Re: [Matplotlib-users] plotting points/locations from data file

[G J. <gle...@gm...>]

As you can see from the error message, it's trying to convert "39.4670," to
a float and complaining that this is not a valid value (because of the
comma. The examples I suggested were for your original space delimited data.
For comma delimited data you'll want to remove the delimiter argument to
csv2rec (or explicitly set delimiter=',' if you prefer). If you want to use
loadtxt, you can set delimiter=','
Again, read the doc strings to see what these functions are expecting by
default.


On Tue, Apr 19, 2011 at 5:26 PM, Michael Rawlins <raw...@ya...>wrote:

>
> The first example produced no plotted symbols but no errors on execution.
> The second example produced this:
>
> Plotting, please wait...maybe more than 10 seconds
>
> Traceback (most recent call last):
>   File "testNew.py", line 137, in <module>
>     data = np.loadtxt('file2.txt')
>   File "/usr/lib/python2.6/dist-packages/numpy/lib/io.py", line 489, in
> loadtxt
>     X.append(tuple([conv(val) for (conv, val) in zip(converters, vals)]))
> ValueError: invalid literal for float(): 39.4670,
>
>
> Grrrr......
>
> My code follows.  I believe this is standard python and matplotlib.  Should
> produce a map of Northeast US.  Perhaps someone could get this working with
> a few example points:
>
>
> 39.4670, -76.1670
> 46.4000, -74.7670
> 45.3830, -75.7170
> 43.6170, -79.3830
> 45.5170, -73.4170
> 45.6170, -74.4170
> 43.8330, -77.1500
> 43.9500, -78.1670
> 43.2500, -79.2170
> 43.8330, -66.0830
>
>
> #!/usr/bin/env python
> # v0.5 19 June 2010
> # General purpose plotter of 2-D gridded data from NetCDF files,
> # plotted with map boundaries.
> # NetCDF file should have data in either 2-D, 3-D or 4-D arrays.
> # Works with the netCDF files in the tutorial, and also the
> # files available for download at:
> # http://www.cdc.noaa.gov/cdc/data.ncep.reanalysis.html
> # Adapted from the basemap example plotmap_pcolor.py,
> # Some of the variable names from that example are retained.
> #
> # Uses basemap's pcolor function.  Pcolor accepts arrays
> # of the longitude and latitude  points of the vertices on the pixels,
> # as well as an array with the numerical value in the pixel.
>
> verbose=0 #verbose=2 says a bit more
>
>
> import sys,getopt
>
> from mpl_toolkits.basemap import Basemap, shiftgrid, cm
> #from netCDF3 import Dataset as NetCDFFile
> from mpl_toolkits.basemap import  NetCDFFile
> from pylab import *
> #from matplotlib.mlab import csv2rec
>
> alloptions, otherargs= getopt.getopt(sys.argv[1:],'ro:p:X:Y:v:t:l:u:n:') #
> note the : after o and p
> proj='lam'
> #plotfile=None
> #plotfile='testmap2.png'
> usejetrev=False
> colorbounds=[None,None]
> extratext=""
> xvar=None
> yvar=None
> thevar=None
>
> therec=None
> thelev=None
> cbot=None
> ctop=None
> startlon=-180 #default assumption for starting longitude
> for theopt,thearg in alloptions:
>     print theopt,thearg
>     if theopt=='-o': # -o needs filename after it, which is now thearg
>         plotfile=thearg
>     elif theopt=='-p':
>         proj=thearg
>     elif theopt=='-X':
>         xvar=thearg
>     elif theopt=='-Y':
>         yvar=thearg
>     elif theopt=='-v':
>         thevar=thearg
>     elif theopt=='-t':
>         thetitle=thearg
>     elif theopt=='-l':
>         cbot=thearg
>     elif theopt=='-u':
>         ctop=thearg
>     elif theopt=='-n':
>         therec=thearg
>     elif theopt=='-m':
>         thelev=thearg
>     elif theopt=='-r':
>         usejetrev=True
>     else: #something went wrong
>         print "hmm, what are these??? ", theopt, thearg
>         sys.exit()
>
> print "\nPlotting, please wait...maybe more than 10 seconds"
> if proj=='lam': #Lambert Conformal
>     m =
> Basemap(llcrnrlon=-80.6,llcrnrlat=38.4,urcrnrlon=-66.0,urcrnrlat=47.7,\
>             resolution='l',area_thresh=1000.,projection='lcc',\
>             lat_1=65.,lon_0=-73.3)
>     xtxt=200000. #offset for text
>     ytxt=200000.
>     parallels = arange(38.,48.,4.)
>     meridians = arange(-80.,-68.,4.)
> else: #cylindrical is default
> #    m =
> Basemap(llcrnrlon=-180.,llcrnrlat=-90,urcrnrlon=180.,urcrnrlat=90.,\
> #            resolution='c',area_thresh=10000.,projection='cyl')
>     m =
> Basemap(llcrnrlon=startlon,llcrnrlat=-90,urcrnrlon=startlon+360.,urcrnrlat=90.,\
>             resolution='c',area_thresh=10000.,projection='cyl')
>     xtxt=1.
>     ytxt=0.
>     parallels = arange(-90.,90.,30.)
>     if startlon==-180:
>         meridians = arange(-180.,180.,60.)
>     else:
>         meridians = arange(0.,360.,60.)
>
> if verbose>1: print m.__doc__
> xsize = rcParams['figure.figsize'][0]
> fig=figure(figsize=(xsize,m.aspect*xsize))
> #ax = fig.add_axes([0.08,0.1,0.7,0.7],axisbg='white')
> ax = fig.add_axes([0.06,0.00,0.8,1.0],axisbg='white')
> # make a pcolor plot.
> #x, y = m(lons, lats)
> #p = m.pcolor(x,y,maskdat,shading='flat',cmap=cmap)
> #clim(*colorbounds)
>
> # axes units units are left, bottom, width, height
> #cax = axes([0.85, 0.1, 0.05, 0.7])  #  colorbar axes for map w/ no
> graticule
> cax = axes([0.88, 0.1, 0.06, 0.81])  #  colorbar axes for map w/ graticule
>
> axes(ax)  # make the original axes current again
>
> #########    Plot symbol at station locations    #################
>
> #lines=open('file2.txt','r').readlines()
>
> #(lats,lons)=([],[])
> #for line in lines:
> #    (lat,lon)=line.strip().split(',')
> #    lats.append(float(lat))
> #    lons.append(float(lon))
>
> #for i in range(len(lons)):
> #    plt.plot(lats,lons,'*')
>
> #plt.plot(lons,lats,'*')
>
> #data = csv2rec('file2.txt',delimiter=',')
>
> #plot(data[:,0],data[:,1],'o')
>
> #data = csv2rec('file2.txt',delimiter=' ',names=['lat','lon'])
>
> #plot(data['lat'],data['lon'],'o')
>
> data = np.loadtxt('file2.txt')
>
> plot(data[:,0],data[:,1],'o')
>
> xpt,ypt = m(-75.0,43.0)
> text(xpt,ypt,'*')
>
>
> # draw coastlines and political boundaries.
> m.drawcoastlines()
> m.drawcountries()
> m.drawstates()
> # draw parallels and meridians.
> # label on left, right and bottom of map.
> m.drawparallels(parallels,labels=[1,0,0,0])
> m.drawmeridians(meridians,labels=[1,1,0,1])
>
> #if plotfile:
> #    savefig(plotfile, dpi=72, facecolor='w', bbox_inches='tight',
> edgecolor='w', orientation='portrait')
> #else:
> #    show()
>
> #plt.savefig('map.png')
> plt.savefig('map.eps')
> #  comment show to mass produce
>
>
>
>
> --- On *Tue, 4/19/11, G Jones <gle...@gm...>* wrote:
>
>
> From: G Jones <gle...@gm...>
>
> Subject: Re: [Matplotlib-users] plotting points/locations from data file
> To: "Michael Rawlins" <raw...@ya...>
> Cc: "Ian Bell" <ib...@pu...>, Mat...@li...
> Date: Tuesday, April 19, 2011, 8:12 PM
>
>
> No need for a header, but I guess my example was a little too simple. You
> could do:
> data = csv2rec(filename,delimiter=' ',names=['lat','lon'])
> plot(data['lat'],data['lon'],'o')
>
> or you could do
> data = np.loadtxt(filename)
> plot(data[:,0],data[:,1],'o')
>
> In general, I strongly recommend developing with ipython --pylab. That way
> all the documentation is at your fingertips using the ? and ?? notation.
>
>