dev_bind.Rmd

---
title: "Untitled"
author: "Gavin Lemley"
date: "February 8, 2019"
output: html_document
---

```{r}

bind_nearest_date <- function(sample.df, match.df, match.col) {

final.df <- lapply(unique(match.df$chemical_name), function(param.i) {
  sample.param.i <- sample.df[sample.df$chemical_name == param.i, ]
  match.param.i <- match.df[match.df$chemical_name == param.i,]
  
  site.df <- lapply(unique(sample.param.i$sys_sample_code), function(site.i) {
    sample.sub <- sample.param.i[sample.param.i$sys_sample_code == site.i, ]
    match.param.i$abs <- abs(match.param.i$sample_date - sample.sub$sample_date) 
    match.param.i$min <- min(abs(match.param.i$sample_date - sample.sub$sample_date))
    match.param.i <- match.param.i[which(match.param.i$abs == match.param.i$min), ]
    sample.sub[, match.col] <- match.param.i[, match.col][1]
    return(sample.sub)
  }) %>% 
    dplyr::bind_rows()

}) %>% 
 dplyr::bind_rows() 

return(final.df)
}

samples <- unique(data[c('sys_sample_code','chemical_name','sample_date')])
spike$percrecovery<-((abs(spike$qc_spike_measured-spike$qc_original_conc))/spike$qc_spike_added)*100
spike$spikeamount<-spike$qc_original_conc/spike$qc_spike_added
spike$pass<-ifelse(spike$spikeamount>4,NA,
            ifelse(spike$percrecover>(100+spike$accuracy)|spike$percrecovery<(100-spike$accuracy),"fail","pass"))
spikes<-unique(spike[c('chemical_name','sample_date','pass')])
library(tidyverse)

test <- bind_nearest_date(samples.df = samples,
                          match.df = spikes,
                          match.col = "pass") %>% 
  rename(spikepass = pass)

test %>% 
  arrange(sys_sample_code) %>% 
  
  identical(dataset)

```