diff --git a/R/box_utils.R b/R/box_utils.R index 3f5f584..62e63c9 100644 --- a/R/box_utils.R +++ b/R/box_utils.R @@ -41,7 +41,7 @@ print.sensebox = function(x, ...) { #' @export summary.sensebox = function(object, ...) { - cat('box total:', nrow(object), fill = T) + cat('boxes total:', nrow(object), fill = T) cat('\nboxes by exposure:') table(object$exposure) %>% print() cat('\nboxes by model:') diff --git a/vignettes/osem-intro.Rmd b/vignettes/osem-intro.Rmd index 5d6126a..6a1a2c1 100644 --- a/vignettes/osem-intro.Rmd +++ b/vignettes/osem-intro.Rmd @@ -26,11 +26,6 @@ Its main goals are to provide means for: - big data analysis of the measurements stored on the platform - sensor metadata analysis (sensor counts, spatial distribution, temporal trends) -> *Please note:* The openSenseMap API is sometimes a bit unstable when streaming -long responses, which results in `curl` complaining about `Unexpected EOF`. This -bug is being worked on upstream. Meanwhile you have to retry the request when -this occurs. - ### Exploring the dataset Before we look at actual observations, lets get a grasp of the openSenseMap datasets' structure. @@ -45,14 +40,14 @@ all_sensors = osem_boxes() summary(all_sensors) ``` -This gives a good overview already: As of writing this, there are more than 600 +This gives a good overview already: As of writing this, there are more than 700 sensor stations, of which ~50% are currently running. Most of them are placed outdoors and have around 5 sensors each. The oldest station is from May 2014, while the latest station was registered a couple of minutes ago. -Another feature of interest is the spatial distribution of the boxes. `plot()` -can help us out here. This function requires a bunch of optional dependcies though. +Another feature of interest is the spatial distribution of the boxes: `plot()` +can help us out here. This function requires a bunch of optional dependencies though. ```{r message=F, warning=F} if (!require('maps')) install.packages('maps') @@ -117,7 +112,7 @@ library(lubridate) berlin = st_point(c(13.4034, 52.5120)) %>% st_sfc(crs = 4326) %>% st_transform(3857) %>% # allow setting a buffer in meters - st_buffer(units::set_units(12, km)) %>% + st_buffer(set_units(12, km)) %>% st_transform(4326) %>% # the opensensemap expects WGS 84 st_bbox() ```