SF.net SVN: matplotlib: [4559] trunk/py4science/examples/skel

[<js...@us...>]

Revision: 4559
          http://matplotlib.svn.sourceforge.net/matplotlib/?rev=4559&view=rev
Author:   jswhit
Date:     2007-12-03 06:41:11 -0800 (Mon, 03 Dec 2007)

Log Message:
-----------
cleanup basemap examples.

Modified Paths:
--------------
    trunk/py4science/examples/skel/basemap1_skel.py
    trunk/py4science/examples/skel/basemap2_skel.py
    trunk/py4science/examples/skel/basemap3_skel.py
    trunk/py4science/examples/skel/basemap4_skel.py
    trunk/py4science/examples/skel/basemap5_skel.py

Modified: trunk/py4science/examples/skel/basemap1_skel.py
===================================================================
--- trunk/py4science/examples/skel/basemap1_skel.py	2007-12-03 13:27:16 UTC (rev 4558)
+++ trunk/py4science/examples/skel/basemap1_skel.py	2007-12-03 14:41:11 UTC (rev 4559)
@@ -1,8 +1,5 @@
 import pylab, numpy
 from matplotlib.toolkits.basemap import Basemap
-
-# create figure.
-fig = pylab.figure()
 # create map by specifying lat/lon values at corners.
 projection = 'lcc' # map projection 
 resolution = XX # resolution of boundaries ('c','l','i',or 'h')

Modified: trunk/py4science/examples/skel/basemap2_skel.py
===================================================================
--- trunk/py4science/examples/skel/basemap2_skel.py	2007-12-03 13:27:16 UTC (rev 4558)
+++ trunk/py4science/examples/skel/basemap2_skel.py	2007-12-03 14:41:11 UTC (rev 4559)
@@ -1,8 +1,5 @@
 import pylab, numpy
 from matplotlib.toolkits.basemap import Basemap, supported_projections
-
-# create figure.
-fig = pylab.figure()
 # create map by specifying width and height in km.
 projection = XX # map projection  ('lcc','stere','laea','aea' etc)
                 # 'print supported_projections' gives a list

Modified: trunk/py4science/examples/skel/basemap3_skel.py
===================================================================
--- trunk/py4science/examples/skel/basemap3_skel.py	2007-12-03 13:27:16 UTC (rev 4558)
+++ trunk/py4science/examples/skel/basemap3_skel.py	2007-12-03 14:41:11 UTC (rev 4559)
@@ -1,27 +1,15 @@
 import pylab, numpy
 from matplotlib.toolkits.basemap import Basemap
-
-# create figure.
-# background color will be used for 'wet' areas.
-fig = pylab.figure()
 # create map by specifying width and height in km.
-resolution = 'l'
-lon_0 = -50
-lat_0 = 60
-projection = 'lcc'
-width = 12000000
-height = 0.75*width
-m = Basemap(lon_0=lon_0,lat_0=lat_0,\
-            width=width,height=height,\
+resolution = 'l'; projection='lcc'
+lon_0 = -50; lat_0 = 60.
+width = 12000000; height = 0.75*width
+m = Basemap(lon_0=lon_0,lat_0=lat_0,width=width,height=height,\
             resolution=resolution,projection=projection)
 # lat/lon and name of location 1.
-lat1 = XX
-lon1 = XX
-name1 = XX
+lat1 = XX; lon1 = XX; name = XX
 # ditto for location 2.
-lat2 = XX
-lon2 = XX
-name2 = XX
+lat2 = XX; lon2 = XX; name2 = XX
 # convert these points to map projection coordinates
 # (using __call__ method of Basemap instance)
 x1, y1 = m(lon1, lat1)

Modified: trunk/py4science/examples/skel/basemap4_skel.py
===================================================================
--- trunk/py4science/examples/skel/basemap4_skel.py	2007-12-03 13:27:16 UTC (rev 4558)
+++ trunk/py4science/examples/skel/basemap4_skel.py	2007-12-03 14:41:11 UTC (rev 4559)
@@ -1,16 +1,10 @@
 import pylab, numpy
 from matplotlib.toolkits.basemap import Basemap
-# create figure.
-fig = pylab.figure()
 # create map by specifying width and height in km.
-resolution = 'l'
-lon_0 = -50
-lat_0 = 60
-projection = 'lcc'
-width = 12000000
-height = 0.75*width
-m = Basemap(lon_0=lon_0,lat_0=lat_0,\
-            width=width,height=height,\
+resolution = 'l'; projection='lcc'
+lon_0 = -50; lat_0 = 60.
+width = 12000000; height = 0.75*width
+m = Basemap(lon_0=lon_0,lat_0=lat_0,width=width,height=height,\
             resolution=resolution,projection=projection)
 m.drawcoastlines(linewidth=0.5)
 m.drawmapboundary(fill_color='aqua')

Modified: trunk/py4science/examples/skel/basemap5_skel.py
===================================================================
--- trunk/py4science/examples/skel/basemap5_skel.py	2007-12-03 13:27:16 UTC (rev 4558)
+++ trunk/py4science/examples/skel/basemap5_skel.py	2007-12-03 14:41:11 UTC (rev 4559)
@@ -1,16 +1,13 @@
 from matplotlib.toolkits.basemap import Basemap, NetCDFFile, cm
 import pylab, numpy
-
 # read in netCDF sea-surface temperature data
 # can be a local file, a URL for a remote opendap dataset,
 # or (if PyNIO is installed) a GRIB or HDF file.
+# See http://nomads.ncdc.noaa.gov/ for some NOAA OPenDAP datasets.
 ncfile = NetCDFFile('data/sst.nc')
 sst = ncfile.variables['analysed_sst'][:]
 lats = ncfile.variables['lat'][:]
 lons = ncfile.variables['lon'][:]
-
-print sst.shape, sst.min(), sst.max()
-
 # Basemap comes with extra colormaps from Generic Mapping Tools
 # (imported as cm, pylab colormaps in pylab.cm)
 cmap = XX
@@ -23,6 +20,8 @@
 x, y = m(*numpy.meshgrid(lons, lats))
 # plot with pcolor
 im = m.pcolormesh(x,y,sst,shading='flat',cmap=cmap)
+# or try 100 filled contours.
+#CS = m.contourf(x,y,sst,100,cmap=cmap)
 # draw parallels and meridians, but don't bother labelling them.
 m.drawparallels(numpy.arange(-90.,120.,30.))
 m.drawmeridians(numpy.arange(0.,420.,60.))


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