# [SciPy-User] conotur plot

Sebastian sebas0@gmail....
Wed Mar 28 15:22:45 CDT 2012

```Dear Folks,

I'm using the python bin of epd-7.0-2-rh5-x86_64
on a Linux 2.6.38.8-32.fc15.x86_64 #1 SMP Mon Jun 13 19:49:05 UTC 2011
x86_64 x86_64 x86_64 GNU/Linux
system.

I'm trying to make a contour plot of astronomical data binning data in a 2D
grid.
When I bin the data in square bins (eg 60 x 60), the contour plot works
fine.
But if I change the binning to (10 x 60), by changing the following line in
the code, from:

"resolucion_x1=(xc1.max()-xc1.min())/(nceldas)"
to
"resolucion_x1=3* (xc1.max()-xc1.min())/(nceldas)"

then I produce three arrays  (x1,y1,z1)
with size 20,60,1200 instead of 60,60,3600
BUT when I try plot a contour map with pylab.contour I get the follow error:

"
TypeError: Length of x must be number of columns in z,
and length of y must be number of rows."
and I think this occurs because:

In [788]: shape(x1),shape(y1),shape(z1)
Out[788]: ((20,), (60,), (20, 60))

Any idea as to how to solve this so I can use rectangular binning
with the code?

I use the following code:

import numpy as N
from subprocess import *
import pyfits
import matplotlib
import pylab
import pickle
from itertools import izip

xc1=N.array(magj-magk)
yc1=N.array(magk)
print ("xc1 max",xc1.max())
print ("yc1 max",yc1.max())
print ("xc1 min",xc1.min())
print ("yc1 min",yc1.min())
print ("is nonnum",N.isnan(xc1).any())
nceldas=60.0
resolucion_x1=(xc1.max()-xc1.min())/(nceldas)
resolucion_y1=(yc1.max()-yc1.min())/(nceldas)
minix1=xc1.min();miniy1=yc1.min()
x1=N.arange(xc1.min(),xc1.max(),resolucion_x1,dtype=xc1.dtype)
y1=N.arange(yc1.min(),yc1.max(),resolucion_y1,dtype=yc1.dtype)
z1=N.zeros((x1.shape[0],y1.shape[0]),yc1.dtype)
print "x1 size" , x1.size
print "y1 size" , y1.size
print "z1 size" , z1.size

xc1=(xc1-xc1.min())/resolucion_x1
yc1=(yc1-yc1.min())/resolucion_y1
print xc1.max(), xc1.min(),yc1.max(),yc1.min()
for i,j in zip(xc1,yc1):
try: z1[int(j),int(i)]+=1.0
except: pass

figure=pylab.figure()
pylab.plot(magj-magk,magk,'b.',ms=2.3,alpha=0.70)
pylab.ylim(pylab.ylim()[::-1])
pylab.contour(x1,y1,z1*100/len(magk),30,alpha=1,linewidths=5)
pylab.show()

confused...
- Sebastian
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