Merge pull request #35 from gorkang/dev

Dev
gorkang · Jul 3, 2020 · 47936b5 · 47936b5
2 parents caeac28 + 6fef637
commit 47936b5
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diff --git a/.Rbuildignore b/.Rbuildignore
@@ -17,3 +17,6 @@ cran-comments.md
 ^cran-comments\.md$
 ^CRAN-RELEASE$
 ^codecov\.yml$
+^_pkgdown\.yml$
+^docs$
+^pkgdown$
diff --git a/.gitignore b/.gitignore
@@ -9,3 +9,4 @@ inst/doc
 DEV/
 .binder/
 google-analytics.html
+docs
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: BayesianReasoning
 Type: Package
 Title: Plot Positive and Negative Predictive Values for Medical Tests
-Version: 0.3.1
-Date: 2020-06-29
+Version: 0.3.2
+Date: 2020-07-03
 Authors@R: c(person("Gorka", "Navarrete", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7678-8656")))
 Maintainer: Gorka Navarrete <[email protected]>
 Description: Functions to plot and help understand positive and negative predictive values (PPV and NPV), and their relationship with sensitivity, specificity, and prevalence. See Akobeng, A.K. (2007) <doi:10.1111/j.1651-2227.2006.00180.x> for a theoretical overview of the technical concepts and Navarrete et al. (2015) for a practical explanation about the importance of their understanding <doi:10.3389/fpsyg.2015.01327>.
@@ -14,9 +14,7 @@ Imports: dplyr,
          tidyr,
          magrittr,
          tibble,
-         ggforce,
-         shinythemes,
-         shinyjs
+         ggforce
 License: CC0
 RoxygenNote: 7.1.1
 URL: https://github.com/gorkang/BayesianReasoning
@@ -26,5 +24,6 @@ Suggests:
     testthat,
     knitr,
     rmarkdown,
-    covr
+    covr,
+    patchwork
 VignetteBuilder: knitr
diff --git a/NEWS.md b/NEWS.md
@@ -1,5 +1,16 @@
 # README
 
+### v0.3.2 Clean up, test, rinse and repeat
+
+Clean up old comments, add more tests...
+
+* 100% code coverage
+* min_possible_prevalence() is now much more efficient
+* Improvements to overlay = "line" en PPV_heatmap(), now using {ggforce} for labels
+* Changed color palette for NPV
+* Tweaked color palette for PPV
+
+
 ### v0.3.1 Testing, testing
 
 Corrected issues raised in CRAN revision
@@ -8,7 +19,7 @@ Corrected issues raised in CRAN revision
 * Do not capitalize things in the Description text
 * Added references to Description explaining main concepts
 * Replaced cat() with message()
-* Aded folder parameter to PPV_diagnostic_vs_screening() and PPV_heatmap() functions
+* Added folder parameter to PPV_diagnostic_vs_screening() and PPV_heatmap() functions
 
 Added tests
 

diff --git a/R/PPV_diagnostic_vs_screening.R b/R/PPV_diagnostic_vs_screening.R
@@ -35,13 +35,6 @@ PPV_diagnostic_vs_screening <- function(Max_FP = 10, Sensitivity = 100, prevalen
                                         # save_plot = FALSE, 
                                         folder = "") {
 
-  # PARAMETERS --------------------------------------------------------------
-  # Max_FP = 10
-  # Sensitivity = 100
-  # prevalence_screening_group = 100
-  # prevalence_diagnostic_group = 2
-  # labels_prevalence = c("Screening", "Diagnostic")
-
 
   # FIXED parameters --------------------------------------------------------
 
@@ -53,6 +46,7 @@ PPV_diagnostic_vs_screening <- function(Max_FP = 10, Sensitivity = 100, prevalen
   Min_FP = 0 #Step_size_FP #0
   FP = seq(Min_FP, Max_FP, Step_size_FP)
 
+
   # Calculate PPVs ----------------------------------------------------------
 
   Real_Prevalence_PPV = list()

diff --git a/R/PPV_heatmap.R b/R/PPV_heatmap.R
@@ -56,52 +56,45 @@ PPV_heatmap <-
 
 
   # Check dimensions -----------------------------------------------------------
-
+
+    if (Min_Prevalence > Max_Prevalence) {
+      message("[WARNING]: Min_Prevalence (", Min_Prevalence , ") is > than Max_Prevalence (", Max_Prevalence, "). [EXPECTED]: Min_Prevalence should be smaller than Max_Prevalence. [CHANGED]: Min_Prevalence = Max_Prevalence/2")
+      Min_Prevalence = Max_Prevalence/2
+    }
 
     # If the dimensions of the overlay are bigger, adjust Max_FP and Max_Prevalence
 
     if (overlay == "area") {
 
       if (overlay_position_FP > Max_FP) {
-      # if (overlay_position_FP_FN > Max_FP) {
-          message("Changing Max_FP to overlay_position_FP to fit overlay")
-        # Max_FP = overlay_position_FP_FN
-        Max_FP = overlay_position_FP 
+        message("[WARNING]: overlay_position_FP (", overlay_position_FP , ") is > than Max_FP (", Max_FP, "). [EXPECTED]: overlay_position_FP should be smaller than Max_FP [CHANGED]: Max_FP = overlay_position_FP")
+        Max_FP = overlay_position_FP
       }
 
       if (overlay_prevalence_2 > Max_Prevalence) {
-        message("Changing Max_Prevalence to overlay_prevalence_2 to fit overlay")
+        message("[WARNING]: overlay_prevalence_2 (", overlay_prevalence_2 , ") is > than Max_Prevalence (", Max_Prevalence, "). [EXPECTED]: overlay_prevalence_2 should be smaller than Max_Prevalence [CHANGED]: Max_Prevalence = overlay_prevalence_2")
         Max_Prevalence = overlay_prevalence_2 
       }
 
-      # if(overlay_position_FP_FN > (100 - Sensitivity)) {
       if(overlay_position_FN > (100 - Sensitivity)) {
+        message("[WARNING]: overlay_position_FN (", overlay_position_FN , ") is > than (100 - Sensitivity) (", (100 - Sensitivity), "). [EXPECTED]: overlay_position_FN should be smaller than (100 - Sensitivity) [CHANGED]: Sensitivity = 100 - overlay_position_FN")
         Sensitivity = 100 - overlay_position_FN
       }
 
-
       if (overlay_prevalence_1/overlay_prevalence_2 < Min_Prevalence/Max_Prevalence) {
-
-        message("Overlay impossible to fit in plot: overlay_prevalence_1/overlay_prevalence_2 < Min_Prevalence/Max_Prevalence: Changing Min_Prevalence to (overlay_prevalence_1/overlay_prevalence_2) * Max_Prevalence to fit overlay")
-
-        # Min Prevalence adjusted to fit overlay
-        Min_Prevalence = (overlay_prevalence_1/overlay_prevalence_2) * Max_Prevalence
-
+        message("[WARNING]: overlay_prevalence_1/overlay_prevalence_2 (", overlay_prevalence_1/overlay_prevalence_2 , ") is > than Min_Prevalence/Max_Prevalence (", Min_Prevalence/Max_Prevalence, "). [EXPECTED]: Prevalence for overlay should be smaller than Prevalence [CHANGED]: Changing Min_Prevalence to (overlay_prevalence_1/overlay_prevalence_2) * Max_Prevalence to fit overlay")
+        Min_Prevalence = (overlay_prevalence_1/overlay_prevalence_2) * Max_Prevalence # Min Prevalence adjusted to fit overlay
       }
 
     }
 
-
-
 
-# Check overlay prevalence ------------------------------------------------
+  # Check overlay prevalence ------------------------------------------------
 
     if (length(overlay_prevalence_1) == 1) {
       if (overlay_prevalence_1 > overlay_prevalence_2) {
-
-        message(overlay_prevalence_1, " is > than ", overlay_prevalence_2)
-        overlay_prevalence_1 = overlay_prevalence_2
-
+        message("[WARNING]: overlay_prevalence_1 (", overlay_prevalence_1 , ") is > than overlay_prevalence_2 (", overlay_prevalence_2, "). [EXPECTED]: overlay_prevalence_1 should be smaller than overlay_prevalence_2 [CHANGED]: overlay_prevalence_1 = overlay_prevalence_2/2")
+        overlay_prevalence_1 = overlay_prevalence_2/2
       }
     } else if (length(overlay_prevalence_1) > 1) {
       if (DEBUG != 0) message("> 1 overlay")
@@ -110,9 +103,6 @@ PPV_heatmap <-
 
   # SYSTEM parameters -------------------------------------------------------
 
-      #GRAPHIC Parameters *************
-
-      # modifier_text_overlay_position = (Max_Prevalence/75)
       if (overlay != "no") {
         filename_overlay = paste0("_", overlay)
       } else {
@@ -169,14 +159,14 @@ PPV_heatmap <-
 
        p = .plot_overlay_line(
           PPV_melted = PPV_melted,
+          uncertainty_prevalence = uncertainty_prevalence,
           Min_Prevalence = Min_Prevalence,
           Max_Prevalence = Max_Prevalence,
           Max_FP = Max_FP,
           Sensitivity = Sensitivity,
 
           overlay_prevalence_2 = overlay_prevalence_2,
 
-          # overlay_position_FP_FN = overlay_position_FP_FN,
           overlay_position_FP = overlay_position_FP,
           overlay_position_FN = overlay_position_FN,
 
@@ -196,6 +186,7 @@ PPV_heatmap <-
 
 
       } else if (overlay == "area") {
+
         p = .plot_overlay_area(
           PPV_melted,
           uncertainty_prevalence = uncertainty_prevalence,
@@ -204,12 +195,10 @@ PPV_heatmap <-
           Sensitivity = Sensitivity,
           Min_FP = Min_FP,
           Max_FP = Max_FP,
-          # Step_size_FP = Step_size_FP,
           overlay_labels = overlay_labels,
           overlay_prevalence_1 = overlay_prevalence_1,
           overlay_prevalence_2 = overlay_prevalence_2,
 
-          # overlay_position_FP_FN = overlay_position_FP_FN,
           overlay_position_FP = overlay_position_FP,
           overlay_position_FN = overlay_position_FN,
 
@@ -228,15 +217,14 @@ PPV_heatmap <-
         )
 
       } else {
-        # if (overlay == "no") {
-
+
           p = .plot_creation(
             PPV_melted = PPV_melted,
             Min_Prevalence = Min_Prevalence,
             Sensitivity = Sensitivity,
             Min_FP = Min_FP,
             Max_FP = Max_FP,
-            # Step_size_FP = Step_size_FP,
+
             decimals_x = decimals_x,
             decimals_y = decimals_y,
 
@@ -250,8 +238,7 @@ PPV_heatmap <-
             PPV_NPV = PPV_NPV
 
           )
-
-
+
       }
 
 
@@ -260,7 +247,6 @@ PPV_heatmap <-
       if (folder != "") {
 
         print(p)
-        # plot_name = here::here(paste0("outputs/PPV_heatmap/", PPV_NPV, "_", Min_Prevalence, "_", Max_Prevalence, "_", Sensitivity, "_", Max_FP, filename_overlay, "_", Language, ".png"))
         plot_name = paste0(folder, "/", PPV_NPV, "_", Min_Prevalence, "_", Max_Prevalence, "_", Sensitivity, "_", Max_FP, filename_overlay, "_", Language, ".png")
         ggsave(plot_name, p, dpi = 300, width = 14, height = 10)
         message("\n Plot created in: ", plot_name, "\n")