soilDB (version 2.5)

fetchNASISWebReport: Extract component tables from a the NASIS Web Reports

Description

Get, format, impute, and return component tables.

Usage

fetchNASISWebReport(projectname, rmHzErrors = FALSE, fill = FALSE,
                    stringsAsFactors = default.stringsAsFactors()
                    )
get_progress_from_NASISWebReport(mlrassoarea, fiscalyear, projecttypename)
get_project_from_NASISWebReport(mlrassoarea, fiscalyear)
get_project_correlation_from_NASISWebReport(mlrassoarea, fiscalyear, projectname)
get_projectmapunit_from_NASISWebReport(projectname, 
                                       stringsAsFactors = default.stringsAsFactors()
                                       )
get_projectmapunit2_from_NASISWebReport(mlrassoarea, fiscalyear, projectname, 
                                        stringsAsFactors = default.stringsAsFactors()
                                        )
get_legend_from_NASISWebReport(areasymbol,
                               droplevels = TRUE,
                               stringsAsFactors = default.stringsAsFactors()
                               )
get_mapunit_from_NASISWebReport(areasymbol,
                                droplevels = TRUE,
                                stringsAsFactors = default.stringsAsFactors()
                                )
get_component_from_NASISWebReport(projectname, 
                                  stringsAsFactors = default.stringsAsFactors()
                                  )
get_chorizon_from_NASISWebReport(projectname, fill = FALSE, 
                                 stringsAsFactors = default.stringsAsFactors()
                                 )
get_cosoilmoist_from_NASISWebReport(projectname, impute = TRUE, 
                                    stringsAsFactors = default.stringsAsFactors()
                                    )
get_sitesoilmoist_from_NASISWebReport(usiteid)

Arguments

projectname

text string vector of project names to be inserted into a SQL WHERE clause (default: NA)

mlrassoarea

text string value identifying the mlra soil survey office areasymbol symbol inserted into a SQL WHERE clause (default: NA)

fiscalyear

text string value identifying the fiscal year inserted into a SQL WHERE clause (default: NA)

projecttypename

text string value identifying the project type name inserted into a SQL WHERE clause (default: NA)

areasymbol

text string value identifying the area symbol (e.g. "IN001" or "IN%") inserted into a SQL WHERE clause (default: NA)

usiteid

text string value identifying the user site id inserted into a SQL WHERE clause (default: NA)

impute

replace missing (i.e. NULL) values with "Not_Populated" for categorical data, or the "RV" for numeric data or 201 cm if the "RV" is also NULL (default: TRUE)

fill

should rows with missing component ids be removed NA (FALSE)

rmHzErrors

should pedons with horizonation errors be removed from the results? (default: FALSE)

stringsAsFactors

logical: should character vectors be converted to factors? This argument is passed to the uncode() function. It does not convert those vectors that have been set outside of uncode() (i.e. hard coded). The 'factory-fresh' default is TRUE, but this can be changed by setting options(stringsAsFactors = FALSE)

droplevels

logical: indicating whether to drop unused levels in classifying factors. This is useful when a class has large number of unused classes, which can waste space in tables and figures.

Value

A dataframe or list with the results.

Examples

# NOT RUN {

if (requireNamespace("curl") &
    curl::has_internet() &
    require("aqp") &
    require("ggplot2") & 
    require("gridExtra")
) {
  # query soil components by projectname
  test = fetchNASISWebReport(
    "EVAL - MLRA 111A - Ross silt loam, 0 to 2 percent slopes, frequently flooded"
  )
  test = test$spc
  
  # profile plot
  plot(test)
  
  # convert the data for depth plot
  clay_slice = horizons(slice(test, 0:200 ~ claytotal_l + claytotal_r + claytotal_h))
  names(clay_slice) <- gsub("claytotal_", "", names(clay_slice))
  
  om_slice = horizons(slice(test, 0:200 ~ om_l + om_r + om_h))
  names(om_slice) = gsub("om_", "", names(om_slice))
  
  test2 = rbind(data.frame(clay_slice, var = "clay"),
                data.frame(om_slice, var = "om")
  )
  
  h = merge(test2, site(test)[c("dmuiid", "coiid", "compname", "comppct_r")],
            by = "coiid", 
            all.x = TRUE
  )
  
  # depth plot of clay content by soil component
  gg_comp <- function(x) {
    ggplot(x) +
      geom_line(aes(y = r, x = hzdept_r)) +
      geom_line(aes(y = r, x = hzdept_r)) +
      geom_ribbon(aes(ymin = l, ymax = h, x = hzdept_r), alpha = 0.2) +
      xlim(200, 0) +
      xlab("depth (cm)") +
      facet_grid(var ~ dmuiid + paste(compname, comppct_r)) +
      coord_flip()
  }
  g1 <- gg_comp(subset(h, var == "clay"))
  g2 <- gg_comp(subset(h, var == "om"))
  
  grid.arrange(g1, g2)
  
  
  # query cosoilmoist (e.g. water table data) by mukey
  # NA depths are interpreted as (???) with impute=TRUE argument
  x <- get_cosoilmoist_from_NASISWebReport(
    "EVAL - MLRA 111A - Ross silt loam, 0 to 2 percent slopes, frequently flooded"
  )
  
  ggplot(x, aes(x = as.integer(month), y = dept_r, lty = status)) +
    geom_rect(aes(xmin = as.integer(month), xmax = as.integer(month) + 1,
                  ymin = 0, ymax = max(x$depb_r),
                  fill = flodfreqcl)) +
    geom_line(cex = 1) +
    geom_point() +
    geom_ribbon(aes(ymin = dept_l, ymax = dept_h), alpha = 0.2) +
    ylim(max(x$depb_r), 0) +
    xlab("month") + ylab("depth (cm)") +
    scale_x_continuous(breaks = 1:12, labels = month.abb, name="Month") +
    facet_wrap(~ paste0(compname, ' (', comppct_r , ')')) +
    ggtitle(paste0(x$nationalmusym[1], 
                   ': Water Table Levels from Component Soil Moisture Month Data'))
  
  
}



# }