Saving Confusion Matrix Plot PNG

eval/metrics.py

@@ -177,7 +177,7 @@ def get_confusion_matrix(y_true, y_pred):
     return confusion_matrix(y_true, y_pred, labels=const.CLASS_LABELS_LIST)
 
 
-def plot_confusion_matrix(confusion_mat, classifier_name):
+def plot_confusion_matrix(confusion_mat, classifier_name, plot_file_name):
 
     plt.figure(figsize=(8, 6))
     plt.imshow(confusion_mat, interpolation='nearest', cmap=plt.get_cmap('Blues'))
@@ -196,10 +196,10 @@ def plot_confusion_matrix(confusion_mat, classifier_name):
                  horizontalalignment="center",
                  color="white" if confusion_mat[i, j] > thresh else "black")
 
-    plt.tight_layout()
+    plt.tight_layout(1.5)
     plt.ylabel('True/Gold')
     plt.xlabel('Predicted')
-    plt.show(block=True)
+    plt.savefig(plot_file_name)
 
 
 class Result:

predict.py

@@ -3,10 +3,11 @@ import testing.intent_predictor as pred
 
 import eval.metrics as metrics
 
-y_pred, y_true = pred.load_model_and_predict_test_data("/mount/arbeitsdaten/studenten1/team-lab-nlp/mandavsi_rileyic/saved_models/experiment_4")
+model_path = '/mount/arbeitsdaten/studenten1/team-lab-nlp/mandavsi_rileyic/saved_models/experiment_4'
+y_pred, y_true = pred.load_model_and_predict_test_data(model_path)
 
 confusion_matrix = metrics.get_confusion_matrix(y_true, y_pred)
 
 print(confusion_matrix)
 
-metrics.plot_confusion_matrix(confusion_matrix, "BiLSTM Classifier + Attention with ELMo")
+metrics.plot_confusion_matrix(confusion_matrix, "BiLSTM Classifier + Attention with ELMo", model_path+'/confusion_matrix_plot.png')