Re-reading the Undoing Project

Test 1

Which of the following two gifts do you prefer?

Gift A: A lottery ticket that offers a 50 percent chance of winning $1,000
Gift B: A certain $500

Test 2

Which of the following do you prefer?

Gift A: A lottery ticket that offers a 50 percent chance of losing $1,000
Gift B: A certain loss of $500

This is the isolation effect

The isolation effect occurs when people have presented two options with the same outcome, but different routes to the outcome. In this case, people are likely to cancel out similar information to lighten the cognitive load, and their conclusions will vary depending on how the options are framed.

I am an LBT

LBT = Low Bullshit Tolerance

  1. An overall inability to entertain nonsense – check
  2. Continuously finding the need to roll your eyes at people – nope
  3. Extreme levels of relationship-threatening sarcasm – nope
  4. Experiencing multiple “smh” worthy moments, within the same day – check
  5. Very short attention span to things that don’t directly concern you – check

View at Medium.com

普鲁斯特问卷 2019.01

1.你认为最完美的快乐是怎样的?

每天早晨都很有动力起床,开始新的一天。

2.你最希望拥有哪种才华?

自动抵御各种负性情绪的能力。

3.你最恐惧的是什么?

在孤独和疾病的包围下老去。

4.你目前的心境怎样?

中年危机。

5.还在世的人中你最钦佩的是谁?

没有。

6.你认为自己最伟大的成就是什么?

没有。

7.你自己的哪个特点让你最觉得痛恨?

负能量。

8.你最喜欢的旅行是哪一次?

下一次。

9.你最痛恨别人的什么特点?

看什么人了。工作伙伴的话,我不能忍受低能和低效率。生活上,我觉得没什么不能忍受的,只要能理解。

10.你最珍惜的财产是什么?

脑力。

11.你最奢侈的是什么?

没有。

12.你认为程度最浅的痛苦是什么?

伤口带来的痛苦。

13.你认为哪种美德是被过高的评估的?

Empathy。

14.你最喜欢的职业是什么?

下一份。

15.你对自己的外表哪一点不满意?

年龄。胖。

16.你最后悔的事情是什么?

所有。

17.还在世的人中你最鄙视的是谁?

没有。

18.你最喜欢男性身上的什么品质?

善良。

19.你使用过的最多的单词或者是词语是什么?

讨厌。

20.你最喜欢女性身上的什么品质?

聪明。

21.你最伤痛的事是什么?

父亲死了多年。

22.你最看重朋友的什么特点?

守时重义。

23.你这一生中最爱的人或东西是什么?

父亲。

24.你希望以什么样的方式死去?

在我不太老、不太丑的时候死去。

25.何时何地让你感觉到最快乐?

忘记自己的时候最快乐。

26.如果你可以改变你的家庭一件事,那会是什么?

让我父亲复活。

27.如果你能选择的话,你希望让什么重现?

父亲。

28.你的座右铭是什么?

生如夏花,死如秋叶。

理想的时间安排:(28, 34, 38)

每周七天,除去每天睡觉八小时之外,一共有 112 小时。今天,我找到了最理想的安排这 112 小时的方式。

休闲娱乐:31 小时(28%)

看书,写日记,拍照片,看电影,玩乐器,等等

  • 周一到周五:每天三小时
  • 周末:每天八小时

健康起居:39 小时(34%)

锻炼健身,洗漱保养,洗衣做饭,打扫收信,账单银行,等等

  • 周一到周五:每天 4.5 小时 (其中 1.5 小时用来锻炼)
  • 周末:每天 8 小时

工作:42 小时(38%)

包括每天一小时上下班时间。

 

Created my first R package

Sometimes MVP is the key.

I’ve been wanting to learn to create my own R package for a while. Four months ago my goal was to create my first R package by end of June. Two days ago I gave it another try and started reading Hadley Wickham’s great book “R Packages”. However the book covered much more than what I needed, namely, to just create an R package and go.

This morning I spent an hour to create an R package following instructions from Hilary Parker. Now it’s officially done!

Next, I’ll grab my favorite functions and put them in a real package on github..

An Application of CDIFTT

2008.04.20.

Today I applied th so-called CDIFTT: Cross Desert Interstate Following Truck Technique. It proved to be successful, since I am alive and kicking right now. I indeed felt lucky having landed at home after a stressful day, which started from the morning.

I woke up at 8am after 5 hours sleep, which was short for a person who usually prefer to sleep for 9 hours. Thinking of the forthcoming 5 hours driving, I thought to myself, “I’m too old for that.” Nonetheless it was unavoidable.. I prepared myself for the trip, or that I thought so, over one cigarette, two cookies, three pieces of fruits, and four cups of coffee. Right after I set up, I found myself quite unreadily on a windy road cross desert where the wind practically blew my car from all directions and sounded scarily loud outside the windows no matter how much louder I turned on the music. The first hour was the hardest, since I was totally unprepared for such a driving condition. To make things worse, my stomach started to feel funny, and there was a kind of headache emerging from the back of my head. Eventually, I had to make an early stop when only less than one fourth of the trip was covered. I took myself to a Kentucky for a meal, and the mountaindew proved to be useful, since at that time, I was shaking from head to tail and felt fragile like a piece of glass. It was about noon and I was in the middle of an unknown highway town in New Mexico, watching the mid- day desert sunshine listening to the wind blowing outside the Kentucky. By the time I finished the two piece chicken meal, I felt much better, at least energy-wise, and kind of figured out what I should do in the rest of the trip. This was when I started the Following Truck Technique and brought myself home safely through this practice. Thinking back, I made the following list of plausibilities of the FTT:

1. On the interstates cross deserts, the highway limits are generally 75 miles per hour, while a car of my size driving at that speed already feels shaky in the wind. It is hence safer if I kept the speed around 70 miles per hour, which is exactly the speed of most trucks.

2. The trucks are very followable since they tend to keep the speed for a long while. Also in the desert area there is no heavy traffic, which makes it easier for the trucks to keep their speed.

3. It is psychologically comfortable to feel the heavy wind being partially blocked by the big thing, the truck, in front of me. What is more, having the sight of endless roads and far-away mountains blocked partially, one feels less hopelessly endless and long with the journey.

4. It is easy to follow a truck since they keep a constant speed so that I can temporarily speed up a bit till I settle down behind a truck with a comfortable distance.

The list may be extended. Today I followed some five trucks over two thirds of the trip. It might be worth mentioning that there were a few trucks that I lost since they were too fast for me to catch up with… I stopped following trucks during the last part, for about 80 miles, when getting closer to home. The end of driving was fast and easy, as always. Still, I found it hard to control the speed at a comfortable level by myself without using the FTT, which confirmed my observation that driving on a windy day, following a truck on a cross desert interstate is just the best thing that one can do!

说说 real-time TeXing

以前有过一个上司,当时的系主任,我非常喜欢这个教授的原因是他幽默聪明而且主意多多。跟他一起做事的几年里,前后学到的小玩意儿一大把。其中有个挺有意思的事情,就是现场做笔记。

起因是有一年几个人过来视察,其中一个人听力不好,而且是这个教授的朋友。所以大家一直没完没了开会的时候,这个教授就坐在这个听力不好的人旁边,中间放个电脑,不停打字给他。

后来我发现这个教授现场打字的能力超强,好比他组织开一个 town-hall 会议让大家给数学系的将来提建议意见,大家畅所欲言的时候,他用 Word 现场打字并且排版,当然都放到大屏幕上给所有人看见,与此同时还主持会议和回答问题(所以经常是自己一边说一边记录自己的回答)。

我受到他的启发,也想试试开发自己这个能力。本着本人说做就做的习惯,尝试的方法就是上课回答学生问题的时候一边说话一边用 LaTeX 画个 diagram(我一直用 LaTeX 写好 slides 来教课,所以上课的时候电脑是一直连着大屏幕的,只要随手打开一个编译器输入就可以了)。尝试了几下感觉不错,让学生觉得跟变戏法一样的好玩也是提高他们兴趣的一个方法,当然 LaTeX 的输出也挺简洁有效的。

比较大型的一次尝试,是有一个学期参与一个实验教学项目,和一个资深高中教师教很多初中教师,我负责听课和帮忙,于是顺手把所有讲课过程都给敲了下来,那些学生还特别喜欢发言,我做的笔记于是有点像法庭记录,基本上是【谁】说了什么什么,然后【谁】又说了什么什么。当然内容都是很数学的,有时还要现场临摹有人随手在白板上画的 diagram,大家三言两语说得激烈或者 diagram 复杂的时候,我这敲字还真不那么容易呢。本来我倒是用这个做一个尝试和锻炼就算了,没想到后来还证明有用 —— 那年假期我接到任务,开始考虑把这个实验课程给变成教科书一样的内容,于是我拿出所有听课笔记,编辑整理剪切添加,折腾了一个假期,还真弄了一本很像书的成果出来。至于后来在那个基础上跟另外一个资深教师改编、演绎,重新设计了一堆教案演变成 beamer 形式的课件,那又是另外一回事了。

总而言之,在这些不断的小小挑战里,我被迫学会了快速用 LaTeX 做笔记的能力,其中包括许多小的 tips and tricks —— 可惜那时觉得将来反正不会忘的,不知道记录下来,其实现在都忘干净了。

最近开会的时候,只会默默打开 Mou 用 markdown 写写啦。真是退化啦。

修辞乏陈的一生

上次说到,我一直有个隐隐的大愿望,只是永远也没法实现。

十来岁的时候父亲开始从学校图书馆往家里搬大部头小说,放书架上,也不说什么,估摸着他是自己想看吧。我当然没能经受住诱惑开始翻。《悲惨世界》,不喜欢,《静静的顿河》,看不进去,《战争与和平》,好晕哪。结果我能翻进去并且还一口气囫囵看完的,只有一套《红楼梦》,当天书一样看着,大部分时候完全不知道书里在说的是什么,但就是孜孜不倦,顽强地看了一遍又一遍,一直到大学毕业还在看。

十年前检阅父亲留下的日记本才发现他老大人当年也曾痴迷《红楼梦》——所以那堆书说不定真是他拿回来给自己看的,他个人的所有稍微优点价值的东西早在六几年都统统损毁啦——还曾在朋友圈里以湘云自诩。哦,我看了那么多年,还是只晓得喜欢一个黛玉,有时爱屋及乌地捎带怜悯一下宝玉而已,境界呢?

猛看红楼梦的结果,不仅视野保持狭小主要光看林黛玉,而且一点也没能把我了无希望的语文和作文水平给带出一点提高出来。从小学开始我的语文基本在及格线上徘徊,作文从没上过像样点的分数,这个记录一直保持到高中毕业。结果是到现在还是稍微偏僻的字就不认得了,范文式的写作完全没成果。即便如此,我还是有过一个作家梦的。

现在想来,这个作家梦的缘起,可能来自于高中时看冰心受到的毒害。上高中之后为了看书方便我自告奋勇做了图书管理员,给同学们打卡借书的同时自己可以一次借几十本,当然更多的时候直接泡在图书馆里乱翻书。那样的看法一般喜欢个什么作家就把全集都给看了。不幸的是,第一个被我看上的作家是冰心。

冰心的小说,现在想来,对于年少的小孩还是有点作用的——不比琼瑶差——五四青年斜披一个白色的长围巾,在风里雨里一通乱走就能如神通一般获得思想和心灵上的大自由,平常看起来神叨叨的自言自语,其实一脑子更糊涂的“我往哪里走”的困惑,等等这些,想想吧,哪个不是能把一个青春期小孩迷到晕七八彩的?我当时简直立刻亲身模拟了以上全套——白围巾除外,那个跟自个的娃娃脸实在不搭——每天晚上在湖边走,不知道的人看见了以为你琢磨自尽,其实只是看看花瓣好玩罢了。光模拟当然不够,我弄了几个好看兮兮的本子,当然开始自己写了。有个小朋友也喜欢写故事,虽然她喜欢琼瑶但本质上反正差不多,我们用本子接力的方式玩玩接龙,倒也不亦乐乎。我还构思了武侠言情长篇巨制,大部分存在脑子里,写了几首给主人公度身定制的歌出来自己日常哼着,很有一种“大作家是我”的劲头儿。

现实是残酷的。冰心的热度刚开始不久我又喜欢上了郁达夫,可是写作风格一点也没能因此进行真正的改变。

2014 年七月写的 learning plan

My Learning Progress Plan

In 2014 Q3 I want to get comfortable with doing data science in the open source setting. This means covering a big ground with pieces of knowledge here and there, while focusing on using Python and R for mathematical computing and statistical modeling. I will read webpages / articles / books to get started with AWS, Hadoop, and Ruby, while using these resources to dive deep into machine learning algorithms. Text mining is going to be provide tremendous value to our business because of our setting, so I have and will be focusing on reading those.

2014.07 Start learning by doing. Conduct basic analysis. Start writing data dictionary. Small sample of data warehousing.
2014.08 Data warehousing in scale for a particular set of questions. Lay out the ground for opportunity scoring.
2014.09 Data warehousing in scale. Initial modeling of opportunity scoring done.

2014 Q3 learning goals (numbers are proficiency achieved out of a scale from 1 to 10)
Python [4] – Comfortable with simple tasks. Basic proficiency munging data using Pandas library.
R [4] – Statistical modeling. Text mining. Be more familiar with frequently used machine learning algorithms and their applicability to our data.
Machine learning [4] – Along with R.
AWS [2] – Comfortable working in the cloud. Find fast way to process the data into reasonable format. Build data warehouse.
Hadoop [2] – Basic knowledge of different solutions. Identify the long term coding tool for big data.
Ruby [1] – Basic knowledge of syntax structures. Efficient reader of the codes.

In 2014 Q4 My personal learning of Python and R will keep progressing, and I will take a 2-week vocation in Oct to Nov. While keeping doing what is started in Q3, I’d like to have a focus of (1) building a data warehouse and (2) finding a big data solution so that more detailed activities can be carried out much faster, and the whole company will eventually benefit from gaining data-driven insights.

2014.10 Data warehousing in scale. Evaluation and presentation of opportunity scoring. Identify next data mining projects.
2014.11 Data warehousing in bigger scale.
2014.12 Data warehousing in reasonable shape to enable quick retrieval of KPIs company wise.

2014 Q4 learning goals
Python [6] – Proficient using python for data munging and basic data analysis. Dive into modeling. Basic proficiency with general python usage.
R [6] – Statistical modeling. Text mining.
Machine learning [6] – Along with R.
AWS [3] – Comfortable working in the cloud.
Hadoop [3] – Implementation of big data solutions.
Ruby [2] – Read codes.