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added mpl_toolkits.mplot3d
svn path=/trunk/matplotlib/; revision=7041
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‎CHANGELOG

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======================================================================
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2008-04-12 Release 0.98.5.3 at r7038
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2008-04-14 Added Jonathan Taylor's Reinier Heeres' port of John
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Porters' mplot3d to svn trunk. Package in
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mpl_toolkits.mplot3d and demo is examples/mplot3d/demo.py.
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Thanks Reiner
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2009-04-06 The pdf backend now escapes newlines and linefeeds in strings.
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Fixes sf bug #2708559; thanks to Tiago Pereira for the report.

‎doc/users/credits.rst

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base. He also rewrote the transformation infrastructure to support
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custom projections and scales.
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John Porter, Jonathon Taylor and Reinier Heeres
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John Porter wrote the mplot3d module for basic 3D plotting in
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matplotlib, and Jonathon Taylor and Reinier Heeres ported it to the
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refactored transform trunk.
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‎doc/users/toolkits.rst

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Natgrid
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========
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mpl_toolkits.natgrid is an interface to natgrid C library for gridding
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irregularly spaced data. This requires a separate installation of the
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natgrid toolkit from the sourceforge `download
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<http://sourceforge.net/project/showfiles.php?group_id=80706&package_id=142792>`_
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page.
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.. _toolkit_mplot3d:
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mplot3d
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===========
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mpl_toolkits.mplot3d provides some basic 3D plotting (scatter, surf,
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line, mesh) tools. Not the fastest or feature complete 3D library out
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there, but ships with matplotlib and thus may be a lighter weight
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solution for some use cases.

‎examples/mplot3d/demo.py

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import random
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import numpy as np
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import matplotlib.pyplot as plt
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import mpl_toolkits.mplot3d.axes3d as axes3d
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from matplotlib.colors import Normalize, colorConverter
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def test_scatter():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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n = 100
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for c,zl,zh in [('r',-50,-25),('b',-30,-5)]:
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xs,ys,zs = zip(*
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[(random.randrange(23,32),
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random.randrange(100),
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random.randrange(zl,zh)
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) for i in range(n)])
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ax.scatter3D(xs,ys,zs, c=c)
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ax.set_xlabel('------------ X Label --------------------')
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ax.set_ylabel('------------ Y Label --------------------')
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ax.set_zlabel('------------ Z Label --------------------')
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def test_wire():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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X,Y,Z = axes3d.get_test_data(0.05)
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ax.plot_wireframe(X,Y,Z, rstride=10,cstride=10)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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def test_surface():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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X,Y,Z = axes3d.get_test_data(0.05)
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ax.plot_surface(X,Y,Z, rstride=10,cstride=10)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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def test_contour():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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X,Y,Z = axes3d.get_test_data(0.05)
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cset = ax.contour3D(X,Y,Z)
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ax.clabel(cset, fontsize=9, inline=1)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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def test_contourf():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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X,Y,Z = axes3d.get_test_data(0.05)
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cset = ax.contourf3D(X,Y,Z)
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ax.clabel(cset, fontsize=9, inline=1)
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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def test_plot():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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xs = np.arange(0,4*np.pi+0.1,0.1)
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ys = np.sin(xs)
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ax.plot(xs,ys, label='zl')
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ax.plot(xs,ys+max(xs),label='zh')
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ax.plot(xs,ys,dir='x', label='xl')
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ax.plot(xs,ys,dir='x', z=max(xs),label='xh')
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ax.plot(xs,ys,dir='y', label='yl')
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ax.plot(xs,ys,dir='y', z=max(xs), label='yh')
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ax.set_xlabel('X')
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ax.set_ylabel('Y')
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ax.set_zlabel('Z')
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ax.legend()
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def test_polys():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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cc = lambda arg: colorConverter.to_rgba(arg, alpha=0.6)
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xs = np.arange(0,10,0.4)
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verts = []
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zs = [0.0,1.0,2.0,3.0]
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for z in zs:
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ys = [random.random() for x in xs]
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ys[0],ys[-1] = 0,0
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verts.append(zip(xs,ys))
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from matplotlib.collections import PolyCollection
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poly = PolyCollection(verts, facecolors = [cc('r'),cc('g'),cc('b'),
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cc('y')])
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poly.set_alpha(0.7)
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ax.add_collection(poly,zs=zs,dir='y')
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ax.set_xlim(0,10)
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ax.set_ylim(-1,4)
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ax.set_zlim(0,1)
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def test_scatter2D():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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xs = [random.random() for i in range(20)]
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ys = [random.random() for x in xs]
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ax.scatter(xs, ys)
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ax.scatter(xs, ys, dir='y', c='r')
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ax.scatter(xs, ys, dir='x', c='g')
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def test_bar2D():
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f = plt.figure()
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ax = axes3d.Axes3D(f)
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for c,z in zip(['r','g','b', 'y'],[30,20,10,0]):
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xs = np.arange(20)
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ys = [random.random() for x in xs]
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ax.bar(xs, ys, z=z, dir='y', color=c, alpha=0.8)
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if __name__ == "__main__":
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test_scatter()
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test_wire()
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test_surface()
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test_contour()
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test_contourf()
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test_plot()
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test_polys()
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test_scatter2D()
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# test_bar2D()
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plt.show()

‎examples/pylab_examples/finance_work2.py

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class MyLocator(mticker.MaxNLocator):
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def __init__(self, *args, **kwargs):
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mticker.MaxNLocator.__init__(self, *args, **kwargs)
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def __call__(self, *args, **kwargs):
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return mticker.MaxNLocator.__call__(self, *args, **kwargs)
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# at most 5 ticks, pruning the upper and lower so they don't overlap
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# with other ticks
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ax2.yaxis.set_major_locator(mticker.MaxNLocator(5, prune='both'))
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ax3.yaxis.set_major_locator(mticker.MaxNLocator(5, prune='both'))
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#ax2.yaxis.set_major_locator(mticker.MaxNLocator(5, prune='both'))
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#ax3.yaxis.set_major_locator(mticker.MaxNLocator(5, prune='both'))
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ax2.yaxis.set_major_locator(MyLocator(5, prune='both'))
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ax3.yaxis.set_major_locator(MyLocator(5, prune='both'))
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plt.show()
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‎examples/tests/backend_driver.py

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]
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mplot3d_dir = os.path.join('..', 'mplot3d')
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mplot3d_files = [
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'demo.py',
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]
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# dict from dir to files we know we don't want to test (eg examples
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# not using pyplot, examples requiring user input, animation examples,
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# examples that may only work in certain environs (usetex examples?),
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files = (
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[os.path.join(api_dir, fname) for fname in api_files] +
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[os.path.join(pylab_dir, fname) for fname in pylab_files] +
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[os.path.join(units_dir, fname) for fname in units_files]
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[os.path.join(units_dir, fname) for fname in units_files] +
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[os.path.join(mplot3d_dir, fname) for fname in mplot3d_files]
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)
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# tests known to fail on a given backend

‎lib/mpl_toolkits/mplot3d/__init__.py

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