update vignettes' images

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: metrica
 Title: Prediction Performance Metrics
-Version: 2.0.5
+Version: 2.0.4
 Date: 2024-03-23
 Authors@R: c(
     person("Adrian A.", "Correndo", email = "correndo@ksu.edu", role = c("cre", "cph"), comment = c(ORCID = "0000-0002-4172-289X")),

NEWS.md

@@ -1,27 +1,22 @@
-# metrica 2.0.5
+# metrica 2.0.4
 This version:
-1) adds a new classification metric called P4 (https://en.wikipedia.org/wiki/P4-metric). https://github.com/adriancorrendo/metrica/issues/36
+1) fixes an issue found for Debian for Importing APSIM NewGeneration files that violated CRAN Policy's.
+
+2) adds a new classification metric called P4, following Sitarz, M. (2023) doi:10.54364/AAIML.2023.1161. 
+https://github.com/adriancorrendo/metrica/issues/36
 Special thanks to Davide Chicco for suggesting this metric.
 
-2) fixes an error in the invF05 formula from the adjusted F-score metric (agf):
+3) fixes an error in the invF05 formula from the adjusted F-score metric (agf):
   - InvF0.5=(5/4) * ((npv * spec)/( (0.5^2*npv) +spec ))
 https://github.com/adriancorrendo/metrica/issues/37
 Special thanks to Gilles Koumou for pointing out the error.
 
-3) adds a new plot argument, shape_fill, indicating the shape fill for the data points on the 'scatter_plot' and 'bland_altman_plot' functions.
+4) adds a new plot argument, shape_fill, indicating the shape fill for the data points on the 'scatter_plot' and 'bland_altman_plot' functions.
 
-######################################################################################################
+#####################################################################################################
 
 - PREVIOUS VERSIONS
 
-# metrica 2.0.4
-This version fixes an issue found for Debian for Importing APSIM NewGeneration files that violated CRAN Policy's.
-
-Change details:
-
-1) Adding the P4-metric to the classification metrics group following Sitarz, M. (2023) doi:10.54364/AAIML.2023.1161
-
-
 # metrica 2.0.3
 This version fixes an issue found for Debian for Importing APSIM NewGeneration files that violated CRAN Policy's.
 

README.Rmd

@@ -194,7 +194,7 @@ example.data <- barley %>%  # or 'wheat', 'sorghum', or 'chickpea'
 
 ### 3.1.1. Plot functions
 ### 3.1.1.1. Create a customizable scatter plot with PO orientation
-```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=300}
+```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=90}
 
 barley.scat.plot <- 
   metrica::scatter_plot(data = example.data, 
@@ -223,7 +223,7 @@ barley.scat.plot
 ```
 
 ### 3.1.1.2. Create tiles plot with OP orientation
-```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=300}
+```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=90}
 barley.tiles.plot <- 
   tiles_plot(data = example.data, 
                       obs = measured, 
@@ -236,7 +236,7 @@ barley.tiles.plot
 ```
 
 ### 3.1.1.3. Create a density plot with OP orientation
-```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=300}
+```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=90}
 barley.density.plot <-
 metrica::density_plot(data = example.data, 
                       obs = measured, pred = simulated,
@@ -249,7 +249,7 @@ barley.density.plot
 ```
 
 ### 3.1.1.4. Create a Bland-Altman plot
-```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=300}
+```{r warning=FALSE, message=FALSE, fig.height=4, fig.width=5, dpi=90}
 barley.ba.plot <- metrica::bland_altman_plot(data = example.data,
                                              obs = measured, pred = simulated)
 
@@ -335,7 +335,7 @@ head(non_nested_summary)
 ```
 
 ### 3.1.4. Print metrics in a plot
-```{r warning=F, message=F, fig.height=5, fig.width=7, dpi=300}
+```{r warning=F, message=F, fig.height=5, fig.width=7, dpi=90}
 df <- metrica::wheat
 
 # Create list of selected metrics
@@ -375,7 +375,7 @@ multinomial_case <- data.frame(labels = sample(c("Red","Green", "Blue"), 100, re
 ### 3.1.1. Confusion Matrix <br/>
 
 ### 3.1.1.1. Binary
-```{r warning=FALSE, message=FALSE, fig.height=6, fig.width=7, dpi=300}
+```{r warning=FALSE, message=FALSE, fig.height=6, fig.width=7, dpi=90}
 # a. Print
 binomial_case %>% confusion_matrix(obs = labels, pred = predictions, 
                                             plot = FALSE, colors = c(low="#f9dbbd" , high="#735d78"), 
@@ -388,7 +388,7 @@ binomial_case %>% confusion_matrix(obs = labels, pred = predictions,
 ```
 
 ### 3.1.1.2. Multiclass
-```{r warning=FALSE, message=FALSE, fig.height=6, fig.width=7, dpi=300}
+```{r warning=FALSE, message=FALSE, fig.height=6, fig.width=7, dpi=90}
 # a. Print
 multinomial_case %>% confusion_matrix(obs = labels, 
                                       pred = predictions,