Creates a date frame (and file export) from depth profile data in the format used by the rLakeAnalyzer package.
export_rLakeAnalyzer(df_data, col_depth = "Depth", col_data, col_rLA)Data frame to be converted for use with rLakeAnalyzer.
Column name for "depth" in df_data. Default = "Depth"
Column names in df_data to transform for use with rLakeAnalyzer. Date time must be the first entry.
Column names to use with rLakeAnalyzer. See details for accepted entries. datetime must be the first entry.
Returns a data frame formatted (wide) for use with the rLakeAnalyzer package suite of functions.
The rLakeAnalyzer package is not included in the LakeMonitoR package. But an example is provided.
To run the example rLakeAnalyzer calculations you will need the rLakeAnalyzer package (from CRAN).
The rLakeAnalyzer format is "datetime" in the format of "yyyy-mm-dd HH:MM:SS" followed by columns of data. The header of these data columns is "Param_Depth"; e.g., wtr_0.5 is water temperature (deg C) at 0.5 meters.
* doobs = Dissolved Oxygen Concentration (mg/L)
* wtr = Water Temperature (degrees C)
* wnd = Wind Speed (m/s)
* airT = Air Temperature (degrees C)
* rh = Relative Humidity (
Files will be saved, if desired, as csv.
# Convert Data for use with rLakeAnalyzer
# Data
data <- laketemp_ddm
# Columns, date listed first
col_depth <- "Depth"
col_data <- c("Date", "Measurement")
col_rLA <- c("datetime", "wtr")
# Run function
df_rLA <- export_rLakeAnalyzer(data, col_depth, col_data, col_rLA)
if (FALSE) {
# Save
write.csv(df_rLA, "example_rLA.csv", row.names = FALSE)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# use rLakeAnalyzer - heat map
library(rLakeAnalyzer)
# Filter Data for only temperature
col_wtr <- colnames(df_rLA)[grepl("wtr_", colnames(df_rLA))]
df_rLA_wtr <- df_rLA[, c("datetime", col_wtr)]
# Create bathymetry data frame
df_rLA_bath <- data.frame(depths=c(3,6,9), areas=c(300,200,100))
# Generate Heat Map
wtr.heat.map(df_rLA_wtr)
# Generate Schmidt Plot
#schmidt.plot(df_rLA_wtr, df_rLA_bath)
# Generate Schmidt Stability Values
df_rLA_Schmidt <- ts.schmidt.stability(df_rLA_wtr, df_rLA_bath)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Plot original data in ggplot
library(ggplot2)
# Plot, Create
p <- ggplot(data, aes(x=Date, y=Measurement)) +
geom_point(aes(color=Depth)) +
scale_color_continuous(trans="reverse") +
labs(title = "Example depth profile data"
, y = "Temperature (Celsius)"
, color = "Depth (m)") +
theme_light()
# Plot, Show
p
}