Test

NAMESPACE

@@ -18,7 +18,7 @@ export(risk_alcohol)
 export(risk_colorectal_screening)
 export(risk_diet_exercise)
 export(risk_smoking)
-export(risk_vaccine)
+export(risk_vaccines)
 export(risk_whealth)
 importFrom(cdlTools,fips)
 importFrom(cli,cli_abort)

R/handle-vaccine.R

@@ -25,7 +25,7 @@ handle_vaccine <- function(vaccine) {
     # "percent who received 3+ doses of hpv vaccine, ages 13-17" = "v71"
 
     "percent with up to date hpv vaccination coverage, ages 13-15" = "v281",
-    "percent with up to date hpv vaccination coverage, ages 13-15" = "v282"
+    "percent with up to date hpv vaccination coverage, ages 13-17" = "v282"
   )
 
   vaccine_code <- vaccine_mapping[vaccine]

R/risk-smoking.R

@@ -99,7 +99,7 @@ risk_smoking <- function(smoking, race=NULL, sex=NULL, datatype=NULL, area=NULL)
 
   #smoking group 4
   if (smoking %in% smoking_group4 && ((is.null(sex) || is.null(area) || is.null(datatype)) || !is.null(race))) {
-    cli_abort("For this smoking type, Sex, Datatype, and Area must not be NULL AND Race and Datatype must be NULL")
+    cli_abort("For this smoking type, Sex, Datatype, and Area must not be NULL AND Race must be NULL")
   } else if (smoking %in% smoking_group4 && datatype == "direct estimates") {
     cli_abort("For this smoking type, Datatype must be county level modeled estimates")
   }
@@ -111,6 +111,7 @@ risk_smoking <- function(smoking, race=NULL, sex=NULL, datatype=NULL, area=NULL)
     cli_abort("For this smoking type, Datatype must be direct estimates")
   }
 
+  #smoking group 6
   if (smoking %in% smoking_group6 && (is.null(race) || is.null(sex))) {
     cli_abort("For this smoking group, Race and Sex must not be NULL")
   } else if (smoking %in% smoking_group6 && (!is.null(race) && !is.null(sex)) && race == "all races (includes hispanic)") {
@@ -161,7 +162,7 @@ risk_smoking <- function(smoking, race=NULL, sex=NULL, datatype=NULL, area=NULL)
 
   if (smoking %in% smoking_group1) {
     resp %>% 
-      setNames(c("State", "FIPS", "Percent", "Number_of_Respondents")) 
+      setNames(c("State", "FIPS", "Percent")) 
   } else if ((smoking %in% c(smoking_group2, smoking_group3, smoking_group4, smoking_group5, smoking_group6))
               && (datatype=="direct estimates")) {
     resp %>% 

R/risk-vaccines.R

@@ -2,9 +2,8 @@
 #' 
 #' This function returns a data frame from Vaccines in State Cancer Profiles
 #'
-#' @param vaccine Either "mammogram in past 2 years, ages 50-74", "mammogram in past 2 years, ages 40+", 
-#'                       "pap smear in past 3 years, no hysterectomy, ages 21-65", 
-#'                       "pap smear in past 3 years, no hysterectomy, ages 18+"
+#' @param vaccine Either "percent with up to date hpv vaccination coverage, ages 13-15",
+#'                       "percent with up to date hpv vaccination coverage, ages 13-17"
 #' @param sex Either "both sexes", "males", "females"
 #' 
 #' @returns A data frame with the following columns "State", "FIPS", "Percent", "Lower 95% CI", "Upper 95% CI", "Number of Respondents"
@@ -13,11 +12,10 @@
 #' 
 #' @examples
 #' \dontrun{
-#' risk_vaccine("percent with up to date hpv vaccination coverage, ages 13-15", "both sexes")
-#' risk_vaccine("percent with up to date hpv vaccination coverage, ages 13-15", "both sexes")
-#' risk_vaccine("percent with up to date hpv vaccination coverage, ages 13-15", "females")
+#' risk_vaccines("percent with up to date hpv vaccination coverage, ages 13-15", "both sexes")
+#' risk_vaccines("percent with up to date hpv vaccination coverage, ages 13-17", "females")
 #' }
-risk_vaccine <- function(vaccine, sex) {
+risk_vaccines <- function(vaccine, sex) {
 
   req <- create_request("risk")
 
@@ -42,10 +40,6 @@ risk_vaccine <- function(vaccine, sex) {
                    "percent who received 3+ doses of HPV vaccine, ages 13-15"
                    )
 
-  vaccine_type2 = c("percent who received 2+ doses of HPV vaccine, ages 13-17",
-                   "percent who received 3+ doses of HPV vaccine, ages 13-17"
-  )
-
   if (vaccine %in% vaccine_type1) {
     resp %>% 
       setNames(c("State", "FIPS", "Met_Objective_of_80.0%?", "Percent", "Lower_95%_CI", "Upper_95%_CI", "Number_of_Respondents"))

R/risk-womens-health.R

@@ -3,7 +3,7 @@
 #' This function returns a data frame from Women's Health in State Cancer Profiles
 #'
 #' @param whealth Either "mammogram in past 2 years, ages 50-74", "mammogram in past 2 years, ages 40+", 
-#'                       "pap smear in past 3 years, no hysterectomy, ages 21-65", "pap smear in past 3 years, no hysterectomy, ages 18+"
+#'                       "pap smear in past 3 years, no hysterectomy, ages 21-65"
 #' @param race One of the following values: "all races (includes hispanic)", "white (non-hispanic)", 
 #'                                          "black (non-hispanic)", "amer. indian / ak native (non-hispanic)", 
 #'                                          "asian / pacific islander (non-hispanic)","hispanic (any race)"
@@ -65,7 +65,7 @@ risk_whealth <- function(whealth, race, datatype="direct estimates", area=NULL)
   resp <- process_screening(resp)
 
   if (datatype == "county level modeled estimates") {
-    if(whealth == "pap smear in past 3 years, no hysterectomy, ages 18+") {
+    if(whealth == "pap smear in past 3 years, no hysterectomy, ages 21-65") {
       resp %>% 
         setNames(c("State", "FIPS", "Percent", "Lower_95%_CI", "Upper_95%_CI", "Number_of_Respondents"))
     } else {

tests/testthat/test-risk-smoking.R

@@ -1,3 +1,136 @@
-test_that("multiplication works", {
-  expect_equal(2 * 2, 4)
+#' Test risk-smoking
+#' 
+#' This testthat file test the risk-smoking function
+#' 
+#tests class and typeof output
+test_that("Output data type is correct", {
+  output <- risk_smoking("smoking laws (any)")
+
+  expect_true(inherits(output, "data.frame"))
 })
+
+#Ensures that variables are present and working on SCP
+
+#group1
+smoking_group1_options <- c("smoking laws (any)",
+                     "smoking laws (bars)",
+                     "smoking laws (restaurants)",
+                     "smoking laws (workplace)",
+                     "smoking laws (workplace; restaurant; & bar)")
+
+for (option in smoking_group1_options) {
+  test_that("smoking group1 returns non-empty data frame", {
+    result <- risk_smoking(option)
+    expect_true(is.data.frame(result))
+  })
+}
+
+#group2
+smoking_group2_options <- c("smokers (stopped for 1 day or longer)",
+                         "smoking not allowed at work (all people)",
+                         "smoking not allowed in home (all people)")
+
+for (option in smoking_group2_options) {
+  test_that("smoking group2 returns non-empty data frame", {
+    result <- risk_smoking(option, sex="both sexes", datatype="direct estimates")
+    expect_true(is.data.frame(result))
+  })
+}
+
+#group3
+smoking_group3_options <- c("smoking not allowed at work (current smokers)",
+                            "smoking not allowed at work (former/never smokers)",
+                            "smoking not allowed in home (current smokers)",
+                            "smoking not allowed in home (former/never smokers)")
+
+for (option in smoking_group3_options) {
+  test_that("smoking group3 returns non-empty data frame", {
+    result <- risk_smoking(option, sex="both sexes", datatype="direct estimates")
+    expect_true(is.data.frame(result))
+  })
+}
+
+#group4
+smoking_group4_options <- c("former smoker; ages 18+",
+                            "former smoker, quit 1 year+; ages 18+")
+
+for (option in smoking_group4_options) {
+  test_that("smoking group4 returns non-empty data frame", {
+    result <- risk_smoking(option, sex="both sexes", 
+                           datatype="county level modeled estimates", area="ca")
+    expect_true(is.data.frame(result))
+  })
+}
+
+#group5
+smoking_group5_options <- c("smokers (ever); ages 18+",
+                            "e-cigarette use; ages 18+")
+
+for (option in smoking_group5_options) {
+  test_that("smoking group5 returns non-empty data frame", {
+    result <- risk_smoking(option, race="hispanic (any race)", 
+                           sex="both sexes", datatype="direct estimates")
+    expect_true(is.data.frame(result))
+  })
+}
+
+#group6
+test_that("smoking group6 returns non-empty data frame", {
+  result <- risk_smoking("smokers (current); ages 18+", race="hispanic (any race)", 
+                         sex="both sexes", datatype="direct estimates")
+  expect_true(is.data.frame(result))
+})
+
+
+#risk-smoking must have 5 columns
+test_that("risk-smoking has correct number of columns", {
+  df1 <- risk_smoking("smoking laws (any)")
+  df2 <- risk_smoking("smokers (stopped for 1 day or longer)", sex="both sexes", 
+                      datatype="county level modeled estimates", area="wa")
+  df3 <- risk_smoking("smoking not allowed at work (current smokers)", sex="both sexes", 
+                      datatype="direct estimates")
+  expected_columns1 <- 3
+  expected_columns2 <- 5
+  expected_columns3 <- 6
+  expect_equal(ncol(df1), expected_columns1)
+  expect_equal(ncol(df2), expected_columns2)
+  expect_equal(ncol(df3), expected_columns3)
+})
+
+#test error handling
+test_that("risk-smoking handles invalid smoking parameters", {
+  expect_error(
+    risk_smoking("smoking laws (any)", sex="both sexes"),
+    "For this smoking type, Race, Sex, Datatype, and Area must ALL be NULL"
+  )
+  expect_error(
+    risk_smoking("smokers (stopped for 1 day or longer)", sex="both sexes", 
+                 datatype="county level modeled estimates"),
+    "For county level modeled estimates on this smoking type, area must NOT be null"
+  )
+  expect_error(
+    risk_smoking("smoking not allowed at work (current smokers)", 
+                 race="all races (includes hispanic)", sex="both sexes", 
+                 datatype="direct estimates"),
+    "For all sexes in this smoking type, race and area should be NULL"
+  )
+  expect_error(
+    risk_smoking("former smoker; ages 18+", sex="both sexes", 
+                 datatype="county level modeled estimates"),
+    "For this smoking type, Sex, Datatype, and Area must not be NULL AND Race must be NULL"
+  )
+  expect_error(
+    risk_smoking("smokers (ever); ages 18+", race="hispanic (any race)", sex="both sexes"),
+    "For this smoking type, Race, Sex, and Datatype must not be NULL AND Datatype and Area must be NULL"
+  )
+  expect_error(
+    risk_smoking("smokers (current); ages 18+", race="all races (includes hispanic)", 
+                 sex="both sexes", area="wa"),
+    "For all races for this smoking type, Datatype must not be NULL"
+  )
+})
+
+#parameter
+test_that("risk-smoking has correct parameters", {
+  expect_error(risk_smoking())
+})

tests/testthat/test-risk-vaccines.R

@@ -1,3 +1,36 @@
-test_that("multiplication works", {
-  expect_equal(2 * 2, 4)
+#' Test risk-vaccines
+#'
+#' This testthat file test the risk-vaccines function
+#'
+# tests class and typeof output
+test_that("Output data type is correct", {
+  output <- risk_vaccines("percent with up to date hpv vaccination coverage, ages 13-15",
+                         "both sexes")
+
+  expect_true(inherits(output, "data.frame"))
 })
+
+#Ensures that variables are present and working on SCP
+vaccine_options <- c("percent with up to date hpv vaccination coverage, ages 13-15",
+                     "percent with up to date hpv vaccination coverage, ages 13-17")
+
+for (option in vaccine_options) {
+  test_that("risk_womens_health returns non-empty data frame", {
+    result <- risk_vaccines(option, "both sexes")
+    expect_true(is.data.frame(result))
+  })
+}
+
+#risk-vaccines must have 5 columns
+test_that("risk-vaccines has correct number of columns", {
+  df <- risk_vaccines("percent with up to date hpv vaccination coverage, ages 13-15",
+                      "both sexes")
+  expected_columns <- 6
+  expect_equal(ncol(df), expected_columns)
+
+})
+
+#parameter
+test_that("risk-vaccines has correct parameters", {
+  expect_error(risk_vaccines())
+})