barplot instead?

app.py

@@ -97,6 +97,27 @@ def plot_emotion_heatmap(heatmap_data):
     plt.tight_layout()
     return fig
 
+
+def plot_emotion_barplot(heatmap_data):
+    most_probable_emotions = heatmap_data.idxmax(axis=1)
+    emotion_counts = most_probable_emotions.value_counts()
+
+    # Normalize to get relative frequencies
+    emotion_frequencies = (emotion_counts / emotion_counts.sum()).sort_values(ascending=False)
+
+    fig, ax = plt.subplots(figsize=(8, 6))
+    sns.barplot(x=emotion_frequencies.values, y=emotion_frequencies.index, palette="coolwarm", ax=ax)
+
+    ax.set_title("Relative Frequencies of Most Probable Emotions")
+    ax.set_xlabel("Relative Frequency")
+    ax.set_ylabel("Emotions")
+
+    for i, value in enumerate(emotion_frequencies.values):
+        ax.text(value + 0.01, i, f"{value:.2f}", va='center')
+
+    plt.tight_layout()
+    return fig
+
 def predict_wrapper(text, language):
     model_id = build_huggingface_path(language)
     tokenizer_id = "xlm-roberta-large"
@@ -116,7 +137,7 @@ def predict_wrapper(text, language):
     print(results)
     print(results_heatmap)
 
-    figure = plot_emotion_heatmap(prepare_heatmap_data(results_heatmap))
+    figure = plot_emotion_barplot(prepare_heatmap_data(results_heatmap))
     output_info = f'Prediction was made using the <a href="https://huggingface.co/{model_id}">{model_id}</a> model.'
     return results, figure, output_info