jebyrnes’s gists

jebyrnes / geospatial_test.R

Last active January 22, 2019 14:11

Try this and make sure there are no errors. If it all runs, you're in good shape! Should make three plots, and install rnaturalearth, which is pretty cool

	#'------------------------------
	#'
	#' Script to make sure everything works
	#' for you for the 2019-01-22 Geospatial
	#' Data Carpentry workshop at UMB
	#'------------------------------

	# Make sure we have rnaturalearth installed
	# If you do, comment out the install.packages line
	#or just don't run it.

jebyrnes / threshold_classifications_sf.R

Created January 3, 2019 19:46

Makes thresholded sf multipolygons from user classifications for floating forests with a sample data set


	library(sf)
	library(fasterize)
	library(spex)
	library(dplyr)
	library(purrr)
	library(ggplot2)
	library(lwgeom)

	test_set <- devtools::source_gist("c95701bd444cda3e342838fd9a090fb3",

jebyrnes / test_set.R

Created January 2, 2019 18:28

a sample sf multipolygon set

	structure(list(classification_id = c(82289537L, 82386012L, 84461998L,
	85718077L, 91018956L, 102059723L, 102656990L, 103374144L, 105820504L,
	108510525L, 113891667L, 120531542L, 133372372L, 133644897L, 134776350L
	), geometry = structure(list(structure(list(structure(list(structure(c(314658.101094576,
	314658.101094576, 314637.103677284, 314616.106259993, 314616.106259993,
	314595.108842701, 314595.108842701, 314574.111425409, 314553.114008117,
	314553.114008117, 314532.116590825, 314532.116590825, 314511.119173533,
	314511.119173533, 314511.119173533, 314511.119173533, 314511.119173533,
	314511.119173533, 314511.119173533, 314532.116590825, 314532.116590825,
	314553.114008117, 314574.111425409, 314595.108842701, 314616.106259993,

jebyrnes / tidy_residuals.R

Created November 4, 2018 02:58

Some residual methods for tidybayes


	tidy_residuals <- function(model){
	UseMethod("tidy_residuals")
	}

	tidy_residuals.brmsfit <- function(model){
	res <- residuals(model, summary=FALSE)
	props <- summary(model)
	nchains <- props$chains
	iter <- props$iter - props$warmup

jebyrnes / data.r

Created November 3, 2018 03:07

	brainGene <- structure(list(group = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
	1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
	2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
	3L, 3L, 3L, 3L, 3L, 3L), .Label = c("control", "schizo", "bipolar"
	), class = "factor"), PLP1.expression = c(-0.02, -0.27, -0.11,
	0.09, 0.25, -0.02, 0.48, -0.24, 0.06, 0.07, -0.3, -0.18, 0.04,
	-0.16, 0.25, -0.1, -0.31, -0.05, 0.11, -0.38, 0.23, -0.23, -0.28,
	-0.36, -0.22, -0.4, -0.19, -0.34, -0.29, -0.12, -0.34, -0.39,

jebyrnes / bayesian_posthoc.R

Last active February 10, 2023 20:29

Posthoc contrasts with emmeans, tidybayes, and brms

	library(tidyverse)
	library(emmeans)
	library(brms)
	library(tidybayes)

	warp.brms <- brm(breaks ~ wool * tension, data = warpbreaks)

	#get the adjusted means
	warp_em <- emmeans (warp.brms, ~ tension \| wool)
	warp_em

jebyrnes / sst_lambert.R

Created October 6, 2018 03:10

SST change in the lambert projection

	library(raster)
	#devtools::install_github("jebyrnes/hadsstr")
	library(hadsstr) #from jebyrnes/hadsstr
	library(ggplot2)
	library(sf)
	library(rnaturalearth)

	#get the world in the lambert projection
	countries_50_sf <- ne_download(scale = 50, category = 'cultural', type = 'countries', returnclass="sf")
	countries_lambert <- st_transform(oceans, 2154)

jebyrnes / glm_profile.R

Last active April 22, 2019 21:20

Take a glm and creates a deviance profile, as MASS::profile only returns a transformed version of the deviance.

	library(ggplot2)

	#A glm from the glm helpfile
	counts <- c(18,17,15,20,10,20,25,13,12)
	outcome <- gl(3,1,9)
	treatment <- gl(3,3)
	print(d.AD <- data.frame(treatment, outcome, counts))
	glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())

	#The old way...

jebyrnes / ocean_lambert.R

Created October 2, 2018 04:20

	library(sf)
	library(rnaturalearth)
	library(rnaturalearthdata)
	library(ggplot2)


	oceans <- ne_download(type = "ocean", category = "physical", returnclass="sf")
	ocean_antarctic <- st_transform(oceans, 2154)
	ggplot(ocean_antarctic) +
	geom_sf(fill = "lightblue", color=NA)

jebyrnes / discrete_grrrowth.R

Created October 2, 2018 03:58

How to use purrr::iwalk to do discrete time logistic growth models.

	#'----------------
	#' Discrete time logistic growth model
	#' Using purrr and iwalk
	#'----------------


	library(purrr)

	r <- 3.95237783423
	n0 <- 0.3

Jarrett Byrnes jebyrnes