how to remove plot elements in python

Question

I'm trying to a 3d figure without any plot elements in python. Sort of a 3d version of this.

When I run the code I have added below, I get regular plot a figure of (Very) simplified surface . I want to remove the axes, axes labels, ticks, and background (and remain only with the surface).

How can I remove them.

Also, is there way to add arrows to the plot?

Here is my code:

import random
import math

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np

pi = 3.14159
bignum = 3
amp = 0.1

mat = []
X = []
Y = []
class mode:
    i=0
    j=0
    phase=0
    amp=0
modes = dict() 
for i in range(0,3):
    submodes = dict()
    for j in range (0,5):
        if not (i==0 and j==2):
            m = mode()
            m.i = i
            m.j = j
            m.amp = amp*random.random()/(pow(i,2) + pow(j-2,2))
            m.phase = random.random()*2*pi
            submodes[j] = m
            modes[i] = submodes

for x in range (0,bignum): 
    mat.append([])
    for y in range (0,bignum):
        dz = 0
        for i in range (0,3):
            for j in range (0,5):
                if not (i == 0 and j == 2):
                    dz += math.cos(i*x*2*pi/bignum + j *y*2/bignum + modes[i][j].phase)*modes[i][j].amp
        mat[x].append(dz)

X = np.mgrid[:bignum,:bignum]
print (len(X[0]))
print (len(mat))
fig = plt.figure(figsize=plt.figaspect(2.))
fig.frameon=True

ax = fig.add_subplot(1,1,1, projection='3d')
ax.frameon=False
ax.xticks=[]
ax.yticks=[]
ax.zticks=[]
surf = ax.plot_surface(X[0],X[1],mat,rstride=1, cstride=1,
        linewidth=0, antialiased=False)
ax.set_zlim3d(0, 1)
plt.show()

Not that this is off topic here (because it isn't), but this kind of question would also fit on Computational Science, and it'd benefit from an audience more dedicated to scientific computation. — David Z
– David Z, Commented Jan 12, 2012 at 23:53

joaquin · Accepted Answer · 2012-01-13 00:13:43Z

1

To eliminate the 3d frame from the figure, use:

ax.set_axis_off()

enter image description here

edited Jan 13, 2012 at 0:13

answered Jan 12, 2012 at 23:36

joaquin

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1 Comment

Matt Over a year ago

add this and you get a totally gray background plt.setp(ax.get_frame(), visible = False). At the very least you should use ndarrays instead of dict, vectorization takes time to learn for sure but can save you on large data sets

Matt · Accepted Answer · 2012-01-13 14:52:58Z

This doesn't answer much of your question. But you can start turning stuff off with

plt.setp(ax.get_xticklabels(), visible=False)

I did some of it below. Also, the plt.annotate() function is how to add arrows in 2d plots...not sure how it upscales.

import random
import math

from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np

pi = 3.14159
bignum = 3
amp = 0.1

mat = []
X = []
Y = []
class mode:
    i=0
    j=0
    phase=0
    amp=0
modes = dict() 
for i in range(0,3):
    submodes = dict()
    for j in range (0,5):
        if not (i==0 and j==2):
            m = mode()
            m.i = i
            m.j = j
            m.amp = amp*random.random()/(pow(i,2) + pow(j-2,2))
            m.phase = random.random()*2*pi
            submodes[j] = m
            modes[i] = submodes

for x in range (0,bignum): 
    mat.append([])
    for y in range (0,bignum):
        dz = 0
        for i in range (0,3):
            for j in range (0,5):
                if not (i == 0 and j == 2):
                    dz += math.cos(i*x*2*pi/bignum + j *y*2/bignum + modes[i][j].phase)*modes[i][j].amp
        mat[x].append(dz)

X = np.mgrid[:bignum,:bignum]
print (len(X[0]))
print (len(mat))
fig = plt.figure(figsize=plt.figaspect(2.))
fig.frameon=True

ax = fig.add_subplot(1,1,1, projection='3d')
ax.frameon=False

surf = ax.plot_surface(X[0],X[1],mat,rstride=1, cstride=1,
        linewidth=0, antialiased=False)
ax.set_zlim3d(0, 1)
plt.setp(ax.get_xticklabels(), visible=False)
plt.setp(ax.get_yticklabels(), visible=False)
plt.setp(ax.get_zticklabels(), visible=False)
plt.setp(ax.get_xticklines(), visible=False)
plt.setp(ax.get_yticklines(), visible=False)
plt.setp(ax.get_zticklines(), visible=False)
plt.setp(ax.get_frame(), visible = False)
#plt.annotate(r'Hello', xy = (.5, .5),
#                xytext = (10,10),
#                textcoords='offset points', arrowprops=dict(arrowstyle='->',
#                                                connectionstyle='arc3,rad=0'))

plt.show()

You didn't ask this...but you should vectorize this code. Most/(all?) of the for loops could be avoided.

Thanks. I know I should avoid loops but I can't see how I can escape them here. Mainly the power of i and j.

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