In leppott/BCGcalc: Biological Condition Gradient, calculator

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Purpose

Demonstrate how to create a map of model output.

Map

Use ggplot to create a map from the example data included in BCGcalc.

The example data only includes data from Washington.

# Packages
library(BCGcalc)
library(ggplot2)
library(readxl)
library(BioMonTools)

# Calculate BCG model
## Calculate Metrics
df.samps.bugs <- read_excel(system.file("./extdata/Data_BCG_PugLowWilVal.xlsx"
                                        , package="BCGcalc")
                            , guess_max = 10^6)
## Run Function
myDF <- df.samps.bugs
col_add_char <- c("INFRAORDER", "HABITAT", "ELEVATION_ATTR", "GRADIENT_ATTR"
                  , "WSAREA_ATTR", "HABSTRUCT")
col_add_num <- "UFC"
myDF[, col_add_char] <- NA_character_
myDF[, col_add_num] <- NA_integer_
myCols <- c("Area_mi2", "SurfaceArea", "Density_m2", "Density_ft2", "Site_Type")
df.metric.values.bugs <- metric.values(myDF, "bugs", fun.cols2keep=myCols) 
## Import Rules
df.rules <- read_excel(system.file("./extdata/Rules.xlsx"
                             , package="BCGcalc")
                       , sheet="Rules") 
## Calculate Metric Memberships
df.Metric.Membership <- BCG.Metric.Membership(df.metric.values.bugs, df.rules
                                              , col_SITE_TYPE = "INDEX_REGION")
## Calculate Level Memberships
df.Level.Membership <- BCG.Level.Membership(df.Metric.Membership, df.rules)
## Run Function
df.Levels <- BCG.Level.Assignment(df.Level.Membership)


# Add Lat-Long
## Get unique stations
df.stations <- as.data.frame(unique(df.samps.bugs[,c("SampleID"
                                                     , "Latitude"
                                                     , "Longitude"
                                                     , "Index_Name"
                                                     , "Index_Region"
                                                     , "Site_Type")]))

## Merge
df.map <- merge(df.Levels
                , df.stations
                , by.x="SampleID"
                , by.y="SampleID"
                , all.x=TRUE)
## Level1 Name to Character
df.map$Lev.1.Name <- as.character(df.map$Lev.1.Name)

# Palette, Color Blind
## http://www.cookbook-r.com/Graphs/Colors_(ggplot2)/
pal_cb <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7", "#999999")
pal_bcg_old <- c("green", "cyan", "blue", "orange", "red")
pal_bcg <- c("blue", "green", "gray", "yellow", "dark orange", "red")

# Map
## Map of OR and WA
m1 <- ggplot(data = subset(map_data("state"), region %in% c("washington"))) + 
  geom_polygon(aes(x = long, y = lat, group = group)
               , fill = "gray90"
               , color = "black") +
  coord_fixed(1.3) + 
  theme_void()

## Add Points
m1 <- m1 + geom_point(data = df.map
                      , aes(Longitude
                            , Latitude
                            , shape = Index_Name
                            , color = Lev.1.Name), na.rm = TRUE)

## Change shape
shp_solid <- c(17, 16) # solid triangle and circle
m1 <- m1 + scale_shape_manual(name = "Site Type", values = shp_solid)

## Change colors
m1 <- m1 + scale_colour_manual(name = "Level 1 Assignment"
                               , values = pal_bcg)

## Map Title
m1 <- m1 + labs(title="Pacific Northwest BCG"
                , subtitle="Example Samples, WA only")
m1 <- m1 + theme(plot.title = element_text(hjust = 0.5)
                 , plot.subtitle = element_text(hjust=0.5))

## Display Map
m1