temporal_step_check.improve: Temporal step check function (new version, can be implemented...

In jieyu97/QCwind: Quality control procedures for citizen science wind observations

Description

Same as the description in temporal_step_check.

Usage

temporal_step_check.improve(
  data,
  data.column,
  datetime.column,
  step.duration,
  max.variation
)

Arguments

data	a data.frame that includes observation data with information.
data.column	a character, the selected column name in the data.frame that represents observation data to be checked.
datetime.column	a character, the selected column name in the data.frame that represents the reporting dates and times of corresponding observations.
step.duration	a positive number, the interval time for step test, the unit is 'second'.
max.variation	a positive number, the maximum allowed variability of observations.

Value

a new tbl_df that extends two new columns on the input data, the first added column flag_step represents the flags (P means pass, fail.step means fail, isolated means missing previous observations), the second added column new_data_step represents the observation data after removing failed observations in the step check.

Examples

library(tidyverse)
datetime = as.POSIXct(seq(0,60000,600), origin = "2017-02-03 08:00:00")
test_data = tibble(datetime = datetime, windspeed = c(rep(10.2,5),rep(NA,5),rep(9.3,35),rep(20,5),
                                                rep(3.5,40),c(1,3,NA,2,NA,5,6,7,NA,2,4)))
test_step_check = temporal_step_check.improve(test_data, data.column = 'windspeed',
                                      datetime.column = 'datetime',
                                      step.duration = 660,
                                      max.variation = 5)
attributes(test_step_check)
test_step_check

jieyu97/QCwind documentation built on June 18, 2021, 3:37 a.m.