pat_timeAverage()

[jonathancallahan]

This function should limit its functionality to wrapping potentially multiple calls to the openair::timeAverage() function and returning a data frame. We will keep the A and B channels separate for now.

We still need to do some investigating of the "pat" data so we can come up with some sort of reasonable QC before we start mixing A and B together to create our "official" number.

Input

• pat = NULL -- pa_timeseries object
• parameter = "pm25_A" -- "pat" data column to process
• period = "10 min" -- used as avg.time ("period" is the terminology preferred by lubridate)
• dataThreshold = 0 -- used as data.thresh
• stats = "all" -- vector of statistics to return as dataframe columns
• fill = FALSE" -- used as fill

Omit all of the following from opener::timeAverage(): "type, "percentile", "start.date", "end.date", "interval" and "vector.ws".

Output
The returned dataframe should have a first column named datetime followed by the names of the requested statistics with "count" replacing openair's "frequency".

When it all works, a user should be able to do the following:

# Generate a plot of 10 minute averages for pm25_A
pat %>%
  pat_timeAverage("pm25_A", "10 min", stats = "mean") %>%
  plot()

# Generate a QC plot of all statistics for channel B
pat %>%
  pat_timeAverage("pm25_B", "1 hour") %>%
  timeAveragePlot(plottype = "QC")

# Test my own ideas for a QC metric
my_qc <- 
  pat_timeAverage("pm25_A", "1 hour", stats = c("median", "sd", "count")) %>%
  mutate(qc_1 = median - sd, qc_2 = median / sd, qc_3 = sd * count)

somePlotFunction(my_qc)