| #include <M5Stack.h> | |
| #include <math.h> | |
| #include "utility/MPU9250.h" | |
| MPU9250 IMU; | |
| const int col_top = TFT_BLACK, col_bottom = TFT_YELLOW; | |
| const float hx = 160, hy = 120; | |
| int qx = hx, qy = 0; |
| $('input[id$="Type1"]').prop('checked', true) |
| function [] = doc(s) | |
| web(sprintf('https://google.co.jp/search?q=%s%s',urlencode(s),urlencode(' site:jp.mathworks.com')),'-browser') | |
| end |
| { | |
| // 他の設定の続きに以下の設定を追記，追記の際，区切りのカンマ(,)が必要な場合もあるので注意 | |
| "latex-workshop.latex.tools": [ | |
| { | |
| "command": "latexmk", | |
| "args": [], | |
| "name": "latexmk" | |
| } | |
| ], | |
| "latex-workshop.latex.recipes": [ |
| % vector field | |
| dxdt = @(x) [x(2);-x(1)]; | |
| % mesh | |
| [GX,GY] = meshgrid(linspace(-2*pi,2*pi,100),linspace(-10,10,100)); | |
| % stream | |
| DX = arrayfun(@(x,y) [1,0]*dxdt([x;y]),GX,GY); | |
| DY = arrayfun(@(x,y) [0,1]*dxdt([x;y]),GX,GY); | |
| [verts,averts] = streamslice(GX,GY,DX,DY,400); |
This is a visualization of citation network around machine learning and control theory.
This visualization is based on Citation Network Dataset by Aminer [1].
[1] Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, and Zhong Su.
ArnetMiner: Extraction and Mining of Academic Social Networks.
In Proceedings of SIGKDD'2008. pp.990-998.
| #!/usr/bin/perl | |
| $pdflatex = 'pdflatex -synctex=1 -src-specials -shell-escape -interaction=nonstopmode -halt-on-error -file-line-error %O %S'; | |
| $bibtex = 'bibtex %O %B'; | |
| $pdf_mode = 1; |
| #!/usr/bin/perl | |
| $latex = 'platex %O -src-specials -shell-escape -interaction=nonstopmode -synctex=1 -kanji=utf8 %S'; | |
| $bibtex = 'pbibtex %O %B -kanji=utf8'; | |
| $dvipdf = 'dvipdfmx %O -o %D %S'; | |
| $pdf_mode = 3; # use dvipdfmx |