Matplotlib：註釋一個三維散點圖

Question

我想使用Matplotlib生成三維散點圖。我想在這裏註釋個別點，如2D案例： Matplotlib: How to put individual tags for a scatter plot。

我試過使用這個函數，並諮詢了Matplotlib docoment，但發現它似乎不支持3D註釋。有誰知道如何做到這一點？

謝謝！

Answer 1

計算點的2D位置，並使用它創建註釋。如果您需要與圖形交互，則可以在鼠標釋放時重新計算位置。

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() 

Answer 2

這裏的HYRY的出色答卷的一個稍微更一般的形式。它適用於任何點和標籤列表。

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() 

有一個惱人的名字空間問題，我只能通過使用全局變量來修復。如果有人能提供更好的解決方案或解釋發生了什麼，請告訴我！

Answer 3

此答案基於user315582先前的回答。我做了一些修改以提供一個不使用全局變量的解決方案。

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() 

Answer 4

也許很容易通過ax.text（...）：

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() 

Answer 5

如果你有很多個數據點，如果你註釋他們所有的圖表會造成非常雜亂。以下解決方案（建立在HYRY答案之上）爲3D圖表中的數據點實現了鼠標懸停（彈出式）解決方案。只有鼠標位置旁邊的數據點纔會被註釋。在每次鼠標移動之後，計算鼠標指針到所有數據點的距離，並對最近的點進行註釋。

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) 

Answer 6

在下面的帖子[1]，[2] 3D箭頭在matplotlib繪製了討論。（從註釋繼承）

同樣Annotation3D類可以被創建：

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) 

此外，我們可以定義annotate3D（）函數：

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

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

使用此功能註釋標籤可以被添加到Axes3d爲例波紋管在：

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() 

Answer 7

在你想@ MSCH的回答情況下旋轉：

from mpl_toolkits.mplot3d import axes3d 
import matplotlib.pyplot as plt 
from numpy.random import rand 

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') 

for angle in range(0, 360): 
    ax.view_init(30, angle) 
    plt.draw() 
    plt.pause(.001)