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Commit 6a5def2

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TrishGillettTrishGillett
committed
DOC Cleaning up mplot3d/tri* examples: comments/docstrings, tweaks, and refactoring. Notably, viewing angles on tricontour examples are tweaked and the graphs of trisurf3d_demo2 are made into subplots. [MEP12]
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‎examples/mplot3d/tricontour3d_demo.py

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+16-9Lines changed: 16 additions & 9 deletions
Original file line numberDiff line numberDiff line change
@@ -1,27 +1,30 @@
11
"""
22
Contour plots of unstructured triangular grids.
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The data used is the same as in the second plot of trisurf3d_demo2.
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tricontourf3d_demo shows the filled version of this example.
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"""
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48
import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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import matplotlib.tri as tri
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import numpy as np
8-
import math
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10-
# First create the x and y coordinates of the points.
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n_angles = 48
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n_radii = 8
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min_radius = 0.25
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radii = np.linspace(min_radius, 0.95, n_radii)
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16-
angles = np.linspace(0, 2*math.pi, n_angles, endpoint=False)
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# Create the mesh in polar coordinates and compute x, y, z.
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radii = np.linspace(min_radius, 0.95, n_radii)
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angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
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angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
18-
angles[:, 1::2] += math.pi/n_angles
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angles[:, 1::2] += np.pi/n_angles
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2023
x = (radii*np.cos(angles)).flatten()
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y = (radii*np.sin(angles)).flatten()
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z = (np.cos(radii)*np.cos(angles*3.0)).flatten()
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24-
# Create a custom triangulation
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# Create a custom triangulation.
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triang = tri.Triangulation(x, y)
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# Mask off unwanted triangles.
@@ -30,7 +33,11 @@
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mask = np.where(xmid*xmid + ymid*ymid < min_radius*min_radius, 1, 0)
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triang.set_mask(mask)
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33-
plt.figure()
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plt.gca(projection='3d')
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plt.tricontour(triang, z)
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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ax.tricontour(triang, z, cmap=plt.cm.CMRmap)
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# Customize the view angle so it's easier to understand the plot.
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ax.view_init(elev=45.)
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3643
plt.show()

‎examples/mplot3d/tricontourf3d_demo.py

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+18-10Lines changed: 18 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -1,27 +1,31 @@
11
"""
2-
Contour plots of unstructured triangular grids.
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Filled contour plots of unstructured triangular grids.
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The data used is the same as in the second plot of trisurf3d_demo2.
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tricontour3d_demo shows the unfilled version of this example.
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"""
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import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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import matplotlib.tri as tri
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import numpy as np
8-
import math
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10-
# First create the x and y coordinates of the points.
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# First create the x, y, z coordinates of the points.
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n_angles = 48
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n_radii = 8
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min_radius = 0.25
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radii = np.linspace(min_radius, 0.95, n_radii)
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16-
angles = np.linspace(0, 2*math.pi, n_angles, endpoint=False)
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# Create the mesh in polar coordinates and compute x, y, z.
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radii = np.linspace(min_radius, 0.95, n_radii)
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angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
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angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
18-
angles[:, 1::2] += math.pi/n_angles
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angles[:, 1::2] += np.pi/n_angles
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2024
x = (radii*np.cos(angles)).flatten()
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y = (radii*np.sin(angles)).flatten()
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z = (np.cos(radii)*np.cos(angles*3.0)).flatten()
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24-
# Create a custom triangulation
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# Create a custom triangulation.
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triang = tri.Triangulation(x, y)
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# Mask off unwanted triangles.
@@ -30,7 +34,11 @@
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mask = np.where(xmid*xmid + ymid*ymid < min_radius*min_radius, 1, 0)
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triang.set_mask(mask)
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33-
plt.figure()
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plt.gca(projection='3d')
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plt.tricontourf(triang, z)
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fig = plt.figure()
38+
ax = fig.gca(projection='3d')
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ax.tricontourf(triang, z, cmap=plt.cm.CMRmap)
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41+
# Customize the view angle so it's easier to understand the plot.
42+
ax.view_init(elev=45.)
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3644
plt.show()

‎examples/mplot3d/trisurf3d_demo.py

Copy file name to clipboardExpand all lines: examples/mplot3d/trisurf3d_demo.py
+12-10Lines changed: 12 additions & 10 deletions
Original file line numberDiff line numberDiff line change
@@ -1,27 +1,29 @@
1+
'''
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Plot a 3D surface with a triangular mesh.
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'''
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from mpl_toolkits.mplot3d import Axes3D
2-
from matplotlib import cm
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import matplotlib.pyplot as plt
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import numpy as np
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6-
n_angles = 36
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n_radii = 8
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n_angles = 36
812

9-
# An array of radii
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# Does not include radius r=0, this is to eliminate duplicate points
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# Make radii and angles spaces (radius r=0 omitted to eliminate duplication).
1114
radii = np.linspace(0.125, 1.0, n_radii)
12-
13-
# An array of angles
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angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
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16-
# Repeat all angles for each radius
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# Repeat all angles for each radius.
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angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
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19-
# Convert polar (radii, angles) coords to cartesian (x, y) coords
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# (0, 0) is added here. There are no duplicate points in the (x, y) plane
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# Convert polar (radii, angles) coords to cartesian (x, y) coords.
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# (0, 0) is manually added at this stage, so there will be no duplicate
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# points in the (x, y) plane.
2123
x = np.append(0, (radii*np.cos(angles)).flatten())
2224
y = np.append(0, (radii*np.sin(angles)).flatten())
2325

24-
# Pringle surface
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# Compute z to make the pringle surface.
2527
z = np.sin(-x*y)
2628

2729
fig = plt.figure()

‎examples/mplot3d/trisurf3d_demo2.py

Copy file name to clipboard
+35-14Lines changed: 35 additions & 14 deletions
Original file line numberDiff line numberDiff line change
@@ -1,11 +1,28 @@
1+
'''
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Two additional examples of plotting surfaces with triangular mesh.
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The first demonstrates use of plot_trisurf's triangles argument, and the
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second sets a Triangulation object's mask and passes the object directly
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to plot_trisurf.
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'''
8+
19
import numpy as np
210
import matplotlib.pyplot as plt
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from mpl_toolkits.mplot3d import Axes3D
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import matplotlib.tri as mtri
513

6-
# u, v are parameterisation variables
7-
u = (np.linspace(0, 2.0 * np.pi, endpoint=True, num=50) * np.ones((10, 1))).flatten()
8-
v = np.repeat(np.linspace(-0.5, 0.5, endpoint=True, num=10), repeats=50).flatten()
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15+
fig = plt.figure(figsize=plt.figaspect(0.5))
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17+
#============
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# First plot
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#============
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21+
# Make a mesh in the space of parameterisation variables u and v
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u = np.linspace(0, 2.0 * np.pi, endpoint=True, num=50)
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v = np.linspace(-0.5, 0.5, endpoint=True, num=10)
24+
u, v = np.meshgrid(u, v)
25+
u, v = u.flatten(), v.flatten()
926

1027
# This is the Mobius mapping, taking a u, v pair and returning an x, y, z
1128
# triple
@@ -16,16 +33,18 @@
1633
# Triangulate parameter space to determine the triangles
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tri = mtri.Triangulation(u, v)
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19-
fig = plt.figure()
20-
ax = fig.add_subplot(1, 1, 1, projection='3d')
21-
22-
# The triangles in parameter space determine which x, y, z points are
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# connected by an edge
36+
# Plot the surface. The triangles in parameter space determine which x, y, z
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# points are connected by an edge.
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ax = fig.add_subplot(1, 2, 1, projection='3d')
2439
ax.plot_trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral)
25-
2640
ax.set_zlim(-1, 1)
2741

28-
# First create the x and y coordinates of the points.
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43+
#============
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# Second plot
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#============
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47+
# Make parameter spaces radii and angles.
2948
n_angles = 36
3049
n_radii = 8
3150
min_radius = 0.25
@@ -35,6 +54,7 @@
3554
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
3655
angles[:, 1::2] += np.pi/n_angles
3756

57+
# Map radius, angle pairs to x, y, z points.
3858
x = (radii*np.cos(angles)).flatten()
3959
y = (radii*np.sin(angles)).flatten()
4060
z = (np.cos(radii)*np.cos(angles*3.0)).flatten()
@@ -45,11 +65,12 @@
4565
# Mask off unwanted triangles.
4666
xmid = x[triang.triangles].mean(axis=1)
4767
ymid = y[triang.triangles].mean(axis=1)
48-
mask = np.where(xmid*xmid + ymid*ymid < min_radius*min_radius, 1, 0)
68+
mask = np.where(xmid**2 + ymid**2 < min_radius**2, 1, 0)
4969
triang.set_mask(mask)
5070

51-
# tripcolor plot.
52-
fig = plt.figure()
53-
ax = fig.add_subplot(1, 1, 1, projection='3d')
71+
# Plot the surface.
72+
ax = fig.add_subplot(1, 2, 2, projection='3d')
5473
ax.plot_trisurf(triang, z, cmap=plt.cm.CMRmap)
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75+
5576
plt.show()

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