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  • python绘制三维图的详细教程

    【相关推荐:python3视频教程

    本文仅仅梳理最基本的绘图方法。

    一、初始化

    假设已经安装了matplotlib工具包。

    利用matplotlib.figure.Figure创建一个图框:

    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3D import Axes3D
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')

    二、直线绘制(Line plots)

    基本用法:

    ax.plot(x,y,z,label=' ')

    code:

    import matplotlib as mpl
    from mpl_toolkits.mplot3d import Axes3D
    import numpy as np
    import matplotlib.pyplot as plt
     
    mpl.rcParams['legend.fontsize'] = 10
     
    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, label='parametric curve')
    ax.legend()
     
    plt.show()

    三、散点绘制(Scatter plots)

    基本用法:

    ax.scatter(xs, ys, zs, s=20, c=None, depthshade=True, *args, *kwargs)
    • xs,ys,zs:输入数据;
    • s:scatter点的尺寸
    • c:颜色,如c = ‘r’就是红色;
    • depthshase:透明化,True为透明,默认为True,False为不透明
    • *args等为扩展变量,如maker = ‘o’,则scatter结果为’o‘的形状

    code:

    from mpl_toolkits.mplot3d import Axes3D
    import matplotlib.pyplot as plt
    import numpy as np
     
     
    def randrange(n, vmin, vmax):
        '''
        Helper function to make an array of random numbers having shape (n, )
        with each number distributed UnifORM(vmin, vmax).
        '''
        return (vmax - vmin)*np.random.rand(n) + vmin
     
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
     
    n = 100
     
    # For each set of style and range settings, plot n random points in the box
    # defined by x in [23, 32], y in [0, 100], z in [zlow, zhigh].
    for c, m, zlow, zhigh in [('r', 'o', -50, -25), ('b', '^', -30, -5)]:
        xs = randrange(n, 23, 32)
        ys = randrange(n, 0, 100)
        zs = randrange(n, zlow, zhigh)
        ax.scatter(xs, ys, zs, c=c, marker=m)
     
    ax.set_xlabel('X Label')
    ax.set_ylabel('Y Label')
    ax.set_zlabel('Z Label')
     
    plt.show()

    四、线框图(Wireframe plots)

    基本用法:

    ax.plot_wireframe(X, Y, Z, *args, **kwargs)
    • X,Y,Z:输入数据
    • rstride:行步长
    • cstride:列步长
    • rcount:行数上限
    • ccount:列数上限

    code:

    from mpl_toolkits.mplot3d import axes3d
    import matplotlib.pyplot as plt
     
     
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
     
    # Grab some test data.
    X, Y, Z = axes3d.get_test_data(0.05)
     
    # Plot a basic wireframe.
    ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
     
    plt.show()

    五、表面图(Surface plots)

    基本用法:

    ax.plot_surface(X, Y, Z, *args, **kwargs)
    • X,Y,Z:数据
    • rstride、cstride、rcount、ccount:同Wireframe plots定义
    • color:表面颜色
    • cmap:图层

    code:

    from mpl_toolkits.mplot3d import Axes3D
    import matplotlib.pyplot as plt
    from matplotlib import cm
    from matplotlib.ticker import LinearLocator, FormatStrFormatter
    import numpy as np
     
     
    fig = plt.figure()
    ax = fig.gca(projection='3d')
     
    # Make data.
    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)
     
    # Plot the surface.
    surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
                           linewidth=0, antialiased=False)
     
    # Customize the z axis.
    ax.set_zlim(-1.01, 1.01)
    ax.zaxis.set_major_locator(LinearLocator(10))
    ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))
     
    # Add a color bar which maps values to colors.
    fig.colorbar(surf, shrink=0.5, aspect=5)
     
    plt.show()

    六、三角表面图(Tri-Surface plots)

    基本用法:

    ax.plot_trisurf(*args, **kwargs)
    • X,Y,Z:数据
    • 其他参数类似surface-plot

    code:

    from mpl_toolkits.mplot3d import Axes3D
    import matplotlib.pyplot as plt
    import numpy as np
     
     
    n_radii = 8
    n_angles = 36
     
    # Make radii and angles spaces (radius r=0 omitted to eliminate duplication).
    radii = np.linspace(0.125, 1.0, n_radii)
    angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
     
    # Repeat all angles for each radius.
    angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
     
    # Convert polar (radii, angles) coords to cartesian (x, y) coords.
    # (0, 0) is manually added at this stage,  so there will be no duplicate
    # points in the (x, y) plane.
    x = np.append(0, (radii*np.cos(angles)).flatten())
    y = np.append(0, (radii*np.sin(angles)).flatten())
     
    # Compute z to make the pringle surface.
    z = np.sin(-x*y)
     
    fig = plt.figure()
    ax = fig.gca(projection='3d')
     
    ax.plot_trisurf(x, y, z, linewidth=0.2, antialiased=True)
     
    plt.show()

    七、等高线(Contour plots)

    基本用法:

    ax.contour(X, Y, Z, *args, **kwargs)

    code:

    from mpl_toolkits.mplot3d import axes3d
    import matplotlib.pyplot as plt
    from matplotlib import cm
     
    fig = plt.figure()
    ax = fig.add_subplot(111, projection='3d')
    X, Y, Z = axes3d.get_test_data(0.05)
    cset = ax.contour(X, Y, Z, cmap=cm.coolwarm)
    ax.clabel(cset, fontsize=9, inline=1)
     
    plt.show()

    二维的等高线,同样可以配合三维表面图一起绘制:

    code:

    from mpl_toolkits.mplot3d import axes3d
    from mpl_toolkits.mplot3d import axes3d
    import matplotlib.pyplot as plt
    from matplotlib import cm
     
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    X, Y, Z = axes3d.get_test_data(0.05)
    ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
    cset = ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
    cset = ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
    cset = ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
     
    ax.set_xlabel('X')
    ax.set_xlim(-40, 40)
    ax.set_ylabel('Y')
    ax.set_ylim(-40, 40)
    ax.set_zlabel('Z')
    ax.set_zlim(-100, 100)
     
    plt.show()

    也可以是三维等高线在二维平面的投影:

    code:

    from mpl_toolkits.mplot3d import axes3d
    import matplotlib.pyplot as plt
    from matplotlib import cm
     
    fig = plt.figure()
    ax = fig.gca(projection='3d')
    X, Y, Z = axes3d.get_test_data(0.05)
    ax.plot_surface(X, Y, Z, rstride=8, cstride=8, alpha=0.3)
    cset = ax.contourf(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
    cset = ax.contourf(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
    cset = ax.contourf(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
     
    ax.set_xlabel('X')
    ax.set_xlim(-40, 40)
    ax.set_ylabel('Y')
    ax.set_ylim(-40, 40)
    ax.set_zlabel('Z')
    ax.set_zlim(-100, 100)
     
    plt.show()

    八、Bar plots(条形图)

    基本用法:

    ax.bar(left, height, zs=0, zdir='z', *args, **kwargs
    • x,y,zs = z,数据
    • zdir:条形图平面化的方向,具体可以对应代码理解。

    code:

    from mpl_toolkits.mplot3d import Axes3D
    import matplotlib.pyplot as plt
    import numpy as np
     
    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.random.rand(20)
     
        # You can provide either a single color or an array. To demonstrate this,
        # the first bar of each set will be colored cyan.
        cs = [c] * len(xs)
        cs[0] = 'c'
        ax.bar(xs, ys, zs=z, zdir='y', color=cs, alpha=0.8)
     
    ax.set_xlabel('X')
    ax.set_ylabel('Y')
    ax.set_zlabel('Z')
     
    plt.show()

    九、子图绘制(subplot)

    A-不同的2-D图形,分布在3-D空间,其实就是投影空间不空,对应code:

    from mpl_toolkits.mplot3d import Axes3D
    import numpy as np
    import matplotlib.pyplot as plt
     
    fig = plt.figure()
    ax = fig.gca(projection='3d')
     
    # Plot a sin curve using the x and y axes.
    x = np.linspace(0, 1, 100)
    y = np.sin(x * 2 * np.pi) / 2 + 0.5
    ax.plot(x, y, zs=0, zdir='z', label='curve in (x,y)')
     
    # Plot scatterplot data (20 2D points per colour) on the x and z axes.
    colors = ('r', 'g', 'b', 'k')
    x = np.random.sample(20*len(colors))
    y = np.random.sample(20*len(colors))
    c_list = []
    for c in colors:
        c_list.append([c]*20)
    # By using zdir='y', the y value of these points is fixed to the zs value 0
    # and the (x,y) points are plotted on the x and z axes.
    ax.scatter(x, y, zs=0, zdir='y', c=c_list, label='points in (x,z)')
     
    # Make legend, set axes limits and labels
    ax.legend()
    ax.set_xlim(0, 1)
    ax.set_ylim(0, 1)
    ax.set_zlim(0, 1)
    ax.set_xlabel('X')
    ax.set_ylabel('Y')
    ax.set_zlabel('Z')

    B-子图Subplot用法

    与MATLAB不同的是,如果一个四子图效果,如:

    MATLAB:

    subplot(2,2,1)
    subplot(2,2,2)
    subplot(2,2,[3,4])

    Python:

    subplot(2,2,1)
    subplot(2,2,2)
    subplot(2,1,2)

    code:

    import matplotlib.pyplot as plt
    from mpl_toolkits.mplot3d.axes3d import Axes3D, get_test_data
    from matplotlib import cm
    import numpy as np
     
     
    # set up a figure twice as wide as it is tall
    fig = plt.figure(figsize=plt.figaspect(0.5))
     
    #===============
    #  First subplot
    #===============
    # set up the axes for the first plot
    ax = fig.add_subplot(2, 2, 1, projection='3d')
     
    # plot a 3D surface like in the example mplot3d/surface3d_demo
    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)
    surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
                           linewidth=0, antialiased=False)
    ax.set_zlim(-1.01, 1.01)
    fig.colorbar(surf, shrink=0.5, aspect=10)
     
    #===============
    # Second subplot
    #===============
    # set up the axes for the second plot
    ax = fig.add_subplot(2,1,2, projection='3d')
     
    # plot a 3D wireframe like in the example mplot3d/wire3d_demo
    X, Y, Z = get_test_data(0.05)
    ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)
     
    plt.show()

    补充:

    文本注释的基本用法:

    code:

    from mpl_toolkits.mplot3d import Axes3D
    import matplotlib.pyplot as plt
     
     
    fig = plt.figure()
    ax = fig.gca(projection='3d')
     
    # Demo 1: zdir
    zdirs = (None, 'x', 'y', 'z', (1, 1, 0), (1, 1, 1))
    xs = (1, 4, 4, 9, 4, 1)
    ys = (2, 5, 8, 10, 1, 2)
    zs = (10, 3, 8, 9, 1, 8)
     
    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)
     
    # Demo 2: color
    ax.text(9, 0, 0, "red", color='red')
     
    # Demo 3: text2D
    # Placement 0, 0 would be the bottom left, 1, 1 would be the top right.
    ax.text2D(0.05, 0.95, "2D Text", transform=ax.transAxes)
     
    # Tweaking display region and labels
    ax.set_xlim(0, 10)
    ax.set_ylim(0, 10)
    ax.set_zlim(0, 10)
    ax.set_xlabel('X axis')
    ax.set_ylabel('Y axis')
    ax.set_zlabel('Z axis')
     
    plt.show()

    【相关推荐:Python3视频教程 】

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