[BUG-FIX] plot()-method for ROC() and prROC() 🔨

* The plots are now correctly displaying lines when `panels = FALSE`
* NEWS.md updated accordingly.

NEWS.Rmd

@@ -49,6 +49,50 @@ SLmetrics::accuracy(
 )
 ```
 
+## Bug-fixes
+
+* The `plot.prROC()`- and `plot.ROC()`-functions now adds a line to the plot when `panels = FALSE`. See Issue https://github.com/serkor1/SLmetrics/issues/9.
+
+```{r}
+# 1) define actual
+# classes
+actual <- factor(
+  sample(letters[1:2], size = 100, replace = TRUE)
+)
+
+# 2) define response
+# probabilities
+response <- runif(100)
+
+# 3) calculate
+# ROC and prROC
+
+# 3.1) ROC
+roc <- SLmetrics::ROC(
+    actual,
+    response
+)
+
+# 3.2) prROC
+prroc <- SLmetrics::prROC(
+    actual,
+    response
+)
+
+# 4) plot with panels
+# FALSE
+par(mfrow = c(1,2))
+plot(
+  roc,
+  panels = FALSE
+)
+
+plot(
+    prroc,
+    panels = FALSE
+)
+```
+
 
 
 # Version 0.1-0

NEWS.md

@@ -25,7 +25,7 @@
 
 ``` r
 # 1) define factors
-actual    <- factor(c("yes", "no"))
+actual    <- factor(c("no", "yes"))
 predicted <- factor(c(NA, "no"))
 
 # 2) accuracy with na.rm = TRUE
@@ -36,7 +36,7 @@ SLmetrics::accuracy(
 )
 ```
 
-    #> [1] 1
+    #> [1] 0
 
 ``` r
 # 2) accuracy with na.rm = FALSE
@@ -49,6 +49,60 @@ SLmetrics::accuracy(
 
     #> [1] NaN
 
+## Bug-fixes
+
+  - The `plot.prROC()`- and `plot.ROC()`-functions now adds a line to
+    the plot when `panels = FALSE`. See Issue
+    <https://github.com/serkor1/SLmetrics/issues/9>.
+
+<!-- end list -->
+
+``` r
+# 1) define actual
+# classes
+actual <- factor(
+  sample(letters[1:2], size = 100, replace = TRUE)
+)
+
+# 2) define response
+# probabilities
+response <- runif(100)
+
+# 3) calculate
+# ROC and prROC
+
+# 3.1) ROC
+roc <- SLmetrics::ROC(
+    actual,
+    response
+)
+
+# 3.2) prROC
+prroc <- SLmetrics::prROC(
+    actual,
+    response
+)
+
+# 4) plot with panels
+# FALSE
+par(mfrow = c(1,2))
+plot(
+  roc,
+  panels = FALSE
+)
+```
+
+![](NEWS_files/figure-gfm/unnamed-chunk-2-1.png)<!-- -->
+
+``` r
+plot(
+    prroc,
+    panels = FALSE
+)
+```
+
+![](NEWS_files/figure-gfm/unnamed-chunk-2-2.png)<!-- -->
+
 # Version 0.1-0
 
 ## General
@@ -71,7 +125,7 @@ print(
 )
 ```
 
-    #>  [1] b a b b a c b c c a
+    #>  [1] a a a b c a b c c a
     #> Levels: a b c
 
 ``` r
@@ -83,7 +137,7 @@ print(
 )
 ```
 
-    #>  [1] c c a b a b c c a c
+    #>  [1] c c b b a a b b c b
     #> Levels: a b c
 
 ``` r
@@ -101,16 +155,16 @@ summary(
     #> Confusion Matrix (3 x 3) 
     #> ================================================================================
     #>   a b c
-    #> a 1 0 2
-    #> b 1 1 2
+    #> a 1 2 2
+    #> b 0 2 0
     #> c 1 1 1
     #> ================================================================================
     #> Overall Statistics (micro average)
-    #>  - Accuracy:          0.30
-    #>  - Balanced Accuracy: 0.31
-    #>  - Sensitivity:       0.30
-    #>  - Specificity:       0.65
-    #>  - Precision:         0.30
+    #>  - Accuracy:          0.40
+    #>  - Balanced Accuracy: 0.51
+    #>  - Sensitivity:       0.40
+    #>  - Specificity:       0.70
+    #>  - Precision:         0.40
 
 ``` r
 # 2) calculate false positive
@@ -121,7 +175,7 @@ SLmetrics::fpr(
 ```
 
     #>         a         b         c 
-    #> 0.2857143 0.1666667 0.5714286
+    #> 0.2000000 0.3750000 0.2857143
 
 ### Supervised regression metrics
 
@@ -142,4 +196,4 @@ SLmetrics::huberloss(
 )
 ```
 
-    #> [1] 0.394088
+    #> [1] 0.4757045

R/S3_PrecisionRecallCurve.R

@@ -121,7 +121,7 @@ plot.prROC <- function(
   # All common options for the
   # plot goes her
   pformula <- precision ~ recall
-  groups   <-unique(x$label)
+  groups   <- x$label
   xlab     <- "Recall"
   ylab     <- "Precision"
   main     <- "Precision-Recall Curve"
@@ -141,12 +141,13 @@ plot.prROC <- function(
   }
 
   roc_plot(
-    formula = pformula,
-    groups  = groups,
-    xlab    = xlab,
-    ylab    = ylab,
-    main    = main,
-    DT      = x,
+    formula  = pformula,
+    groups   = groups,
+    xlab     = xlab,
+    ylab     = ylab,
+    main     = main,
+    DT       = x,
+    add_poly = panels,
     ...  
   )
 

R/S3_RecieverOperatorCharacteristics.R

@@ -129,7 +129,7 @@ plot.ROC <- function(
   # All common options for the
   # plot goes her
   pformula <- tpr ~ fpr
-  groups   <- unique(x$label)
+  groups   <- x$label
   xlab     <- "False Positive Rate (FPR)"
   ylab     <- "True Positive Rate (TPR)"
   main     <- "Reciever Operator Characteristics"
@@ -150,12 +150,13 @@ plot.ROC <- function(
 
 
   roc_plot(
-    formula = pformula,
-    groups  = groups,
-    xlab    = xlab,
-    ylab    = ylab,
-    main    = main,
-    DT      = x,
+    formula  = pformula,
+    groups   = groups,
+    xlab     = xlab,
+    ylab     = ylab,
+    main     = main,
+    DT       = x,
+    add_poly = panels,
     ...  
   )
 

R/utils.R

@@ -28,6 +28,7 @@ roc_plot <- function(
   xlab = NULL,
   ylab = NULL,
   main = NULL,
+  add_poly = FALSE,
   ...) {
 
 
@@ -42,25 +43,30 @@ roc_plot <- function(
     lwd      = 2,
     auto.key = list(
       space = "bottom",
-      columns = length(unique(DT$label))
+      columns = length(unique(DT$label)),
+      between.columns = 1
     ),
     xlim = c(0, 1),
     ylim = c(0, 1),
     panel = function(x, y, ...) {
 
-      # 1) vertices for the polygon
-      poly_x <- c(0, x, 1)
-      poly_y <- c(0, y, 0)
-
-      # 1.1) plot the polygon
-      lattice::panel.polygon(
-        poly_x,
-        poly_y,
-        col = grDevices::adjustcolor(
-        col = "lightblue",
-        alpha.f = 0.4),
-        border = NA
-      )
+      if (add_poly) {
+
+        # 1) vertices for the polygon
+        poly_x <- c(0, x, 1)
+        poly_y <- c(0, y, 0)
+
+        # 1.1) plot the polygon
+        lattice::panel.polygon(
+          poly_x,
+          poly_y,
+          col = grDevices::adjustcolor(
+          col = "lightblue",
+          alpha.f = 0.4),
+          border = NA
+        )
+
+      }
 
       # 2) xyplot
       lattice::panel.xyplot(