View asci_csci_diff.R
library(tidyverse) | |
library(patchwork) | |
toplo1 <- sqidat %>% | |
select(MasterID, yr, asci_mean, csci_mean, TN, TP, indexscore_cram) %>% | |
gather('nuts', 'val', TN, TP) %>% | |
na.omit %>% | |
mutate( | |
inddif = asci_mean - csci_mean, | |
cramcat = case_when( |
View evaldat
library(tidyverse) | |
library(gridExtra) | |
library(grid) | |
library(imputeTestbench) | |
library(PSF) | |
library(imputePSF) | |
library(imputeTS) | |
library(scales) | |
# total obs in each simulated time series |
View tmapex
# load libraries | |
library(sf) | |
library(maps) | |
library(tmap) | |
# get states as sf | |
states <- st_as_sf(map('state', plot = F, fill = T)) | |
# calculate area, add to states | |
area <- st_area(states) |
View gist:1870bb6f093b86139addcc515503a39e
# load packages | |
library(sf) | |
library(plotly) | |
library(mapview) | |
# download data and save in memory | |
wsa <- read.csv("https://www.epa.gov/sites/production/files/2014-10/wsa_siteinfo_ts_final.csv") | |
# make an sf object | |
wsa <- st_as_sf(wsa, coords = c("LON_DD", "LAT_DD"), crs = 4269,agr = "constant") |
View chloroex
# load libraries | |
library(sf) | |
library(maps) | |
library(ggplot2) | |
# get states as sf | |
states <- st_as_sf(map('state', plot = F, fill = T)) | |
# calculate area, add to states | |
area <- st_area(states) |
View meuse exercise
# load libraries | |
library(sp) # for meuse | |
library(sf) # for sf objects | |
library(ggmap) # for base maps | |
library(ggplot2) # for mapping | |
# import dataset, check structure | |
data(meuse) | |
str(meuse) |
View basic-mappingex1
--- | |
title: "Basic mapping" | |
author: "Turbo Todd" | |
output: html_document | |
--- | |
This lessons covers base graphics, ggplot, and other R packags for mapping spatial data. | |
```{r} | |
library(maps) |
View gist:5ecb73e1304e7faee83eb05b922937e7
echo sha, contributor, date, message > log.csv | |
git log --date=local --pretty=format:'%h, %an, %ad, "%s"' >> log.csv |
View moth_form.R
#' Format a text file for mothur | |
#' | |
#' @param fl chr string for input file | |
#' @param rev_cmp logical if file needs reverse complemeNT | |
#' @param savefl logical if output file is saved, otherwise the output is returned in the console | |
moth_form <- function(fl, rev_cmp = FALSE, savefl = TRUE, flnm = 'myfile.txt'){ | |
# import file | |
dat <- read.table(fl, sep = '\t') | |
View plotFlowConc.r
plotFlowConc <- function(eList, month = c(1:12), years = NULL, col_vec = c('red', 'green', 'blue'), ylabel = NULL, xlabel = NULL, alpha = 1, size = 1, allflo = FALSE, ncol = NULL, grids = TRUE, scales = NULL, interp = 4, pretty = TRUE, use_bw = TRUE, fac_nms = NULL, ymin = 0){ | |
localDaily <- getDaily(eList) | |
localINFO <- getInfo(eList) | |
localsurfaces <- getSurfaces(eList) | |
# plot title | |
toplab <- with(eList$INFO, paste(shortName, paramShortName, sep = ', ')) | |
# flow, date info for interpolation surface |
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