mirror of
https://github.com/sensebox/opensensmapr
synced 2025-07-06 09:00:23 +02:00
75 lines
2.5 KiB
R
75 lines
2.5 KiB
R
## ----setup, include=FALSE-----------------------------------------------------
|
|
knitr::opts_chunk$set(echo = TRUE)
|
|
|
|
## ----results = FALSE----------------------------------------------------------
|
|
library(magrittr)
|
|
library(opensensmapr)
|
|
|
|
# all_sensors = osem_boxes(cache = '.')
|
|
all_sensors = readRDS('boxes_precomputed.rds') # read precomputed file to save resources
|
|
|
|
## -----------------------------------------------------------------------------
|
|
summary(all_sensors)
|
|
|
|
## ---- message=FALSE, warning=FALSE--------------------------------------------
|
|
plot(all_sensors)
|
|
|
|
## -----------------------------------------------------------------------------
|
|
phenoms = osem_phenomena(all_sensors)
|
|
str(phenoms)
|
|
|
|
## -----------------------------------------------------------------------------
|
|
phenoms[phenoms > 20]
|
|
|
|
## ----results = FALSE, eval=FALSE----------------------------------------------
|
|
# pm25_sensors = osem_boxes(
|
|
# exposure = 'outdoor',
|
|
# date = Sys.time(), # ±4 hours
|
|
# phenomenon = 'PM2.5'
|
|
# )
|
|
|
|
## -----------------------------------------------------------------------------
|
|
pm25_sensors = readRDS('pm25_sensors.rds') # read precomputed file to save resources
|
|
|
|
summary(pm25_sensors)
|
|
plot(pm25_sensors)
|
|
|
|
## ---- results=FALSE, message=FALSE--------------------------------------------
|
|
library(sf)
|
|
library(units)
|
|
library(lubridate)
|
|
library(dplyr)
|
|
|
|
|
|
## ----bbox, results = FALSE, eval=FALSE----------------------------------------
|
|
# # construct a bounding box: 12 kilometers around Berlin
|
|
# berlin = st_point(c(13.4034, 52.5120)) %>%
|
|
# st_sfc(crs = 4326) %>%
|
|
# st_transform(3857) %>% # allow setting a buffer in meters
|
|
# st_buffer(set_units(12, km)) %>%
|
|
# st_transform(4326) %>% # the opensensemap expects WGS 84
|
|
# st_bbox()
|
|
# pm25 = osem_measurements(
|
|
# berlin,
|
|
# phenomenon = 'PM2.5',
|
|
# from = now() - days(3), # defaults to 2 days
|
|
# to = now()
|
|
# )
|
|
#
|
|
|
|
## -----------------------------------------------------------------------------
|
|
pm25 = readRDS('pm25_berlin.rds') # read precomputed file to save resources
|
|
plot(pm25)
|
|
|
|
## ---- warning=FALSE-----------------------------------------------------------
|
|
outliers = filter(pm25, value > 100)$sensorId
|
|
bad_sensors = outliers[, drop = TRUE] %>% levels()
|
|
|
|
pm25 = mutate(pm25, invalid = sensorId %in% bad_sensors)
|
|
|
|
## -----------------------------------------------------------------------------
|
|
st_as_sf(pm25) %>% st_geometry() %>% plot(col = factor(pm25$invalid), axes = TRUE)
|
|
|
|
## -----------------------------------------------------------------------------
|
|
pm25 %>% filter(invalid == FALSE) %>% plot()
|
|
|