动画散点图
Animate scatter plot
我正在构建一个 Python 工具，用于在 3D 中可视化数据结构。下面的代码是完整的程序，它甚至设置了 运行 一个带有一些随机数据的默认测试模型；你只需要 numpy 和 matplotlib。基本上，您声明一个节点，将它连接到其他节点，然后它就形成了漂亮的 3D 网络。我希望能够调用 switchNode() 并让它在黑色和白色之间翻转节点的颜色。按照现在的工作方式，每次实例化一个节点时，都会将绘图添加到另一个数据点。我对 matplotlib 的动画工具不够熟悉，不知道这样做的最佳方法（我尝试遵循 another post 中的示例在第 83 行被注释掉，希望有人能给我一些提示。谢谢！！
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import matplotlib.animation as anim
# user-defined variables
debug = False
axisOn = False
labelsOn = True
maxNodes = 20
edgeColor = 'b'
dottedLine = ':'
darkGrey = '#191919'
lightGrey = '#a3a3a3'
plotBackgroundColor = lightGrey
fontColor = darkGrey
gridColor = 'k'
numFrames = 200
# global variables
fig = None
hTable = []
ax = None
numNodes = 0
# initialize plot
def initPlot():
global ax, fontColor, fig
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d', axisbg=plotBackgroundColor)
if axisOn == False:
ax.set_axis_off()
else:
ax.set_axis_on()
fontColor = darkGrey
# gives n random float values between vmin and vmax
def randrange(n, vmin, vmax):
return (vmax - vmin) * np.random.rand(n) + vmin
# builds an empty node with a given value, helper method for makeNode
def makeNodeS(value):
global hTable, numNodes
n = Node(value)
hTable.append(n)
numNodes = len(hTable)
return n
# builds a node with given parameters
def makeNode(value, location, color, marker):
n = makeNodeS(value)
n.setLoc(location)
n.setStyle(color, marker)
if debug:
print("Building node {} at {} with color = {}, marker = {}, and associations = {}.".format(value, location, color, marker, n.assocs))
return n
# aggregate nodes in hTable and plot them in 3D
def plotNodes():
global hTable
if debug:
print("Plotting Graph...")
for elem in hTable:
if debug:
print(" Plotting node {}...".format(elem.value))
global fig, numFrames
scat = ax.scatter(elem.location[0], elem.location[1], elem.location[2], c=elem.color, marker=elem.marker)
for c in elem.assocs:
if (getNode(c).value != elem.value):
if elem.count in getNode(c).assocs: # if the two nodes are associated to each other, draw solid line
ax.plot([elem.location[0], getNode(c).location[0]], [elem.location[1], getNode(c).location[1]], [elem.location[2], getNode(c).location[2]], edgeColor)
if debug:
print(" Plotting double edge between {} and {}...".format(elem.value, getNode(c).value))
else:
ax.plot([elem.location[0], getNode(c).location[0]], [elem.location[1], getNode(c).location[1]], [elem.location[2], getNode(c).location[2]], edgeColor + dottedLine)
if debug:
print(" Plotting single edge from {} to {}...".format(elem.value, getNode(c).value))
#ani = anim.FuncAnimation(fig, update_plot, frames=xrange(numFrames), fargs=(['b', 'w'], scat))
# build single connection from node A to node B
def sConnect(nodeA, nodeB):
nodeA.addAssoc(nodeB)
if debug:
print(" Drawing single connection from node {} to node {}...".format(nodeA.value, nodeB.value))
# build double connection from node A to node B, and from node B to node A
def dConnect(nodeA, nodeB):
if debug:
print("\nDouble node connection steps:")
sConnect(nodeA, nodeB)
sConnect(nodeB, nodeA)
# update scatter with new color data
def update_plot(i, data, scat):
scat.set_array(data[i])
return scat
# returns the node with given count
def getNode(count):
global hTable
n = hTable[count-1]
return n
# set up axis info
def defineAxis():
ax.set_xlabel('X Label')
ax.xaxis.label.set_color(lightGrey)
ax.tick_params(axis='x', colors=lightGrey)
ax.set_ylabel('Y Label')
ax.yaxis.label.set_color(lightGrey)
ax.tick_params(axis='y', colors=lightGrey)
ax.set_zlabel('Z Label')
ax.zaxis.label.set_color(lightGrey)
ax.tick_params(axis='z', colors=lightGrey)
# randomly populate nodes and connect them
def test():
for i in range (0, maxNodes):
rand = np.random.rand(2)
if (0 <= rand[0] <= 0.25):
q = makeNode(i, np.random.rand(3), 'r', '^')
elif (0.25 < rand[0] <= 0.5):
q = makeNode(i, np.random.rand(3), 'b', 'o')
elif (0.5 < rand[0] <= 0.75):
q = makeNode(i, np.random.rand(3), 'g', 'v')
elif (0.75 < rand[0]):
q = makeNode(i, np.random.rand(3), 'w', 'o')
if (0 < i < maxNodes-1):
if (rand[1] <= 0.2):
dConnect(q, getNode(q.count-1))
elif (rand[1] < 0.5):
sConnect(q, getNode(q.count-1))
# randomly populate binary nodes and connect them
def test2():
for i in range (0, maxNodes):
rand = np.random.rand(2)
if (0 <= rand[0] <= 0.80):
q = makeNode(i, np.random.rand(3), 'k', 'o')
else:
q = makeNode(i, np.random.rand(3), 'w', 'o')
if (i > 0):
if (rand[1] <= 0.2):
dConnect(q, getNode(q.count-1))
elif (rand[1] > 0.2):
sConnect(q, getNode(q.count-1))
# switches a binary node between black and white
def switchNode(count):
q = getNode(count)
if (q.color == 'b'):
q.color = 'w'
else:
q.color = 'b'
# main program
def main():
## MAIN PROGRAM
initPlot()
test2()
plotNodes()
defineAxis()
plt.show()
# class structure for Node class
class Node(str):
value = None
location = None
assocs = None
count = 0
color = None
marker = None
# initiate node
def __init__(self, val):
self.value = val
global numNodes
numNodes += 1
self.count = numNodes
self.assocs = []
self.color = 'b'
self.marker = '^'
# set node location and setup 3D text label
def setLoc(self, coords):
self.location = coords
global labelsOn
if labelsOn:
ax.text(self.location[0], self.location[1], self.location[2], self.value, color=fontColor)
# define node style
def setStyle(self, color, marker):
self.color = color
self.marker = marker
# define new association
def addAssoc(self, newAssociation):
self.assocs.append(newAssociation.count)
if debug:
print(" Informing node association: Node {} -> Node {}".format(self.value, newAssociation.value))
main()
散布 returns 个 collection，您可以使用 set_facecolor 更改集合中点的颜色。以下是您可以根据自己的代码进行调整的示例：
plt.figure()
n = 3
# Plot 3 white points.
c = [(1,1,1), (1,1,1), (1,1,1)]
p = plt.scatter(np.random.rand(n), np.random.rand(n), c = c, s = 100)
# Change the color of the second point to black.
c[1] = (0,0,0)
p.set_facecolor(c)
plt.show()
我正在构建一个 Python 工具，用于在 3D 中可视化数据结构。下面的代码是完整的程序，它甚至设置了 运行 一个带有一些随机数据的默认测试模型；你只需要 numpy 和 matplotlib。基本上，您声明一个节点，将它连接到其他节点，然后它就形成了漂亮的 3D 网络。我希望能够调用 switchNode() 并让它在黑色和白色之间翻转节点的颜色。按照现在的工作方式，每次实例化一个节点时，都会将绘图添加到另一个数据点。我对 matplotlib 的动画工具不够熟悉，不知道这样做的最佳方法（我尝试遵循 another post 中的示例在第 83 行被注释掉，希望有人能给我一些提示。谢谢！！
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import matplotlib.animation as anim
# user-defined variables
debug = False
axisOn = False
labelsOn = True
maxNodes = 20
edgeColor = 'b'
dottedLine = ':'
darkGrey = '#191919'
lightGrey = '#a3a3a3'
plotBackgroundColor = lightGrey
fontColor = darkGrey
gridColor = 'k'
numFrames = 200
# global variables
fig = None
hTable = []
ax = None
numNodes = 0
# initialize plot
def initPlot():
global ax, fontColor, fig
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d', axisbg=plotBackgroundColor)
if axisOn == False:
ax.set_axis_off()
else:
ax.set_axis_on()
fontColor = darkGrey
# gives n random float values between vmin and vmax
def randrange(n, vmin, vmax):
return (vmax - vmin) * np.random.rand(n) + vmin
# builds an empty node with a given value, helper method for makeNode
def makeNodeS(value):
global hTable, numNodes
n = Node(value)
hTable.append(n)
numNodes = len(hTable)
return n
# builds a node with given parameters
def makeNode(value, location, color, marker):
n = makeNodeS(value)
n.setLoc(location)
n.setStyle(color, marker)
if debug:
print("Building node {} at {} with color = {}, marker = {}, and associations = {}.".format(value, location, color, marker, n.assocs))
return n
# aggregate nodes in hTable and plot them in 3D
def plotNodes():
global hTable
if debug:
print("Plotting Graph...")
for elem in hTable:
if debug:
print(" Plotting node {}...".format(elem.value))
global fig, numFrames
scat = ax.scatter(elem.location[0], elem.location[1], elem.location[2], c=elem.color, marker=elem.marker)
for c in elem.assocs:
if (getNode(c).value != elem.value):
if elem.count in getNode(c).assocs: # if the two nodes are associated to each other, draw solid line
ax.plot([elem.location[0], getNode(c).location[0]], [elem.location[1], getNode(c).location[1]], [elem.location[2], getNode(c).location[2]], edgeColor)
if debug:
print(" Plotting double edge between {} and {}...".format(elem.value, getNode(c).value))
else:
ax.plot([elem.location[0], getNode(c).location[0]], [elem.location[1], getNode(c).location[1]], [elem.location[2], getNode(c).location[2]], edgeColor + dottedLine)
if debug:
print(" Plotting single edge from {} to {}...".format(elem.value, getNode(c).value))
#ani = anim.FuncAnimation(fig, update_plot, frames=xrange(numFrames), fargs=(['b', 'w'], scat))
# build single connection from node A to node B
def sConnect(nodeA, nodeB):
nodeA.addAssoc(nodeB)
if debug:
print(" Drawing single connection from node {} to node {}...".format(nodeA.value, nodeB.value))
# build double connection from node A to node B, and from node B to node A
def dConnect(nodeA, nodeB):
if debug:
print("\nDouble node connection steps:")
sConnect(nodeA, nodeB)
sConnect(nodeB, nodeA)
# update scatter with new color data
def update_plot(i, data, scat):
scat.set_array(data[i])
return scat
# returns the node with given count
def getNode(count):
global hTable
n = hTable[count-1]
return n
# set up axis info
def defineAxis():
ax.set_xlabel('X Label')
ax.xaxis.label.set_color(lightGrey)
ax.tick_params(axis='x', colors=lightGrey)
ax.set_ylabel('Y Label')
ax.yaxis.label.set_color(lightGrey)
ax.tick_params(axis='y', colors=lightGrey)
ax.set_zlabel('Z Label')
ax.zaxis.label.set_color(lightGrey)
ax.tick_params(axis='z', colors=lightGrey)
# randomly populate nodes and connect them
def test():
for i in range (0, maxNodes):
rand = np.random.rand(2)
if (0 <= rand[0] <= 0.25):
q = makeNode(i, np.random.rand(3), 'r', '^')
elif (0.25 < rand[0] <= 0.5):
q = makeNode(i, np.random.rand(3), 'b', 'o')
elif (0.5 < rand[0] <= 0.75):
q = makeNode(i, np.random.rand(3), 'g', 'v')
elif (0.75 < rand[0]):
q = makeNode(i, np.random.rand(3), 'w', 'o')
if (0 < i < maxNodes-1):
if (rand[1] <= 0.2):
dConnect(q, getNode(q.count-1))
elif (rand[1] < 0.5):
sConnect(q, getNode(q.count-1))
# randomly populate binary nodes and connect them
def test2():
for i in range (0, maxNodes):
rand = np.random.rand(2)
if (0 <= rand[0] <= 0.80):
q = makeNode(i, np.random.rand(3), 'k', 'o')
else:
q = makeNode(i, np.random.rand(3), 'w', 'o')
if (i > 0):
if (rand[1] <= 0.2):
dConnect(q, getNode(q.count-1))
elif (rand[1] > 0.2):
sConnect(q, getNode(q.count-1))
# switches a binary node between black and white
def switchNode(count):
q = getNode(count)
if (q.color == 'b'):
q.color = 'w'
else:
q.color = 'b'
# main program
def main():
## MAIN PROGRAM
initPlot()
test2()
plotNodes()
defineAxis()
plt.show()
# class structure for Node class
class Node(str):
value = None
location = None
assocs = None
count = 0
color = None
marker = None
# initiate node
def __init__(self, val):
self.value = val
global numNodes
numNodes += 1
self.count = numNodes
self.assocs = []
self.color = 'b'
self.marker = '^'
# set node location and setup 3D text label
def setLoc(self, coords):
self.location = coords
global labelsOn
if labelsOn:
ax.text(self.location[0], self.location[1], self.location[2], self.value, color=fontColor)
# define node style
def setStyle(self, color, marker):
self.color = color
self.marker = marker
# define new association
def addAssoc(self, newAssociation):
self.assocs.append(newAssociation.count)
if debug:
print(" Informing node association: Node {} -> Node {}".format(self.value, newAssociation.value))
main()
散布 returns 个 collection，您可以使用 set_facecolor 更改集合中点的颜色。以下是您可以根据自己的代码进行调整的示例：
plt.figure()
n = 3
# Plot 3 white points.
c = [(1,1,1), (1,1,1), (1,1,1)]
p = plt.scatter(np.random.rand(n), np.random.rand(n), c = c, s = 100)
# Change the color of the second point to black.
c[1] = (0,0,0)
p.set_facecolor(c)
plt.show()