import pytest from mpl_toolkits.mplot3d import Axes3D, axes3d, proj3d, art3d import matplotlib as mpl from matplotlib import cm from matplotlib import path as mpath from matplotlib import colors as mcolors from matplotlib.testing.decorators import image_comparison, check_figures_equal from matplotlib.cbook.deprecation import MatplotlibDeprecationWarning from matplotlib.collections import LineCollection, PolyCollection from matplotlib.patches import Circle import matplotlib.pyplot as plt import numpy as np def test_aspect_equal_error(): fig = plt.figure() ax = fig.add_subplot(111, projection='3d') with pytest.raises(NotImplementedError): ax.set_aspect('equal') @image_comparison(['bar3d.png'], remove_text=True) 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) @image_comparison(['bar3d_shaded.png'], remove_text=True) 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 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() @image_comparison(['bar3d_notshaded.png'], remove_text=True) 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]) @image_comparison(['contour3d.png'], remove_text=True, style='mpl20') 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) @image_comparison(['contourf3d.png'], remove_text=True) 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) @image_comparison(['contourf3d_fill.png'], remove_text=True) 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) @image_comparison(['tricontour.png'], remove_text=True, style='mpl20') 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) @image_comparison(['lines3d.png'], remove_text=True) 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) @image_comparison(['mixedsubplot.png'], remove_text=True) 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') @image_comparison(['scatter3d.png'], remove_text=True) 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') ax.scatter(np.arange(10, 20), np.arange(10, 20), np.arange(10, 20), c='b', marker='^') @image_comparison(['scatter3d_color.png'], remove_text=True) 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') @image_comparison(['plot_3d_from_2d.png'], remove_text=True) 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') @image_comparison(['surface3d.png'], remove_text=True) 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) @image_comparison(['surface3d_shaded.png'], remove_text=True) 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) @image_comparison(['text3d.png']) 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') @image_comparison(['trisurf3d.png'], remove_text=True, 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) @image_comparison(['trisurf3d_shaded.png'], remove_text=True, 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) @image_comparison(['wireframe3d.png'], remove_text=True) 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) @image_comparison(['wireframe3dzerocstride.png'], remove_text=True) 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) @image_comparison(['wireframe3dzerorstride.png'], remove_text=True) 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) @image_comparison(['quiver3d.png'], remove_text=True) def test_quiver3d(): fig = plt.figure() ax = fig.gca(projection='3d') 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 = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)) ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tip', normalize=True) @image_comparison(['quiver3d_empty.png'], remove_text=True) def test_quiver3d_empty(): fig = plt.figure() ax = fig.gca(projection='3d') x, y, z = np.ogrid[-1:0.8:0j, -1:0.8:0j, -1:0.6:0j] 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 = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)) ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tip', normalize=True) @image_comparison(['quiver3d_masked.png'], remove_text=True) 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 = (np.sqrt(2.0 / 3.0) * 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) @image_comparison(['quiver3d_pivot_middle.png'], remove_text=True) def test_quiver3d_pivot_middle(): fig = plt.figure() ax = fig.gca(projection='3d') 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 = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)) ax.quiver(x, y, z, u, v, w, length=0.1, pivot='middle', normalize=True) @image_comparison(['quiver3d_pivot_tail.png'], remove_text=True) def test_quiver3d_pivot_tail(): fig = plt.figure() ax = fig.gca(projection='3d') 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 = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) * np.sin(np.pi * z)) ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tail', normalize=True) @image_comparison(['poly3dcollection_closed.png'], remove_text=True) 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() == [] @image_comparison(['poly3dcollection_alpha.png'], remove_text=True) 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) @image_comparison(['axes3d_labelpad.png']) 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) @image_comparison(['axes3d_cla.png']) 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) 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 @image_comparison(['proj3d_axes_cube.png'], remove_text=True, style='default') 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) @image_comparison(['proj3d_axes_cube_ortho.png'], remove_text=True, style='default') 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]]) @image_comparison(['proj3d_lines_dists.png'], remove_text=True, style='default') 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) @image_comparison(['axes3d_ortho.png'], style='default') 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: @image_comparison(['voxels-simple.png'], remove_text=True) 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) @image_comparison(['voxels-edge-style.png'], remove_text=True, style='default') 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') @image_comparison(['voxels-named-colors.png'], remove_text=True) 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) @image_comparison(['voxels-rgb-data.png'], remove_text=True) 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) @image_comparison(['voxels-alpha.png'], remove_text=True) 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) @image_comparison(['voxels-xyz.png'], tol=0.01) 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) as exc: ax.voxels(x, y, z, filled, filled=filled) exc.match(".*voxels.*") # missing arguments with pytest.raises(TypeError) as exc: ax.voxels(x, y) exc.match(".*voxels.*") # 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_art3d_deprecated(): with pytest.warns(MatplotlibDeprecationWarning): art3d.norm_angle(0.0) with pytest.warns(MatplotlibDeprecationWarning): art3d.norm_text_angle(0.0) path = mpath.Path(np.empty((0, 2))) with pytest.warns(MatplotlibDeprecationWarning): art3d.path_to_3d_segment(path) with pytest.warns(MatplotlibDeprecationWarning): art3d.paths_to_3d_segments([path]) with pytest.warns(MatplotlibDeprecationWarning): art3d.path_to_3d_segment_with_codes(path) with pytest.warns(MatplotlibDeprecationWarning): art3d.paths_to_3d_segments_with_codes([path]) with pytest.warns(MatplotlibDeprecationWarning): art3d.get_colors([], 1) with pytest.warns(MatplotlibDeprecationWarning): art3d.zalpha([], []) def test_proj3d_deprecated(): with pytest.warns(MatplotlibDeprecationWarning): proj3d.line2d([0, 1], [0, 1]) with pytest.warns(MatplotlibDeprecationWarning): proj3d.line2d_dist([0, 1, 3], [0, 1]) with pytest.warns(MatplotlibDeprecationWarning): proj3d.mod([1, 1, 1]) vec = np.arange(4) M = np.ones((4, 4)) with pytest.warns(MatplotlibDeprecationWarning): proj3d.proj_transform_vec(vec, M) with pytest.warns(MatplotlibDeprecationWarning): proj3d.proj_transform_vec_clip(vec, M) with pytest.warns(MatplotlibDeprecationWarning): proj3d.vec_pad_ones(np.ones(3), np.ones(3), np.ones(3)) with pytest.warns(MatplotlibDeprecationWarning): proj3d.proj_trans_clip_points(np.ones((4, 3)), M) 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)