improved pat_monitorComparison() legend

DESCRIPTION

@@ -1,6 +1,6 @@
 Type: Package
 Package: AirSensor
-Version: 1.0.2
+Version: 1.0.3
 Title: Process and Display Data from Air Quality Sensors
 Authors@R: c(
     person("Jonathan", "Callahan", email="[email protected]", role=c("aut","cre")), 

NEWS.md

@@ -1,3 +1,7 @@
+# AirSensor 1.0.3
+
+* Improved legend in `pat_monitorComparision()`.
+
 # AirSensor 1.0.2
 
 * CRAN submission tweaks.

R/pat_monitorComparison.R

@@ -38,18 +38,17 @@ pat_monitorComparison <- function(
 
   # ----- Configurable plot options --------------------------------------------
 
-  a_size = 1
-  a_shape = 15
-  a_color = "gray80"
-  b_size = 1
-  b_shape = 15
-  b_color = "gray80"
-  ab_alpha = 0.5
-  hourly_size = 2
-  hourly_shape = 1
-  hourly_stroke = 0.6
-  pa_color = "purple3"
-  pwfsl_color = "grey10"
+  raw_size <- 1
+  raw_shape <- 15
+  raw_stroke <- 1.0
+  raw_alpha <- 0.5
+  raw_color <- "gray80"
+  hourly_size <- 2
+  hourly_shape <- 1
+  hourly_stroke <- 0.6
+  hourly_alpha <- 1
+  pa_color <- "purple2"
+  pwfsl_color <- "grey10"
 
   # ----- Validate parameters --------------------------------------------------
 
@@ -74,6 +73,9 @@ pat_monitorComparison <- function(
     pat <- pat_outliers(pat, showPlot = FALSE, replace = TRUE) 
   }
 
+  # Add "source" column to pat$data so it can be used by ggplot2
+  pat$data$source <- "PA raw"
+
   # Get the hourly aggregated data
   paHourly_data <-
     pat %>% 
@@ -156,34 +158,73 @@ pat_monitorComparison <- function(
   # Labels
   yearLabel <- strftime(pat$data$datetime[1], "%Y (%Z)", tz = timezone)
 
+  cols <- c(
+    "PA raw" = raw_color, 
+    "PA hourly" = pa_color, 
+    "PWFSL" = pwfsl_color
+  )
+
+  shapes = c(
+    "PA raw" = raw_shape, 
+    "PA hourly" = hourly_shape, 
+    "PWFSL" = hourly_shape
+  )
+
+  sizes = c(
+    "PA raw" = raw_size, 
+    "PA hourly" = hourly_size, 
+    "PWFSL" = hourly_size
+  )
+
   # ----- ggplot ---------------------------------------------------------------
 
   pm25_plot <-
     pat$data %>%
     ggplot2::ggplot() +
     ggplot2::geom_point(
-      ggplot2::aes(x = .data$datetime, y = .data$pm25_A),
-      size = a_size,
-      shape = a_shape,
-      color = a_color,
-      alpha = ab_alpha
+      ggplot2::aes(
+        x = .data$datetime, 
+        y = .data$pm25_A,
+        color = .data$source, 
+        shape = .data$source,
+        size = .data$source
+      ),
+      alpha = raw_alpha
     ) +
     ggplot2::geom_point(
-      ggplot2::aes(x = .data$datetime, y = .data$pm25_B),
-      size = b_size,
-      shape = b_shape,
-      color = b_color,
-      alpha = ab_alpha
+      ggplot2::aes(
+        x = .data$datetime, 
+        y = .data$pm25_B, 
+        color = .data$source, 
+        shape = .data$source,
+        size = .data$source
+      ),
+      alpha = raw_alpha
     ) +
     ggplot2::geom_point(
       data = tidy_data,
-      ggplot2::aes(x = .data$datetime, y = .data$pm25, color = source),
-      size = hourly_size,
-      shape = hourly_shape,
+      ggplot2::aes(
+        x = .data$datetime, 
+        y = .data$pm25, 
+        color = .data$source, 
+        shape = .data$source,
+        size = .data$source
+      ),
       stroke = hourly_stroke,
-      alpha = 1
+      alpha = hourly_alpha
+    ) +
+    ggplot2::scale_color_manual(
+      values = cols, 
+      breaks = c("PA raw", "PA hourly", "PWFSL")
+    ) +
+    ggplot2::scale_shape_manual(
+      values = shapes,
+      breaks = c("PA raw", "PA hourly", "PWFSL")
+    ) +
+    ggplot2::scale_size_manual(
+      values = sizes,
+      breaks = c("PA raw", "PA hourly", "PWFSL")
     ) +
-    ggplot2::scale_color_manual(values = c(pa_color, pwfsl_color)) +
     ggplot2::ylim(ylim) +
     ggplot2::scale_x_datetime(breaks = '1 day', date_labels = '%b %d') +
     ggplot2::xlab(yearLabel) + 

docker/Dockerfile

@@ -32,7 +32,7 @@ RUN wget -nv http://mazamascience.com/RData/Spatial/CA_AirBasins_01.RData \
 
 WORKDIR /
 
-COPY AirSensor_1.0.2.tar.gz /
+COPY AirSensor_1.0.3.tar.gz /
 
-RUN R CMD INSTALL AirSensor_1.0.2.tar.gz
+RUN R CMD INSTALL AirSensor_1.0.3.tar.gz
 

docker/Makefile

@@ -3,14 +3,14 @@
 
 AirSensor_tarball:
 	cd ..; R CMD build --resave-data .
-	mv ../AirSensor_1.0.2.tar.gz .
+	mv ../AirSensor_1.0.3.tar.gz .
 
 # PRODUCTION version -----------------------------------------------------------
 
 production_build:
-	docker build --no-cache -t mazamascience/airsensor:1.0.2 -t mazamascience/airsensor:latest .
+	docker build --no-cache -t mazamascience/airsensor:1.0.3 -t mazamascience/airsensor:latest .
 
 production_publish:
-	docker login && docker push mazamascience/airsensor:1.0.2
+	docker login && docker push mazamascience/airsensor:1.0.3
 
 

docker/README.md

@@ -16,7 +16,7 @@ You should then be able to see something like the following:
 $ docker images
 REPOSITORY                    TAG         IMAGE ID            CREATED             SIZE
 ...
-mazamascience/airsensor       1.0.2       796ae3ba57e5        2 minutes ago       3.74GB
+mazamascience/airsensor       1.0.3       796ae3ba57e5        2 minutes ago       3.74GB
 mazamascience/airsensor       latest      796ae3ba57e5        2 minutes ago       3.74GB
 ...
 ```
@@ -88,6 +88,6 @@ make production_publish
 A recent image can also be obtained from DockerHub with:
 
 ```
-docker pull mazamascience/airsensor:1.0.2
+docker pull mazamascience/airsensor:1.0.3
 ```