How to obtain the following surface via Matplotlib?
It is easy in matlab via:
mesh(peaks)
It seems matplotlib does not have an exact counterpart of mesh in matlab.
the Wireframe plots does not have any colormap option
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LCFactorization
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How mplot3d? http://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html#wireframe-plots ? – EJG89 Jul 23 '14 at 11:43
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None of them works. I need exactly the same `colormap` being applied on the `mesh` or the `wireframe` – LCFactorization Jul 23 '14 at 12:00
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Do you require a `mesh` or would a `surface` suffice? – Justin Fletcher Jul 23 '14 at 13:21
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`mesh` not `surface`; Surface plot can be easily implemented via matplotlib – LCFactorization Jul 23 '14 at 13:42
4 Answers
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While answering another question I found that you can easily do this using plot_surface to produce a color mapped surface, and then exchanging face and edge colors:
surf = ax.plot_surface(X, Y, Z, rstride=2, cstride=2, shade=False, cmap="jet", linewidth=1)
draw()
surf.set_edgecolors(surf.to_rgba(surf._A))
surf.set_facecolors("white")
show()
produces
The disadvantage this solution has over the other one is that the edges do not have smooth, per-pixel colouring, but one single color each.
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1This doesn't seem to work anymore in 1.5.1. This does: `surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, shade=False, cmap=mpl.colors.ListedColormap(['white']))` `m = plt.cm.ScalarMappable(surf.norm)` `surf.set_edgecolors(m.to_rgba(surf.get_array()))` – wilywampa Jun 07 '16 at 03:50
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@wilywampa Thanks. Your fix doesn't work for me; but [this question](http://stackoverflow.com/questions/12355410/edgelines-vanish-in-mplot3d-surf-when-facecolors-are-specified) gave me the hint to add the `linewidth` keyword to the `plot_surface` call, which does fix the behaviour. – Phillip Jun 07 '16 at 07:51
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If hidden lines behind surface is not desirable, one can use `surf.set_facecolor([0]*4)` instead of `'white'` – herrlich10 Aug 25 '16 at 08:17
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It seems to be possible with matplotlib even if it is a bit of a hack:
from mpl_toolkits.mplot3d import axes3d
from mpl_toolkits.mplot3d import art3d
import matplotlib.pyplot as plt
import numpy as np
import matplotlib as mpl
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
wire = ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
# Retrive data from internal storage of plot_wireframe, then delete it
nx, ny, _ = np.shape(wire._segments3d)
wire_x = np.array(wire._segments3d)[:, :, 0].ravel()
wire_y = np.array(wire._segments3d)[:, :, 1].ravel()
wire_z = np.array(wire._segments3d)[:, :, 2].ravel()
wire.remove()
# create data for a LineCollection
wire_x1 = np.vstack([wire_x, np.roll(wire_x, 1)])
wire_y1 = np.vstack([wire_y, np.roll(wire_y, 1)])
wire_z1 = np.vstack([wire_z, np.roll(wire_z, 1)])
to_delete = np.arange(0, nx*ny, ny)
wire_x1 = np.delete(wire_x1, to_delete, axis=1)
wire_y1 = np.delete(wire_y1, to_delete, axis=1)
wire_z1 = np.delete(wire_z1, to_delete, axis=1)
scalars = np.delete(wire_z, to_delete)
segs = [list(zip(xl, yl, zl)) for xl, yl, zl in \
zip(wire_x1.T, wire_y1.T, wire_z1.T)]
# Plots the wireframe by a a line3DCollection
my_wire = art3d.Line3DCollection(segs, cmap="hsv")
my_wire.set_array(scalars)
ax.add_collection(my_wire)
plt.colorbar(my_wire)
plt.show()
GBy
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An official feature request is underway:
https://github.com/matplotlib/matplotlib/issues/3562
The accepted solution doesn't work when X and Y arrays are not the same size.
Adam Hughes
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It seems the current matplotlib 1.3.1 does not handle such mesh plot or further PDF export. gnuplot.pygnuplot.py 1.8 might be a choice before there is further updates in matplotlib.
Here is an example created via gnuplot:
MayaVI2 does not support PDF exports but might be another good choice.
LCFactorization
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