TSNE动态可视化

这里将上一篇博客中的迭代数据保存下来，用matplotlib一次次更新数据，利用moviepy合成一个小视频，效果看上去有点酷酷的，因为mp4格式无法上传。。。。所以：生成视频链接：http://pan.baidu.com/s/1ge7BYXd

# -*-encoding:utf-8-*-
from sklearn import manifold
from sklearn import decomposition
from sklearn import datasets
from sklearn import svm
from sklearn.preprocessing import scale,MinMaxScaler
from matplotlib import pyplot,colors
import numpy,pandas
from pandas.tools import plotting
from pylab import mpl
mpl.rcParams['axes.unicode_minus']=False
mpl.rcParams['font.sans-serif']=['SimHei']

from moviepy.video.io.bindings import mplfig_to_npimage as figage
import moviepy.editor as mpe
import shelve

from scipy import spatial,sparse
a=sparse.csc_matrix
spatial.distance

# data get
data=datasets.load_digits()
x=data.data
y=data.target

# color list
'''
color=[]
for i in colors.cnames:
color.append(i)
'''
color=['yellow','black','green','red','blue','orange','brown','pink','purple','grey']

def make_frame(t):
tt=int(t/0.1)
# print tt
pyplot.clf()
for i in range(10):
xxx1 = XX[tt][YY == i, 0]
xxx2 = XX[tt][YY == i, 1]
#print xxx1.shape,xxx2.shape
pyplot.scatter(xxx1,xxx2,c=color[i])
pyplot.title('SNE VISUALIZING DYNAMIC '.decode('utf-8', 'ignore'))
pyplot.axis('off')
M1=numpy.min(XX[tt])
M2=numpy.max(XX[tt])
if M1>0:
M1=M1*0.8
else:
M1=M1*1.2
if M2>0:
M2=M2*1.2
else:
M2=M2*0.8
pyplot.xlim(M1, M2)
pyplot.ylim(M1, M2)
return figage(figure1)

DD=shelve.open('tsne.dat')
XX=DD['data']
YY=y
N=len(XX)
DD.close()
figure1=pyplot.figure('SNE VISUALIZING DYNAMIC',dpi=800)
picture=mpe.VideoClip(make_frame,duration=40)
picture.write_videofile("tsne_0.mp4",codec='mpeg4',fps=10)