简体   繁体   English

Matplotlib:注释 3D 散点图

[英]Matplotlib: Annotating a 3D scatter plot

I'm trying to generate a 3D scatter plot using Matplotlib.我正在尝试使用 Matplotlib 生成 3D 散点图。 I would like to annotate individual points like the 2D case here: Matplotlib: How to put individual tags for a scatter plot .我想在这里注释单个点,例如 2D 案例: Matplotlib: How to put individual tags for a scatter plot

I've tried to use this function and consulted the Matplotlib docoment but found it seems that the library does not support 3D annotation.我尝试使用此函数并查阅了 Matplotlib 文档,但发现该库似乎不支持 3D 注释。 Does anyone know how to do this?有谁知道如何做到这一点?

Thanks!谢谢!

Maybe easier via ax.text(...):也许通过 ax.text(...) 更容易:

from matplotlib import pyplot
from mpl_toolkits.mplot3d import Axes3D
from numpy.random import rand
from pylab import figure


m=rand(3,3) # m is an array of (x,y,z) coordinate triplets

fig = figure()
ax = Axes3D(fig)


for i in range(len(m)): #plot each point + it's index as text above
 ax.scatter(m[i,0],m[i,1],m[i,2],color='b') 
 ax.text(m[i,0],m[i,1],m[i,2],  '%s' % (str(i)), size=20, zorder=1,  
 color='k') 

ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')
pyplot.show()

在此处输入图片说明

Calculate the 2D position of the point, and use it create the annotation.计算点的二维位置,并使用它创建注释。 If you need interactive with the figure, you can recalculate the location when mouse released.如果您需要与图形交互,您可以在鼠标释放时重新计算位置。

import pylab
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d
fig = pylab.figure()
ax = fig.add_subplot(111, projection = '3d')
x = y = z = [1, 2, 3]
sc = ax.scatter(x,y,z)
# now try to get the display coordinates of the first point

x2, y2, _ = proj3d.proj_transform(1,1,1, ax.get_proj())

label = pylab.annotate(
    "this", 
    xy = (x2, y2), xytext = (-20, 20),
    textcoords = 'offset points', ha = 'right', va = 'bottom',
    bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),
    arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))

def update_position(e):
    x2, y2, _ = proj3d.proj_transform(1,1,1, ax.get_proj())
    label.xy = x2,y2
    label.update_positions(fig.canvas.renderer)
    fig.canvas.draw()
fig.canvas.mpl_connect('button_release_event', update_position)
pylab.show()

在此处输入图片说明

In the following posts [1] , [2] the plotting of 3D arrows in matplotlib is discussed.在以下帖子[1][2]中讨论了 matplotlib 中 3D 箭头的绘制。

Similarly Annotation3D class (inherited from Annotation) can be created:同样可以创建 Annotation3D 类(继承自 Annotation):

from mpl_toolkits.mplot3d.proj3d import proj_transform
from matplotlib.text import Annotation

class Annotation3D(Annotation):
    '''Annotate the point xyz with text s'''

    def __init__(self, s, xyz, *args, **kwargs):
        Annotation.__init__(self,s, xy=(0,0), *args, **kwargs)
        self._verts3d = xyz        

    def draw(self, renderer):
        xs3d, ys3d, zs3d = self._verts3d
        xs, ys, zs = proj_transform(xs3d, ys3d, zs3d, renderer.M)
        self.xy=(xs,ys)
        Annotation.draw(self, renderer)

Further, we can define the annotate3D() function:此外,我们可以定义 annotate3D() 函数:

def annotate3D(ax, s, *args, **kwargs):
    '''add anotation text s to to Axes3d ax'''

    tag = Annotation3D(s, *args, **kwargs)
    ax.add_artist(tag)

Using this function annotation tags can be added to Axes3d as in example bellow:使用此函数注释标签可以添加到 Axes3d 中,如下例所示:

3D 图形示例

import matplotlib.pyplot as plt    
from mpl_toolkits.mplot3d import axes3d
from mpl_toolkits.mplot3d.art3d import Line3DCollection

# data: coordinates of nodes and links
xn = [1.1, 1.9, 0.1, 0.3, 1.6, 0.8, 2.3, 1.2, 1.7, 1.0, -0.7, 0.1, 0.1, -0.9, 0.1, -0.1, 2.1, 2.7, 2.6, 2.0]
yn = [-1.2, -2.0, -1.2, -0.7, -0.4, -2.2, -1.0, -1.3, -1.5, -2.1, -0.7, -0.3, 0.7, -0.0, -0.3, 0.7, 0.7, 0.3, 0.8, 1.2]
zn = [-1.6, -1.5, -1.3, -2.0, -2.4, -2.1, -1.8, -2.8, -0.5, -0.8, -0.4, -1.1, -1.8, -1.5, 0.1, -0.6, 0.2, -0.1, -0.8, -0.4]
group = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 2, 2, 2, 3, 3, 3, 3]
edges = [(1, 0), (2, 0), (3, 0), (3, 2), (4, 0), (5, 0), (6, 0), (7, 0), (8, 0), (9, 0), (11, 10), (11, 3), (11, 2), (11, 0), (12, 11), (13, 11), (14, 11), (15, 11), (17, 16), (18, 16), (18, 17), (19, 16), (19, 17), (19, 18)]
xyzn = zip(xn, yn, zn)
segments = [(xyzn[s], xyzn[t]) for s, t in edges]                

# create figure        
fig = plt.figure(dpi=60)
ax = fig.gca(projection='3d')
ax.set_axis_off()

# plot vertices
ax.scatter(xn,yn,zn, marker='o', c = group, s = 64)    
# plot edges
edge_col = Line3DCollection(segments, lw=0.2)
ax.add_collection3d(edge_col)
# add vertices annotation.
for j, xyz_ in enumerate(xyzn): 
    annotate3D(ax, s=str(j), xyz=xyz_, fontsize=10, xytext=(-3,3),
               textcoords='offset points', ha='right',va='bottom')    
plt.show()

In case you want to make @msch's answer rotate:如果您想让@msch 的答案轮换:

在此处输入图片说明

from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from numpy.random import rand
from IPython.display import HTML
from matplotlib import animation

m = rand(3,3) # m is an array of (x,y,z) coordinate triplets

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

for i in range(len(m)): # plot each point + it's index as text above
  x = m[i,0]
  y = m[i,1]
  z = m[i,2]
  label = i
  ax.scatter(x, y, z, color='b')
  ax.text(x, y, z, '%s' % (label), size=20, zorder=1, color='k')

ax.set_xlabel('x')
ax.set_ylabel('y')
ax.set_zlabel('z')

def animate(frame):
  ax.view_init(30, frame/4)
  plt.pause(.001)
  return fig

anim = animation.FuncAnimation(fig, animate, frames=200, interval=50)
HTML(anim.to_html5_video())

If you have many data points, the chart can get very cluttered if you annotate them all.如果您有很多数据点,如果您对它们全部进行注释,图表可能会变得非常混乱。 The following solution (built on top of HYRY's answer) implements a mouse-over (pop-over) solution for data points in 3d charts.以下解决方案(建立在 HYRY 的回答之上)为 3d 图表中的数据点实现了鼠标悬停(弹出)解决方案。 Only the data point next to your mouse position will be annotated.只会注释鼠标位置旁边的数据点。 After every mouse movement, the distance of the mouse pointer to all data points is calculated, and the closest point is annotated.每次鼠标移动后,计算鼠标指针到所有数据点的距离,并标注最近的点。

import matplotlib.pyplot as plt, numpy as np
from mpl_toolkits.mplot3d import proj3d

def visualize3DData (X):
    """Visualize data in 3d plot with popover next to mouse position.

    Args:
        X (np.array) - array of points, of shape (numPoints, 3)
    Returns:
        None
    """
    fig = plt.figure(figsize = (16,10))
    ax = fig.add_subplot(111, projection = '3d')
    ax.scatter(X[:, 0], X[:, 1], X[:, 2], depthshade = False, picker = True)


    def distance(point, event):
        """Return distance between mouse position and given data point

        Args:
            point (np.array): np.array of shape (3,), with x,y,z in data coords
            event (MouseEvent): mouse event (which contains mouse position in .x and .xdata)
        Returns:
            distance (np.float64): distance (in screen coords) between mouse pos and data point
        """
        assert point.shape == (3,), "distance: point.shape is wrong: %s, must be (3,)" % point.shape

        # Project 3d data space to 2d data space
        x2, y2, _ = proj3d.proj_transform(point[0], point[1], point[2], plt.gca().get_proj())
        # Convert 2d data space to 2d screen space
        x3, y3 = ax.transData.transform((x2, y2))

        return np.sqrt ((x3 - event.x)**2 + (y3 - event.y)**2)


    def calcClosestDatapoint(X, event):
        """"Calculate which data point is closest to the mouse position.

        Args:
            X (np.array) - array of points, of shape (numPoints, 3)
            event (MouseEvent) - mouse event (containing mouse position)
        Returns:
            smallestIndex (int) - the index (into the array of points X) of the element closest to the mouse position
        """
        distances = [distance (X[i, 0:3], event) for i in range(X.shape[0])]
        return np.argmin(distances)


    def annotatePlot(X, index):
        """Create popover label in 3d chart

        Args:
            X (np.array) - array of points, of shape (numPoints, 3)
            index (int) - index (into points array X) of item which should be printed
        Returns:
            None
        """
        # If we have previously displayed another label, remove it first
        if hasattr(annotatePlot, 'label'):
            annotatePlot.label.remove()
        # Get data point from array of points X, at position index
        x2, y2, _ = proj3d.proj_transform(X[index, 0], X[index, 1], X[index, 2], ax.get_proj())
        annotatePlot.label = plt.annotate( "Value %d" % index,
            xy = (x2, y2), xytext = (-20, 20), textcoords = 'offset points', ha = 'right', va = 'bottom',
            bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),
            arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))
        fig.canvas.draw()


    def onMouseMotion(event):
        """Event that is triggered when mouse is moved. Shows text annotation over data point closest to mouse."""
        closestIndex = calcClosestDatapoint(X, event)
        annotatePlot (X, closestIndex)

    fig.canvas.mpl_connect('motion_notify_event', onMouseMotion)  # on mouse motion
    plt.show()


if __name__ == '__main__':
    X = np.random.random((30,3))
    visualize3DData (X)

Here's a slightly more general form of HYRY's excellent answer.这是 HYRY 出色答案的更一般形式。 It works for any list of points and labels.它适用于任何点和标签列表。

import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d

points = np.array([(1,1,1), (2,2,2)])
labels = ['billy', 'bobby']

fig = plt.figure()
ax = fig.add_subplot(111, projection = '3d')
xs, ys, zs = np.split(points, 3, axis=1)
sc = ax.scatter(xs,ys,zs)

# if this code is placed inside a function, then
# we must use a predefined global variable so that
# the update function has access to it. I'm not
# sure why update_positions() doesn't get access
# to its enclosing scope in this case.
global labels_and_points
labels_and_points = []

for txt, x, y, z in zip(labels, xs, ys, zs):
    x2, y2, _ = proj3d.proj_transform(x,y,z, ax.get_proj())
    label = plt.annotate(
        txt, xy = (x2, y2), xytext = (-20, 20),
        textcoords = 'offset points', ha = 'right', va = 'bottom',
        bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),
        arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))
    labels_and_points.append((label, x, y, z))


def update_position(e):
    for label, x, y, z in labels_and_points:
        x2, y2, _ = proj3d.proj_transform(x, y, z, ax.get_proj())
        label.xy = x2,y2
        label.update_positions(fig.canvas.renderer)
    fig.canvas.draw()

fig.canvas.mpl_connect('motion_notify_event', update_position)

plt.show()

There's an annoying name space problem that I could only fix by (hackily) using a global variable.有一个烦人的命名空间问题,我只能通过(hackily)使用全局变量来解决。 If anyone can provide a better solution or explain what's going on, please let me know!如果有人可以提供更好的解决方案或解释发生了什么,请告诉我!

This answer is based on previous answer by user315582.此答案基于 user315582 之前的答案。 I did a few modifications to provide a solution without using global variables.我做了一些修改以提供不使用全局变量的解决方案。

import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import proj3d

def main():
    fig = plt.figure()
    ax = fig.add_subplot(111, projection = '3d')
    points = np.array([(1,1,1), (2,2,2)])
    labels = ['billy', 'bobby']
    plotlabels = []
    xs, ys, zs = np.split(points, 3, axis=1)
    sc = ax.scatter(xs,ys,zs)

    for txt, x, y, z in zip(labels, xs, ys, zs):
        x2, y2, _ = proj3d.proj_transform(x,y,z, ax.get_proj())
        label = plt.annotate(
            txt, xy = (x2, y2), xytext = (-20, 20),
            textcoords = 'offset points', ha = 'right', va = 'bottom',
            bbox = dict(boxstyle = 'round,pad=0.5', fc = 'yellow', alpha = 0.5),
            arrowprops = dict(arrowstyle = '-', connectionstyle = 'arc3,rad=0'))
        plotlabels.append(label)
    fig.canvas.mpl_connect('motion_notify_event', lambda event: update_position(event,fig,ax,zip(plotlabels, xs, ys, zs)))
    plt.show()


def update_position(e,fig,ax,labels_and_points):
    for label, x, y, z in labels_and_points:
        x2, y2, _ = proj3d.proj_transform(x, y, z, ax.get_proj())
        label.xy = x2,y2
        label.update_positions(fig.canvas.renderer)
    fig.canvas.draw()



if __name__ == '__main__':
    main()

声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM