Reputation: 923
I've searched in the forum, but I've found only similar but different answers and questions. I have a problem in plotting a 3D histogram starting from a matrix of z-values.
That's the matrix I obtained from previous operations:
[[ 84. 80.76923077 68.05555556 56.57894737 60.
44.7761194 55.2238806 39.0625 27.41935484 29.8245614 ]
[ 82.44274809 67.70833333 63.75 44.44444444 47.76119403
33.33333333 22.78481013 19.23076923 9.21052632 2.63157895]
[ 53.33333333 61.76470588 48.64864865 34.61538462 0.
16.66666667 0. 0. 0. 0. ]
[ 48. 25. 0. 0. 0.
0. 0. 0. 0. 0. ]]
These are all z-values. The x and y values are simply their positions along the matrix. I've just looked in the matplotlib pages but all the examples start from x,y-values. I have also looked in the forum but this problem is slightly different.
I'm trying with something like:
hist, xedges, yedges = np.histogram2d(x, y, bins=(20,20))
xpos, ypos = np.meshgrid(xedges[:-1]+xedges[1:], yedges[:-1]+yedges[1:])
dx = xedges [1] - xedges [0]
dy = yedges [1] - yedges [0]
dz = hist.flatten()
ax.bar3d(xpos, ypos, zpos, dx, dy, dz, zsort='average')
But I'm in trouble with understanding how to put in x,y values. Someone could help me?
UPDATE:
len_x, len_y = matrix.shape
x = np.linspace(0,len_x-1,len_x)
y = np.linspace(0,len_y-1,len_y)
# 3D PLOT:
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
hist, xedges, yedges = np.histogram2d(x,y)
xpos, ypos = np.meshgrid(xedges[:-1]+xedges[1:], yedges[:-1]+yedges[1:])
xpos = xpos.flatten()/2.
ypos = ypos.flatten()/2.
zpos = np.zeros_like(xpos)
dx = xedges [1] - xedges [0]
dy = yedges [1] - yedges [0]
dz = hist.flatten()
max_height = np.max(dz)
min_height = np.min(dz)
ax.bar3d(xpos, ypos, zpos, dx, dy, dz, zsort='average')
Upvotes: 0
Views: 1530
Reputation:
Not sure what you want to get. Try the following code as a starting point:
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
matrix = np.array([
[84., 80.76923077, 68.05555556, 56.57894737, 60.,
44.7761194, 55.2238806, 39.0625, 27.41935484, 29.8245614],
[82.44274809, 67.70833333, 63.75, 44.44444444, 47.76119403,
33.33333333, 22.78481013, 19.23076923, 9.21052632, 2.63157895],
[53.33333333, 61.76470588, 48.64864865, 34.61538462, 0.,
16.66666667, 0., 0., 0., 0.],
[48., 25., 0., 0., 0., 0., 0., 0., 0., 0. ]])
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
xpos = [range(matrix.shape[0])]
ypos = [range(matrix.shape[1])]
xpos, ypos = np.meshgrid(xpos, ypos)
xpos = xpos.flatten('F')
ypos = ypos.flatten('F')
zpos = np.zeros_like(xpos)
dx = 0.5 * np.ones_like(zpos)
dy = dx.copy()
dz = matrix.flatten()
ax.bar3d(xpos, ypos, zpos, dx, dy, dz, color='b', zsort='average')
plt.show()
Result is:
The code is a modification of this example from matplotlib.org.
Upvotes: 2