cran fixes

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: thunder
 Type: Package
 Title: Computation and Visualisation of Atmospheric Convective Parameters
-Version: 1.1.2
+Version: 1.1.3
 Authors@R: c(person("Bartosz", "Czernecki",
              email = "nwp@amu.edu.pl",
              role = c("aut", "cre"), comment = c(ORCID = "0000-0001-6496-1386")),
@@ -47,7 +47,7 @@ Depends:
 Suggests:
     knitr,
     rmarkdown,
-    testthat (>= 2.0.0)
+    testthat (>= 3.0.0)
 LinkingTo: Rcpp
 RoxygenNote: 7.2.3
 Encoding: UTF-8

NEWS.md

@@ -1,3 +1,7 @@
+# thundeR 1.1.3
+
+* Adding new tests for thermodynamic indices failing with metPy 1.5, but working smoothly with thundeR and sharppy
+
 # thundeR 1.1.2
 
 * Allowing to keep NA values in `get_sounding()` which might be not harmful if missing data occur on higher altitudes for dew point temperatures

tests/testthat/test-get_sounding.R

@@ -1,5 +1,5 @@
 test_that("Downloading sounding profile", {
-
+  skip_on_cran() # skip on CRAN due to frequently being recognized as DDOS attack
   profile = get_sounding(wmo_id = 12120, 
                          yy = 2010,
                          mm = 8, 
@@ -11,12 +11,12 @@ test_that("Downloading sounding profile", {
 })
 
 test_that("Sounding profile error", {
-
+  skip_on_cran() # skip on CRAN due to frequently being recognized as DDOS attack
   expect_error(get_sounding(wmo_id = 99999, 
-                         yy = 2010,
-                         mm = 8, 
-                         dd = 20, 
-                         hh = 12)
+                            yy = 2010,
+                            mm = 8, 
+                            dd = 20, 
+                            hh = 12)
                )
-  
+
 })

tests/testthat/test-sounding_compute.R

@@ -12,6 +12,5 @@ test_that("sounding_compute", {
         res = sounding_compute(pressure, altitude, temp, dpt, wd, ws, accuracy = 1)
         nams = length(unique(names(res)))
         no_of_elements = length(res)
-        expect_equal(nams, no_of_elements) # the no. of parametrs should be > 100
-
+        expect_equal(nams, no_of_elements) # the no. of named parameters should be > 200
 })

tests/testthat/test-sounding_default.R

@@ -1,21 +1,61 @@
 
-context("Computation efficiency")
+context("sounding_default and sounding_compute should be equal")
 
-test_that("sounding_default should compute below 0.5s", {
+test_that("sounding_default should return the same values as sounding_compute for thermodynamics", {
         pressure <- c(1000, 855, 700, 500, 300, 100, 10)
         altitude <- c(0, 1500, 2500, 6000, 8500, 12000, 25000)
         temp <- c(25, 10, 0, -15, -30, -50, -92)
         dpt <- c(20, 5, -5, -30, -55, -80, -99)
         wd <- c(0, 90, 135, 180, 270, 350, 0)
         ws <- c(5, 10, 20, 30, 40, 5, 0)
         options(scipen = 999) # change formatting
-        t1 <- system.time(sounding_default(pressure, altitude, temp, dpt, wd, ws,
-                                           export_profile = 0,
-                                           accuracy = 2,
-                                           interpolate_step = 1000,
-                                           meanlayer_bottom_top = c(0, 500),
-                                           storm_motion = c(999, 999)))
-        t1 <- as.numeric(t1[3])
-        print(paste("Computation time for a single sounding:", t1, "s"))
-        expect_lt(t1, 60.0)  # changed for valgrind compilator, which might be superslow in debugging mode
+        res_default = sounding_default(pressure, altitude, temp, dpt, wd, ws,
+                                       export_profile = 0,
+                                       accuracy = 2,
+                                       interpolate_step = 1000,
+                                       meanlayer_bottom_top = c(0, 500),
+                                       storm_motion = c(999, 999))
+        res_compute = sounding_compute(pressure, altitude, temp, dpt, wd, ws,
+                                       accuracy = 2, 
+                                       interpolate_step = 1000,
+                                       meanlayer_bottom_top = c(0, 500),
+                                       storm_motion = c(999, 999))
+
+        indices_cape = grep(x = names(res_compute), "CAPE")
+        indices_cin = grep(x = names(res_compute), "CIN")
+
+        expect_equal(as.numeric(res_compute[indices_cape]), res_default[indices_cape])
+        expect_equal(as.numeric(res_compute[indices_cin]), res_default[indices_cin])
 })
+
+
+
+test_that("sounding_default should have CAPE 2k+ values for profile having CAPE=1 in MetPy", {
+  p = c(1009.57453125, 1000, 975, 950, 925, 900, 875, 850, 825, 800, 775, 750, 700, 650, 600, 550, 500, 450, 400, 
+        350, 300, 250, 225, 200, 175, 150, 125, 100, 70, 50)
+  t = c(25.92, 25.07, 23.13, 21.55, 20.54, 19.39, 18.19, 16.96, 15.84, 14.75, 13.55, 12.3, 9.39, 6.73, 3.08, 0.01,
+        -4.14, -8.98, -14.8, -22.84, -32.18, -42.92, -48.6, -53.6, -57.96, -67.31, -72.61, -76.33, -75.49, -64.64) 
+  alt = c(0, 84, 307, 534, 766, 1003, 1246, 1495, 1750, 2012, 2281, 2557, 3135, 3748, 4402, 5103, 5860, 6683, 7584, 
+          8579, 9688, 10945, 11646, 12411, 13261, 14212, 15297, 16586, 18636, 20653)
+  q = c(24.13, 21.86, 21.28, 21.13, 20.07, 18.6, 17.6, 16.7, 15.79, 14.75, 13.55, 12.21, 8.52, 3.77, -4.53, -16.51, 
+        -21.2, -23.21, -32.89, -40.98, -50.96, -59.87, -64.33, -66.62, -65.41, -75.21, -82.58, -85.87, -87.36, -86.24)
+  ws = runif(length(q))
+  wd = runif(length(q))
+
+  res_default = sounding_default(p, alt, t, q, wd, ws,
+                                 export_profile = 0,
+                                 accuracy = 2,
+                                 interpolate_step = 10,
+                                 meanlayer_bottom_top = c(0, 500),
+                                 storm_motion = c(999, 999))
+  res_compute = sounding_compute(p, alt, t, q, wd, ws,
+                                 accuracy = 2, 
+                                 interpolate_step = 1000,
+                                 meanlayer_bottom_top = c(0, 500),
+                                 storm_motion = c(999, 999))
+
+  indices_cape = grep(x = names(res_compute), "SB_CAPE$")
+  expect_equal(as.numeric(res_compute[indices_cape]), res_default[indices_cape])
+  expect_gt(res_default[indices_cape], 2000)
+
+})