| `inla.update` = function(lib = NULL, testing = FALSE, force = FALSE, build.epoch=NULL, build.date=NULL) | |
| { | |
| inla.installer(lib=lib, testing=testing, force=force, build.epoch=build.epoch, build.date=build.date) | |
| } | |
| `inla.installer` = function(lib = NULL, testing = FALSE, force = FALSE, build.epoch=NULL, build.date=NULL) | |
| { | |
| ## include depends-on packages here | |
| for(p in c("sp", "Matrix", "splines")) { | |
| if (length(grep(paste("^package:", p, "$", sep=""), search())) == 0) { |
| library(spdep) | |
| library(INLA) | |
| # Take a subset of the data. | |
| diamina <- read.csv("~/Downloads/diamina_meadows_125000_sample.csv", sep=";", dec=",") | |
| diamina <- subset(diamina, Xcoord>230000 & Ycoord>6910000) | |
| diamina$habitable <- as.factor(diamina$habitable) | |
| diamina$id <- 1:nrow(diamina) | |
| library(INLA) | |
| m = 50 | |
| points = matrix(runif(m*2), m, 2) | |
| mesh = inla.mesh.2d(loc=points,cutoff=0.05,offset=c(0.1, 0.4),max.edge=c(0.05, 0.5) ) | |
| bnd = inla.nonconvex.hull(points, convex=0.12) | |
| mesh = inla.mesh.2d(boundary=bnd,cutoff=0.05,offset = c(1, 0.5),max.edge=c(0.1, 0.5) ) | |
| A = inla.spde.make.A(mesh, loc=points) | |
| sigma0 = 1 ## Field std.dev. for theta=0 | |
| size = min(c(diff(range(mesh$loc[,1])), diff(range(mesh$loc[,2])))) | |
| range0 = size/5 ## A fifth of the approximate domain width. |
The count of contributions (summary of Pull Requests, opened issues and commits) to public repos at GitHub.com from Wed, 29 Jul 2015 01:52:41 GMT till Fri, 29 Jul 2016 01:52:41 GMT.
Only first 1000 GitHub users according to the count of followers are taken. This is because of limitations of GitHub search. Sorting algo in pseudocode:
githubUsers
.filter(user => user.followers > 6)| jsoncatfun() { cat $1 | python -c'import fileinput, json;print(json.dumps(json.loads("".join(fileinput.input())),sort_keys=True, indent=4))'; } | |
| alias jsoncat=jsoncatfun |
| #!/bin/bash | |
| ffmpeg -f x11grab -framerate 25 -s 1920x1080 -i :0.0+1920,0 -c:v libx264 -crf 0 -preset ultrafast -qp 0 output.mpg |
| # 1. Copy table from http://thai-language.com/ref/starred | |
| # 2. Paste to Google Sheets | |
| # 3. Save as CSV | |
| # 4. Run through top_1000_thai_words.R | |
| # 5. Upload to Anki App via https://api.ankiapp.com/nexus/ | |
| library(tidyverse) | |
| library(stringr) | |
| setwd("~/Downloads") |
| DROP TABLE IF EXISTS temp; | |
| CREATE TABLE temp ( | |
| id INT, | |
| geom GEOMETRY(POINT, 4326) | |
| ); | |
| -- \d temp | |
| INSERT INTO temp VALUES (1, 'SRID=4326;0000000001C051C3DC37A3DB3C4048374D37C1376D'); |
| from typing import Any | |
| import fsspec | |
| import pickle | |
| def write_pickle(data: Any, path: str) -> None: | |
| with fsspec.open(path, "wb") as file: | |
| pickle.dump(data, file) | |
| def read_pickle(path: str) -> Any: |