In mschmidty/AIMtools: Tools for working with AIM Data.

knitr::opts_chunk$set(echo = TRUE)

options(
  max.print=50,
  vsc.use_httpgd = TRUE,
  device = 'windows'
)
library(AIMtools)
library(tidyverse)
library(arcgisbinding)
arc.check_product()

Check to see what plants are in LPI that are not in Species Richness

'%!in%' <- function(x,y)!('%in%'(x,y))

data_20<-load_data()

rich<-sp_rich(data=data_20,unknowns=T)%>%
  rename(symbol=2, rich_count=3)

lpi<-cover(data_20, type="detailed", by="plot")%>%
  count(PlotID,symbol)%>%
  rename(lpi_count=n)%>%
  filter(str_detect(symbol, ".{3,}"))

left_join(lpi, rich, by=c("PlotID", "symbol"))%>%
  filter(is.na(rich_count))

  ##write_csv("test_data/output/qa_qc/found_in_lpi_but_not_rich.csv")

## Check Function
sp_rich_qc(data_20)

cover(data_20, type="detailed")%>%
  View()

data_20$lpi_detail%>%
  dplyr::filter(stringr::str_detect(RecKey, "TRFO|COS01000"))%>%
  View()

read_csv("data/plant_list/CO_Survey123_species_20200504.csv")%>%
  View()

rich%>%
  filter(PlotID=="SS-099")

Check unknown codes with plant list

library(tidyverse)
plant_list<-read_csv("data/plant_list/CO_Survey123_species_20200504.csv")

agol_20$unknown%>%
  filter(stringr::str_detect(PlotKey, "TRFO|COS01000"))%>%
  select(PlotID, FinalCode)%>%
  mutate(FinalCode=str_trim(FinalCode))%>%
  left_join(plant_list, by=c("FinalCode"="name"))%>%
  filter(is.na(label))

agol_20$unknown%>%
  filter(stringr::str_detect(PlotKey, "TRFO|COS01000"))%>%
  filter(is.na(FinalCode))%>%
  View()

Find unknowns that are not in species richness

library(magrittr)
data_20[["unknown_plants"]]<-data_20$unknown_plants%>%
      dplyr::mutate(FinalCode==stringr::str_trim(FinalCode))

unknowns<-data_20$unknown_plants%>%
  dplyr::filter(stringr::str_detect(PlotKey, "TRFO|COS01000"))%>%
  dplyr::mutate(FinalCode=ifelse(is.na(FinalCode), UnknownCode, FinalCode))%>%
  dplyr::select(PlotID, FinalCode)%>%
  dplyr::filter(!is.na(FinalCode))

richness<-sp_rich(data_20)

dplyr::left_join(unknowns, richness, by=c("PlotID", "FinalCode"="species_code") )%>%
  dplyr::mutate(FinalCode=stringr::str_trim(FinalCode))%>%
  dplyr::filter(is.na(count))%>%
  dplyr::select(PlotID, FinalCode)%>%
  dplyr::mutate(error=paste0(FinalCode, ": Found in Unknown Plant list but not in Species  Richness on ", PlotID),
                fix=NA)

sp_rich_qc(data_20)

library(AIMtools)
library(arcgisbinding)
arc.check_product()
data_20<-load_data()


unknown_qc(data_20)

sp_rich_qc(data_20)

qa_qc(data_20)

Make Plant list with Symbols

co_plant_list<-readr::read_csv("data/plant_list/co_plant_list_08262020.txt")
accepted_symbols<-readr::read_csv("data/plant_list/co_plant_list_synonyms_10272020.csv")%>%
  dplyr::filter(`Accepted Symbol`==Symbol)

readr::read_csv("data/plant_list/co_plant_list_synonyms_10272020.csv")%>%
  dplyr::filter(`Accepted Symbol`!=Symbol)%>%
  dplyr::select(-`Common Name`, -Family)%>%
  dplyr::left_join(dplyr::select(accepted_symbols, `Accepted Symbol`, `Common Name`, Family), by="Accepted Symbol")%>%
  dplyr::select(Symbol:Family)%>%
  dplyr::bind_rows(dplyr::select(accepted_symbols, Symbol:Family))%>%
  readr::write_csv("data/plant_list/plant_list_with_synonyms_10272020.csv")

New Plants 2020

library(AIMtools)
library(arcgisbinding)
library(magrittr)
arc.check_product()

agol_20<-load_data()
agol_19<-load_data(year=2019)
dima_18<-readRDS("test_cache/DIMA_2018.rds")

count_20<-sp_rich(agol_20)%>%
  dplyr::count(species_code)%>%
  dplyr::rename(agol_20=n)

count_19<-sp_rich(agol_19)%>%
  dplyr::count(species_code)%>%
  dplyr::rename(agol_19=n)

count_18<-sp_rich_dima(dima_18)%>%
  dplyr::count(symbol)%>%
  dplyr::rename(species_code=symbol, dima_18=n)

total_plants<-dplyr::full_join(count_18, count_19)%>%
  dplyr::full_join(count_20)%>%
  dplyr::filter(!stringr::str_detect(species_code, "^[A-Z]{2}[0-9]{2}"))


plant_list<-readr::read_csv("data/plant_list/plant_list_with_synonyms_10272020.csv")

plant_list%>%
  dplyr::filter(Symbol %in% c("ERLE10", "PORE", "LAPA5", "SYER", "CAFL", "FOPU2"))


total_plants%>%
  dplyr::filter(is.na(agol_19)&is.na(dima_18))%>%
  dplyr::select(species_code)%>%
  dplyr::left_join(plant_list, by=c("species_code"="Symbol"))%>%
  readr::write_csv("test_data/output/qa_qc/new_species_2020_V2.csv")

total_plants%>%
  dplyr::filter(is.na(agol_20)&is.na(dima_18))%>%
  View()

sp_rich(agol_20)%>%
  dplyr::filter(species_code=="PLJA")

Plant_list for Synonyms

library(tidyverse)
synonym_check<-readr::read_csv("data/plant_list/co_plant_list_synonyms_10272020.csv")%>%
  dplyr::select(`Accepted Symbol`, `Symbol`, `Scientific Name`)

synonym_check%>%
  filter(str_detect(Symbol, "^PODO"))

Frequency All

Need to run this post all the checks!

total_plants%>%
  dplyr::left_join(synonym_check, by=c("species_code"="Symbol"))%>%
  dplyr::mutate(species_code=ifelse(`Accepted Symbol`==species_code, species_code, `Accepted Symbol`))%>%
  dplyr::select(-`Accepted Symbol`)%>%
  dplyr::mutate_if(is.numeric, tidyr::replace_na, replace=0)%>%
  dplyr::group_by(species_code, `Scientific Name`)%>%
  dplyr::summarise_if(is.numeric,sum)%>%
  dplyr::ungroup()%>%
  dplyr::mutate(total=(dima_18+agol_19+agol_20))%>%
  dplyr::rename(yr_2018=dima_18, yr_2019=agol_19, yr_2020=agol_20)%>%
  dplyr::arrange(desc(total))%>%
  write_csv("test_data/output/final_data/sp_rich/freqency_by_species_all_years.csv")

Unknowns

sp_rich(agol_20)%>%
  filter(str_detect(species_code, "[A-Z]{2}[0-9]{5}|XXXX$"))

sp_rich(agol_20)%>%
  dplyr::filter(species_code=="ROBL")

unknown_qc(agol_20)

library(arcgisbinding)
arc.check_product()
library(tidyverse)
library(devtools)
library(AIMtools)

load_all()

data<-load_data()

rich<-sp_rich(data=data,unknowns=T)%>%
    dplyr::rename(symbol=2, rich_count=3)

lpi<-cover(data, type="detailed", by="plot")%>%
  dplyr::count(PlotID, symbol, PlotKey)%>%
  dplyr::rename(lpi_count=n)%>%
  dplyr::filter(stringr::str_detect(symbol, ".{3,}"))

lpi_check<-dplyr::left_join(lpi, rich, by=c("PlotID", "symbol"))%>%
  dplyr::filter(is.na(rich_count))%>%
  dplyr::select(PlotID, symbol, PlotKey)%>%
  dplyr::mutate(error="Symbol appears in LPI form but not in Species Richness",
                fix=paste0("Add this symbol to Species Richness to plot ", PlotID))

unknowns<-data$unknown_plants%>%
  dplyr::select(PlotID, Office, PlotKey, UnknownCode, FinalCode)%>%
  dplyr::mutate(FinalCode=ifelse(is.na(FinalCode), UnknownCode, FinalCode))%>%
  dplyr::filter(!is.na(FinalCode))

richness<-sp_rich(data)

unknown_check<-dplyr::left_join(unknowns, richness, by=c("PlotID", "FinalCode"="species_code") )%>%
  dplyr::filter(is.na(count))%>%
  dplyr::select(PlotID, UnknownCode, Office, PlotKey)%>%
  dplyr::rename(symbol=UnknownCode)%>%
  dplyr::mutate(error=paste0(symbol, ": Found in Unknown Plant list but not in Species  Richness on ", PlotID),
                fix=NA)

final_check<-dplyr::bind_rows(unknown_check, lpi_check)

Have we Evaled

data$plots%>%
  filter_fo()%>%
  filter(panel!="Oversample")%>%
  count(EvalStatus)

check 2021

qa_qc_2021<-qa_qc(data)

qa_qc_2021$sp_rich_check%>%
  filter_fo()%>%
  View()

Check number of plots complete

library(arcgisbinding)
arc.check_product()
library(tidyverse)
library(devtools)
library(AIMtools)
library(here)

data<-load_data(year=2021)

data$plots%>%
  filter_fo()%>%
  count(EvalStatus)

qaqc<-qa_qc(data)%>%
  lapply(filter_fo)

qaqc$unknown_symbol_check%>%
  write_csv(here("test/output/qaqc_2021_unknown_symbol_check.csv"))

qaqc$sp_rich_check%>%
  write_csv(here("test/output/qaqc_2021_sp_rich_check.csv"))

DIMA QA QC

dima<-read_dima("test_data/DIMA_2021.mdb")

dima_cover(dima)%>%
  filter(is.na(list_name), symbol!="None")%>%
  select(symbol, LineID, PlotID)%>%
  mutate(fix = "Symbol does not match plant list. Revise to species that is on the plant list.")%>%
  write_csv("test_data/output/qa_qc_DIMA_2021_LPI.csv")

sp_rich_dima(dima)%>%
  left_join(dima$plant_list, by=c("symbol" = "name"))%>%
  filter(is.na(list_name))%>%
  mutate(error = "Not found in Plant list.  Correct or replace with Synonym.")%>%
  write_csv("test_data/output/qa_qc_DIMA_2021_sp_rich.csv")

dima$plant_list

2022 Tests

library(AIMtools)
library(tidyverse)
data<-readRDS("test_cache/agol_2022_08.rds")

qa_qc(data)

rich<-sp_rich(data, unknowns=T)%>%
  dplyr::rename(symbol=2, rich_count=3)

lpi<-cover(data, type="detailed", by="plot")%>%
  dplyr::count(PlotID, symbol, PlotKey)%>%
  dplyr::rename(lpi_count=n)%>%
  dplyr::filter(stringr::str_detect(symbol, ".{3,}"))

lpi_check<-dplyr::left_join(lpi, rich, by=c("PlotID" = "symbol"))

qa_qc(data)