AirSensor Function Overview

Function Overview

This document has been updated to reflect functions in AirSensor version 0.6.x.

Synoptic Data

Purple Air Synoptic (PAS) data provides a view of their sensor network with location metadata and an instantaneous view of measured values. Within the AirSensor package, this data is available as a pas object. All functions beginning with pas_ are designed for creating or working with this data. The following functions are the most common end-user functions:

function	params
Creating a `pas`
`pas_createNew()`	`countryCodes, includePWFSL, lookbackDays, baseUrl`
Loading a `pas`
`pas_load()`	`datestamp, retries, timezone, archival`
Obtaining information from a `pas`
`pas_getColumn()`	`pas, name, pattern, isOutside, isParent`
`pas_getDeviceDeploymentIDs()`	`pas, pattern, isOutside, isParent`
`pas_getIDs()`	`pas, pattern, isOutside, isParent`
`pas_getLabels()`	`pas, pattern, isOutside, isParent`
Manipulating a `pas`
`pas_filter()`	`pas, ...`
`pas_filterArea()`	`pas, w, e, s, n`
`pas_filterNear()`	`pas, longitude, latitude, radius`
Plotting a `pas`
`pas_leaflet()`	`pas, parameter, paletteName, ...`
`pas_staticMap()`	`pas, parameter, paletteName, ...`

Timeseries Data

PurpleAir Timeseries (PAT) data is available on a per-sensor basis. Within the AirSensor package, this data is available as a pat object. All functions beginning with pat_ are designed for creating or working with this data. The following functions are the most common end-user functions:

function	params
Creating a `pat`
`pat_createNew()`	`id, label, pas, startdate, enddate, timezone, baseUrl`
Loading a `pat`
`pat_load()`	`id, label, pas, startdate, enddate, days, timezone`
`pat_loadLatest()`	`id, label, pas`
`pat_loadMonth()`	`id, label, pas, datestamp, timezone`
Manipulating a `pat`
`pat_filter()`	`pat, ...`
`pat_filterDate()`	`pat, startdate, enddate, ...`
`pat_filterDatetime()`	`pat, startdate, enddate, ...`
`pat_join()`	`pat, pat, ...`
`pat_outliers()`	`pat, windowSize, thresholdMin, replace, showPlot, ...`
`pat_qc()`	`pat, ...`
`pat_sample()`	`pat, sampleSize`
Plotting a `pat`
`pat_dygraph()`	`pat, parameter, sampleSize, ...`
`pat_multiPlot()`	`pat, plottype, sampleSize, ...`
`pat_scatterPlotMatrix()`	`pat, parameters, sampleSize, ...`
State-of-Health functions
`pat_dailySoH()`	`pat, Soh_functions`
`pat_dailySoHIndex_Plot_00()`	`pat, minPctReporting, breaks`
`pat_dailySoHIndexPlot()`	`pat, minPctReporting, breaks, SoHIndex_FUN`
`pat_dailySoHPlot()`	`pat, ncol`
Other functions
`pat_aggregate()`	`pat, FUN, ...`
`pat_aggregateOutliserCounts()`	`pat, period, windowSize, thresholdMin`
`pat_externalFit()`	`pat, ...`
`pat_internalFit()`	`pat, ...`
`pat_monitorComparison()`	`pat, ...`

Hourly Aggregated Data

Hourly Aggregated data can be generated from pat objects with the pat_createAirSensor() function. Within the AirSensor package, this data is available as an airsensor object. All functions beginning with sensor_ are designed for obtaining or working with this data. The following functions are the most common end-user functions:

function	params
Creating an `airsensor`
`pat_createAirSensor()`	`pat, parameter, FUN, ...`
Loading an `airsensor`
`sensor_load()`	`collection, startdate, enddate, days, timezone`
`sensor_loadLatest()`	`collection, days`
`sensor_loadMonth()`	`collection, datestamp, timezone`
`sensor_loadYear()`	`collection, datestamp, timezone`
Manipulating an `airsensor`
`sensor_filter()`	`sensor, ...`
`sensor_filterMeta()`	`sensor, ...`
`sensor_filterDate()`	`sensor, startdate, enddate, days, ...`
`sensor_filterDate()`	`sensor, startdate, enddate, timezone`
Plotting an `airsensor`
`sensor_polarPlot()`	`sensor, windData, statistic, ...`
`sensor_pollutionRose()`	`sensor, windData, statistic, ...`
`sensor_calendarPlot()`	`sensor, ...`

Note that each airsensor object is also a ws_monitor object and can be manipulated and plotted with functions from the PWFSLSmoke package.

Mazama Science

2020-01-04

Function Overview

Synoptic Data

Timeseries Data

Hourly Aggregated Data