source("libtest.R") test_that("mc_prep_clean", { differnt_values_warning(cleaned_data <- mc_read_files("../data/clean-datetime_step", "TOMST", silent=T)) expect_warning(mc_prep_clean(cleaned_data, silent=T)) test_raw_data_format(cleaned_data) expect_equal(cleaned_data$localities[["94184102"]]$loggers[[1]]$clean_info@count_duplicities, 1) expect_equal(cleaned_data$localities[["94184102"]]$loggers[[1]]$clean_info@count_missing, 2) expect_equal(cleaned_data$localities[["94184165"]]$loggers[[1]]$clean_info@count_duplicities, 25) expect_equal(cleaned_data$localities[["94184169"]]$loggers[[1]]$clean_info@count_disordered, 1) diff_datetime <- diff(as.numeric(cleaned_data$localities[["94184169"]]$loggers[[1]]$datetime)) %/% 60 expect_equal(diff_datetime, rep(15, 5)) diff_datetime <- diff(as.numeric(cleaned_data$localities[["94184170"]]$loggers[[1]]$datetime)) %/% 60 expect_equal(diff_datetime, rep(15, 5)) test_function <- if(exists(".prep_is_logger_cleaned")) .prep_is_logger_cleaned else .prep_is_logger_cleaned expect_true(test_function(cleaned_data$localities[["94184102"]]$loggers[[1]])) expect_true(.prep_clean_was_error_in_logger(cleaned_data$localities[["94184102"]]$loggers[[1]])) expect_equal(length(cleaned_data$localities[["94184102"]]$loggers[[1]]$datetime), 49) expect_true(is.na(cleaned_data$localities[["94184102"]]$loggers[[1]]$sensors$TMS_T1$values[[19]])) expect_equal(cleaned_data$localities[["91184133"]]$loggers[[1]]$clean_info@step, 15 * 60) expect_equal(cleaned_data$localities[["91184133"]]$loggers[[1]]$sensors$Thermo_T$states$start, dplyr::first(cleaned_data$localities[["91184133"]]$loggers[[1]]$datetime)) agg_data <- mc_agg(cleaned_data) expect_error(mc_prep_clean(agg_data)) }) test_that("mc_prep_clean defined step", { differnt_values_warning(cleaned_data <- mc_read_files("../data/clean-datetime_step", "TOMST", step=30*60, silent=T)) %>% suppressWarnings() expect_equal(cleaned_data$localities[["94184102"]]$loggers[[1]]$clean_info@step, 30*60) expect_equal(length(cleaned_data$localities[["94184102"]]$loggers[[1]]$datetime), 25) }) test_that("mc_prep_clean rounding", { cleaned_data <- mc_read_files("../data/clean-rounding", "TOMST_join", silent=T) test_raw_data_format(cleaned_data) expect_equal(cleaned_data$localities$A1E01_TS$loggers[[1]]$datetime, c(lubridate::ymd_hm("2018-10-18 09:00"), lubridate::ymd_hm("2018-10-18 11:00"), lubridate::ymd_hm("2018-10-18 13:00"), lubridate::ymd_hm("2018-10-18 15:00"), lubridate::ymd_hm("2018-10-18 17:00"), lubridate::ymd_hm("2018-10-18 19:00"))) }) test_that("mc_prep_clean 1.5 hour step", { data <- mc_read_files("../data/HOBO/6265.csv", "HOBO", date_format = "%m/%d/%y %I:%M:%S %p", clean=FALSE, silent=TRUE) cleaned_data <- mc_prep_clean(data, silent=T) test_raw_data_format(cleaned_data) expect_equal(data$`20396265`$loggers[[1]]$datetime, cleaned_data$`20396265`$loggers[[1]]$datetime) }) test_that("mc_prep_clean one record", { data <- mc_read_files("../data/clean-one-record", "TOMST", clean = FALSE) expect_warning(cleaned_data <- mc_prep_clean(data, silent=T)) expect_true(is.na(cleaned_data$localities[["94208611"]]$loggers[[1]]$clean_info@step)) expect_true(is.na(cleaned_data$localities[["94208611"]]$loggers[[1]]$clean_info@count_duplicities)) expect_true(is.na(cleaned_data$localities[["94208611"]]$loggers[[1]]$clean_info@count_disordered)) expect_true(is.na(cleaned_data$localities[["94208611"]]$loggers[[1]]$clean_info@count_missing)) }) test_that("mc_prep_clean ok", { cleaned_data <- mc_read_files("../data/TOMST/data_94184102_0.csv", "TOMST", silent=T) expect_true(.prep_is_logger_cleaned(cleaned_data$localities[[1]]$loggers[[1]])) expect_false(.prep_clean_was_error_in_logger(cleaned_data$localities[[1]]$loggers[[1]])) }) test_that("mc_prep_solar_tz", { data <- mc_read_data("../data/TOMST/files_table.csv", "../data/TOMST/localities_table.csv", clean = FALSE) data <- mc_prep_solar_tz(data) test_raw_data_format(data) expect_equal(data$localities$A1E05$metadata@tz_offset, 57) }) test_that("mc_prep_meta_locality", { data <- mc_read_data("../data/TOMST/files_table.csv", "../data/TOMST/localities_table.csv", clean = FALSE) expect_error(changed_data <- mc_prep_meta_locality(data, list(A1E05=50))) changed_data <- mc_prep_meta_locality(data, list(A1E05=50), param_name="tz_offset") test_raw_data_format(changed_data) expect_equal(changed_data$localities$A1E05$metadata@tz_offset, 50) expect_equal(changed_data$localities$A1E05$metadata@tz_type, myClim:::.model_const_TZ_USER_DEFINED) changed_data <- mc_prep_meta_locality(data, list(A1E05="abc", A2E32="def"), param_name="my_super_param") test_raw_data_format(changed_data) expect_equal(changed_data$localities$A1E05$metadata@user_data[["my_super_param"]], "abc") metadata <- as.data.frame(tibble::tribble( ~locality_id, ~lat_wgs84, ~lon_wgs84, ~my, "A1E05" , 1, 2, NA, "A2E32" , 3, 4, 0, "TEST" , 1, 1, 10 )) expect_error(changed_data <- mc_prep_meta_locality(data, metadata, param_name="tz_offset")) expect_warning(changed_data <- mc_prep_meta_locality(data, metadata), "There isn't locality TEST.") %>% expect_warning("There isn't locality TEST.") %>% expect_warning("There isn't locality TEST.") test_raw_data_format(changed_data) expect_equal(changed_data$localities$A1E05$metadata@lat_wgs84, 1) expect_equal(changed_data$localities$A1E05$metadata@lon_wgs84, 2) expect_true(is.na(changed_data$localities$A1E05$metadata@user_data[["my"]])) data_clean <- mc_prep_clean(data, silent=T) data_calc <- mc_agg(data_clean) expect_warning(changed_data <- mc_prep_meta_locality(data_calc, metadata), "There isn't locality TEST.") %>% expect_warning("There isn't locality TEST.") %>% expect_warning("There isn't locality TEST.") test_agg_data_format(changed_data) expect_equal(changed_data$localities$A1E05$metadata@lat_wgs84, 1) }) test_that("mc_prep_meta_locality rename", { data <- mc_read_data("../data/TOMST/files_table.csv", clean=FALSE) renamed_data <- mc_prep_meta_locality(data, list(A1E05="ABC05", A2E32="CDE32"), "locality_id") expect_equal(sort(names(renamed_data$localities)), sort(c("ABC05", "CDE32", "A6W79"))) values <- as.data.frame(tibble::tribble( ~locality_id, ~new_locality_id, "A1E05" , "ABC05", "A2E32" , "CDE32", )) renamed_data <- mc_prep_meta_locality(data, values) expect_equal(sort(names(renamed_data$localities)), sort(c("ABC05", "CDE32", "A6W79"))) renamed_data <- mc_prep_clean(renamed_data, silent=T) renamed_data <- mc_agg(renamed_data, c("min", "max"), "hour") renamed_data <- mc_prep_meta_locality(renamed_data, list(ABC05="AAA05"), "locality_id") expect_equal(names(renamed_data$localities), c("AAA05", "CDE32", "A6W79")) }) test_that("mc_prep_crop", { data <- mc_read_data("../data/TOMST/files_table.csv", "../data/TOMST/localities_table.csv", clean=FALSE) cropped_data <- mc_prep_crop(data, start=as.POSIXct("2020-10-16 08:00", tz="UTC")) test_raw_data_format(cropped_data) expect_equal(length(cropped_data$localities$A2E32$loggers[[1]]$datetime), 68) expect_equal(length(cropped_data$localities$A2E32$loggers[[1]]$sensors$TMS_T1$values), 68) expect_equal(cropped_data$localities$A2E32$loggers[[1]]$sensors$TMS_T1$states$start, lubridate::ymd_h("2020-10-16 08")) cropped_data <- mc_prep_crop(data, end=as.POSIXct("2020-10-16 08:00", tz="UTC")) test_raw_data_format(cropped_data) expect_equal(length(cropped_data$localities$A2E32$loggers[[1]]$datetime), 8) expect_equal(length(cropped_data$localities$A2E32$loggers[[1]]$sensors$TMS_T1$values), 8) expect_equal(cropped_data$localities$A2E32$loggers[[1]]$sensors$TMS_T1$states$end, lubridate::ymd_h("2020-10-16 08")) cropped_data <- mc_prep_crop(data, end=as.POSIXct("2020-10-16 08:00", tz="UTC"), end_included=FALSE) test_raw_data_format(cropped_data) expect_equal(length(cropped_data$localities$A2E32$loggers[[1]]$datetime), 7) expect_equal(length(cropped_data$localities$A2E32$loggers[[1]]$sensors$TMS_T1$values), 7) data_clean <- mc_prep_clean(data, silent=T) data_calc <- mc_agg(data_clean) data_calc <- mc_calc_snow(data_calc, "TMS_T2", localities = c("A2E32", "A6W79")) cropped_agg_data <- mc_prep_crop(data_calc, start=as.POSIXct("2020-10-16 06:00", tz="UTC"), end=as.POSIXct("2020-10-16 08:00", tz="UTC")) expect_equal(cropped_agg_data$localities$A6W79$sensors$TMS_T1$states$start, lubridate::ymd_h("2020-10-16 06")) expect_equal(cropped_agg_data$localities$A6W79$sensors$TMS_T1$states$end, lubridate::ymd_h("2020-10-16 08")) expect_equal(nrow(cropped_agg_data$localities$A1E05$sensors$Thermo_T$states), 0) test_agg_data_format(cropped_agg_data) }) test_that("mc_prep_crop by localities", { data <- mc_read_data("../data/TOMST/files_table.csv", "../data/TOMST/localities_table.csv", clean=TRUE, silent=TRUE) agg_data <- mc_agg(data) cropped_data <- mc_prep_crop(data, start=as.POSIXct("2020-10-16 06:00", tz="UTC"), end=as.POSIXct("2020-10-16 08:00", tz="UTC"), localities=c("A1E05", "A2E32")) test_raw_data_format(cropped_data) expect_equal(length(cropped_data$localities$A2E32$loggers[[1]]$datetime), 8) expect_equal(cropped_data$localities$A6W79$loggers[[1]]$datetime, data$localities$A6W79$loggers[[1]]$datetime) cropped_agg_data <- mc_prep_crop(agg_data, start=as.POSIXct("2020-10-16 06:00", tz="UTC"), end=as.POSIXct("2020-10-16 08:00", tz="UTC"), localities=c("A1E05", "A2E32")) test_agg_data_format(cropped_agg_data) expect_equal(length(cropped_agg_data$localities$A2E32$datetime), 8) expect_equal(cropped_agg_data$localities$A6W79$datetime, agg_data$localities$A6W79$datetime) expect_error(cropped_data <- mc_prep_crop(data, start=as.POSIXct(c("2020-10-28 09:00", "2020-10-16 07:00"), tz="UTC"), end=as.POSIXct(c("2020-10-28 10:00", "2020-10-16 08:00"), tz="UTC"), localities="A1E05")) expect_error(cropped_data <- mc_prep_crop(data, start=as.POSIXct(c("2020-10-28 09:00", "2020-10-16 07:00"), tz="UTC"), end=as.POSIXct(c("2020-10-28 10:00", "2020-10-16 08:00"), tz="UTC"))) cropped_data <- mc_prep_crop(data, start=as.POSIXct(c("2020-10-28 09:00", "2020-10-16 07:00"), tz="UTC"), end=as.POSIXct(c("2020-10-28 10:00", "2020-10-16 08:00"), tz="UTC"), localities=c("A1E05", "A2E32")) test_raw_data_format(cropped_data) expect_equal(cropped_data$localities$A1E05$loggers[[1]]$datetime, as.POSIXct(c("2020-10-28 09:00", "2020-10-28 09:15", "2020-10-28 09:30", "2020-10-28 09:45", "2020-10-28 10:00"), tz="UTC")) expect_equal(cropped_data$localities$A2E32$loggers[[1]]$datetime, as.POSIXct(c("2020-10-16 07:00", "2020-10-16 07:15", "2020-10-16 07:30", "2020-10-16 07:45", "2020-10-16 08:00"), tz="UTC")) expect_equal(cropped_data$localities$A6W79$loggers[[1]]$datetime, data$localities$A6W79$loggers[[1]]$datetime) cropped_agg_data <- mc_prep_crop(agg_data, start=as.POSIXct(c("2020-10-28 09:00", "2020-10-16 07:00"), tz="UTC"), end=as.POSIXct(c("2020-10-28 10:00", "2020-10-16 08:00"), tz="UTC"), localities=c("A1E05", "A2E32")) test_agg_data_format(cropped_agg_data) expect_equal(cropped_agg_data$localities$A1E05$datetime, as.POSIXct(c("2020-10-28 09:00", "2020-10-28 09:15", "2020-10-28 09:30", "2020-10-28 09:45", "2020-10-28 10:00"), tz="UTC")) expect_equal(cropped_agg_data$localities$A2E32$datetime, as.POSIXct(c("2020-10-16 07:00", "2020-10-16 07:15", "2020-10-16 07:30", "2020-10-16 07:45", "2020-10-16 08:00"), tz="UTC")) expect_equal(cropped_agg_data$localities$A6W79$datetime, agg_data$localities$A6W79$datetime) }) test_that("mc_prep_crop errors", { expect_warning(data <- mc_read_files("../data/TOMST-error", "TOMST", clean=FALSE)) cropped_data <- mc_prep_crop(data, start=lubridate::ymd_hm("2022-02-24 07:45"), end=lubridate::ymd_hm("2022-02-24 10:30")) states <- dplyr::filter(cropped_data$localities$data_93142777$loggers[[1]]$sensors$TMS_T2$states, .data$tag == .model_const_SENSOR_STATE_ERROR) expect_equal(nrow(states), 4) expect_equal(states$start, c(lubridate::ymd_hm("2022-02-24 07:45"), lubridate::ymd_hm("2022-02-24 09:00"), lubridate::ymd_hm("2022-02-24 09:45"), lubridate::ymd_hm("2022-02-24 10:15"))) expect_equal(states$end, c(lubridate::ymd_hm("2022-02-24 08:30"), lubridate::ymd_hm("2022-02-24 09:15"), lubridate::ymd_hm("2022-02-24 09:45"), lubridate::ymd_hm("2022-02-24 10:30"))) }) test_that(".prep_get_loggers_datetime_step_unprocessed", { data <- mc_read_data("../data/TOMST/files_table.csv", "../data/TOMST/localities_table.csv", clean=FALSE) test_function <- if(exists(".prep_get_uncleaned_loggers")) .prep_get_uncleaned_loggers else .prep_get_uncleaned_loggers expect_equal(test_function(data), c("91184101", "94184103", "94184102")) data_clean <- mc_prep_clean(data, silent=T) expect_equal(length(test_function(data_clean)), 0) }) test_that(".prep_get_utc_localities", { not_applicable_format_warning(data <- mc_read_files("../data/TOMST", "TOMST", clean=FALSE)) %>% not_applicable_format_warning() %>% not_applicable_format_warning() test_function <- if(exists(".prep_get_utc_localities")) .prep_get_utc_localities else .prep_get_utc_localities expect_equal(test_function(data), c("91184101", "92192250", "94184102", "94184103", "94184104", "94230002")) data_clean <- mc_prep_meta_locality(data, list(`91184101`=60, `92192250`=60, `94184102`=60, `94184103`=60, `94184104`=60, `94230002`=60), "tz_offset") expect_equal(length(test_function(data_clean)), 0) }) test_that("mc_prep_meta_sensor", { cleaned_data <- mc_read_data("../data/flat/files_table.csv", silent=T) cleaned_data <- mc_prep_meta_sensor(cleaned_data, list(TMS_T1="TMS_Tsoil"), "name") expect_true("TMS_Tsoil" %in% names(cleaned_data$localities$main$loggers[[1]]$sensors)) cleaned_data <- mc_prep_meta_sensor(cleaned_data, list(TMS_T2="T2"), param_name = "name", logger_types="TMS") expect_true("T2" %in% names(cleaned_data$localities$main$loggers[[1]]$sensors)) expect_false("T2" %in% names(cleaned_data$localities$main$loggers[[2]]$sensors)) expect_warning(agg_data <- mc_agg(cleaned_data), "TMS_Tsoil is renamed to TMS_Tsoil_1") %>% expect_warning("sensor TMS_T3 is renamed to TMS_T3_1") %>% expect_warning("sensor TMS_moist is renamed to TMS_moist_1") agg_data <- mc_prep_meta_sensor(agg_data, list(TMS_T3_1="TMS_T3_secondary"), localities="main", param_name="name") expect_true("TMS_T3_secondary" %in% names(agg_data$localities$main$sensors)) agg_data <- mc_prep_meta_sensor(agg_data, list(TMS_T3_secondary="air"), param_name="height") expect_equal(agg_data$localities$main$sensors$TMS_T3_secondary$metadata@height, "air") }) test_that("mc_prep_meta_sensor wrong", { data <- mc_read_data("../data/flat/files_table.csv", clean=FALSE) expect_error(data <- mc_prep_meta_sensor(data, list(TMS_T1="TMS_T2"), param_name = "name")) }) test_that("mc_prep_merge wrong", { data <- mc_read_data("../data/TOMST/files_table.csv", clean=FALSE) cleaned_data <- mc_prep_clean(data, silent=T) agg_data <- mc_agg(cleaned_data) expect_error(mc_prep_merge(data, agg_data)) hour_data <- mc_agg(agg_data, "max", "hour") expect_error(mc_prep_merge(agg_data, hour_data)) }) test_that("mc_prep_merge", { data1 <- mc_read_files(c("../data/TOMST/data_91184101_0.csv", "../data/TOMST/data_94184102_0.csv"), "TOMST", clean=FALSE) data2 <- mc_read_files("../data/TOMST/data_94184103_0.csv", "TOMST", clean=FALSE) merged_data <- mc_prep_merge(list(data1, data2)) test_raw_data_format(merged_data) expect_equal(length(merged_data$localities), 3) data1 <- mc_prep_clean(data1, silent=T) data2 <- mc_prep_clean(data2, silent=T) merged_data <- mc_prep_merge(list(data1, data2)) test_raw_data_format(merged_data) expect_equal(length(merged_data$localities), 3) hour_data1 <- mc_agg(data1, c("min", "max"), "hour") hour_data2 <- mc_agg(data2, c("min", "max"), "hour") merged_hour_data <- mc_prep_merge(list(hour_data1, hour_data2)) test_agg_data_format(merged_hour_data) expect_equal(length(merged_hour_data$localities), 3) }) test_that("mc_prep_merge raw-format same name", { data <- mc_read_data("../data/TOMST/files_table.csv", clean=FALSE) merged_data <- mc_prep_merge(list(data, data)) test_raw_data_format(merged_data) expect_equal(names(merged_data$localities), c("A1E05", "A2E32", "A6W79")) expect_equal(length(merged_data$localities$A1E05$loggers), 2) }) test_that("mc_prep_merge agg-format same name", { data <- mc_read_data("../data/TOMST/files_table.csv", silent=T) day_data_1 <- mc_agg(data, "mean", "hour") day_data_2 <- mc_agg(data, c("mean", "max"), "hour") expect_warning(merged_data <- mc_prep_merge(list(day_data_1, day_data_2)), "sensor .+ is renamed to .+") %>% suppressWarnings() test_agg_data_format(merged_data) expect_equal(names(merged_data$localities), c("A1E05", "A2E32", "A6W79")) expect_equal(length(merged_data$localities$A2E32$sensors), 12) }) test_that("mc_prep_rename_locality wrong", { data <- mc_read_data("../data/TOMST/files_table.csv", clean=FALSE) expect_error(data <- mc_prep_rename_locality(data, list(A1E05="A6W79"))) }) test_that("mc_prep_calib_load, mc_prep_calib", { data <- mc_read_data("../data/TOMST/files_table.csv", clean=FALSE) calib_table <- as.data.frame(tibble::tribble( ~serial_number, ~sensor_id, ~datetime, ~cor_factor, "91184101", "Thermo_T", lubridate::ymd_h("2020-10-28 00"), 0.1, "91184101", "Thermo_T", lubridate::ymd_h("2020-10-28 10"), 0, "94184102", "TMS_T1", lubridate::ymd_h("2020-10-16 00"), 0.12, "94184102", "TMS_T2", lubridate::ymd_h("2020-10-16 01"), 0.15, "94184102", "TMS_T3", lubridate::ymd_h("2020-10-16 00"), 0.2, "94184102", "TMS_moist", lubridate::ymd_h("2020-10-16 00"), 0.01, )) param_data <- mc_prep_calib_load(data, calib_table) test_raw_data_format(param_data) calib_table <- as.data.frame(tibble::tribble( ~serial_number, ~sensor_id, ~datetime, ~cor_factor, ~cor_slope, "91184101", "Thermo_T", lubridate::ymd_h("2020-10-28 00"), 0.1, 0, "91184101", "Thermo_T", lubridate::ymd_h("2020-10-28 10"), 0, -0.05, "94184102", "TMS_T1", lubridate::ymd_h("2020-10-16 00"), 0.12, 0.1, "94184102", "TMS_T2", lubridate::ymd_h("2020-10-16 01"), 0.15, 0.05, "94184102", "TMS_T3", lubridate::ymd_h("2020-10-16 00"), 0.2, 0, "94184102", "TMS_moist", lubridate::ymd_h("2020-10-16 00"), 0.01, 0, )) param_data <- mc_prep_calib_load(data, calib_table) test_raw_data_format(param_data) expect_error(calib_data <- mc_prep_calib(param_data)) param_data <- mc_prep_clean(param_data, silent = T) calib_data <- mc_prep_calib(param_data) test_raw_data_format(calib_data) expect_true(calib_data$localities$A1E05$loggers[[1]]$sensors$Thermo_T$metadata@calibrated) expect_equal(calib_data$localities$A1E05$loggers[[1]]$sensors$Thermo_T$values[[1]], 9.875 + 0.1) expect_equal(calib_data$localities$A1E05$loggers[[1]]$sensors$Thermo_T$values[[6]], 6.875 * 0.95) expect_equal(calib_data$localities$A6W79$loggers[[1]]$sensors$TMS_T2$values[[1]], 9.5 * 1.05 + 0.15) expect_equal(calib_data$localities$A6W79$loggers[[1]]$sensors$TMS_T2$values[[5]], 9.5 * 1.05 + 0.15) expect_true(calib_data$localities$A6W79$loggers[[1]]$sensors$TMS_T3$metadata@calibrated) expect_false(calib_data$localities$A6W79$loggers[[1]]$sensors$TMS_moist$metadata@calibrated) agg_data <- mc_agg(param_data) calib_data <- mc_prep_calib(agg_data, sensors = "Thermo_T") test_agg_data_format(calib_data) expect_true(calib_data$localities$A1E05$sensors$Thermo_T$metadata@calibrated) expect_equal(calib_data$localities$A1E05$sensors$Thermo_T$values[[1]], 9.875 + 0.1) expect_equal(calib_data$localities$A1E05$sensors$Thermo_T$values[[6]], 6.875 * 0.95) }) test_that("mc_prep_calib_load wrong type", { data <- mc_read_data("../data/TOMST/files_table.csv", clean=FALSE) calib_table <- as.data.frame(tibble::tribble( ~serial_number, ~sensor_id, ~datetime, ~cor_factor, "91184101", "Thermo_T", "2020-10-28 00", 0.1, "91184101", "Thermo_T", "2020-10-28 10", 0, )) expect_error(mc_prep_calib_load(data, calib_table)) calib_table <- as.data.frame(tibble::tribble( ~serial_number, ~sensor_id, ~datetime, ~cor_factor, "91184101", "Thermo_T", lubridate::ymd("2020-10-28"), 0.1, "91184101", "Thermo_T", lubridate::ymd("2020-10-29"), 0, )) expect_error(mc_prep_calib_load(data, calib_table)) }) test_that("mc_prep_fillNA", { data <- mc_read_files("../data/agg", "TOMST", clean=F) expect_error(mc_prep_fillNA(data)) data <- mc_prep_clean(data, silent=T) data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[1:4] <- NA_real_ data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[50:52] <- NA_real_ data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[71:75] <- NA_real_ data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[90:95] <- NA_real_ data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[[192]] <- NA_real_ data_dupl <- mc_prep_meta_locality(data, list(`91184101`="abc"), "locality_id") data_dupl <- mc_prep_meta_sensor(data_dupl, list(Thermo_T="T"), "name") data <- mc_prep_merge(list(data, data_dupl)) approx_data <- mc_prep_fillNA(data, maxgap=5, localities="91184101") expect_true(is.na(approx_data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[[1]])) expect_false(is.na(approx_data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[[51]])) expect_false(is.na(approx_data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[[71]])) expect_true(is.na(approx_data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[[95]])) expect_true(is.na(approx_data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[[192]])) expect_true(is.na(approx_data$localities$abc$loggers[[1]]$sensors$T$values[[50]])) approx_data <- mc_prep_fillNA(data, maxgap=5, sensors="T") expect_false(is.na(approx_data$localities$abc$loggers[[1]]$sensors$T$values[[50]])) expect_true(is.na(approx_data$localities$`91184101`$loggers[[1]]$sensors$Thermo_T$values[[50]])) }) test_that("mc_prep_TMSoffsoil", { data <- mc_read_files("../data/TMSoffsoil/data_93142760_201904.csv", "TOMST", clean=F) expect_error(mc_prep_TMSoffsoil(data)) data <- mc_prep_clean(data, silent=T) data_offsoil <- mc_prep_TMSoffsoil(data, smooth=F) test_raw_data_format(data_offsoil) sel0 <- data_offsoil$localities$`93142760`$loggers[[1]]$datetime <= lubridate::ymd_hm("2018-12-05 8:45") sel0 <- sel0 | data_offsoil$localities$`93142760`$loggers[[1]]$datetime > lubridate::ymd_hm("2018-12-09 12:30") expect_true(all(data_offsoil$localities$`93142760`$loggers[[1]]$sensors$off_soil$values[sel0] == 0)) sel1 <- data_offsoil$localities$`93142760`$loggers[[1]]$datetime > lubridate::ymd_hm("2018-12-05 8:45") sel1 <- sel1 & data_offsoil$localities$`93142760`$loggers[[1]]$datetime <= lubridate::ymd_hm("2018-12-09 12:30") expect_true(all(data_offsoil$localities$`93142760`$loggers[[1]]$sensors$off_soil$values[sel1] == 1)) data_offsoil <- mc_prep_TMSoffsoil(data, smooth=T) expect_true(all(data_offsoil$localities$`93142760`$loggers[[1]]$sensors$off_soil$values == 0)) agg_data <- mc_agg(data) agg_data_offsoil <- mc_prep_TMSoffsoil(agg_data, smooth=F) test_agg_data_format(agg_data_offsoil) })