The pylab scatter plot appears to be transposed
I play with different interpolation methods - and especially love the varieties shown in the YouTube video https://www.youtube.com/watch?v=_cJLVhdj0j4
However, the scatter module displays the points in the wrong place. I moved them below (example 5) to get it working, but that doesn't work unless the area of interest is focused on the origin (Test_Rbf).
Am I misunderstanding something fundamental, or is this a problem in the pylab scatter module?
# Example 5
#
# https://www.youtube.com/watch?v=_cJLVhdj0j4
import numpy as np
from scipy import interpolate
import pylab as py
def func(x,y):
return (x+y)*np.cos(-5.0*x + 4.0*y)
x = np.random.uniform(-1.0, 1.0,size=50)
y = np.random.uniform(-1.0, 1.0,size=50)
fvals = func(x,y)
newfunc = interpolate.Rbf(x, y, fvals, function='multiquadric')
xnew, ynew = np.mgrid[-1:1:100j, -1:1:100j]
fnew = newfunc(xnew, ynew)
true = func(xnew, ynew)
py.figure()
py.clf()
py.imshow( fnew, extent=[-1,1,-1,1], cmap=py.cm.jet)
# py.scatter( x, y, 30, fvals, cmap=py.cm.jet)
py.scatter( y, -x, 30, fvals, cmap=py.cm.jet)
py.show()
from enthought.mayavi import mlab
mlab.clf()
mlab.surf(xnew, ynew, fnew*2)
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If you are using
ynew, xnew = np.mgrid[-1:1:100j, -2:2:100j]
instead
xnew, ynew = np.mgrid[-1:1:100j, -2:2:100j]
This xnew
will change as you move through the columns, and ynew
will change as you move through the rows. (I changed the x-range from [-1.1] to [-2.2] to make it clear which numbers control the range).
Combine that with @ hitzg's suggestion to add origin='lower'
to the call imshow
and you get:
import numpy as np
from scipy import interpolate
import matplotlib.pyplot as plt
np.random.seed(2015)
def func(x,y):
return (x+y)*np.cos(-5.0*x + 4.0*y)
x = np.random.uniform(-2.0, 2.0, size=50)
y = np.random.uniform(-1.0, 1.0, size=50)
fvals = func(x,y)
newfunc = interpolate.Rbf(x, y, fvals, function='multiquadric')
ynew, xnew = np.mgrid[-1:1:100j, -2:2:100j]
fnew = newfunc(xnew, ynew)
plt.figure()
plt.imshow(fnew, extent=[-2,2,-1,1], cmap=plt.cm.jet, origin='lower')
plt.scatter(x, y, s=30, c=fvals, cmap=plt.cm.jet)
plt.show()
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