Vehicle-Anti-Theft-Face-Rec.../venv/Lib/site-packages/mpl_toolkits/tests/test_mplot3d.py

1083 lines
34 KiB
Python

import functools
import itertools
import pytest
from mpl_toolkits.mplot3d import Axes3D, axes3d, proj3d, art3d
import matplotlib as mpl
from matplotlib import cm
from matplotlib import colors as mcolors
from matplotlib.testing.decorators import image_comparison, check_figures_equal
from matplotlib.collections import LineCollection, PolyCollection
from matplotlib.patches import Circle
import matplotlib.pyplot as plt
import numpy as np
mpl3d_image_comparison = functools.partial(
image_comparison, remove_text=True, style='default')
def test_aspect_equal_error():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
with pytest.raises(NotImplementedError):
ax.set_aspect('equal')
@mpl3d_image_comparison(['bar3d.png'])
def test_bar3d():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for c, z in zip(['r', 'g', 'b', 'y'], [30, 20, 10, 0]):
xs = np.arange(20)
ys = np.arange(20)
cs = [c] * len(xs)
cs[0] = 'c'
ax.bar(xs, ys, zs=z, zdir='y', align='edge', color=cs, alpha=0.8)
def test_bar3d_colors():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
for c in ['red', 'green', 'blue', 'yellow']:
xs = np.arange(len(c))
ys = np.zeros_like(xs)
zs = np.zeros_like(ys)
# Color names with same length as xs/ys/zs should not be split into
# individual letters.
ax.bar3d(xs, ys, zs, 1, 1, 1, color=c)
@mpl3d_image_comparison(['bar3d_shaded.png'])
def test_bar3d_shaded():
x = np.arange(4)
y = np.arange(5)
x2d, y2d = np.meshgrid(x, y)
x2d, y2d = x2d.ravel(), y2d.ravel()
z = x2d + y2d + 1 # Avoid triggering bug with zero-depth boxes.
views = [(-60, 30), (30, 30), (30, -30), (120, -30)]
fig = plt.figure(figsize=plt.figaspect(1 / len(views)))
axs = fig.subplots(
1, len(views),
subplot_kw=dict(projection='3d')
)
for ax, (azim, elev) in zip(axs, views):
ax.bar3d(x2d, y2d, x2d * 0, 1, 1, z, shade=True)
ax.view_init(azim=azim, elev=elev)
fig.canvas.draw()
@mpl3d_image_comparison(['bar3d_notshaded.png'])
def test_bar3d_notshaded():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = np.arange(4)
y = np.arange(5)
x2d, y2d = np.meshgrid(x, y)
x2d, y2d = x2d.ravel(), y2d.ravel()
z = x2d + y2d
ax.bar3d(x2d, y2d, x2d * 0, 1, 1, z, shade=False)
fig.canvas.draw()
def test_bar3d_lightsource():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection="3d")
ls = mcolors.LightSource(azdeg=0, altdeg=90)
length, width = 3, 4
area = length * width
x, y = np.meshgrid(np.arange(length), np.arange(width))
x = x.ravel()
y = y.ravel()
dz = x + y
color = [cm.coolwarm(i/area) for i in range(area)]
collection = ax.bar3d(x=x, y=y, z=0,
dx=1, dy=1, dz=dz,
color=color, shade=True, lightsource=ls)
# Testing that the custom 90° lightsource produces different shading on
# the top facecolors compared to the default, and that those colors are
# precisely the colors from the colormap, due to the illumination parallel
# to the z-axis.
np.testing.assert_array_equal(color, collection._facecolors3d[1::6])
@mpl3d_image_comparison(['contour3d.png'])
def test_contour3d():
fig = plt.figure()
ax = fig.gca(projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
ax.set_xlim(-40, 40)
ax.set_ylim(-40, 40)
ax.set_zlim(-100, 100)
@mpl3d_image_comparison(['contourf3d.png'])
def test_contourf3d():
fig = plt.figure()
ax = fig.gca(projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
ax.contourf(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
ax.contourf(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
ax.contourf(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
ax.set_xlim(-40, 40)
ax.set_ylim(-40, 40)
ax.set_zlim(-100, 100)
@mpl3d_image_comparison(['contourf3d_fill.png'])
def test_contourf3d_fill():
fig = plt.figure()
ax = fig.gca(projection='3d')
X, Y = np.meshgrid(np.arange(-2, 2, 0.25), np.arange(-2, 2, 0.25))
Z = X.clip(0, 0)
# This produces holes in the z=0 surface that causes rendering errors if
# the Poly3DCollection is not aware of path code information (issue #4784)
Z[::5, ::5] = 0.1
ax.contourf(X, Y, Z, offset=0, levels=[-0.1, 0], cmap=cm.coolwarm)
ax.set_xlim(-2, 2)
ax.set_ylim(-2, 2)
ax.set_zlim(-1, 1)
@mpl3d_image_comparison(['tricontour.png'])
def test_tricontour():
fig = plt.figure()
np.random.seed(19680801)
x = np.random.rand(1000) - 0.5
y = np.random.rand(1000) - 0.5
z = -(x**2 + y**2)
ax = fig.add_subplot(1, 2, 1, projection='3d')
ax.tricontour(x, y, z)
ax = fig.add_subplot(1, 2, 2, projection='3d')
ax.tricontourf(x, y, z)
@mpl3d_image_comparison(['lines3d.png'])
def test_lines3d():
fig = plt.figure()
ax = fig.gca(projection='3d')
theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)
z = np.linspace(-2, 2, 100)
r = z ** 2 + 1
x = r * np.sin(theta)
y = r * np.cos(theta)
ax.plot(x, y, z)
@check_figures_equal(extensions=["png"])
def test_plot_scalar(fig_test, fig_ref):
ax1 = fig_test.gca(projection='3d')
ax1.plot([1], [1], "o")
ax2 = fig_ref.gca(projection='3d')
ax2.plot(1, 1, "o")
@mpl3d_image_comparison(['mixedsubplot.png'])
def test_mixedsubplots():
def f(t):
return np.cos(2*np.pi*t) * np.exp(-t)
t1 = np.arange(0.0, 5.0, 0.1)
t2 = np.arange(0.0, 5.0, 0.02)
fig = plt.figure(figsize=plt.figaspect(2.))
ax = fig.add_subplot(2, 1, 1)
ax.plot(t1, f(t1), 'bo', t2, f(t2), 'k--', markerfacecolor='green')
ax.grid(True)
ax = fig.add_subplot(2, 1, 2, projection='3d')
X, Y = np.meshgrid(np.arange(-5, 5, 0.25), np.arange(-5, 5, 0.25))
R = np.hypot(X, Y)
Z = np.sin(R)
ax.plot_surface(X, Y, Z, rcount=40, ccount=40,
linewidth=0, antialiased=False)
ax.set_zlim3d(-1, 1)
@check_figures_equal(extensions=['png'])
def test_tight_layout_text(fig_test, fig_ref):
# text is currently ignored in tight layout. So the order of text() and
# tight_layout() calls should not influence the result.
ax1 = fig_test.gca(projection='3d')
ax1.text(.5, .5, .5, s='some string')
fig_test.tight_layout()
ax2 = fig_ref.gca(projection='3d')
fig_ref.tight_layout()
ax2.text(.5, .5, .5, s='some string')
@mpl3d_image_comparison(['scatter3d.png'])
def test_scatter3d():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(np.arange(10), np.arange(10), np.arange(10),
c='r', marker='o')
x = y = z = np.arange(10, 20)
ax.scatter(x, y, z, c='b', marker='^')
z[-1] = 0 # Check that scatter() copies the data.
@mpl3d_image_comparison(['scatter3d_color.png'])
def test_scatter3d_color():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(np.arange(10), np.arange(10), np.arange(10),
color='r', marker='o')
ax.scatter(np.arange(10, 20), np.arange(10, 20), np.arange(10, 20),
color='b', marker='s')
@pytest.mark.parametrize('depthshade', [True, False])
@check_figures_equal(extensions=['png'])
def test_scatter3d_sorting(fig_ref, fig_test, depthshade):
"""Test that marker properties are correctly sorted."""
y, x = np.mgrid[:10, :10]
z = np.arange(x.size).reshape(x.shape)
sizes = np.full(z.shape, 25)
sizes[0::2, 0::2] = 100
sizes[1::2, 1::2] = 100
facecolors = np.full(z.shape, 'C0')
facecolors[:5, :5] = 'C1'
facecolors[6:, :4] = 'C2'
facecolors[6:, 6:] = 'C3'
edgecolors = np.full(z.shape, 'C4')
edgecolors[1:5, 1:5] = 'C5'
edgecolors[5:9, 1:5] = 'C6'
edgecolors[5:9, 5:9] = 'C7'
linewidths = np.full(z.shape, 2)
linewidths[0::2, 0::2] = 5
linewidths[1::2, 1::2] = 5
x, y, z, sizes, facecolors, edgecolors, linewidths = [
a.flatten()
for a in [x, y, z, sizes, facecolors, edgecolors, linewidths]
]
ax_ref = fig_ref.gca(projection='3d')
sets = (np.unique(a) for a in [sizes, facecolors, edgecolors, linewidths])
for s, fc, ec, lw in itertools.product(*sets):
subset = (
(sizes != s) |
(facecolors != fc) |
(edgecolors != ec) |
(linewidths != lw)
)
subset = np.ma.masked_array(z, subset, dtype=float)
# When depth shading is disabled, the colors are passed through as
# single-item lists; this triggers single path optimization. The
# following reshaping is a hack to disable that, since the optimization
# would not occur for the full scatter which has multiple colors.
fc = np.repeat(fc, sum(~subset.mask))
ax_ref.scatter(x, y, subset, s=s, fc=fc, ec=ec, lw=lw, alpha=1,
depthshade=depthshade)
ax_test = fig_test.gca(projection='3d')
ax_test.scatter(x, y, z, s=sizes, fc=facecolors, ec=edgecolors,
lw=linewidths, alpha=1, depthshade=depthshade)
@pytest.mark.parametrize('azim', [-50, 130]) # yellow first, blue first
@check_figures_equal(extensions=['png'])
def test_marker_draw_order_data_reversed(fig_test, fig_ref, azim):
"""
Test that the draw order does not depend on the data point order.
For the given viewing angle at azim=-50, the yellow marker should be in
front. For azim=130, the blue marker should be in front.
"""
x = [-1, 1]
y = [1, -1]
z = [0, 0]
color = ['b', 'y']
ax = fig_test.add_subplot(projection='3d')
ax.scatter(x, y, z, s=3500, c=color)
ax.view_init(elev=0, azim=azim)
ax = fig_ref.add_subplot(projection='3d')
ax.scatter(x[::-1], y[::-1], z[::-1], s=3500, c=color[::-1])
ax.view_init(elev=0, azim=azim)
@check_figures_equal(extensions=['png'])
def test_marker_draw_order_view_rotated(fig_test, fig_ref):
"""
Test that the draw order changes with the direction.
If we rotate *azim* by 180 degrees and exchange the colors, the plot
plot should look the same again.
"""
azim = 130
x = [-1, 1]
y = [1, -1]
z = [0, 0]
color = ['b', 'y']
ax = fig_test.add_subplot(projection='3d')
# axis are not exactly invariant under 180 degree rotation -> deactivate
ax.set_axis_off()
ax.scatter(x, y, z, s=3500, c=color)
ax.view_init(elev=0, azim=azim)
ax = fig_ref.add_subplot(projection='3d')
ax.set_axis_off()
ax.scatter(x, y, z, s=3500, c=color[::-1]) # color reversed
ax.view_init(elev=0, azim=azim - 180) # view rotated by 180 degrees
@mpl3d_image_comparison(['plot_3d_from_2d.png'], tol=0.01)
def test_plot_3d_from_2d():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
xs = np.arange(0, 5)
ys = np.arange(5, 10)
ax.plot(xs, ys, zs=0, zdir='x')
ax.plot(xs, ys, zs=0, zdir='y')
@mpl3d_image_comparison(['surface3d.png'])
def test_surface3d():
fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.hypot(X, Y)
Z = np.sin(R)
surf = ax.plot_surface(X, Y, Z, rcount=40, ccount=40, cmap=cm.coolwarm,
lw=0, antialiased=False)
ax.set_zlim(-1.01, 1.01)
fig.colorbar(surf, shrink=0.5, aspect=5)
@mpl3d_image_comparison(['surface3d_shaded.png'])
def test_surface3d_shaded():
fig = plt.figure()
ax = fig.gca(projection='3d')
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X ** 2 + Y ** 2)
Z = np.sin(R)
ax.plot_surface(X, Y, Z, rstride=5, cstride=5,
color=[0.25, 1, 0.25], lw=1, antialiased=False)
ax.set_zlim(-1.01, 1.01)
@mpl3d_image_comparison(['text3d.png'], remove_text=False)
def test_text3d():
fig = plt.figure()
ax = fig.gca(projection='3d')
zdirs = (None, 'x', 'y', 'z', (1, 1, 0), (1, 1, 1))
xs = (2, 6, 4, 9, 7, 2)
ys = (6, 4, 8, 7, 2, 2)
zs = (4, 2, 5, 6, 1, 7)
for zdir, x, y, z in zip(zdirs, xs, ys, zs):
label = '(%d, %d, %d), dir=%s' % (x, y, z, zdir)
ax.text(x, y, z, label, zdir)
ax.text(1, 1, 1, "red", color='red')
ax.text2D(0.05, 0.95, "2D Text", transform=ax.transAxes)
ax.set_xlim3d(0, 10)
ax.set_ylim3d(0, 10)
ax.set_zlim3d(0, 10)
ax.set_xlabel('X axis')
ax.set_ylabel('Y axis')
ax.set_zlabel('Z axis')
@mpl3d_image_comparison(['trisurf3d.png'], tol=0.03)
def test_trisurf3d():
n_angles = 36
n_radii = 8
radii = np.linspace(0.125, 1.0, n_radii)
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi/n_angles
x = np.append(0, (radii*np.cos(angles)).flatten())
y = np.append(0, (radii*np.sin(angles)).flatten())
z = np.sin(-x*y)
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_trisurf(x, y, z, cmap=cm.jet, linewidth=0.2)
@mpl3d_image_comparison(['trisurf3d_shaded.png'], tol=0.03)
def test_trisurf3d_shaded():
n_angles = 36
n_radii = 8
radii = np.linspace(0.125, 1.0, n_radii)
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi/n_angles
x = np.append(0, (radii*np.cos(angles)).flatten())
y = np.append(0, (radii*np.sin(angles)).flatten())
z = np.sin(-x*y)
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.plot_trisurf(x, y, z, color=[1, 0.5, 0], linewidth=0.2)
@mpl3d_image_comparison(['wireframe3d.png'])
def test_wireframe3d():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
ax.plot_wireframe(X, Y, Z, rcount=13, ccount=13)
@mpl3d_image_comparison(['wireframe3dzerocstride.png'])
def test_wireframe3dzerocstride():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
ax.plot_wireframe(X, Y, Z, rcount=13, ccount=0)
@mpl3d_image_comparison(['wireframe3dzerorstride.png'])
def test_wireframe3dzerorstride():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
ax.plot_wireframe(X, Y, Z, rstride=0, cstride=10)
def test_wireframe3dzerostrideraises():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
with pytest.raises(ValueError):
ax.plot_wireframe(X, Y, Z, rstride=0, cstride=0)
def test_mixedsamplesraises():
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
with pytest.raises(ValueError):
ax.plot_wireframe(X, Y, Z, rstride=10, ccount=50)
with pytest.raises(ValueError):
ax.plot_surface(X, Y, Z, cstride=50, rcount=10)
@mpl3d_image_comparison(
['quiver3d.png', 'quiver3d_pivot_middle.png', 'quiver3d_pivot_tail.png'])
def test_quiver3d():
x, y, z = np.ogrid[-1:0.8:10j, -1:0.8:10j, -1:0.6:3j]
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = (2/3)**0.5 * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)
for pivot in ['tip', 'middle', 'tail']:
ax = plt.figure().add_subplot(projection='3d')
ax.quiver(x, y, z, u, v, w, length=0.1, pivot=pivot, normalize=True)
@check_figures_equal(extensions=["png"])
def test_quiver3d_empty(fig_test, fig_ref):
fig_ref.add_subplot(projection='3d')
x = y = z = u = v = w = []
ax = fig_test.add_subplot(projection='3d')
ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tip', normalize=True)
@mpl3d_image_comparison(['quiver3d_masked.png'])
def test_quiver3d_masked():
fig = plt.figure()
ax = fig.gca(projection='3d')
# Using mgrid here instead of ogrid because masked_where doesn't
# seem to like broadcasting very much...
x, y, z = np.mgrid[-1:0.8:10j, -1:0.8:10j, -1:0.6:3j]
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
w = (2/3)**0.5 * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)
u = np.ma.masked_where((-0.4 < x) & (x < 0.1), u, copy=False)
v = np.ma.masked_where((0.1 < y) & (y < 0.7), v, copy=False)
ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tip', normalize=True)
@mpl3d_image_comparison(['poly3dcollection_closed.png'])
def test_poly3dcollection_closed():
fig = plt.figure()
ax = fig.gca(projection='3d')
poly1 = np.array([[0, 0, 1], [0, 1, 1], [0, 0, 0]], float)
poly2 = np.array([[0, 1, 1], [1, 1, 1], [1, 1, 0]], float)
c1 = art3d.Poly3DCollection([poly1], linewidths=3, edgecolor='k',
facecolor=(0.5, 0.5, 1, 0.5), closed=True)
c2 = art3d.Poly3DCollection([poly2], linewidths=3, edgecolor='k',
facecolor=(1, 0.5, 0.5, 0.5), closed=False)
ax.add_collection3d(c1)
ax.add_collection3d(c2)
def test_poly_collection_2d_to_3d_empty():
poly = PolyCollection([])
art3d.poly_collection_2d_to_3d(poly)
assert isinstance(poly, art3d.Poly3DCollection)
assert poly.get_paths() == []
@mpl3d_image_comparison(['poly3dcollection_alpha.png'])
def test_poly3dcollection_alpha():
fig = plt.figure()
ax = fig.gca(projection='3d')
poly1 = np.array([[0, 0, 1], [0, 1, 1], [0, 0, 0]], float)
poly2 = np.array([[0, 1, 1], [1, 1, 1], [1, 1, 0]], float)
c1 = art3d.Poly3DCollection([poly1], linewidths=3, edgecolor='k',
facecolor=(0.5, 0.5, 1), closed=True)
c1.set_alpha(0.5)
c2 = art3d.Poly3DCollection([poly2], linewidths=3, edgecolor='k',
facecolor=(1, 0.5, 0.5), closed=False)
c2.set_alpha(0.5)
ax.add_collection3d(c1)
ax.add_collection3d(c2)
@mpl3d_image_comparison(['axes3d_labelpad.png'], remove_text=False)
def test_axes3d_labelpad():
fig = plt.figure()
ax = Axes3D(fig)
# labelpad respects rcParams
assert ax.xaxis.labelpad == mpl.rcParams['axes.labelpad']
# labelpad can be set in set_label
ax.set_xlabel('X LABEL', labelpad=10)
assert ax.xaxis.labelpad == 10
ax.set_ylabel('Y LABEL')
ax.set_zlabel('Z LABEL')
# or manually
ax.yaxis.labelpad = 20
ax.zaxis.labelpad = -40
# Tick labels also respect tick.pad (also from rcParams)
for i, tick in enumerate(ax.yaxis.get_major_ticks()):
tick.set_pad(tick.get_pad() - i * 5)
@mpl3d_image_comparison(['axes3d_cla.png'], remove_text=False)
def test_axes3d_cla():
# fixed in pull request 4553
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.set_axis_off()
ax.cla() # make sure the axis displayed is 3D (not 2D)
@mpl3d_image_comparison(['axes3d_rotated.png'], remove_text=False)
def test_axes3d_rotated():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')
ax.view_init(90, 45) # look down, rotated. Should be square
def test_plotsurface_1d_raises():
x = np.linspace(0.5, 10, num=100)
y = np.linspace(0.5, 10, num=100)
X, Y = np.meshgrid(x, y)
z = np.random.randn(100)
fig = plt.figure(figsize=(14, 6))
ax = fig.add_subplot(1, 2, 1, projection='3d')
with pytest.raises(ValueError):
ax.plot_surface(X, Y, z)
def _test_proj_make_M():
# eye point
E = np.array([1000, -1000, 2000])
R = np.array([100, 100, 100])
V = np.array([0, 0, 1])
viewM = proj3d.view_transformation(E, R, V)
perspM = proj3d.persp_transformation(100, -100)
M = np.dot(perspM, viewM)
return M
def test_proj_transform():
M = _test_proj_make_M()
xs = np.array([0, 1, 1, 0, 0, 0, 1, 1, 0, 0]) * 300.0
ys = np.array([0, 0, 1, 1, 0, 0, 0, 1, 1, 0]) * 300.0
zs = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1]) * 300.0
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
ixs, iys, izs = proj3d.inv_transform(txs, tys, tzs, M)
np.testing.assert_almost_equal(ixs, xs)
np.testing.assert_almost_equal(iys, ys)
np.testing.assert_almost_equal(izs, zs)
def _test_proj_draw_axes(M, s=1, *args, **kwargs):
xs = [0, s, 0, 0]
ys = [0, 0, s, 0]
zs = [0, 0, 0, s]
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
o, ax, ay, az = zip(txs, tys)
lines = [(o, ax), (o, ay), (o, az)]
fig, ax = plt.subplots(*args, **kwargs)
linec = LineCollection(lines)
ax.add_collection(linec)
for x, y, t in zip(txs, tys, ['o', 'x', 'y', 'z']):
ax.text(x, y, t)
return fig, ax
@mpl3d_image_comparison(['proj3d_axes_cube.png'])
def test_proj_axes_cube():
M = _test_proj_make_M()
ts = '0 1 2 3 0 4 5 6 7 4'.split()
xs = np.array([0, 1, 1, 0, 0, 0, 1, 1, 0, 0]) * 300.0
ys = np.array([0, 0, 1, 1, 0, 0, 0, 1, 1, 0]) * 300.0
zs = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1]) * 300.0
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
fig, ax = _test_proj_draw_axes(M, s=400)
ax.scatter(txs, tys, c=tzs)
ax.plot(txs, tys, c='r')
for x, y, t in zip(txs, tys, ts):
ax.text(x, y, t)
ax.set_xlim(-0.2, 0.2)
ax.set_ylim(-0.2, 0.2)
@mpl3d_image_comparison(['proj3d_axes_cube_ortho.png'])
def test_proj_axes_cube_ortho():
E = np.array([200, 100, 100])
R = np.array([0, 0, 0])
V = np.array([0, 0, 1])
viewM = proj3d.view_transformation(E, R, V)
orthoM = proj3d.ortho_transformation(-1, 1)
M = np.dot(orthoM, viewM)
ts = '0 1 2 3 0 4 5 6 7 4'.split()
xs = np.array([0, 1, 1, 0, 0, 0, 1, 1, 0, 0]) * 100
ys = np.array([0, 0, 1, 1, 0, 0, 0, 1, 1, 0]) * 100
zs = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1]) * 100
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
fig, ax = _test_proj_draw_axes(M, s=150)
ax.scatter(txs, tys, s=300-tzs)
ax.plot(txs, tys, c='r')
for x, y, t in zip(txs, tys, ts):
ax.text(x, y, t)
ax.set_xlim(-200, 200)
ax.set_ylim(-200, 200)
def test_rot():
V = [1, 0, 0, 1]
rotated_V = proj3d.rot_x(V, np.pi / 6)
np.testing.assert_allclose(rotated_V, [1, 0, 0, 1])
V = [0, 1, 0, 1]
rotated_V = proj3d.rot_x(V, np.pi / 6)
np.testing.assert_allclose(rotated_V, [0, np.sqrt(3) / 2, 0.5, 1])
def test_world():
xmin, xmax = 100, 120
ymin, ymax = -100, 100
zmin, zmax = 0.1, 0.2
M = proj3d.world_transformation(xmin, xmax, ymin, ymax, zmin, zmax)
np.testing.assert_allclose(M,
[[5e-2, 0, 0, -5],
[0, 5e-3, 0, 5e-1],
[0, 0, 1e1, -1],
[0, 0, 0, 1]])
@mpl3d_image_comparison(['proj3d_lines_dists.png'])
def test_lines_dists():
fig, ax = plt.subplots(figsize=(4, 6), subplot_kw=dict(aspect='equal'))
xs = (0, 30)
ys = (20, 150)
ax.plot(xs, ys)
p0, p1 = zip(xs, ys)
xs = (0, 0, 20, 30)
ys = (100, 150, 30, 200)
ax.scatter(xs, ys)
dist = proj3d._line2d_seg_dist(p0, p1, (xs[0], ys[0]))
dist = proj3d._line2d_seg_dist(p0, p1, np.array((xs, ys)))
for x, y, d in zip(xs, ys, dist):
c = Circle((x, y), d, fill=0)
ax.add_patch(c)
ax.set_xlim(-50, 150)
ax.set_ylim(0, 300)
def test_autoscale():
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
ax.margins(x=0, y=.1, z=.2)
ax.plot([0, 1], [0, 1], [0, 1])
assert ax.get_w_lims() == (0, 1, -.1, 1.1, -.2, 1.2)
ax.autoscale(False)
ax.set_autoscalez_on(True)
ax.plot([0, 2], [0, 2], [0, 2])
assert ax.get_w_lims() == (0, 1, -.1, 1.1, -.4, 2.4)
@mpl3d_image_comparison(['axes3d_ortho.png'], remove_text=False)
def test_axes3d_ortho():
fig = plt.figure()
ax = fig.gca(projection='3d')
ax.set_proj_type('ortho')
@pytest.mark.parametrize('value', [np.inf, np.nan])
@pytest.mark.parametrize(('setter', 'side'), [
('set_xlim3d', 'left'),
('set_xlim3d', 'right'),
('set_ylim3d', 'bottom'),
('set_ylim3d', 'top'),
('set_zlim3d', 'bottom'),
('set_zlim3d', 'top'),
])
def test_invalid_axes_limits(setter, side, value):
limit = {side: value}
fig = plt.figure()
obj = fig.add_subplot(111, projection='3d')
with pytest.raises(ValueError):
getattr(obj, setter)(**limit)
class TestVoxels:
@mpl3d_image_comparison(['voxels-simple.png'])
def test_simple(self):
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
x, y, z = np.indices((5, 4, 3))
voxels = (x == y) | (y == z)
ax.voxels(voxels)
@mpl3d_image_comparison(['voxels-edge-style.png'])
def test_edge_style(self):
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
x, y, z = np.indices((5, 5, 4))
voxels = ((x - 2)**2 + (y - 2)**2 + (z-1.5)**2) < 2.2**2
v = ax.voxels(voxels, linewidths=3, edgecolor='C1')
# change the edge color of one voxel
v[max(v.keys())].set_edgecolor('C2')
@mpl3d_image_comparison(['voxels-named-colors.png'])
def test_named_colors(self):
"""Test with colors set to a 3d object array of strings."""
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
x, y, z = np.indices((10, 10, 10))
voxels = (x == y) | (y == z)
voxels = voxels & ~(x * y * z < 1)
colors = np.full((10, 10, 10), 'C0', dtype=np.object_)
colors[(x < 5) & (y < 5)] = '0.25'
colors[(x + z) < 10] = 'cyan'
ax.voxels(voxels, facecolors=colors)
@mpl3d_image_comparison(['voxels-rgb-data.png'])
def test_rgb_data(self):
"""Test with colors set to a 4d float array of rgb data."""
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
x, y, z = np.indices((10, 10, 10))
voxels = (x == y) | (y == z)
colors = np.zeros((10, 10, 10, 3))
colors[..., 0] = x / 9
colors[..., 1] = y / 9
colors[..., 2] = z / 9
ax.voxels(voxels, facecolors=colors)
@mpl3d_image_comparison(['voxels-alpha.png'])
def test_alpha(self):
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
x, y, z = np.indices((10, 10, 10))
v1 = x == y
v2 = np.abs(x - y) < 2
voxels = v1 | v2
colors = np.zeros((10, 10, 10, 4))
colors[v2] = [1, 0, 0, 0.5]
colors[v1] = [0, 1, 0, 0.5]
v = ax.voxels(voxels, facecolors=colors)
assert type(v) is dict
for coord, poly in v.items():
assert voxels[coord], "faces returned for absent voxel"
assert isinstance(poly, art3d.Poly3DCollection)
@mpl3d_image_comparison(['voxels-xyz.png'], tol=0.01, remove_text=False)
def test_xyz(self):
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
def midpoints(x):
sl = ()
for i in range(x.ndim):
x = (x[sl + np.index_exp[:-1]] +
x[sl + np.index_exp[1:]]) / 2.0
sl += np.index_exp[:]
return x
# prepare some coordinates, and attach rgb values to each
r, g, b = np.indices((17, 17, 17)) / 16.0
rc = midpoints(r)
gc = midpoints(g)
bc = midpoints(b)
# define a sphere about [0.5, 0.5, 0.5]
sphere = (rc - 0.5)**2 + (gc - 0.5)**2 + (bc - 0.5)**2 < 0.5**2
# combine the color components
colors = np.zeros(sphere.shape + (3,))
colors[..., 0] = rc
colors[..., 1] = gc
colors[..., 2] = bc
# and plot everything
ax.voxels(r, g, b, sphere,
facecolors=colors,
edgecolors=np.clip(2*colors - 0.5, 0, 1), # brighter
linewidth=0.5)
def test_calling_conventions(self):
x, y, z = np.indices((3, 4, 5))
filled = np.ones((2, 3, 4))
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
# all the valid calling conventions
for kw in (dict(), dict(edgecolor='k')):
ax.voxels(filled, **kw)
ax.voxels(filled=filled, **kw)
ax.voxels(x, y, z, filled, **kw)
ax.voxels(x, y, z, filled=filled, **kw)
# duplicate argument
with pytest.raises(TypeError, match='voxels'):
ax.voxels(x, y, z, filled, filled=filled)
# missing arguments
with pytest.raises(TypeError, match='voxels'):
ax.voxels(x, y)
# x, y, z are positional only - this passes them on as attributes of
# Poly3DCollection
with pytest.raises(AttributeError):
ax.voxels(filled=filled, x=x, y=y, z=z)
def test_line3d_set_get_data_3d():
x, y, z = [0, 1], [2, 3], [4, 5]
x2, y2, z2 = [6, 7], [8, 9], [10, 11]
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
lines = ax.plot(x, y, z)
line = lines[0]
np.testing.assert_array_equal((x, y, z), line.get_data_3d())
line.set_data_3d(x2, y2, z2)
np.testing.assert_array_equal((x2, y2, z2), line.get_data_3d())
@check_figures_equal(extensions=["png"])
def test_inverted(fig_test, fig_ref):
# Plot then invert.
ax = fig_test.add_subplot(projection="3d")
ax.plot([1, 1, 10, 10], [1, 10, 10, 10], [1, 1, 1, 10])
ax.invert_yaxis()
# Invert then plot.
ax = fig_ref.add_subplot(projection="3d")
ax.invert_yaxis()
ax.plot([1, 1, 10, 10], [1, 10, 10, 10], [1, 1, 1, 10])
def test_inverted_cla():
# GitHub PR #5450. Setting autoscale should reset
# axes to be non-inverted.
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
# 1. test that a new axis is not inverted per default
assert not ax.xaxis_inverted()
assert not ax.yaxis_inverted()
assert not ax.zaxis_inverted()
ax.set_xlim(1, 0)
ax.set_ylim(1, 0)
ax.set_zlim(1, 0)
assert ax.xaxis_inverted()
assert ax.yaxis_inverted()
assert ax.zaxis_inverted()
ax.cla()
assert not ax.xaxis_inverted()
assert not ax.yaxis_inverted()
assert not ax.zaxis_inverted()
def test_ax3d_tickcolour():
fig = plt.figure()
ax = Axes3D(fig)
ax.tick_params(axis='x', colors='red')
ax.tick_params(axis='y', colors='red')
ax.tick_params(axis='z', colors='red')
fig.canvas.draw()
for tick in ax.xaxis.get_major_ticks():
assert tick.tick1line._color == 'red'
for tick in ax.yaxis.get_major_ticks():
assert tick.tick1line._color == 'red'
for tick in ax.zaxis.get_major_ticks():
assert tick.tick1line._color == 'red'
@check_figures_equal(extensions=["png"])
def test_ticklabel_format(fig_test, fig_ref):
axs = fig_test.subplots(4, 5, subplot_kw={"projection": "3d"})
for ax in axs.flat:
ax.set_xlim(1e7, 1e7 + 10)
for row, name in zip(axs, ["x", "y", "z", "both"]):
row[0].ticklabel_format(
axis=name, style="plain")
row[1].ticklabel_format(
axis=name, scilimits=(-2, 2))
row[2].ticklabel_format(
axis=name, useOffset=not mpl.rcParams["axes.formatter.useoffset"])
row[3].ticklabel_format(
axis=name, useLocale=not mpl.rcParams["axes.formatter.use_locale"])
row[4].ticklabel_format(
axis=name,
useMathText=not mpl.rcParams["axes.formatter.use_mathtext"])
def get_formatters(ax, names):
return [getattr(ax, name).get_major_formatter() for name in names]
axs = fig_ref.subplots(4, 5, subplot_kw={"projection": "3d"})
for ax in axs.flat:
ax.set_xlim(1e7, 1e7 + 10)
for row, names in zip(
axs, [["xaxis"], ["yaxis"], ["zaxis"], ["xaxis", "yaxis", "zaxis"]]
):
for fmt in get_formatters(row[0], names):
fmt.set_scientific(False)
for fmt in get_formatters(row[1], names):
fmt.set_powerlimits((-2, 2))
for fmt in get_formatters(row[2], names):
fmt.set_useOffset(not mpl.rcParams["axes.formatter.useoffset"])
for fmt in get_formatters(row[3], names):
fmt.set_useLocale(not mpl.rcParams["axes.formatter.use_locale"])
for fmt in get_formatters(row[4], names):
fmt.set_useMathText(
not mpl.rcParams["axes.formatter.use_mathtext"])
@check_figures_equal(extensions=["png"])
def test_quiver3D_smoke(fig_test, fig_ref):
pivot = "middle"
# Make the grid
x, y, z = np.meshgrid(
np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.2),
np.arange(-0.8, 1, 0.8)
)
u = v = w = np.ones_like(x)
for fig, length in zip((fig_ref, fig_test), (1, 1.0)):
ax = fig.gca(projection="3d")
ax.quiver(x, y, z, u, v, w, length=length, pivot=pivot)
@image_comparison(["minor_ticks.png"], style="mpl20")
def test_minor_ticks():
ax = plt.figure().add_subplot(projection="3d")
ax.set_xticks([0.25], minor=True)
ax.set_xticklabels(["quarter"], minor=True)
ax.set_yticks([0.33], minor=True)
ax.set_yticklabels(["third"], minor=True)
ax.set_zticks([0.50], minor=True)
ax.set_zticklabels(["half"], minor=True)
@image_comparison(["equal_box_aspect.png"], style="mpl20")
def test_equal_box_aspect():
from itertools import product, combinations
fig = plt.figure()
ax = fig.add_subplot(111, projection="3d")
# Make data
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100)
x = np.outer(np.cos(u), np.sin(v))
y = np.outer(np.sin(u), np.sin(v))
z = np.outer(np.ones_like(u), np.cos(v))
# Plot the surface
ax.plot_surface(x, y, z)
# draw cube
r = [-1, 1]
for s, e in combinations(np.array(list(product(r, r, r))), 2):
if np.sum(np.abs(s - e)) == r[1] - r[0]:
ax.plot3D(*zip(s, e), color="b")
# Make axes limits
xyzlim = np.column_stack(
[ax.get_xlim3d(), ax.get_ylim3d(), ax.get_zlim3d()]
)
XYZlim = [min(xyzlim[0]), max(xyzlim[1])]
ax.set_xlim3d(XYZlim)
ax.set_ylim3d(XYZlim)
ax.set_zlim3d(XYZlim)
ax.axis('off')
ax.set_box_aspect((1, 1, 1))
def test_colorbar_pos():
num_plots = 2
fig, axs = plt.subplots(1, num_plots, figsize=(4, 5),
constrained_layout=True,
subplot_kw={'projection': '3d'})
for ax in axs:
p_tri = ax.plot_trisurf(np.random.randn(5), np.random.randn(5),
np.random.randn(5))
cbar = plt.colorbar(p_tri, ax=axs, orientation='horizontal')
fig.canvas.draw()
# check that actually on the bottom
assert cbar.ax.get_position().extents[1] < 0.2