()

Modified: trunk/toolkits/basemap/examples/show_colormaps.py
===================================================================
--- trunk/toolkits/basemap/examples/show_colormaps.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/show_colormaps.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -1,16 +1,17 @@
-import numpy, pylab
+import numpy as np
+import matplotlib.pyplot as plt
 from mpl_toolkits.basemap import cm
-a=numpy.outer(numpy.arange(0,1,0.01),numpy.ones(10))
-pylab.figure(figsize=(10,7))
-pylab.subplots_adjust(top=0.8,bottom=0.05,left=0.01,right=0.99)
+a=np.outer(np.arange(0,1,0.01),np.ones(10))
+plt.figure(figsize=(10,7))
+plt.subplots_adjust(top=0.8,bottom=0.05,left=0.01,right=0.99)
 maps=[m for m in cm.datad.keys() if not m.endswith("_r")]
 maps.sort()
 l=len(maps)+1
 i=1
 for m in maps:
-    pylab.subplot(1,l,i)
-    pylab.axis("off")
-    pylab.imshow(a,aspect='auto',cmap=cm.__dict__[m],origin="lower")
-    pylab.title(m,rotation=90,fontsize=10)
+    plt.subplot(1,l,i)
+    plt.axis("off")
+    plt.imshow(a,aspect='auto',cmap=cm.__dict__[m],origin="lower")
+    plt.title(m,rotation=90,fontsize=10)
     i=i+1
-pylab.show()
+plt.show()

Modified: trunk/toolkits/basemap/examples/testgdal.py
===================================================================
--- trunk/toolkits/basemap/examples/testgdal.py	2008-05-20 11:52:12 UTC (rev 5196)
+++ trunk/toolkits/basemap/examples/testgdal.py	2008-05-20 12:22:09 UTC (rev 5197)
@@ -3,13 +3,14 @@
 gdal (http://gdal.maptools.org).
 
 Data files must be downloaded manually from USGS:
-http://edcftp.cr.usgs.gov/pub/data/DEM/250/D/denver-w.gz
-http://edcftp.cr.usgs.gov/pub/data/nationalatlas/countyp020.tar.gz
+http://edcftplt.cr.usgs.gov/pub/data/DEM/250/D/denver-w.gz
+http://edcftplt.cr.usgs.gov/pub/data/nationalatlas/countyp020.tar.gz
 """
 import gdal
 from mpl_toolkits.basemap import Basemap
 from gdalconst import *
-import pylab as p
+import numpy as np
+import matplotlib.pyplot as plt
 
 # download from 
 # http://edcftp.cr.usgs.gov/pub/data/DEM/250/D/denver-w.gz
@@ -26,17 +27,17 @@
 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()
+fig = plt.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
+cax = plt.axes([0.875, 0.1, 0.05, 0.75]) # setup colorbar axes.
+plt.colorbar(cax=cax) # draw colorbar
+plt.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')
+m.drawmeridians(np.linspace(llcrnrlon+0.1,urcrnrlon-0.1,5),labels=[0,0,0,1],fmt='%4.2f')
+m.drawparallels(np.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)
@@ -46,6 +47,6 @@
 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()
+    plt.text(xx+0.01,yy+0.01,name)
+plt.title(gd.GetDescription()+' USGS DEM with county boundaries')
+plt.show()


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