A diagnostic plot is generated showing time series for the aggregation statistics used in the QC algorithm. Reviewing these time series for different "pat" objects can provide insight into what kinds of instrument problems a QC algorithm will catch or miss.

Current QC algorithms include:

  • hourly_AB_00

  • hourly_AB_01

PurpleAirQC_validationPlot(
  pat = NULL,
  period = "1 hour",
  qc_algorithm = "hourly_AB_01",
  min_count = 20
)

Arguments

pat

PurpleAir Timeseries pat object.

period

Time period to average over. Can be "sec", "min", "hour", "day", "DSTday", "week", "month", "quarter" or "year". A number can also precede these options followed by a space (i.e. "2 day" or "37 min").

qc_algorithm

Named QC algorithm to apply to hourly aggregation stats.

min_count

Aggregation bins with fewer than `min_count` measurements will be marked as `NA`.

Value

A dataframe of aggregation statistics.

See also

PurpleAirQC_hourly_AB_00

PurpleAirQC_hourly_AB_01

Examples

if (FALSE) { library(AirSensor) scsg_15 <- pat_load("SCSG_15", "2019-06-13", "2019-06-20") PurpleAirQC_validationPlot(scsg_15) scap_14 <- pat_load("SCAP_14", "2019-06-13", "2019-06-20") PurpleAirQC_validationPlot(scap_14) scem_05 <- pat_load("SCEM_05", "2019-06-13", "2019-06-20") PurpleAirQC_validationPlot(scem_05) }