WD-20151006
来源:互联网 发布:js给标签添加属性 编辑:程序博客网 时间:2024/04/29 16:01
1. Afternoon
- worked with Jon to port his old tahirTrackViewer.cpp into new cvg2, and works.
- be aware of the origin convention when using Calibration related functions
2. Morning
- Trajectories with 3D coords done, sent to Luis
- Silly mistake of config file of calibration, waisted 2 hours in total…
3. Worth-noting points this week
1. SDS tracker
2. ported MTT stuff into cvg2
Basically it’s a point tracker
3. Hungarian Algorithm
- Also called Munkres’ Assignment Algorithm
- It appears to be two different solutions…
- Assignment Problem and Hungarian Algorithm
- Munkres’ Assignment Algorithm
4. JPDAF 5. New ColorMap in Matplotlib
A Better Default Colormap for Matplotlib
How We Designed Matplotlib’s New Default Colormap (and You Can Too)
Perceptual Color Maps in matplotlib for Oceanography
6. Theono
Still don not quite get the idea of all algorithms are defined symbolically, therefore It’s more like writing out math than writing code
All the examples (entry level of course) I’ve come across so far,
- Theano at a Glance
- Theano Tutorial
- Baby Steps - Algebra
They are use the same letter/word for ‘symbol’ and variable, like
>>> import theano.tensor as T>>> from theano import function>>> x = T.dscalar('x')>>> y = T.dscalar('y')>>> z = x + y>>> f = function([x, y], z)
or,
# The theano.tensor submodule has various primitive symbolic variable types.# Here, we're defining a scalar (0-d) variable.# The argument gives the variable its name.foo = T.scalar('foo')# Now, we can define another variable bar which is just foo squared.bar = foo**2# It will also be a theano variable.print type(bar)print bar.type# Using theano's pp (pretty print) function, we see that # bar is defined symbolically as the square of fooprint theano.pp(bar)
4. Highlights from last week
1. presentation on GMM2. scikit-learn
Gaussian mixture models
Density Estimation for a mixture of Gaussians
Gaussian Mixture Model Ellipsoids
Gaussian Mixture Model Selection
GMM classification
1D Gaussian Mixture Example
How to draw PDF
x = np.linspace(-6, 6, 1000)logprob, responsibilities = M_best.eval(x)pdf = np.exp(logprob)pdf_individual = responsibilities * pdf[:, np.newaxis]
GMM and score_samples(X) back to probabilities
The probability density can be greater than 1. The only normalization criterion is that it integrates to 1.
Take a simple 1D example of where the probability is zero except in the range (0, 0.1). Then the probability density must have an average value of 10 in that region for the normalization criterion to be met!
data = []for _ in range(100) : data.append( [np.random.rand(), np.random.rand(), np.random.rand()] )model = GMM(n_components=1).fit(data)logprob, _ = model.score_samples(data)print (np.max(np.exp(logprob)))# 2.57627579814grid = np.linspace(-0.5, 1.5, 100)x, y, z = np.meshgrid(grid, grid, grid)X = np.vstack([x.ravel(), y.ravel(), z.ravel()]).Tlogprob, _ = model.score_samples(X)print (np.max(np.exp(logprob)))# 2.65717824707print(np.exp(logprob).sum() * (grid[1] - grid[0]) ** 3)# 0.998503826652
3. matplotlib
Pyplot tutorial
- Working with multiple figures and axes
import matplotlib.pyplot as pltplt.figure(1) # the first figureplt.subplot(211) #the first subplot in the first figureplt.plot([1,2,3])plt.subplot(212) #the second subplot in the first figureplt.plot([4,5,6])plt.figure(2) # a second figureplt.plot([4,5,6]) # creates a subplot(111) by defaultplt.figure(1) #figure 1 current; #subplot(212) still currentplt.subplot(211) # make subplot(211) in figure1 currentplt.title('Easy as 1,2,3') # subplot 211 title
- WD-20151006
- wd
- wd
- WD
- WD
- -无意义-wD
- WD align
- WD MyBookLive 安装小记
- “神油”-WD-40
- jmeter wd结合
- WD Element(E元素) 和 WD Element SE
- 如何拆卸的WD Mybook
- WD:controller and context programming
- WD MyBook Live安装SVN
- ObQueryNameString的使用--WD笔记
- WD linux 一键安装
- WD蓝盘绿盘黑盘红盘的区别
- wd cloud nas for linux
- CF#324-C-Marina and Vasya-字符串水题
- CF#324-B. Kolya and Tanya-组合数学题
- *LeetCode-Populating Next Right Pointers in Each Node II
- cf#324-A. Olesya and Rodion-水题
- 研究云计算与大数据分析处理领域建议看的学术论文列表
- WD-20151006
- *LeetCode-Longest Consecutive Sequence
- [笔试题目] 简单总结笔试和面试中的海量数据问题
- 我的Web学习之路4——Javascript、Jquery中数组的定义与操作
- IOS开发笔记-01按钮操作-09.私有扩展&IBAction
- IOS开发笔记-01按钮操作-10.创建应用程序中的一些细节
- Java 连接SQL Server 连接
- STM32自学笔记——UCOSIII
- **LeetCode-Distinct Subsequences