Updated ml plot

examples/ml_kmeans_plot/main.v

@@ -30,5 +30,5 @@ fn main() {
 	model.train(epochs: 6)
 
 	// Plot the results using the new plot method
-	model.plot()!
+	model.get_plotter().show()!
 }

examples/ml_knn_plot/main.v

@@ -42,5 +42,5 @@ fn main() {
 	println('Prediction: ${prediction}')
 
 	// Plot the KNN model
-	knn.plot()!
+	knn.get_plotter().show()!
 }

examples/ml_linreg_plot/main.v

@@ -30,5 +30,5 @@ fn main() {
 
 	reg.train()
 
-	reg.plot()!
+	reg.get_plotter().show()!
 }

ml/kmeans.v

@@ -149,8 +149,8 @@ pub fn (o &Kmeans) str() string {
 	return res.join('\n')
 }
 
-// plot method for visualizing the clustering
-pub fn (o &Kmeans) plot() ! {
+// get_plotter returns a plot.Plot struct for plotting
+pub fn (o &Kmeans) get_plotter() &plot.Plot {
 	mut plt := plot.Plot.new()
 	plt.layout(
 		title: 'K-means Clustering'
@@ -194,5 +194,5 @@ pub fn (o &Kmeans) plot() ! {
 		}
 	)
 
-	plt.show()!
+	return plt
 }

ml/knn.v

@@ -204,8 +204,9 @@ pub fn (o &KNN) str() string {
 	return res.join('\n')
 }
 
-// plot method for visualizing the KNN model
-pub fn (o &KNN) plot() ! {
+// get_plotter returns a plot.Plot struct with the data needed to plot
+// the KNN model.
+pub fn (o &KNN) get_plotter() &plot.Plot {
 	mut plt := plot.Plot.new()
 	plt.layout(
 		title: 'K-Nearest Neighbors'
@@ -237,5 +238,5 @@ pub fn (o &KNN) plot() ! {
 		)
 	}
 
-	plt.show()!
+	return plt
 }

ml/linreg.v

@@ -150,8 +150,8 @@ pub fn (o &LinReg) str() string {
 	return res.join('\n')
 }
 
-// plot plots the data and the linear regression model
-pub fn (o &LinReg) plot() ! {
+// get_plotter returns a plot.Plot struct for plotting the data and the linear regression model
+pub fn (o &LinReg) get_plotter() &plot.Plot {
 	// Get the minimum and maximum values of the features
 	min_x := o.stat.min_x[0]
 	max_x := o.stat.max_x[0]
@@ -167,28 +167,18 @@ pub fn (o &LinReg) plot() ! {
 	plt.layout(
 		title: 'Linear Regression Example'
 	)
-
 	plt.scatter(
 		name: 'dataset'
 		x: o.data.x.get_col(0)
 		y: o.data.y
 		mode: 'markers'
-		colorscale: 'smoker'
-		marker: plot.Marker{
-			size: []f64{len: o.data.y.len, init: 10.0}
-		}
 	)
-
 	plt.scatter(
-		name: 'linear regression'
+		name: 'prediction'
 		x: x_values
 		y: y_values
 		mode: 'lines'
-		colorscale: 'smoker'
-		line: plot.Line{
-			color: 'red'
-		}
 	)
 
-	plt.show()!
+	return plt
 }

plot/plot.v

@@ -10,8 +10,8 @@ pub mut:
 	layout Layout
 }
 
-pub fn Plot.new() Plot {
-	return Plot{}
+pub fn Plot.new() &Plot {
+	return &Plot{}
 }
 
 // add_trace adds a trace to the plot