jlehtoma

library(rworldmap)
library(rgdal)

# Latlon
world_map_wgs84 <- getMap()
plot(world_map_wgs84, main = "WGS84")
proj4string(world_map_wgs84)

# Mollweide
world_map_mollweide <- spTransform(world_map_wgs84, CRS("+proj=moll"))

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# Tell all slaves to return a message identifying themselves. 
mpi.remote.exec(paste("I am",mpi.comm.rank(),"of",mpi.comm.size())) 
mpi.remote.exec(paste(mpi.comm.get.parent()))

# Send execution commands to the slaves
x <- 5
x <- mpi.remote.exec(rnorm,x) 
length(x)
x

jlehtoma

install.packages(c("maptools", "rworldmap", "rworldxtra"))

# Load required packages
library(maptools)
library(rworldmap)

# Define LAEA projection for Europe
crs.laea <- CRS("+proj=laea +lat_0=52 +lon_0=10 +x_0=4321000 +y_0=3210000 +ellps=GRS80 +units=m +no_defs")  # Lambert Azimuthal Equal Area

# Grab the whole world, NOTE that you will also need package rworldextra

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library("dplyr")
library("magrittr")
library("rvest")

urls <- c("http://koivu.luomus.fi/seurannat/linjalaskenta/vakiolinjat.php")

site <- html(urls)
linjat_table <- site %>% 
                  html_node("table") %>%
                  html_nodes("tr")

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library(dplyr)
library(tidyr)

dat <- data.frame(laji=c("accgen", "accnis", "accgen", "accnis" , "accgen",
                         "accnis", "accgen", "accnis"),
                  lkm=c(2, 2, 1, 4, 3, 2, 2, 6),
                  linja_P_E = c("P", "P", "E", "E", "P", "P", "E", "E"))

dat_agg <- dat %>% 
  # Group by both laji and linja_P_E

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library(dplyr)
library(magrittr)

museum_transects <- read.table("data/museon_linjat.csv", as.is = TRUE, 
                               sep = ";", header = TRUE)

standard_transects <- read.table("data/vakioreitit_lista_suojelualueet.csv", 
                                 as.is = TRUE, sep = ";", header = TRUE)

# Select only columns Reitti and Suojelualue form standard_transects

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# Tell all slaves to return a message identifying themselves. 
mpi.remote.exec(paste("I am",mpi.comm.rank(),"of",mpi.comm.size())) 
mpi.remote.exec(paste(mpi.comm.get.parent()))

# Send execution commands to the slaves
x <- 5
x <- mpi.remote.exec(rnorm, x) 
x

mpi.close.Rslaves()

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# Based on solution given here: http://geospatialpython.com/2011/11/generating-shapefile-shx-files.html
# Depends on pyshp

# Build a new shx index file
import fnmatch
import os
import shapefile

# List all the shapefiles
def find(pattern, path):

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Keybase proof

I hereby claim:

• I am jlehtoma on github.
• I am jlehtoma (https://keybase.io/jlehtoma) on keybase.
• I have a public key whose fingerprint is CCCE BB9B C821 8250 74F4 28BA B49C 7E97 E9C2 A513

To claim this, I am signing this object:

jlehtoma

library(rlist)
 
x <- list(list("ID"=1, "var1"="B", "var2"="D"),
          list("ID"=2, "var1"="F", "var2"="H"),
          list("ID"=3, "var1"="I", "var2"=NULL))
 
# rlist approach - returns FALSE
list.any(x, l ~ is.null(l))
 
# 2-level lapply - returns TRUE