diff --git a/R/chkinp.R b/R/chkinp.R
index 1619d71..0958171 100644
--- a/R/chkinp.R
+++ b/R/chkinp.R
@@ -58,7 +58,8 @@ chkinp <- function(data, purge = FALSE, msgs = FALSE){
algae <- c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached')
channelsinuosity <- c('Slope', 'Length, Segment', 'Elevation Difference', 'Bearing', 'Proportion', 'Length, Reach')
densiometer <- c('Canopy Cover')
- sels <- c(algae, channelsinuosity, densiometer)
+ ripveg <- c('Riparian GroundCover Barren', 'Riparian GroundCover NonWoody Plants', 'Riparian GroundCover Woody Shrubs', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian GroundCover Woody Shrubs', 'Riparian GroundCover NonWoody Plants')
+ sels <- c(algae, channelsinuosity, densiometer, ripveg)
# see if duplicate id, locationcode, analytename
chk <- data %>%
diff --git a/R/misc.R b/R/misc.R
index 21e12fa..ad69992 100644
--- a/R/misc.R
+++ b/R/misc.R
@@ -9,7 +9,7 @@
#' @examples
#' misc(sampdat)
misc <- function(data){
-
+
data <- data[which(data$AnalyteName %in% c('Riffle/Run Channel Alteration', 'Riffle/Run Epifaunal Substrate', 'Riffle/Run Sediment Deposition', 'Dominant Land Use', 'Evidence of Fire', 'Evidence of Recent Rainfall')),]
###Report###
data$VariableResult[data$ResQualCode=="NR"] <- NA
@@ -43,7 +43,7 @@ misc <- function(data){
dplyr::full_join(RBP_SED, by = 'id') %>%
as.data.frame(stringsAsFactors = F)
- rownames(misc_metrics) <- gsub('\\s.*$', '', misc_metrics$id)
+ rownames(misc_metrics) <- misc_metrics$id
misc_metrics <- misc_metrics[, !names(misc_metrics) %in% 'id']
colnames(misc_metrics)<- c("NFC_DLU.result", "NFC_EFR.result", "NFC_ERN.result",
diff --git a/R/phabmetrics.R b/R/phabmetrics.R
index 6a05057..dc44aef 100644
--- a/R/phabmetrics.R
+++ b/R/phabmetrics.R
@@ -10,6 +10,7 @@
#' }
phabmetrics <- function(data){
data <- phabformat(data)
+ data <- chkinp(data, purge = TRUE)
metrics <- list(bankmorph(data), channelmorph(data), channelsinuosity(data),
densiometer(data), habitat(data), disturbance(data), flow(data),
misc(data), bankstability(data), quality(data), ripveg(data),
diff --git a/R/ripveg.R b/R/ripveg.R
index 4a1caa7..eb2eb4c 100644
--- a/R/ripveg.R
+++ b/R/ripveg.R
@@ -14,16 +14,19 @@ ripveg <- function(data){
barren <- data.frame(cbind(data$id[barrenindex], as.character(data$AnalyteName[barrenindex]),
as.character(data$VariableResult[barrenindex])))
colnames(barren) <- c("id", "AnalyteName", "result")
- barren$result <- as.numeric(as.character(barren$result))
+ barren$result <- as.character(barren$result)
###Compute XGB###
-
- for(i in (1:length(barren$result))[which(!is.na(barren$result))]){
- if(barren$result[i] == 1){barren$result[i] <- 5} else
- if(barren$result[i] == 2){barren$result[i] <- 25} else
- if(barren$result[i] == 3){barren$result[i] <- 57.5} else
- if(barren$result[i] == 4){barren$result[i] <- 87.5}
- }
+
+ barren$result <- dplyr::case_when(
+ barren$result == '0' ~ 0,
+ barren$result == '1' ~ 5,
+ barren$result == '2' ~ 25,
+ barren$result == '3' ~ 57.5,
+ barren$result == '4' ~ 87.5,
+ TRUE ~ NaN
+ )
+
sumna <- function(data){
sum(data, na.rm = T)
}
@@ -45,15 +48,18 @@ ripveg <- function(data){
nonwoody <- data.frame(cbind(data$id[nonwoodyindex], as.character(data$AnalyteName[nonwoodyindex]),
as.character(data$VariableResult[nonwoodyindex])))
colnames(nonwoody) <- c("id", "AnalyteName", "result")
- nonwoody$result <- as.numeric(as.character(nonwoody$result))
+ nonwoody$result <- as.character(nonwoody$result)
###Compute XGH###
- for(i in (1:length(nonwoody$result))[which(!is.na(nonwoody$result))]){
- if(nonwoody$result[i] == 1){nonwoody$result[i] <- 5} else
- if(nonwoody$result[i] == 2){nonwoody$result[i] <- 25} else
- if(nonwoody$result[i] == 3){nonwoody$result[i] <- 57.5} else
- if(nonwoody$result[i] == 4){nonwoody$result[i] <- 87.5}
- }
+ nonwoody$result <- dplyr::case_when(
+ nonwoody$result == '0' ~ 0,
+ nonwoody$result == '1' ~ 5,
+ nonwoody$result == '2' ~ 25,
+ nonwoody$result == '3' ~ 57.5,
+ nonwoody$result == '4' ~ 87.5,
+ TRUE ~ NaN
+ )
+
sumna <- function(data){
sum(data, na.rm = T)
}
@@ -78,16 +84,18 @@ ripveg <- function(data){
woody$result[woody$result %in% 'Not Recorded'] <- NA
woody$result <- as.numeric(as.character(woody$result))
- head(woody)
###Compute XGW###
- for(i in (1:length(woody$result))[which(!is.na(woody$result))]){
- if(woody$result[i] == 1){woody$result[i] <- 5} else
- if(woody$result[i] == 2){woody$result[i] <- 25} else
- if(woody$result[i] == 3){woody$result[i] <- 57.5} else
- if(woody$result[i] == 4){woody$result[i] <- 87.5}
- }
+ woody$result <- dplyr::case_when(
+ woody$result == '0' ~ 0,
+ woody$result == '1' ~ 5,
+ woody$result == '2' ~ 25,
+ woody$result == '3' ~ 57.5,
+ woody$result == '4' ~ 87.5,
+ TRUE ~ NaN
+ )
+
sumna <- function(data){
sum(data, na.rm = T)
}
@@ -109,17 +117,19 @@ ripveg <- function(data){
lowercanopy <- data.frame(cbind(data$id[lowercanopyindex], as.character(data$AnalyteName[lowercanopyindex]),
as.character(data$VariableResult[lowercanopyindex])))
colnames(lowercanopy) <- c("id", "AnalyteName", "result")
- lowercanopy$result <- as.numeric(as.character(lowercanopy$result))
- head(lowercanopy)
+ lowercanopy$result <- as.character(lowercanopy$result)
###Compute XM###
- for(i in (1:length(lowercanopy$result))[which(!is.na(lowercanopy$result))]){
- if(lowercanopy$result[i] == 1){lowercanopy$result[i] <- 5} else
- if(lowercanopy$result[i] == 2){lowercanopy$result[i] <- 25} else
- if(lowercanopy$result[i] == 3){lowercanopy$result[i] <- 57.5} else
- if(lowercanopy$result[i] == 4){lowercanopy$result[i] <- 87.5}
- }
+ lowercanopy$result <- dplyr::case_when(
+ lowercanopy$result == '0' ~ 0,
+ lowercanopy$result == '1' ~ 5,
+ lowercanopy$result == '2' ~ 25,
+ lowercanopy$result == '3' ~ 57.5,
+ lowercanopy$result == '4' ~ 87.5,
+ TRUE ~ NaN
+ )
+
sumna <- function(data){
sum(data, na.rm = T)
}
@@ -142,17 +152,19 @@ ripveg <- function(data){
as.character(data$VariableResult[uppercanopyindex])))
colnames(uppercanopy) <- c("id", "AnalyteName", "result")
- uppercanopy$result <- as.numeric(as.character(uppercanopy$result))
- head(uppercanopy)
+ uppercanopy$result <- as.character(uppercanopy$result)
###Compute XC###
- for(i in (1:length(uppercanopy$result))[which(!is.na(uppercanopy$result))]){
- if(uppercanopy$result[i] == 1){uppercanopy$result[i] <- 5} else
- if(uppercanopy$result[i] == 2){uppercanopy$result[i] <- 25} else
- if(uppercanopy$result[i] == 3){uppercanopy$result[i] <- 57.5} else
- if(uppercanopy$result[i] == 4){uppercanopy$result[i] <- 87.5}
- }
+ uppercanopy$result <- dplyr::case_when(
+ uppercanopy$result == '0' ~ 0,
+ uppercanopy$result == '1' ~ 5,
+ uppercanopy$result == '2' ~ 25,
+ uppercanopy$result == '3' ~ 57.5,
+ uppercanopy$result == '4' ~ 87.5,
+ TRUE ~ NaN
+ )
+
sumna <- function(data){
sum(data, na.rm = T)
}
@@ -185,6 +197,7 @@ ripveg <- function(data){
lowercanopy <- data.frame(cbind(data$id[lowercanopyindex], as.character(data$AnalyteName[lowercanopyindex]),
as.character(data$VariableResult[lowercanopyindex])))
colnames(lowercanopy) <- c("id", "AnalyteName", "result")
+ lowercanopy$result[lowercanopy$result %in% 'Not Recorded'] <- NA
lowercanopy$result <- as.numeric(as.character(lowercanopy$result))
XPMID_total <- tapply(lowercanopy$result, lowercanopy$id, lengthna)
@@ -202,8 +215,8 @@ ripveg <- function(data){
uppercanopy <- data.frame(cbind(data$id[uppercanopyindex], as.character(data$AnalyteName[uppercanopyindex]),
as.character(data$VariableResult[uppercanopyindex])))
colnames(uppercanopy) <- c("id", "AnalyteName", "result")
+ uppercanopy$result[uppercanopy$result %in% 'Not Recorded'] <- NA
uppercanopy$result <- as.numeric(as.character(uppercanopy$result))
- head(uppercanopy)
XPCAN_total <- tapply(uppercanopy$result, uppercanopy$id, lengthna)
@@ -213,7 +226,7 @@ ripveg <- function(data){
}
XPCAN_subcount <- tapply(uppercanopy$result, uppercanopy$id, XPCAN_subcountf)
XPCAN.result <- XPCAN_subcount/XPCAN_total
-
+
###Compute XPGVEG###
woodyindex <- which(data$AnalyteName == "Riparian GroundCover Woody Shrubs")
woody <- data.frame(cbind(data$id[woodyindex], as.character(data$AnalyteName[woodyindex]),
@@ -226,6 +239,7 @@ ripveg <- function(data){
nonwoody <- data.frame(cbind(data$id[nonwoodyindex], as.character(data$AnalyteName[nonwoodyindex]),
as.character(data$VariableResult[nonwoodyindex])))
colnames(nonwoody) <- c("id", "AnalyteName", "result")
+ nonwoody$result[nonwoody$result %in% 'Not Recorded'] <- NA
nonwoody$result <- as.numeric(as.character(nonwoody$result))
head(nonwoody)
woody$XPGVEG<-apply((cbind(woody$result, nonwoody$result)), 1, sum, na.rm=T)
diff --git a/R/substrate.R b/R/substrate.R
index d4fa109..eaae68a 100644
--- a/R/substrate.R
+++ b/R/substrate.R
@@ -4,10 +4,21 @@
#'
#' @export
#'
+#' @importFrom magrittr "%>%"
+#'
#' @examples
#' substrate(sampdat)
substrate <- function(data){
data <- data[which(data$AnalyteName %in% c('Substrate Size Class', 'Embeddedness', 'CPOM')),]
+
+ data <- data %>%
+ dplyr::select(id, LocationCode, AnalyteName, VariableResult, Result) %>%
+ unique %>%
+ tidyr::complete(id, LocationCode, AnalyteName) %>%
+ dplyr::group_by(id) %>%
+ dplyr::filter(!all(is.na(VariableResult) & !all(is.na(Result)))) %>%
+ dplyr::ungroup()
+
data$VariableResult <- as.character(data$VariableResult)
data$VariableResult[data$VariableResult=="a"]<-"SA"
data$VariableResult[data$VariableResult=="as"]<-"SA"
@@ -33,12 +44,11 @@ substrate <- function(data){
###Compute
metric <- c('RS', 'RR', 'RC', 'XB', 'SB', 'CB', 'GC', 'GF', 'SA', 'FN', 'HP', 'WD', 'OT')
-
sub$VariableResult <- lapply(sub$VariableResult, toupper)
-
+
lengths <- function(data){
length(which(((data != "NOT RECORDED") &(data != "NA"))&(data != "FNOT RECORDED")))}
- totals <- tapply(sub$VariableResult, sub$id, lengths)
+ totals <- tapply(unlist(sub$VariableResult), sub$id, lengths)
tnames <- as.vector(dimnames(totals))
qq <-unlist(tnames)
l <- matrix(NA, ncol=length(metric), nrow=length(totals))
@@ -140,13 +150,13 @@ substrate <- function(data){
result$XEMBED.result <- XEMBED_sum/XEMBED_count
result$XEMBED.count <- XEMBED_count
result$XEMBED.sd <- tapply(embed$Result, embed$id, sdna)
-
+
cpom <- data[data$AnalyteName=="CPOM",]
present <- function(data){
- sum(data == "Present")
+ sum(data == "Present", na.rm = TRUE)
}
cpomtotal <- function(data){
- sum((data == "Present") | (data == "Absent"))
+ sum((data == "Present") | (data == "Absent"), na.rm = TRUE)
}
cpresent <- tapply(cpom$VariableResult, cpom$id, present)
ctotal <- tapply(cpom$VariableResult, cpom$id, cpomtotal)
diff --git a/README.Rmd b/README.Rmd
index ae62145..ac4b862 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -41,14 +41,25 @@ phabmetrics(sampdat)
# Required data checks
-* Every unique `id`, `LocationCode`, `AnalyteName`, and `VariableResult` combination should have only one entry in `VariableResult` for `AnalyteName %in% c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached')`. The `algae.R` function will remove duplicate entries but a checker should be built that verifies a unique value can be determined.
+* For every function, make sure there are no duplicate or conflicting values for every unique combination of `id`, `LocationCode`, `AnalyteName`, and `VariableResult` (or `Result`). This should be specific to the metric classes just to be safe. For example, every combination should have only one entry in `VariableResult` for `AnalyteName %in% c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached')` for the algae metrics. The `algae.R` function will remove duplicate entries but a checker should be built that verifies a unique value can be determined.
* Required column names, see those in `sampdat`.
* Check for required values in `AnalyteName` (note that `chkinp()` can check of the columns exist but we'll need a checker on data input to check for these and only these):
* `c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached')` for `algae()`
* `c('Bankfull Height', 'Bankfull Width', 'StationWaterDepth', 'Wetted Width')` for `bankmorph()`
- * `c(Slope', 'Length, Segment', 'Elevation Difference', 'Bearing', 'Proportion', 'Length, Reach')` for `channelsinuosity()`
* `c('Cascade/Falls', 'Dry', 'Glide', 'Pool', 'Rapid', 'Riffle', 'Run'))` for `channelmorph()`
+ * `c(Slope', 'Length, Segment', 'Elevation Difference', 'Bearing', 'Proportion', 'Length, Reach')` for `channelsinuosity()`
+ * `c('Canopy Cover')` for `densiometer()`
+ * `c('Distance from Bank', 'StationWaterDepth', 'Velocity', 'Distance, Float', 'Float Time', 'Wetted Width')` for `flow()`
+ * `c('Fish Cover Macrophytes', 'Fish Cover Artificial Structures', 'Fish Cover Boulders', 'Fish Cover Filamentous Algae', 'Fish Cover Woody Debris >0.3 m', 'Fish Cover Live Trees/Roots', 'Fish Cover Overhang.Veg', 'Fish Cover Woody Debris <0.3 m', 'Fish Cover Undercut Banks')` for `habitat()`
+ * `c('Riparian Bridges/Abutments', 'Riparian Buildings', 'Riparian Landfill/Trash', 'Riparian Logging', 'Riparian Mining', 'Riparian Orchards/Vineyards', 'Riparian Park/Lawn', 'Riparian Pasture/Range', 'Riparian Pavement', 'Riparian Pipes', 'Riparian Road', 'Riparian Row Crops', 'Riparian Vegetation Management', 'Riparian Wall/Dike')` for `disturbance()`
+ * `c('Riffle/Run Channel Alteration', 'Riffle/Run Epifaunal Substrate', 'Riffle/Run Sediment Deposition', 'Dominant Land Use', 'Evidence of Fire', 'Evidence of Recent Rainfall')` for `misc()`
+ * `c('Bank Stability')` for `bankstability()`
+ * `c("Alkalinity as CaCO3", "Oxygen, Dissolved", "pH", "Salinity", "SpecificConductivity", "Temperature", "Turbidity")` for `quality()`
+ * `c('Riparian GroundCover Barren', 'Riparian GroundCover NonWoody Plants', 'Riparian GroundCover Woody Shrubs', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian GroundCover Woody Shrubs', 'Riparian GroundCover NonWoody Plants')` for `ripveg()`
+ * `c('Substrate Size Class', 'Embeddedness', 'CPOM')` for `substrate()`
-* Check for required values in `LocationCode` (note that `chkinp()` can check of the columns exist but we'll need a checker on data input to check for these and only these)
\ No newline at end of file
+* Check for required values in `LocationCode` (note that `chkinp()` can check of the columns exist but we'll need a checker on data input to check for these and only these)
+
+* Maybe we need to add a checker to make sure all values in each field are present but with appropriate NA values for `Result`, `VariableResult`, this can be done with `tidyr::complete()` but may be unnecessary since this will increase data volume
\ No newline at end of file
diff --git a/README.html b/README.html
index 503781a..f12ea35 100644
--- a/README.html
+++ b/README.html
@@ -144,9 +144,6 @@ Installing the package
Usage
The core function is phabmetrics().
phabmetrics(sampdat)
-## Warning in reach[which(unlist(dimnames(reach)) %in%
-## unlist(dimnames(SLOPE_0_reach)))] <- SLOPE_0_reach: number of items to
-## replace is not a multiple of replacement length
## XBKF_H.result XBKF_H.count
## 402M00002_2015-08-13_1 "0.659090909090909" "11"
## SMC00710_2009-05-20_1 "0.491818181818182" "77"
@@ -249,44 +246,44 @@ Usage
## SMC04383_2010-06-09_1 "47" "0"
## XSLOPE.count XSLOPE.sd
## 402M00002_2015-08-13_1 "11" "0.00301511344577764"
-## SMC00710_2009-05-20_1 "13" "0"
+## SMC00710_2009-05-20_1 "12" "0"
## SMC00957_2010-06-21_1 "11" "0"
## SMC04383_2010-06-09_1 "11" "0"
## SLOPE_0.result SLOPE_0.count SLOPE_0_5.result
## 402M00002_2015-08-13_1 "0" "10" "666.666666666667"
-## SMC00710_2009-05-20_1 "666.666666666667" "12" "0"
+## SMC00710_2009-05-20_1 "666.666666666667" "10" "0"
## SMC00957_2010-06-21_1 "666.666666666667" "10" "0"
## SMC04383_2010-06-09_1 "666.666666666667" "10" "0"
## SLOPE_0_5.count SLOPE_1.result SLOPE_1.count
## 402M00002_2015-08-13_1 "10" "666.666666666667" "10"
-## SMC00710_2009-05-20_1 "12" "0" "12"
+## SMC00710_2009-05-20_1 "10" "0" "10"
## SMC00957_2010-06-21_1 "10" "0" "10"
## SMC04383_2010-06-09_1 "10" "0" "10"
## SLOPE_2.result SLOPE_2.count
## 402M00002_2015-08-13_1 "666.666666666667" "10"
-## SMC00710_2009-05-20_1 "0" "12"
+## SMC00710_2009-05-20_1 "0" "10"
## SMC00957_2010-06-21_1 "0" "10"
## SMC04383_2010-06-09_1 "0" "10"
## XBEARING.result XBEARING.count
## 402M00002_2015-08-13_1 "0.00909090909090909" "11"
-## SMC00710_2009-05-20_1 "0.414615384615385" "13"
-## SMC00957_2010-06-21_1 "0.0363636363636364" "11"
-## SMC04383_2010-06-09_1 "0.0363636363636364" "11"
+## SMC00710_2009-05-20_1 "0.0075" "12"
+## SMC00957_2010-06-21_1 "0.00909090909090909" "11"
+## SMC04383_2010-06-09_1 "0.00909090909090909" "11"
## XBEARING.sd SINU.NOT_WORKING
## 402M00002_2015-08-13_1 "0.00301511344577764" "28.6493442492751"
-## SMC00710_2009-05-20_1 "0.184011565968709" "4.10275452406255"
-## SMC00957_2010-06-21_1 "0.0120604537831105" "14.3268541739219"
-## SMC04383_2010-06-09_1 "0.0120604537831105" "14.3268541739219"
+## SMC00710_2009-05-20_1 "0.00452267016866645" "31.8326047214168"
+## SMC00957_2010-06-21_1 "0.00301511344577764" "28.6493442492751"
+## SMC04383_2010-06-09_1 "0.00301511344577764" "28.6493442492751"
## XCDENMID.result XCDENMID.count
## 402M00002_2015-08-13_1 "77.0053475935829" "44"
-## SMC00710_2009-05-20_1 "84.7593582887701" "308"
-## SMC00957_2010-06-21_1 "53.8770053475936" "88"
-## SMC04383_2010-06-09_1 "50" "88"
+## SMC00710_2009-05-20_1 "84.7593582887701" "88"
+## SMC00957_2010-06-21_1 "53.8770053475936" "44"
+## SMC04383_2010-06-09_1 "50" "44"
## XCDENMID.sd XCDENBK.result XCDENBK.count
## 402M00002_2015-08-13_1 "35.0841493056178" "NaN" "0"
-## SMC00710_2009-05-20_1 "18.5179940474629" "NaN" "0"
-## SMC00957_2010-06-21_1 "34.1240156751681" "NaN" "0"
-## SMC04383_2010-06-09_1 "34.8974782696344" "NaN" "0"
+## SMC00710_2009-05-20_1 "18.5938566922201" "NaN" "0"
+## SMC00957_2010-06-21_1 "34.321837713125" "NaN" "0"
+## SMC04383_2010-06-09_1 "35.0997841862817" "NaN" "0"
## XCDENBK.sd XFC_AQM.result XFC_AQM.count
## 402M00002_2015-08-13_1 NA "22.9545454545455" "11"
## SMC00710_2009-05-20_1 NA "3.63636363636364" "77"
@@ -504,37 +501,37 @@ Usage
## SMC04383_2010-06-09_1 "16.22" "61.196" "10.8"
## XGB.result XGB.count XGB.sd
## 402M00002_2015-08-13_1 "82.0454545454545" "22" "11.8431305092758"
-## SMC00710_2009-05-20_1 "14.8863636363636" "154" "13.9950414570034"
-## SMC00957_2010-06-21_1 "20.3409090909091" "44" "34.4583963385428"
-## SMC04383_2010-06-09_1 "33.8636363636364" "44" "14.6415955876764"
+## SMC00710_2009-05-20_1 "14.8863636363636" "22" "14.2777981313828"
+## SMC00957_2010-06-21_1 "20.3409090909091" "22" "34.8662022061058"
+## SMC04383_2010-06-09_1 "33.8636363636364" "22" "14.8148749397529"
## XGH.result XGH.count XGH.sd
## 402M00002_2015-08-13_1 "19.5454545454545" "22" "9.11684611677104"
-## SMC00710_2009-05-20_1 "12.2727272727273" "154" "9.65230354657369"
-## SMC00957_2010-06-21_1 "20.9090909090909" "44" "26.5512389075619"
-## SMC04383_2010-06-09_1 "21.0227272727273" "44" "12.02369489386"
+## SMC00710_2009-05-20_1 "12.2727272727273" "22" "9.84731927834662"
+## SMC00957_2010-06-21_1 "20.9090909090909" "22" "26.865465690236"
+## SMC04383_2010-06-09_1 "21.0227272727273" "22" "12.1659920942093"
## XGW.result XGW.count XGW.sd
## 402M00002_2015-08-13_1 "5" "22" "0"
-## SMC00710_2009-05-20_1 "26.0690789473684" "152" "14.6498931287047"
-## SMC00957_2010-06-21_1 "4.31818181818182" "44" "8.53112693903298"
-## SMC04383_2010-06-09_1 "23.1818181818182" "44" "5.81606726902305"
+## SMC00710_2009-05-20_1 "25.7954545454545" "22" "15.0472739905092"
+## SMC00957_2010-06-21_1 "4.31818181818182" "22" "8.63209053549527"
+## SMC04383_2010-06-09_1 "23.1818181818182" "22" "5.884898863365"
## XM.result XM.count XM.sd
## 402M00002_2015-08-13_1 "41.25" "22" "16.6324052608727"
-## SMC00710_2009-05-20_1 "58.6363636363636" "154" "26.3787937659523"
-## SMC00957_2010-06-21_1 "23.1818181818182" "44" "23.4667233246161"
-## SMC04383_2010-06-09_1 "22.1590909090909" "44" "16.9694570794984"
+## SMC00710_2009-05-20_1 "58.6363636363636" "22" "26.9117525301201"
+## SMC00957_2010-06-21_1 "23.1818181818182" "22" "23.7444456936502"
+## SMC04383_2010-06-09_1 "22.1590909090909" "22" "17.1702860472306"
## XC.result XC.count XC.sd
## 402M00002_2015-08-13_1 "15.1136363636364" "22" "14.0678050359016"
-## SMC00710_2009-05-20_1 "58.75" "154" "24.6184113311681"
-## SMC00957_2010-06-21_1 "20.6818181818182" "44" "24.2465751379378"
-## SMC04383_2010-06-09_1 "28.9772727272727" "44" "21.3995638255524"
+## SMC00710_2009-05-20_1 "58.75" "22" "25.1158032208522"
+## SMC00957_2010-06-21_1 "20.6818181818182" "22" "24.5335268437691"
+## SMC04383_2010-06-09_1 "28.9772727272727" "22" "21.6528219170088"
## XG.result XCM.result
## 402M00002_2015-08-13_1 "24.5454545454545" "56.3636363636364"
-## SMC00710_2009-05-20_1 "38.3418062200957" "117.386363636364"
+## SMC00710_2009-05-20_1 "38.0681818181818" "117.386363636364"
## SMC00957_2010-06-21_1 "25.2272727272727" "43.8636363636364"
## SMC04383_2010-06-09_1 "44.2045454545455" "51.1363636363636"
## XCMG.result XPMID.result
## 402M00002_2015-08-13_1 "80.9090909090909" "1"
-## SMC00710_2009-05-20_1 "155.728169856459" "1"
+## SMC00710_2009-05-20_1 "155.454545454545" "1"
## SMC00957_2010-06-21_1 "69.0909090909091" "1.46666666666667"
## SMC04383_2010-06-09_1 "95.3409090909091" "1"
## XPCAN.result XPGVEG.result XPCM.result
@@ -544,47 +541,47 @@ Usage
## SMC04383_2010-06-09_1 "1" "1" "1"
## XPCMG.result XPMGVEG.result PCT_RS.result
## 402M00002_2015-08-13_1 "1" "0" "0"
-## SMC00710_2009-05-20_1 "1" "1" "0"
-## SMC00957_2010-06-21_1 "1" "1" "0"
-## SMC04383_2010-06-09_1 "1" "1" "0"
+## SMC00710_2009-05-20_1 "1" "0" "0"
+## SMC00957_2010-06-21_1 "1" "0" "0"
+## SMC04383_2010-06-09_1 "1" "0" "0"
## PCT_RR.result PCT_RC.result PCT_XB.result
## 402M00002_2015-08-13_1 "0" "0" "0"
## SMC00710_2009-05-20_1 "0" "0" "0"
## SMC00957_2010-06-21_1 "0" "0" "0"
## SMC04383_2010-06-09_1 "0" "0" "6.66666666666667"
-## PCT_SB.result PCT_CB.result
-## 402M00002_2015-08-13_1 "7.21649484536082" "11.340206185567"
-## SMC00710_2009-05-20_1 "0.952380952380952" "31.4285714285714"
-## SMC00957_2010-06-21_1 "0" "0"
-## SMC04383_2010-06-09_1 "20" "16.1904761904762"
+## PCT_SB.result PCT_CB.result
+## 402M00002_2015-08-13_1 "7.21649484536082" "11.340206185567"
+## SMC00710_2009-05-20_1 "0.78740157480315" "32.2834645669291"
+## SMC00957_2010-06-21_1 "0" "0"
+## SMC04383_2010-06-09_1 "20" "16.1904761904762"
## PCT_GC.result PCT_GF.result
## 402M00002_2015-08-13_1 "9.27835051546392" "4.12371134020619"
-## SMC00710_2009-05-20_1 "39.0476190476191" "9.52380952380952"
+## SMC00710_2009-05-20_1 "39.3700787401575" "10.2362204724409"
## SMC00957_2010-06-21_1 "0" "21.9047619047619"
## SMC04383_2010-06-09_1 "13.3333333333333" "28.5714285714286"
## PCT_SA.result PCT_FN.result PCT_HP.result
## 402M00002_2015-08-13_1 "9.27835051546392" "35.0515463917526" "0"
-## SMC00710_2009-05-20_1 "17.1428571428571" "0" "0"
+## SMC00710_2009-05-20_1 "14.9606299212598" "0" "0"
## SMC00957_2010-06-21_1 "78.0952380952381" "0" "0"
## SMC04383_2010-06-09_1 "13.3333333333333" "1.9047619047619" "0"
## PCT_WD.result PCT_OT.result
## 402M00002_2015-08-13_1 "4.12371134020619" "19.5876288659794"
-## SMC00710_2009-05-20_1 "0" "1.9047619047619"
+## SMC00710_2009-05-20_1 "0" "2.36220472440945"
## SMC00957_2010-06-21_1 "0" "0"
## SMC04383_2010-06-09_1 "0" "0"
## PCT_BDRK.result PCT_BIGR.result
## 402M00002_2015-08-13_1 "0" "27.8350515463918"
-## SMC00710_2009-05-20_1 "0" "71.4285714285714"
+## SMC00710_2009-05-20_1 "0" "72.4409448818898"
## SMC00957_2010-06-21_1 "0" "0"
## SMC04383_2010-06-09_1 "0" "56.1904761904762"
## PCT_SFGF.result PCT_SAFN.result
## 402M00002_2015-08-13_1 "48.4536082474227" "44.3298969072165"
-## SMC00710_2009-05-20_1 "26.6666666666667" "17.1428571428571"
+## SMC00710_2009-05-20_1 "25.1968503937008" "14.9606299212598"
## SMC00957_2010-06-21_1 "100" "78.0952380952381"
## SMC04383_2010-06-09_1 "43.8095238095238" "15.2380952380952"
## XSDGM.result XSPGM.result
## 402M00002_2015-08-13_1 "1.37777627459172" "1.37777627459172"
-## SMC00710_2009-05-20_1 "29.0593994149964" "29.0593994149964"
+## SMC00710_2009-05-20_1 "31.3770054930211" "31.3770054930211"
## SMC00957_2010-06-21_1 "1.65595988091177" "1.65595988091177"
## SMC04383_2010-06-09_1 "39.827686445097" "39.827686445097"
## SB_PT_D50.result SB_PT_D10.result SB_PT_D25.result
@@ -604,29 +601,29 @@ Usage
## SMC04383_2010-06-09_1 "1.03" "9" "625"
## SB_PP_D90.result XEMBED.result XEMBED.count
## 402M00002_2015-08-13_1 "157" "45.4166666666667" "12"
-## SMC00710_2009-05-20_1 "157" "12.4242424242424" "231"
+## SMC00710_2009-05-20_1 "157" "13.2926829268293" "41"
## SMC00957_2010-06-21_1 "9" "NaN" "0"
-## SMC04383_2010-06-09_1 "625" "44.2857142857143" "28"
+## SMC04383_2010-06-09_1 "625" "44.2857142857143" "14"
## XEMBED.sd PCT_CPOM.result
## 402M00002_2015-08-13_1 "30.7081817150157" "20.6185567010309"
-## SMC00710_2009-05-20_1 "11.1788667548899" "58.0952380952381"
+## SMC00710_2009-05-20_1 "11.0459130506243" "56.6929133858268"
## SMC00957_2010-06-21_1 NA "48.5714285714286"
-## SMC04383_2010-06-09_1 "27.4777447223468" "26.6666666666667"
+## SMC04383_2010-06-09_1 "28.001177369281" "26.6666666666667"
## XMIAT.result XMIAT.count XMIAT.sd
## 402M00002_2015-08-13_1 "0.103260869565217" "92" "0.537280716722528"
-## SMC00710_2009-05-20_1 "0.314516129032258" "651" "0.175588341038592"
-## SMC00957_2010-06-21_1 "0.166666666666667" "210" "0.331133089266261"
-## SMC04383_2010-06-09_1 "0.11734693877551" "196" "0.160943060614031"
+## SMC00710_2009-05-20_1 "0.324561403508772" "114" "0.172596723432415"
+## SMC00957_2010-06-21_1 "0.166666666666667" "105" "0.331928127839871"
+## SMC04383_2010-06-09_1 "0.11734693877551" "98" "0.161357329151621"
## XMIATP.result XMIATP.count
## 402M00002_2015-08-13_1 "2.375" "4"
-## SMC00710_2009-05-20_1 "0.370253164556962" "553"
-## SMC00957_2010-06-21_1 "0.388888888888889" "90"
-## SMC04383_2010-06-09_1 "0.302631578947368" "76"
+## SMC00710_2009-05-20_1 "0.373737373737374" "99"
+## SMC00957_2010-06-21_1 "0.388888888888889" "45"
+## SMC04383_2010-06-09_1 "0.302631578947368" "38"
## XMIATP.sd PCT_MIATP.result
## 402M00002_2015-08-13_1 "1.25" "4.34782608695652"
-## SMC00710_2009-05-20_1 "0.125022929469146" "84.9462365591398"
-## SMC00957_2010-06-21_1 "0.412431661194985" "42.8571428571429"
-## SMC04383_2010-06-09_1 "0.102597835208515" "38.7755102040816"
+## SMC00710_2009-05-20_1 "0.125629726907402" "86.8421052631579"
+## SMC00957_2010-06-21_1 "0.414768403187644" "42.8571428571429"
+## SMC04383_2010-06-09_1 "0.103288737528069" "38.7755102040816"
## PCT_MIAT1.result PCT_MIAT1P.result
## 402M00002_2015-08-13_1 "3.26086956521739" "75"
## SMC00710_2009-05-20_1 "0" "0"
@@ -634,32 +631,43 @@ Usage
## SMC04383_2010-06-09_1 "0" "0"
## PCT_MAA.result PCT_MCP.result
## 402M00002_2015-08-13_1 "2.12765957446809" "13.8297872340426"
-## SMC00710_2009-05-20_1 "66.9902912621359" "3.80952380952381"
+## SMC00710_2009-05-20_1 "69.6" "3.93700787401575"
## SMC00957_2010-06-21_1 "10.4761904761905" "39.0476190476191"
## SMC04383_2010-06-09_1 "36.3636363636364" "0"
## PCT_MAU.result PCT_MAP.result
## 402M00002_2015-08-13_1 "0" "2.12765957446809"
-## SMC00710_2009-05-20_1 "0" "66.9902912621359"
+## SMC00710_2009-05-20_1 "0" "69.6"
## SMC00957_2010-06-21_1 "0.952380952380952" "11.4285714285714"
## SMC04383_2010-06-09_1 "4.04040404040404" "39.3939393939394"
## PCT_NSA.result
## 402M00002_2015-08-13_1 "5.31914893617021"
-## SMC00710_2009-05-20_1 "66.9902912621359"
+## SMC00710_2009-05-20_1 "69.6"
## SMC00957_2010-06-21_1 "12.3809523809524"
## SMC04383_2010-06-09_1 "39.7959183673469"
Required data checks
-Every unique id, LocationCode, AnalyteName, and VariableResult combination should have only one entry in VariableResult for AnalyteName %in% c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached'). The algae.R function will remove duplicate entries but a checker should be built that verifies a unique value can be determined.
For every function, make sure there are no duplicate or conflicting values for every unique combination of id, LocationCode, AnalyteName, and VariableResult (or Result). This should be specific to the metric classes just to be safe. For example, every combination should have only one entry in VariableResult for AnalyteName %in% c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached') for the algae metrics. The algae.R function will remove duplicate entries but a checker should be built that verifies a unique value can be determined.
Required column names, see those in sampdat.
- Check for required values in
AnalyteName (note that chkinp() can check of the columns exist but we’ll need a checker on data input to check for these and only these):
c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached') for algae()c('Bankfull Height', 'Bankfull Width', 'StationWaterDepth', 'Wetted Width') for bankmorph()c(Slope', 'Length, Segment', 'Elevation Difference', 'Bearing', 'Proportion', 'Length, Reach') for channelsinuosity()c('Cascade/Falls', 'Dry', 'Glide', 'Pool', 'Rapid', 'Riffle', 'Run')) for channelmorph()c(Slope', 'Length, Segment', 'Elevation Difference', 'Bearing', 'Proportion', 'Length, Reach') for channelsinuosity()c('Canopy Cover') for densiometer()c('Distance from Bank', 'StationWaterDepth', 'Velocity', 'Distance, Float', 'Float Time', 'Wetted Width') for flow()c('Fish Cover Macrophytes', 'Fish Cover Artificial Structures', 'Fish Cover Boulders', 'Fish Cover Filamentous Algae', 'Fish Cover Woody Debris >0.3 m', 'Fish Cover Live Trees/Roots', 'Fish Cover Overhang.Veg', 'Fish Cover Woody Debris <0.3 m', 'Fish Cover Undercut Banks') for habitat()c('Riparian Bridges/Abutments', 'Riparian Buildings', 'Riparian Landfill/Trash', 'Riparian Logging', 'Riparian Mining', 'Riparian Orchards/Vineyards', 'Riparian Park/Lawn', 'Riparian Pasture/Range', 'Riparian Pavement', 'Riparian Pipes', 'Riparian Road', 'Riparian Row Crops', 'Riparian Vegetation Management', 'Riparian Wall/Dike') for disturbance()c('Riffle/Run Channel Alteration', 'Riffle/Run Epifaunal Substrate', 'Riffle/Run Sediment Deposition', 'Dominant Land Use', 'Evidence of Fire', 'Evidence of Recent Rainfall') for misc()c('Bank Stability') for bankstability()c("Alkalinity as CaCO3", "Oxygen, Dissolved", "pH", "Salinity", "SpecificConductivity", "Temperature", "Turbidity") for quality()c('Riparian GroundCover Barren', 'Riparian GroundCover NonWoody Plants', 'Riparian GroundCover Woody Shrubs', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian GroundCover Woody Shrubs', 'Riparian GroundCover NonWoody Plants') for ripveg()c('Substrate Size Class', 'Embeddedness', 'CPOM') for substrate()
+Check for required values in LocationCode (note that chkinp() can check of the columns exist but we’ll need a checker on data input to check for these and only these)
Maybe we need to add a checker to make sure all values in each field are present but with appropriate NA values for Result, VariableResult, this can be done with tidyr::complete() but may be unnecessary since this will increase data volume
diff --git a/README.md b/README.md
index 6b8946c..7251882 100755
--- a/README.md
+++ b/README.md
@@ -30,12 +30,6 @@ The core function is `phabmetrics()`.
phabmetrics(sampdat)
```
-```
-## Warning in reach[which(unlist(dimnames(reach)) %in%
-## unlist(dimnames(SLOPE_0_reach)))] <- SLOPE_0_reach: number of items to
-## replace is not a multiple of replacement length
-```
-
```
## XBKF_H.result XBKF_H.count
## 402M00002_2015-08-13_1 "0.659090909090909" "11"
@@ -139,44 +133,44 @@ phabmetrics(sampdat)
## SMC04383_2010-06-09_1 "47" "0"
## XSLOPE.count XSLOPE.sd
## 402M00002_2015-08-13_1 "11" "0.00301511344577764"
-## SMC00710_2009-05-20_1 "13" "0"
+## SMC00710_2009-05-20_1 "12" "0"
## SMC00957_2010-06-21_1 "11" "0"
## SMC04383_2010-06-09_1 "11" "0"
## SLOPE_0.result SLOPE_0.count SLOPE_0_5.result
## 402M00002_2015-08-13_1 "0" "10" "666.666666666667"
-## SMC00710_2009-05-20_1 "666.666666666667" "12" "0"
+## SMC00710_2009-05-20_1 "666.666666666667" "10" "0"
## SMC00957_2010-06-21_1 "666.666666666667" "10" "0"
## SMC04383_2010-06-09_1 "666.666666666667" "10" "0"
## SLOPE_0_5.count SLOPE_1.result SLOPE_1.count
## 402M00002_2015-08-13_1 "10" "666.666666666667" "10"
-## SMC00710_2009-05-20_1 "12" "0" "12"
+## SMC00710_2009-05-20_1 "10" "0" "10"
## SMC00957_2010-06-21_1 "10" "0" "10"
## SMC04383_2010-06-09_1 "10" "0" "10"
## SLOPE_2.result SLOPE_2.count
## 402M00002_2015-08-13_1 "666.666666666667" "10"
-## SMC00710_2009-05-20_1 "0" "12"
+## SMC00710_2009-05-20_1 "0" "10"
## SMC00957_2010-06-21_1 "0" "10"
## SMC04383_2010-06-09_1 "0" "10"
## XBEARING.result XBEARING.count
## 402M00002_2015-08-13_1 "0.00909090909090909" "11"
-## SMC00710_2009-05-20_1 "0.414615384615385" "13"
-## SMC00957_2010-06-21_1 "0.0363636363636364" "11"
-## SMC04383_2010-06-09_1 "0.0363636363636364" "11"
+## SMC00710_2009-05-20_1 "0.0075" "12"
+## SMC00957_2010-06-21_1 "0.00909090909090909" "11"
+## SMC04383_2010-06-09_1 "0.00909090909090909" "11"
## XBEARING.sd SINU.NOT_WORKING
## 402M00002_2015-08-13_1 "0.00301511344577764" "28.6493442492751"
-## SMC00710_2009-05-20_1 "0.184011565968709" "4.10275452406255"
-## SMC00957_2010-06-21_1 "0.0120604537831105" "14.3268541739219"
-## SMC04383_2010-06-09_1 "0.0120604537831105" "14.3268541739219"
+## SMC00710_2009-05-20_1 "0.00452267016866645" "31.8326047214168"
+## SMC00957_2010-06-21_1 "0.00301511344577764" "28.6493442492751"
+## SMC04383_2010-06-09_1 "0.00301511344577764" "28.6493442492751"
## XCDENMID.result XCDENMID.count
## 402M00002_2015-08-13_1 "77.0053475935829" "44"
-## SMC00710_2009-05-20_1 "84.7593582887701" "308"
-## SMC00957_2010-06-21_1 "53.8770053475936" "88"
-## SMC04383_2010-06-09_1 "50" "88"
+## SMC00710_2009-05-20_1 "84.7593582887701" "88"
+## SMC00957_2010-06-21_1 "53.8770053475936" "44"
+## SMC04383_2010-06-09_1 "50" "44"
## XCDENMID.sd XCDENBK.result XCDENBK.count
## 402M00002_2015-08-13_1 "35.0841493056178" "NaN" "0"
-## SMC00710_2009-05-20_1 "18.5179940474629" "NaN" "0"
-## SMC00957_2010-06-21_1 "34.1240156751681" "NaN" "0"
-## SMC04383_2010-06-09_1 "34.8974782696344" "NaN" "0"
+## SMC00710_2009-05-20_1 "18.5938566922201" "NaN" "0"
+## SMC00957_2010-06-21_1 "34.321837713125" "NaN" "0"
+## SMC04383_2010-06-09_1 "35.0997841862817" "NaN" "0"
## XCDENBK.sd XFC_AQM.result XFC_AQM.count
## 402M00002_2015-08-13_1 NA "22.9545454545455" "11"
## SMC00710_2009-05-20_1 NA "3.63636363636364" "77"
@@ -394,37 +388,37 @@ phabmetrics(sampdat)
## SMC04383_2010-06-09_1 "16.22" "61.196" "10.8"
## XGB.result XGB.count XGB.sd
## 402M00002_2015-08-13_1 "82.0454545454545" "22" "11.8431305092758"
-## SMC00710_2009-05-20_1 "14.8863636363636" "154" "13.9950414570034"
-## SMC00957_2010-06-21_1 "20.3409090909091" "44" "34.4583963385428"
-## SMC04383_2010-06-09_1 "33.8636363636364" "44" "14.6415955876764"
+## SMC00710_2009-05-20_1 "14.8863636363636" "22" "14.2777981313828"
+## SMC00957_2010-06-21_1 "20.3409090909091" "22" "34.8662022061058"
+## SMC04383_2010-06-09_1 "33.8636363636364" "22" "14.8148749397529"
## XGH.result XGH.count XGH.sd
## 402M00002_2015-08-13_1 "19.5454545454545" "22" "9.11684611677104"
-## SMC00710_2009-05-20_1 "12.2727272727273" "154" "9.65230354657369"
-## SMC00957_2010-06-21_1 "20.9090909090909" "44" "26.5512389075619"
-## SMC04383_2010-06-09_1 "21.0227272727273" "44" "12.02369489386"
+## SMC00710_2009-05-20_1 "12.2727272727273" "22" "9.84731927834662"
+## SMC00957_2010-06-21_1 "20.9090909090909" "22" "26.865465690236"
+## SMC04383_2010-06-09_1 "21.0227272727273" "22" "12.1659920942093"
## XGW.result XGW.count XGW.sd
## 402M00002_2015-08-13_1 "5" "22" "0"
-## SMC00710_2009-05-20_1 "26.0690789473684" "152" "14.6498931287047"
-## SMC00957_2010-06-21_1 "4.31818181818182" "44" "8.53112693903298"
-## SMC04383_2010-06-09_1 "23.1818181818182" "44" "5.81606726902305"
+## SMC00710_2009-05-20_1 "25.7954545454545" "22" "15.0472739905092"
+## SMC00957_2010-06-21_1 "4.31818181818182" "22" "8.63209053549527"
+## SMC04383_2010-06-09_1 "23.1818181818182" "22" "5.884898863365"
## XM.result XM.count XM.sd
## 402M00002_2015-08-13_1 "41.25" "22" "16.6324052608727"
-## SMC00710_2009-05-20_1 "58.6363636363636" "154" "26.3787937659523"
-## SMC00957_2010-06-21_1 "23.1818181818182" "44" "23.4667233246161"
-## SMC04383_2010-06-09_1 "22.1590909090909" "44" "16.9694570794984"
+## SMC00710_2009-05-20_1 "58.6363636363636" "22" "26.9117525301201"
+## SMC00957_2010-06-21_1 "23.1818181818182" "22" "23.7444456936502"
+## SMC04383_2010-06-09_1 "22.1590909090909" "22" "17.1702860472306"
## XC.result XC.count XC.sd
## 402M00002_2015-08-13_1 "15.1136363636364" "22" "14.0678050359016"
-## SMC00710_2009-05-20_1 "58.75" "154" "24.6184113311681"
-## SMC00957_2010-06-21_1 "20.6818181818182" "44" "24.2465751379378"
-## SMC04383_2010-06-09_1 "28.9772727272727" "44" "21.3995638255524"
+## SMC00710_2009-05-20_1 "58.75" "22" "25.1158032208522"
+## SMC00957_2010-06-21_1 "20.6818181818182" "22" "24.5335268437691"
+## SMC04383_2010-06-09_1 "28.9772727272727" "22" "21.6528219170088"
## XG.result XCM.result
## 402M00002_2015-08-13_1 "24.5454545454545" "56.3636363636364"
-## SMC00710_2009-05-20_1 "38.3418062200957" "117.386363636364"
+## SMC00710_2009-05-20_1 "38.0681818181818" "117.386363636364"
## SMC00957_2010-06-21_1 "25.2272727272727" "43.8636363636364"
## SMC04383_2010-06-09_1 "44.2045454545455" "51.1363636363636"
## XCMG.result XPMID.result
## 402M00002_2015-08-13_1 "80.9090909090909" "1"
-## SMC00710_2009-05-20_1 "155.728169856459" "1"
+## SMC00710_2009-05-20_1 "155.454545454545" "1"
## SMC00957_2010-06-21_1 "69.0909090909091" "1.46666666666667"
## SMC04383_2010-06-09_1 "95.3409090909091" "1"
## XPCAN.result XPGVEG.result XPCM.result
@@ -434,47 +428,47 @@ phabmetrics(sampdat)
## SMC04383_2010-06-09_1 "1" "1" "1"
## XPCMG.result XPMGVEG.result PCT_RS.result
## 402M00002_2015-08-13_1 "1" "0" "0"
-## SMC00710_2009-05-20_1 "1" "1" "0"
-## SMC00957_2010-06-21_1 "1" "1" "0"
-## SMC04383_2010-06-09_1 "1" "1" "0"
+## SMC00710_2009-05-20_1 "1" "0" "0"
+## SMC00957_2010-06-21_1 "1" "0" "0"
+## SMC04383_2010-06-09_1 "1" "0" "0"
## PCT_RR.result PCT_RC.result PCT_XB.result
## 402M00002_2015-08-13_1 "0" "0" "0"
## SMC00710_2009-05-20_1 "0" "0" "0"
## SMC00957_2010-06-21_1 "0" "0" "0"
## SMC04383_2010-06-09_1 "0" "0" "6.66666666666667"
-## PCT_SB.result PCT_CB.result
-## 402M00002_2015-08-13_1 "7.21649484536082" "11.340206185567"
-## SMC00710_2009-05-20_1 "0.952380952380952" "31.4285714285714"
-## SMC00957_2010-06-21_1 "0" "0"
-## SMC04383_2010-06-09_1 "20" "16.1904761904762"
+## PCT_SB.result PCT_CB.result
+## 402M00002_2015-08-13_1 "7.21649484536082" "11.340206185567"
+## SMC00710_2009-05-20_1 "0.78740157480315" "32.2834645669291"
+## SMC00957_2010-06-21_1 "0" "0"
+## SMC04383_2010-06-09_1 "20" "16.1904761904762"
## PCT_GC.result PCT_GF.result
## 402M00002_2015-08-13_1 "9.27835051546392" "4.12371134020619"
-## SMC00710_2009-05-20_1 "39.0476190476191" "9.52380952380952"
+## SMC00710_2009-05-20_1 "39.3700787401575" "10.2362204724409"
## SMC00957_2010-06-21_1 "0" "21.9047619047619"
## SMC04383_2010-06-09_1 "13.3333333333333" "28.5714285714286"
## PCT_SA.result PCT_FN.result PCT_HP.result
## 402M00002_2015-08-13_1 "9.27835051546392" "35.0515463917526" "0"
-## SMC00710_2009-05-20_1 "17.1428571428571" "0" "0"
+## SMC00710_2009-05-20_1 "14.9606299212598" "0" "0"
## SMC00957_2010-06-21_1 "78.0952380952381" "0" "0"
## SMC04383_2010-06-09_1 "13.3333333333333" "1.9047619047619" "0"
## PCT_WD.result PCT_OT.result
## 402M00002_2015-08-13_1 "4.12371134020619" "19.5876288659794"
-## SMC00710_2009-05-20_1 "0" "1.9047619047619"
+## SMC00710_2009-05-20_1 "0" "2.36220472440945"
## SMC00957_2010-06-21_1 "0" "0"
## SMC04383_2010-06-09_1 "0" "0"
## PCT_BDRK.result PCT_BIGR.result
## 402M00002_2015-08-13_1 "0" "27.8350515463918"
-## SMC00710_2009-05-20_1 "0" "71.4285714285714"
+## SMC00710_2009-05-20_1 "0" "72.4409448818898"
## SMC00957_2010-06-21_1 "0" "0"
## SMC04383_2010-06-09_1 "0" "56.1904761904762"
## PCT_SFGF.result PCT_SAFN.result
## 402M00002_2015-08-13_1 "48.4536082474227" "44.3298969072165"
-## SMC00710_2009-05-20_1 "26.6666666666667" "17.1428571428571"
+## SMC00710_2009-05-20_1 "25.1968503937008" "14.9606299212598"
## SMC00957_2010-06-21_1 "100" "78.0952380952381"
## SMC04383_2010-06-09_1 "43.8095238095238" "15.2380952380952"
## XSDGM.result XSPGM.result
## 402M00002_2015-08-13_1 "1.37777627459172" "1.37777627459172"
-## SMC00710_2009-05-20_1 "29.0593994149964" "29.0593994149964"
+## SMC00710_2009-05-20_1 "31.3770054930211" "31.3770054930211"
## SMC00957_2010-06-21_1 "1.65595988091177" "1.65595988091177"
## SMC04383_2010-06-09_1 "39.827686445097" "39.827686445097"
## SB_PT_D50.result SB_PT_D10.result SB_PT_D25.result
@@ -494,29 +488,29 @@ phabmetrics(sampdat)
## SMC04383_2010-06-09_1 "1.03" "9" "625"
## SB_PP_D90.result XEMBED.result XEMBED.count
## 402M00002_2015-08-13_1 "157" "45.4166666666667" "12"
-## SMC00710_2009-05-20_1 "157" "12.4242424242424" "231"
+## SMC00710_2009-05-20_1 "157" "13.2926829268293" "41"
## SMC00957_2010-06-21_1 "9" "NaN" "0"
-## SMC04383_2010-06-09_1 "625" "44.2857142857143" "28"
+## SMC04383_2010-06-09_1 "625" "44.2857142857143" "14"
## XEMBED.sd PCT_CPOM.result
## 402M00002_2015-08-13_1 "30.7081817150157" "20.6185567010309"
-## SMC00710_2009-05-20_1 "11.1788667548899" "58.0952380952381"
+## SMC00710_2009-05-20_1 "11.0459130506243" "56.6929133858268"
## SMC00957_2010-06-21_1 NA "48.5714285714286"
-## SMC04383_2010-06-09_1 "27.4777447223468" "26.6666666666667"
+## SMC04383_2010-06-09_1 "28.001177369281" "26.6666666666667"
## XMIAT.result XMIAT.count XMIAT.sd
## 402M00002_2015-08-13_1 "0.103260869565217" "92" "0.537280716722528"
-## SMC00710_2009-05-20_1 "0.314516129032258" "651" "0.175588341038592"
-## SMC00957_2010-06-21_1 "0.166666666666667" "210" "0.331133089266261"
-## SMC04383_2010-06-09_1 "0.11734693877551" "196" "0.160943060614031"
+## SMC00710_2009-05-20_1 "0.324561403508772" "114" "0.172596723432415"
+## SMC00957_2010-06-21_1 "0.166666666666667" "105" "0.331928127839871"
+## SMC04383_2010-06-09_1 "0.11734693877551" "98" "0.161357329151621"
## XMIATP.result XMIATP.count
## 402M00002_2015-08-13_1 "2.375" "4"
-## SMC00710_2009-05-20_1 "0.370253164556962" "553"
-## SMC00957_2010-06-21_1 "0.388888888888889" "90"
-## SMC04383_2010-06-09_1 "0.302631578947368" "76"
+## SMC00710_2009-05-20_1 "0.373737373737374" "99"
+## SMC00957_2010-06-21_1 "0.388888888888889" "45"
+## SMC04383_2010-06-09_1 "0.302631578947368" "38"
## XMIATP.sd PCT_MIATP.result
## 402M00002_2015-08-13_1 "1.25" "4.34782608695652"
-## SMC00710_2009-05-20_1 "0.125022929469146" "84.9462365591398"
-## SMC00957_2010-06-21_1 "0.412431661194985" "42.8571428571429"
-## SMC04383_2010-06-09_1 "0.102597835208515" "38.7755102040816"
+## SMC00710_2009-05-20_1 "0.125629726907402" "86.8421052631579"
+## SMC00957_2010-06-21_1 "0.414768403187644" "42.8571428571429"
+## SMC04383_2010-06-09_1 "0.103288737528069" "38.7755102040816"
## PCT_MIAT1.result PCT_MIAT1P.result
## 402M00002_2015-08-13_1 "3.26086956521739" "75"
## SMC00710_2009-05-20_1 "0" "0"
@@ -524,30 +518,42 @@ phabmetrics(sampdat)
## SMC04383_2010-06-09_1 "0" "0"
## PCT_MAA.result PCT_MCP.result
## 402M00002_2015-08-13_1 "2.12765957446809" "13.8297872340426"
-## SMC00710_2009-05-20_1 "66.9902912621359" "3.80952380952381"
+## SMC00710_2009-05-20_1 "69.6" "3.93700787401575"
## SMC00957_2010-06-21_1 "10.4761904761905" "39.0476190476191"
## SMC04383_2010-06-09_1 "36.3636363636364" "0"
## PCT_MAU.result PCT_MAP.result
## 402M00002_2015-08-13_1 "0" "2.12765957446809"
-## SMC00710_2009-05-20_1 "0" "66.9902912621359"
+## SMC00710_2009-05-20_1 "0" "69.6"
## SMC00957_2010-06-21_1 "0.952380952380952" "11.4285714285714"
## SMC04383_2010-06-09_1 "4.04040404040404" "39.3939393939394"
## PCT_NSA.result
## 402M00002_2015-08-13_1 "5.31914893617021"
-## SMC00710_2009-05-20_1 "66.9902912621359"
+## SMC00710_2009-05-20_1 "69.6"
## SMC00957_2010-06-21_1 "12.3809523809524"
## SMC04383_2010-06-09_1 "39.7959183673469"
```
# Required data checks
-* Every unique `id`, `LocationCode`, `AnalyteName`, and `VariableResult` combination should have only one entry in `VariableResult` for `AnalyteName %in% c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached')`. The `algae.R` function will remove duplicate entries but a checker should be built that verifies a unique value can be determined.
+* For every function, make sure there are no duplicate or conflicting values for every unique combination of `id`, `LocationCode`, `AnalyteName`, and `VariableResult` (or `Result`). This should be specific to the metric classes just to be safe. For example, every combination should have only one entry in `VariableResult` for `AnalyteName %in% c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached')` for the algae metrics. The `algae.R` function will remove duplicate entries but a checker should be built that verifies a unique value can be determined.
* Required column names, see those in `sampdat`.
* Check for required values in `AnalyteName` (note that `chkinp()` can check of the columns exist but we'll need a checker on data input to check for these and only these):
* `c('Microalgae Thickness', 'Macrophyte Cover', 'Macroalgae Cover, Attached', 'Macroalgae Cover, Unattached')` for `algae()`
* `c('Bankfull Height', 'Bankfull Width', 'StationWaterDepth', 'Wetted Width')` for `bankmorph()`
- * `c(Slope', 'Length, Segment', 'Elevation Difference', 'Bearing', 'Proportion', 'Length, Reach')` for `channelsinuosity()`
* `c('Cascade/Falls', 'Dry', 'Glide', 'Pool', 'Rapid', 'Riffle', 'Run'))` for `channelmorph()`
+ * `c(Slope', 'Length, Segment', 'Elevation Difference', 'Bearing', 'Proportion', 'Length, Reach')` for `channelsinuosity()`
+ * `c('Canopy Cover')` for `densiometer()`
+ * `c('Distance from Bank', 'StationWaterDepth', 'Velocity', 'Distance, Float', 'Float Time', 'Wetted Width')` for `flow()`
+ * `c('Fish Cover Macrophytes', 'Fish Cover Artificial Structures', 'Fish Cover Boulders', 'Fish Cover Filamentous Algae', 'Fish Cover Woody Debris >0.3 m', 'Fish Cover Live Trees/Roots', 'Fish Cover Overhang.Veg', 'Fish Cover Woody Debris <0.3 m', 'Fish Cover Undercut Banks')` for `habitat()`
+ * `c('Riparian Bridges/Abutments', 'Riparian Buildings', 'Riparian Landfill/Trash', 'Riparian Logging', 'Riparian Mining', 'Riparian Orchards/Vineyards', 'Riparian Park/Lawn', 'Riparian Pasture/Range', 'Riparian Pavement', 'Riparian Pipes', 'Riparian Road', 'Riparian Row Crops', 'Riparian Vegetation Management', 'Riparian Wall/Dike')` for `disturbance()`
+ * `c('Riffle/Run Channel Alteration', 'Riffle/Run Epifaunal Substrate', 'Riffle/Run Sediment Deposition', 'Dominant Land Use', 'Evidence of Fire', 'Evidence of Recent Rainfall')` for `misc()`
+ * `c('Bank Stability')` for `bankstability()`
+ * `c("Alkalinity as CaCO3", "Oxygen, Dissolved", "pH", "Salinity", "SpecificConductivity", "Temperature", "Turbidity")` for `quality()`
+ * `c('Riparian GroundCover Barren', 'Riparian GroundCover NonWoody Plants', 'Riparian GroundCover Woody Shrubs', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian Lower Canopy All Vegetation', 'Riparian Upper Canopy All Trees', 'Riparian GroundCover Woody Shrubs', 'Riparian GroundCover NonWoody Plants')` for `ripveg()`
+ * `c('Substrate Size Class', 'Embeddedness', 'CPOM')` for `substrate()`
+* Check for required values in `LocationCode` (note that `chkinp()` can check of the columns exist but we'll need a checker on data input to check for these and only these)
+
+* Maybe we need to add a checker to make sure all values in each field are present but with appropriate NA values for `Result`, `VariableResult`, this can be done with `tidyr::complete()` but may be unnecessary since this will increase data volume