fixing get_heat_map for streams and changing readme examples

R/get_heat_map.R

@@ -11,7 +11,7 @@
 #' @param acts numeric indicating which activities to plot based on index in the activities list, defaults to most recent
 #' @param id optional numeric vector to specify the id(s) of the activity/activities to plot, \code{acts} is ignored if provided
 #' @param alpha the opacity of the line desired. A single activity should be 1. Defaults to 0.5
-#' @param add_elev logical indicating if elevation is overlayed by color shading on the activity lines
+#' @param add_elev logical indicating if elevation is shown by color shading on the activity lines
 #' @param as_grad logical indicating if elevation is plotted as percent gradient, applies only if \code{add_elev = TRUE}
 #' @param filltype chr string specifying which stream variable to use for filling line segments, applies only to \code{strframe} objects, acceptable values are \code{"elevation"}, \code{"distance"}, \code{"slope"}, or \code{"speed"}
 #' @param distlab logical if distance labels are plotted along the route
@@ -185,10 +185,7 @@ get_heat_map.actframe <- function(act_data, key, alpha = NULL, add_elev = FALSE,
 			dplyr::ungroup(.) %>% 
 			dplyr::select(-tosel, -diffdist) %>% 
 			dplyr::mutate(distance = as.character(round(distance)))
-		# final <- temp[nrow(temp), ] 
-		# final$distance <- format(final$distance, nsmall = 1, digits = 1)
-		# disttemp <- rbind(disttemp, final)
-
+
 		# add to plot
 		p <- p + 
 			ggspatial::geom_spatial_label_repel(
@@ -252,7 +249,7 @@ get_heat_map.strframe <- function(act_data, alpha = NULL, filltype = 'elevation'
 		alti <- stats::approx(x= x$altitude, n = expand * nrow(x))$y
 		grds <- stats::approx(x= x$grade_smooth, n = expand * nrow(x))$y
 		vels <- stats::approx(x= x$velocity_smooth, n = expand * nrow(x))$y
-		data.frame(id = unique(x$id), lat = yint, lng = xint, distance = dist, elevation = alti, slope = grds, speed = vels)
+		data.frame(id = unique(x$id), lat = yint, lon = xint, distance = dist, elevation = alti, slope = grds, speed = vels)
 
 	})
 	temp <- do.call('rbind', temp)
@@ -270,7 +267,7 @@ get_heat_map.strframe <- function(act_data, alpha = NULL, filltype = 'elevation'
 	if(filltype == 'slope') leglab <- '%'
 	else leglab <- unit_vals[filltype]
 	p <- pbase +
-		ggspatial::geom_spatial_path(ggplot2::aes_string(x = 'lng', y = 'lat', group = 'id', colour = filltype), 
+		ggspatial::geom_spatial_path(ggplot2::aes_string(x = 'lon', y = 'lat', group = 'id', colour = filltype), 
 											 alpha = alpha, data = temp, linewidth = size, crs = 4326) +
 		ggplot2::scale_colour_distiller(leglab, palette = col)
 
@@ -288,21 +285,21 @@ get_heat_map.strframe <- function(act_data, alpha = NULL, filltype = 'elevation'
 			dplyr::ungroup(.) %>% 
 			dplyr::select(-tosel, -diffdist) %>% 
 			dplyr::mutate(distance = as.character(round(distance)))
-		# final <- temp[nrow(temp), ] 
-		# final$distance <- format(final$distance, nsmall = 1, digits = 1)
-		# disttemp <- rbind(disttemp, final)
 
 		# add to plot
 		p <- p + 
 			ggspatial::geom_spatial_label_repel(
 				data = disttemp, 
-				ggplot2::aes(x = lng, y = lat, label = distance),
+				ggplot2::aes(x = lon, y = lat, label = distance),
 				point.padding = grid::unit(0.4, "lines"), 
 				crs = 4326
 			)
 
 	}
 
+	p <- p +
+		ggplot2::coord_sf(xlim = range(temp$lon), ylim = range(temp$lat))
+
 	return(p)
 
 }

README.Rmd

@@ -109,49 +109,50 @@ An example creating a heat map of activities:
 ```{r message = F, fig.height = 5.5, fig.width = 7, message = F, warning = F}
 library(dplyr)
 
-# get activities, get activities by lat/lon, distance, plot
-my_acts <- get_activity_list(stoken)
-act_data <- compile_activities(my_acts) %>% 
-	filter(start_latlng2 < -86.5 & start_latlng2 > -88.5) %>% 
-	filter(start_latlng1 < 31.5 & start_latlng1 > 30) %>% 
-	filter(distance > 20)
-	
-get_heat_map(act_data, key = google_key, col = 'darkgreen', size = 2, distlab = F, f = 0.4)
+# get activities by date range
+my_acts <- get_activity_list(stoken, after = as.Date('2020-12-31'))
+act_data <- compile_activities(my_acts) 
+
+# subset by location
+toplo <- act_data %>% 
+	filter(grepl('Run$', name)) %>% 
+	filter(start_latlng2 < -82.63 & start_latlng2 > -82.65) %>% 
+	filter(start_latlng1 < 27.81 & start_latlng1 > 27.78) 
+
+get_heat_map(toplo, key = google_key, col = 'darkred', size = 1.5, distlab = F, alpha = 0.6, zoom = 13)
 ```
 
 Plotting elevation and grade for a single ride:
 ```{r}
-# activity id
-id <- 1784292574
+# get data for a single activity
+my_acts <- get_activity_list(stoken, id = 1784292574)
+act_data <- compile_activities(my_acts) 
 
 # plot elevation along a single ride
-get_heat_map(my_acts, id = id, alpha = 1, add_elev = T, distlab = F, key = google_key, size = 2, col = 'Spectral', units = 'imperial')
+get_heat_map(my_acts, alpha = 1, add_elev = T, distlab = F, key = google_key, size = 2, col = 'Spectral', units = 'imperial')
 
 # plot % gradient along a single ride
-get_heat_map(my_acts, id = id, alpha = 1, add_elev = T, distlab = F, as_grad = T, key = google_key, size = 2, col = 'Spectral', expand = 5, units = 'imperial')
+get_heat_map(my_acts, alpha = 1, add_elev = T, distlab = F, as_grad = T, key = google_key, size = 2, col = 'Spectral', units = 'imperial')
 ```
 
 Get elevation profiles for activities:
 ```{r message = F, fig.height = 3, fig.width = 9}
-# get activities
-my_acts <- get_activity_list(stoken) 
-
-get_elev_prof(my_acts, id = id, key = google_key, units = 'imperial')
-get_elev_prof(my_acts, id = id, key = google_key, units = 'imperial', total = T)
+get_elev_prof(my_acts, key = google_key, units = 'imperial')
+get_elev_prof(my_acts, key = google_key, units = 'imperial', total = T)
 ```  
 
 Plot average speed per split (km or mile) for an activity:
 ```{r message = F, fig.height = 3, fig.width = 9}
 # plots for most recent activity
-plot_spdsplits(my_acts, stoken, id = id, units = 'imperial')
+plot_spdsplits(my_acts, stoken, units = 'imperial')
 ```
 
 Additional functions are provided to get "stream" information for individual activities.  Streams provide more detailed information about location, time, speed, elevation, gradient, cadence, watts, temperature, and moving status (yes/no) for an individual activity.
 
 Use `get_activity_streams` for detailed info about activities:
 ```{r, fig.height = 4, fig.with = 4}
 # get streams for the first activity in my_acts
-strms_data <- get_activity_streams(my_acts, stoken, id = id)
+strms_data <- get_activity_streams(my_acts, stoken)
 head(strms_data)
 ```