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remove note about #3, fix typos

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noerw 2017-08-24 19:17:07 +02:00
parent d7d1bf0300
commit c216ec9f61
2 changed files with 5 additions and 10 deletions
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2
R/box_utils.R
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@ -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:')

13
vignettes/osem-intro.Rmd
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@ -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()
```