The matplotlib function contourf() should do what you want. Have a look at
this example:
http://matplotlib.org/examples/pylab_examples/contourf_demo.html
I apologize if it is not what you're looking for. I haven't read your whole
script, because it is not *a minimal working example* (http://www.sscce.org/)
and I'm not going to do your homework. If, after having tried contourf, you
find a bug or an explained feature, please do post again.
2014-03-15 19:06 GMT+01:00 sweep <reminderzs...@gmail.com>:
> Hi, im trying to create a heatmap/colourmap/contour style plot similar to
> http://www.idlcoyote.com/cg_tips/outcontourbar.png but I cant seem to get
> it
> working correctly. The code takes a number of parameters on the command
> line
> because it is passed by an external PHP script. Essentially its a list of
> lat/lon/values which I want to interpolate and plot but I cant get anything
> like the image above, I cant get the vmin/vmax to work for the colorbar and
> I dont know why the whole plot is squared off rather than fading to white
> if
> you see what I mean
>
> import os
> import tempfile
> import math
> os.environ['MPLCONFIGDIR'] = tempfile.mkdtemp()
> import argparse
> import numpy as np
> import matplotlib
> matplotlib.use('Agg')
> import matplotlib.pyplot as plt
> import scipy.interpolate
>
> width = 800
> height = 600
>
> lat_min = []
> lon_min = []
> lat_max = []
> lon_max = []
>
> # assumes lat is y, lon is x, and image is 800x600
> def latToXY(lat):
> global width, height, lat_min, lat_max
> y = ((lat - lat_min) / (lat_max - lat_min)) * height
> #print y
> return y
>
> def lonToXY(lon):
> global width, height, lon_min, lon_max
> lon = math.fabs(lon)
> x = ((lon - lon_min) / (lon_max - lon_min)) * width
> #print x
> return x
>
> def scipy_idw(x, y, z, xi, yi):
> #interp = scipy.interpolate.Rbf(x, y, z, function='linear')
> interp = scipy.interpolate.Rbf(x, y, z)
> return interp(xi, yi)
>
> def plot(x,y,z,grid,legend_min,legend_max,filename):
> plt.figure()
> fig = plt.imshow(grid, vmin=legend_min, vmax=legend_max, extent=[0,
> 1024, 0, 768])
> fig.axes.get_xaxis().set_visible(False) # hide axis labels
> fig.axes.get_yaxis().set_visible(False)
> #plt.hold(True)
> plt.scatter(x,y,c=z)
> plt.colorbar()
> plt.savefig(filename)
>
> # grab all floats from command line
> parser = argparse.ArgumentParser()
> parser.add_argument('--l1', type=str)
> parser.add_argument('--l2', type=str)
> parser.add_argument('--l3', type=str)
> parser.add_argument('--min', type=str)
> parser.add_argument('--max', type=str)
> parser.add_argument('--filename', type=str)
> args = parser.parse_args()
>
> # create a list by splitting at the comma
> l1_list = args.l1.split(',') # ['1','2','3','4']
> l2_list = args.l2.split(',')
> l3_list = args.l3.split(',')
>
> legend_min = float(args.min)
> legend_max = float(args.max)
> filename = args.filename
>
> # convert string list to list of floats
> for i in range(len(l1_list)):
> l1_list[i] = float(l1_list[i])
> l2_list[i] = float(l2_list[i])
> l3_list[i] = float(l3_list[i])
>
> lat_min = min( math.fabs(yy) for yy in l2_list )
> lat_max = max( math.fabs(yy) for yy in l2_list )
> lon_min = min( math.fabs(xx) for xx in l1_list )
> lon_max = max( math.fabs(xx) for xx in l1_list )
>
> # convert list of floats to x,y
> for i in range(len(l1_list)):
> l1_list[i] = lonToXY(l1_list[i])
> l2_list[i] = latToXY(l2_list[i])
>
> # convert list to numpy array
> x = np.array(l1_list)
> y = np.array(l2_list)
> z = np.array(l3_list)
>
> #print x
> #print y
> #print z
> nx, ny = 50, 50
> xi, yi = np.linspace(x.min(), x.max(), nx), np.linspace(y.min(), y.max(),
> ny)
> xi, yi = np.meshgrid(xi, yi)
> xi, yi = xi.flatten(), yi.flatten()
>
> grid2 = scipy_idw(x,y,z,xi,yi)
> grid2 = grid2.reshape((ny, nx))
>
> plot(x,y,z,grid2,legend_min,legend_max,filename)
>
> I call the script with the following parameters:
>
> plot.py --l1=-1.8791363,-1.8786206,-1.8796862,-1.878171
> --l2=57.458459,57.458153,57.458495,57.458036 --l3=42.3,37.8,43.5,47.7
> --min=0 --max=100 --filename=/tmp/plot.png
>
>
>
> Any help is greatly appreciated
>
> Thanks
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/matplolib-imshow-contour-heatmap-tp43078.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
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"Graph Databases" is the definitive new guide to graph databases and their
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this first edition is now available. Download your free book today!
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