Merge remote-tracking branch 'origin_ssh/i38-generic-var-templates' i…

…nto i39-single-val-per-month

tests/test_generic_scalar_stats.R

@@ -4,7 +4,7 @@ library(RUnit)
 # Setup
 wd <- "./"
 
-# # compute.stat.scalar Tests
+## compute.stat.scalar Tests
 
 climdex.pcic.test.compute.stat.scalar.mean <- function() {
   # Test data and dates
@@ -49,6 +49,7 @@ climdex.pcic.test.compute.stat.scalar.max <- function() {
   checkEqualsNumeric(as.numeric(result[1]), expected_max)
 }
 
+
 climdex.pcic.test.scalar.exact.dates <- function() {
   set.seed(123)
 
@@ -78,6 +79,7 @@ climdex.pcic.test.scalar.exact.dates <- function() {
                           "Expected exact date:", expected_max_date))
 }
 
+
 climdex.pcic.test.compute.stat.scalar.sum <- function() {
 
   data <- c(1, 2, 3, 4, 5) 
@@ -99,6 +101,7 @@ climdex.pcic.test.compute.stat.scalar.sum <- function() {
                      msg = paste("Computed sum:", result[1], "Expected sum:", expected_sum))
 }
 
+
 climdex.pcic.test.compute.stat.scalar.sd <- function() {
 
   data <- c(2, 4, 6, 8, 10) 
@@ -119,6 +122,7 @@ climdex.pcic.test.compute.stat.scalar.sd <- function() {
                      msg = paste("Computed SD:", result[1], "Expected SD:", expected_sd))
 }
 
+
 climdex.pcic.test.compute.stat.scalar.var <- function() {
   # Test data and dates
   data <- c(3, 6, 9, 12, 15) 

tests/test_generic_stat_helpers.R

@@ -22,6 +22,7 @@ climdex.pcic.test.convert.cartesian.to.polar <- function() {
   checkTrue(is.na(result_zero$direction), "Expected direction to be NA when both u and v are 0")
 }
 
+
 climdex.pcic.test.convert.polar.to.cartesian <- function() {
   speed <- sqrt(2)
   direction <- 45
@@ -41,6 +42,7 @@ climdex.pcic.test.convert.polar.to.cartesian <- function() {
 
 }
 
+
 climdex.pcic.test.convert.degrees.to.cardinal <- function() {
   # Test all 16 cardinal directions and boundary cases
   degrees <- c(0, 22.5, 45, 67.5, 90, 112.5, 135, 157.5, 180, 
@@ -72,9 +74,9 @@ climdex.pcic.test.convert.cardinal.to.degrees <- function() {
   # Mixed-case input
   mixed_case_result <- convert_cardinal_to_degrees(c('n', 'Ne', 'e', 'SE', 'S', 'sW', 'W', 'nw'))
   checkEqualsNumeric(as.numeric(mixed_case_result), expected)
-
 }
 
+
 climdex.pcic.test.filter.by.direction.range <- function() {
   primary_data <- 1:10
   degrees <- seq(0, 360, length.out = 10)
@@ -101,6 +103,7 @@ climdex.pcic.test.filter.by.direction.range <- function() {
   checkEquals(filtered$degrees, expected_degrees_cross_0, "Expected filtered degrees for range crossing 0 to have NA")
 }
 
+
 climdex.pcic.test.filter.by.direction.range.full.na <- function() {
   primary_data <- 1:10
   degrees <- seq(0, 360, length.out = 10) # 0  40  80 120 160 200 240 280 320 360
@@ -116,6 +119,7 @@ climdex.pcic.test.filter.by.direction.range.full.na <- function() {
   checkEquals(filtered$degrees, expected_degrees, "Expected all degrees to be NA")
 }
 
+
 climdex.pcic.test.compute.circular.mean <- function() {
   direction_degrees <- c(350, 10)  # Should average to 0 degrees
   date.factors <- 1
@@ -131,6 +135,7 @@ climdex.pcic.test.compute.circular.mean <- function() {
                  msg = "direction_degrees cannot be empty or NULL.")
 }
 
+
 climdex.pcic.test.compute.circular.mean.with.na <- function() {
   direction_degrees <- c(350, 10, NA)  # Should average to 0 degrees
   date.factors <- 1
@@ -140,6 +145,7 @@ climdex.pcic.test.compute.circular.mean.with.na <- function() {
   checkEqualsNumeric(result, expected, tolerance = 1e-6)
 }
 
+
 climdex.pcic.test.compute.circular.sd <- function() {
   direction_degrees <- c(350, 10)
   date.factors <- 1
@@ -152,6 +158,7 @@ climdex.pcic.test.compute.circular.sd <- function() {
                  msg = "direction_degrees cannot be empty or NULL.")
 }
 
+
 climdex.pcic.test.compute.circular.sd.with.na <- function() {
   direction_degrees <- c(350, 10, NA)
   date.factors <- 1

tests/test_generic_variable_inputs.R

@@ -1,4 +1,4 @@
-climdex.pcic.test.na_masks_with_missing_data_thresholds <- function() climdex.pcic.test.na_masks_with_missing_data_thresholds <- function() {
+climdex.pcic.test.na_masks_with_missing_data_thresholds <- function() {
   set.seed(123)
   speed <- runif(366, 0, 20)
   direction <- runif(366, 0, 360)
@@ -74,7 +74,6 @@ climdex.pcic.test.na_masks_with_missing_data_thresholds <- function() climdex.pc
 }
 
 
-
 climdex.pcic.test.scalar.raw.and.csv.construction <- function() {
   set.seed(123)
 
@@ -112,6 +111,7 @@ climdex.pcic.test.scalar.raw.and.csv.construction <- function() {
   checkTrue(all.equal(scalar_obj_csv, scalar_obj_raw), msg = "Scalar_obj built from csv is not identical to raw")
 }
 
+
 climdex.pcic.test.calendar.handling <- function() {
   set.seed(123)
 
@@ -148,6 +148,7 @@ climdex.pcic.test.calendar.handling <- function() {
   checkTrue(!any(format(scalar_obj_noleap@dates, "%m-%d") == "02-29"), "Leap day present in no-leap calendar dates.")
 }
 
+
 climdex.pcic.test.vector.raw.and.csv.construction <- function() {
   set.seed(123)
 
@@ -259,6 +260,7 @@ climdex.pcic.test.vector.construction.validity <- function() {
   checkEqualsNumeric(polar_data$direction, expected_polar$direction, tolerance = 1e-6, "Direction conversion from cartesian to polar incorrect.")
 }
 
+
 climdex.pcic.test.scalar_construction_with_malformed_inputs <- function() {
   # Valid data
   data <- c(10.5, 12.3, 11.2)
@@ -313,7 +315,6 @@ climdex.pcic.test.scalar_construction_with_malformed_inputs <- function() {
 }
 
 
-
 climdex.pcic.test.vector_construction_with_malformed_inputs <- function() {
   # Setup valid data for comparison
   valid_speed <- c(5, 10, 15)
@@ -434,6 +435,5 @@ climdex.pcic.test.vector_construction_with_malformed_inputs <- function() {
     ),
     msg = "Error not raised for invalid calendar type."
   )
-
 }
 

tests/test_generic_vector_stats.R

@@ -4,7 +4,7 @@ library(circular)
 # Setup
 wd <- "./"
 
-# # compute.stat.vector Tests
+## compute.stat.vector Tests
 # Helper function to update primary and secondary values in a vector object. Dates need to be readded to avoid data-date length mismatch.
 update_vector_obj <- function(base_vector_obj, primary, secondary, dates) {
   return(climdexGenericVector.raw(
@@ -84,9 +84,6 @@ climdex.pcic.test.compute.stat.vector.circular.mean <- function() {
 }
 
 
-
-
-
 climdex.pcic.test.compute.stat.vector.circular.sd <- function() {
 
   speed <- c(5, 5)
@@ -186,6 +183,7 @@ climdex.pcic.test.compute.stat.vector.mean.magnitude <- function() {
                      msg = paste("Result magnitude differs from expected:", result$magnitude))
 }
 
+
 climdex.pcic.test.compute.stat.vector.filtered.direction.range <- function() {
 
   speed <- c(5, 10, 15, 20)
@@ -218,6 +216,7 @@ climdex.pcic.test.compute.stat.vector.filtered.direction.range <- function() {
   checkEqualsNumeric(as.numeric(result$magnitude[1]), expected_max_magnitude)
 }
 
+
 climdex.pcic.test.compute.stat.vector.missing.values <- function() {
   speed <- c(5, 10, NA, 20) # One NA speed
   direction <- c(45, 90, 135, NA)  # One NA direction
@@ -247,6 +246,7 @@ climdex.pcic.test.compute.stat.vector.missing.values <- function() {
                      msg = paste("Result magnitude differs from expected. Result:", result$magnitude))
 }
 
+
 climdex.pcic.test.compute.stat.vector.overlapping.years <- function() {
   # Full winter season (Dec-Feb)
   set.seed(123)
@@ -280,6 +280,7 @@ climdex.pcic.test.compute.stat.vector.overlapping.years <- function() {
                                  "Expected seasonal mean:", expected_mean_speed))
 }
 
+
 climdex.pcic.test.compute.stat.vector.filtered.direction.crossing.360 <- function() {
   speed <- c(5, 10, 15, 20)
   direction <- c(350, 10, 135, 180)  # Directions crossing the 360-degree boundary
@@ -309,6 +310,7 @@ climdex.pcic.test.compute.stat.vector.filtered.direction.crossing.360 <- functio
   checkEqualsNumeric(as.numeric(result$magnitude[1]), expected_max_magnitude)
 }
 
+
 climdex.pcic.test.compute.stat.vector.no.data.in.direction.range <- function() {
   speed <- c(5, 10, 15, 20)
   direction <- c(45, 90, 135, 180)
@@ -338,6 +340,7 @@ climdex.pcic.test.compute.stat.vector.no.data.in.direction.range <- function() {
   checkTrue(is.na(result$magnitude[1]), "Expected NA result when no data is in the specified direction range.")
 }
 
+
 climdex.pcic.test.compute.stat.vector.cartesian.format <- function() {
   u <- c(5, 10, 15)
   v <- c(5, 0, -5)  # Cartesian components
@@ -386,6 +389,7 @@ climdex.pcic.test.compute.stat.vector.cartesian.format <- function() {
                                  "Expected circular mean direction:", expected_circular_mean))
 }
 
+
 climdex.pcic.test.compute.stat.vector.cardinal.format <- function() {
   speed <- c(5, 10, 15)
   direction <- c('N', 'E', 'S')  # Cardinal directions
@@ -415,6 +419,7 @@ climdex.pcic.test.compute.stat.vector.cardinal.format <- function() {
   checkEqualsNumeric(as.numeric(result$magnitude[1]), expected_mean_speed, tolerance = 1e-6)
 }
 
+
 climdex.pcic.test.compute.stat.vector.inverted.direction.range <- function() {
   speed <- c(5, 10, 15, 20)
   direction <- c(45, 90, 135, 180)