Merge GitHub Pull Requests

 Posted on November 18, 2018  |  2 minutes  |  Vincent Tam  |   0 comment

Aim Merge a pull request. How? Let’s take Staticman PR 231 as an example. I would like to test it before commiting this merget to Heroku. $ cd ~/staticman $ git branch -a * deploy dev master ... $ git remote -v eduardoboucas https://github.com/eduardoboucas/staticman.git (fetch) eduardoboucas https://github.com/eduardoboucas/staticman.git (push) heroku https://git.heroku.com/staticman3.git (fetch) heroku https://git.heroku.com/staticman3.git (push) ... $ git pull eduardoboucas pull/231/head:deploy remote: Enumerating objects: 10, done. remote: Counting objects: 100% (10/10), done. [Read More]
Git  Staticman 

Nested Comments in Beautiful Hugo

 Posted on November 17, 2018  |  8 minutes  |  Vincent Tam  |   0 comment

Quick links A minimal demo site on GitLab (Source) Beautiful Hugo pull request 222 Pre-release notes for this pull request Motivation For the mathematical ones, please see my previous post. As a math student, it’s inefficient to reinvent the wheel like engineering students. Thanks to three existing examples, I had convinced myself that I could bring this to the theme Beautiful Hugo. Zongren’s Hexo theme (worked best) Made Mistakes Jekyll theme Network Hobo’s customization of Beautiful Hugo (inspired by the second one, but contains a logic error) [Read More]
Hugo  Staticman  jQuery 

Interactive Blog on Static Web Host

 Posted on November 17, 2018  |  4 minutes  |  Vincent Tam  |   0 comment

Vision gain autonomy: freedom is the basis of moral actions. No freedom, no morality. transcend ourselves: change/improve our lives through free thoughts Goal Convert our free thoughts into free code. Free code allows users around the world to run and/or improve them. This would bring real enhancement to our tools. For example, beautiful math writing used to be a complicated process. A decade ago, this required the installation of a typesetting engine called $\LaTeX$. [Read More]
Hugo  Staticman  GitLab 

Simplex Calculations for Stokes' Theorem

 Posted on November 3, 2018  |  3 minutes  |  Vincent Tam  |   0 comment

Oriented affine $k$-simplex $\sigma = [{\bf p}_0,{\bf p}_1,\dots,{\bf p}_k]$ A $k$-surface given by the affine function $$\sigma\left(\sum_{i=1}^k a_i {\bf e}_i \right) := {\bf p}_0 + \sum_{i=1}^k a_i ({\bf p}_i - {\bf p}_0) \tag{1},$$ where ${\bf p}_i \in \R^n$ for all $i \in \{1,\dots,k\}$. In particular, $\sigma({\bf 0})={\bf p}_0$ and for each $i\in\{1,\dots,k\}$, $\sigma({\bf e}_i)={\bf p}_i$. Standard simplex $Q^k := [{\bf 0}, {\bf e}_1, \dots, {\bf e}_k]$ A particular type of oriented affine $k$-simplex with the standard basis $\{{\bf e}_1, \dots, {\bf e}_k\}$ of $\R^k$. [Read More]
simplexes 

La norme lipschitzienne est complète

 Posted on November 2, 2018  |  2 minutes  |  Vincent Tam  |   0 comment

Dans l’article de Robert Fortet et Edith Mourier en 1953, une distance entre deux mesures de probabilité sur un espace métrique est définie. De nos jours, je trouve la façon dont ils l’ont écrit assez difficile à comprendre. Je suis plus à l’aise avec $\sup$ que “b.s.” que désigne “borne supérieure”. Ils se sont servi de $M[f]$ pour $\lVert f \rVert_{\rm Lip}$, où $$\lVert f \rVert_{\rm Lip} = \sup_{x \ne y} \frac{|f(x) - f(y)|}{d(x, y)}. [Read More]
real analysis 

Mesurabilité des réalisations trajectorielles

$X: \omega \mapsto X(\cdot, \omega) \in \mathcal{M}((\Omega, \mathcal{A}), (\CO(\Bbb{T},\R), \Bor{\CO}))$

 Posted on October 11, 2018  |  5 minutes  |  Vincent Tam  |   0 comment

Notations Supposons toutes les notations dans Espace de trajectoires. Problématique La mesurabilité de l’application dans le sous-titre est basée sur l’égalité suivante. $$\Bor{\R}{\OXT} \cap \CO = \Bor{\CO}$$ J’ai passé quatres heures pour comprendre pourquoi ça entraîne la mesurabilité ? pourquoi l’égalité elle-même est vraie ? Réponses Mesurabilité de la trace sur $\CO$ de $\Bor{\R}{\OXT}$ A la première lecture, je ne connaisais même pas la définition de la trace d’une tribu sur un emsemble. [Read More]
probability 

What are Dataframes?

Understand dataframes from a non-example

 Posted on October 7, 2018  |  1 minutes  |  Vincent Tam  |   0 comment

Motivation The books that I read in the past didn’t explain what a dataframe meant. Definition Dataframe A table of data in which the values of each observed variable is contained in the same column. Counterexample I’ve difficulty in reading long lines of text like the above definition, so let’s illustrate this definition with a counterexample. We have carried out repeated experiments with four types of things and obtaine some data. [Read More]
statistics 

Enlarged /var Partition

Used GParted to grow /var partition

 Posted on October 6, 2018  |  1 minutes  |  Vincent Tam  |   0 comment

Background

I’ve installed Ubuntu 18.04 on my new laptop.

Problem

The /var partition was too small. The system complained that only 200 MB was left.

Solution

  1. Rebooted with my live USB.
  2. Opened GParted.
  3. Moved /tmp partition to the left and grew it to 6 GB.
  4. Grew /var partition to 16 GB
  5. Click

GParted screenshot

Results

GParted result partition table

Details

View GParted generated files.

Linux  GParted  repartition 

Ultrafilters Are Maximal

 Posted on October 5, 2018  |  2 minutes  |  Vincent Tam  |   0 comment

Ultra filter A filer $\mathcal{F}$ containing either $Y$ or $Y^\complement$ for any $Y \subseteq X$. Two days ago, I spent an afternoon to understand Dudley’s proof of this little result. A filter is contained in some ultrafilter. A filter is an ultrafilter iff it’s maximal. At the first glance, I didn’t even understand the organisation of the proof! I’m going to rephrase it for future reference. [Read More]
topology 

2018-10-04 Seminar Notes

 Posted on October 4, 2018  |  3 minutes  |  Vincent Tam  |   0 comment

I jotted down only a few keywords that might be reusable. I didn’t understand any of the talks. Functional Data Analysis Goal: predict equipment temperature Tools: Fourier coefficients (trigo ones), followed by discretisation, min-error estimation, cross-validation 10-folds, $R^2$ adjusted ?, MAE, MSPE Comparison with non-functional data Tolérancement Thème : Traiter les incertitudes sur les dimensions des pièces de l’avion Objectif : établir une modélisation mathématiques construire un virtual twin de l’avion Outils : Modèle de variabilité Modèle d’assemblage $\text{airbus}: Y = \sum_{i = 1}^n a_iX_i? [Read More]
seminar  probability  statistics