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74 lines
2.3 KiB
R
74 lines
2.3 KiB
R
2 years ago
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## ----setup, include=FALSE-----------------------------------------------------
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knitr::opts_chunk$set(echo = TRUE)
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## ----results = F--------------------------------------------------------------
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library(magrittr)
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library(opensensmapr)
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all_sensors = osem_boxes()
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## -----------------------------------------------------------------------------
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summary(all_sensors)
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## ----message=F, warning=F-----------------------------------------------------
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if (!require('maps')) install.packages('maps')
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if (!require('maptools')) install.packages('maptools')
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if (!require('rgeos')) install.packages('rgeos')
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plot(all_sensors)
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## -----------------------------------------------------------------------------
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phenoms = osem_phenomena(all_sensors)
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str(phenoms)
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## -----------------------------------------------------------------------------
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phenoms[phenoms > 20]
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## ----results = F--------------------------------------------------------------
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pm25_sensors = osem_boxes(
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exposure = 'outdoor',
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date = Sys.time(), # ±4 hours
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phenomenon = 'PM2.5'
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)
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## -----------------------------------------------------------------------------
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summary(pm25_sensors)
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plot(pm25_sensors)
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## -----------------------------------------------------------------------------
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library(sf)
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library(units)
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library(lubridate)
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library(dplyr)
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# construct a bounding box: 12 kilometers around Berlin
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berlin = st_point(c(13.4034, 52.5120)) %>%
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st_sfc(crs = 4326) %>%
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st_transform(3857) %>% # allow setting a buffer in meters
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st_buffer(set_units(12, km)) %>%
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st_transform(4326) %>% # the opensensemap expects WGS 84
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st_bbox()
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## ----results = F--------------------------------------------------------------
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pm25 = osem_measurements(
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berlin,
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phenomenon = 'PM2.5',
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from = now() - days(3), # defaults to 2 days
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to = now()
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)
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plot(pm25)
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## -----------------------------------------------------------------------------
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outliers = filter(pm25, value > 100)$sensorId
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bad_sensors = outliers[, drop = T] %>% levels()
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pm25 = mutate(pm25, invalid = sensorId %in% bad_sensors)
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## -----------------------------------------------------------------------------
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st_as_sf(pm25) %>% st_geometry() %>% plot(col = factor(pm25$invalid), axes = T)
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## -----------------------------------------------------------------------------
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pm25 %>% filter(invalid == FALSE) %>% plot()
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