from numpy import exp,arange from pylab import meshgrid,cm,imshow,contour,clabel,colorbar,axis,title,show # the function that I'm going to plot def z_func(x,y): return (1-(x**2+y**3))*exp(-(x**2+y**2)/2) x = arange(-3.0,3.0,0.1) y = arange(-3.0,3.0,0.1) X,Y = meshgrid(x, y) # grid of point Z = z_func(X, Y) # evaluation of the function on the grid im = imshow(Z,cmap=cm.RdBu) # drawing the function # adding the Contour lines with labels cset = contour(Z,arange(-1,1.5,0.2),linewidths=2,cmap=cm.Set2) clabel(cset,inline=True,fmt='%1.1f',fontsize=10) colorbar(im) # adding the colobar on the right # latex fashion title title('$z=(1-x^2+y^3) e^{-(x^2+y^2)/2}$') show()The script would have the following output:

And now we are going to use the values stored in X,Y and Z to make a 3D plot using the mplot3d toolkit. Here's the snippet:

from mpl_toolkits.mplot3d import Axes3D from matplotlib import cm from matplotlib.ticker import LinearLocator, FormatStrFormatter import matplotlib.pyplot as plt fig = plt.figure() ax = fig.gca(projection='3d') surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.RdBu,linewidth=0, antialiased=False) ax.zaxis.set_major_locator(LinearLocator(10)) ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f')) fig.colorbar(surf, shrink=0.5, aspect=5) plt.show()And this is the result:

i would like to see a demo using d3py from

ReplyDeletehttps://github.com/mikedewar/D3py/tree/v2

Which version of matplotlib do you use? I get attribute error

ReplyDelete--> 34 ax.zaxis.set_major_locator(LinearLocator(10))

AttributeError: 'Axes3DSubplot' object has no attribute 'zaxis'

I made this code using matplotlib 1.1.0

ReplyDeleteOh, I have 1.0.1. Thanks

ReplyDeleteStack Overflow hints at how to do the 2nd example with matplotlib 0.99:

ReplyDeletehttp://stackoverflow.com/questions/3810865/need-help-with-matplotlib

These small changes worked for me:

http://pastebin.com/PnSMLqDD

Hello there! thank you very much indeed.

ReplyDeleteAtte,

Ignacio Aular

:)

This comment has been removed by the author.

ReplyDeleteThanks! This post was very helpful to me in gaining proficieny with Python plotting. However, there are a number of errors associated with the contour map / intensity image code as presented.

ReplyDeleteFirst, I'm not sure why your contour map axes extend from 0 to 249 (I suppose), rather than from 0 to 59, as set by arange(). But e that as it may, it is really much better to set extents on the contour map's axes so that they can be labeled properly - that is, with the values actually presented to the function z_func(). This can be achieved by replacing the current imshow() with:

im = imshow(Z,cmap=cm.RdBu, extent=[-3.0,3.0,-3.0,3.0], origin='lower') # drawing the function

And by adding the x and y arrays to the call to contour() as follows:

cset = contour(x,y,Z,arange(-1,1.5,0.2),linewidths=2,cmap=cm.Set2)

Doing so clears up another problem with the contour map as drawn above, and that is that it does not adhere to the Cartesian coordinate system, in that the origin (0,0) should be in the lower left. In the graph above it is in the upper left, resulting in the plot being presented upside down. [Note that it was necessary to set the origin to 'lower' to inform imshow() of the switch.]

Finally, z_func() differs from the displayed title. In the actual function, due to the parentheses, the negative sign is distributed over x-squared *and* y-cubed, rather than just applying to x-squared, as the title depicts.

With respect to the 3D plot, it is helpful to label its axes and to set its elevation and azimuth angles. It's also useful to reverse the order of the x-coordinates [from the call to arange()] so that the Cartesian orientation is preserved. The code I used to achieve these things appears below:

ReplyDeletedef z_func(x,y):

return (1-(x**2+y**3))*exp(-(x**2+y**2)/2)

x = arange(3.0,-3.0,-0.1)

y = arange(-3.0,3.0,0.1)

X,Y = meshgrid(x, y) # grid of point

Z = z_func(X, Y) # evaluation of the function on the grid

fig = plt.figure()

ax = fig.gca(projection='3d')

surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.RdBu,linewidth=0, antialiased=False)

ax.zaxis.set_major_locator(LinearLocator(10))

ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

ax.set_xlabel('x-axis')

ax.set_ylabel('y-axis')

ax.set_zlabel('z-axis')

ax.view_init(elev=25, azim=-120)

fig.colorbar(surf, shrink=0.5, aspect=5)

plt.show()

It seems that in the posted contour map image the arange() had a different stepsize, thereby accounting for the different number of elements it displays. Something like:

ReplyDeletex = y = arange(-3.0, 3.0, 0.024)

Hi, your code has been very helpful.

ReplyDeleteHowever I tried something different and I can't figure the mistake here since I simply made a bigger function (which has complex value, btw) but the result is always real so...

def Reflectance(x,y):

Rpart = (1 -((pf()*tau)**2 / (1+(py*x*tau)**2)) )

#pf() is a simple function that returns a value

#py is just 2pi

Ipart = ((pf()**2*tau)/(py*x*(1+(py*x*tau)**2)))*1j

Zt = 377/(((Rpart+Ipart)**(0.5)))

Xt = np.arcsin((377/Zt)*np.sin(y))

A = Zt/377

G = np.cos(x)/np.cos(Xt)

ErM = (A-G)/(A+G)

R= np.conjugate(ErM)*ErM

return R

a,b = 1e13,1*1e16

c = (b-a)/100

freq = arange(a,b,c)

angle = arange(0,py/4,py/100)

X,Y = meshgrid(freq, angle)

Z = Reflectance(X,Y) # evaluation of the function on the grid

im = imshow(Z,cmap=cm.RdBu)

cset = contour(Z,arange(0,1,0.1),linewidths=2,cmap=cm.Set2)

clabel(cset,inline=True,fmt='%1.1f',fontsize=10)

colorbar(im) # adding the colobar on the right

title('Reflection according to frequency and angle')

show()

any chance to plot a pure python function that don't used numpy function stuff (like np.exp in your example)? I am just being interested in ploting a two or three argument function.

ReplyDeleteHi there, you can avoid using bumpy in your function. It will work as long as the output has the same shape as Z.

Delete