nemochina2008’s gists

nemochina2008 / animate_accumulate_wbd.R

Created December 11, 2018 07:24 — forked from dblodgett-usgs/animate_accumulate_wbd.R

A visualization script to create frames of an animated gif of WBD accumulation where all paths terminate on the last time step.

	# https://github.com/dblodgett-usgs/nhdplusTools
	library(nhdplusTools)
	# https://github.com/USGS-R/HUCAgg
	library(HUCAgg)
	library(sf)
	library(dplyr)
	library(snow)

	wbd_gdb <- "WBD_National_GDB.gdb"

nemochina2008 / national_dem_example.R

Created November 29, 2018 15:36 — forked from jhollist/national_dem_example.R

	library(USAboundaries)
	library(sf)
	library(dplyr)
	library(elevatr)
	library(raster)

	# Get map of lower 48 states
	usa_l48 <- us_boundaries() %>%
	filter(state_abbr != "HI" &
	state_abbr != "AK" &

nemochina2008 / animate-mcelreath-fig-6.3.R

Created November 27, 2018 02:20 — forked from datalorax/animate-mcelreath-fig-6.3.R

	# Code from Richard McElreath's book, chapter 6
	sppnames <- c( "afarensis","africanus","habilis","boisei",
	"rudolfensis","ergaster","sapiens")
	brainvolcc <- c( 438 , 452 , 612, 521, 752, 871, 1350 )
	masskg <- c( 37.0 , 35.5 , 34.5 , 41.5 , 55.5 , 61.0 , 53.5 )
	d <- data.frame( species=sppnames , brain=brainvolcc , mass=masskg )

	## R code 6.2
	m6.1 <- lm( brain ~ mass , data=d )

nemochina2008 / lmer_vs_inla_lmm.R

Created November 25, 2018 01:58 — forked from aghaynes/lmer_vs_inla_lmm.R

Compare variances from lmer and INLA for a linear mixed model (random intercept)

	#
	# Compare lmer and inla for LMM
	# largely taken from Spatial and spatio-temporal bayesian models with R-INLA (Blangiardo & Cameletti, 2015), section 5.4.2
	#

	m <- 10000 # N obs
	set.seed(1234)
	x <- rnorm(m)
	group <- sample(seq(1, 100), size = m, replace = TRUE)

nemochina2008 / world_maps.Rmd

Created November 23, 2018 18:37 — forked from clauswilke/world_maps.Rmd

	---
	title: "World maps"
	output:
	html_document:
	df_print: paged
	---

	```{r echo = FALSE, message = FALSE}
	library(tidyverse)
	library(sf)

nemochina2008 / animated_humidity_regression.md

Created October 20, 2018 03:07 — forked from andrewheiss/animated_humidity_regression.md

library(tidyverse)
library(lubridate)
library(broom)
library(scales)
library(gganimate)

# Load and clean data
# This data comes from Dark Sky's API
weather_provo_raw <- read_csv("https://andhs.co/provoweather")

nemochina2008 / base_r_plotting_tutorial_koontz_d-rug.r

Created September 6, 2018 05:04 — forked from Pakillo/base_r_plotting_tutorial_koontz_d-rug.r

	### Title: Back to basics: High quality plots using base R graphics
	### An interactive tutorial for the Davis R Users Group meeting on April 24, 2015
	###
	### Date created: 20150418
	### Last updated: 20150423
	###
	### Author: Michael Koontz
	### Email: [email protected]
	### Twitter: @michaeljkoontz
	###

nemochina2008 / themes.R

Created September 6, 2018 05:00 — forked from Pakillo/themes.R

ggplot_themes

	### My favourite ggplot2 themes, always accessible ###
	## just source this gist from any project ##


	#####################################################################################

	# Noam's default ggplot2 styling #####
	# Source: https://github.com/noamross/noamtools/blob/master/R/theme_nr.R
	theme_nr <-theme(text=element_text(family="Helvetica", size=14),
	panel.grid.major.x=element_blank(),

nemochina2008 / fig_label.R

Created September 6, 2018 04:58 — forked from Pakillo/fig_label.R

R function to draw figure labels in base plots

	## from: https://logfc.wordpress.com/2017/03/15/adding-figure-labels-a-b-c-in-the-top-left-corner-of-the-plotting-region/

	fig_label <- function(text, region="figure", pos="topleft", cex=NULL, ...) {

	region <- match.arg(region, c("figure", "plot", "device"))
	pos <- match.arg(pos, c("topleft", "top", "topright",
	"left", "center", "right",
	"bottomleft", "bottom", "bottomright"))

	if(region %in% c("figure", "device")) {

nemochina2008 / patchwork-plot

Created July 19, 2018 03:04 — forked from ColinFay/patchwork-plot

	library(patchwork)
	library(ggplot2)
	library(purrr)
	library(dplyr)
	library(glue)
	map(
	5:8,
	~iris %>%
	filter(Petal.Length < .x) %>%
	ggplot() +

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