plotting and eval metrics

JenkinsfileEval

@@ -0,0 +1,20 @@
+node {
+ stage('Preparation') {
+    checkout scm
+     copyArtifacts projectName: 's470618-metrics', filter: 'metrics.txt', fingerprintArtifacts: true, selector: lastSuccessful(), optional: true, target: './train-eval'
+     copyArtifacts projectName: 's470618-training', filter: '*.pt', fingerprintArtifacts: true, selector: lastSuccessful(), target: '.'
+ 
+ stage('Evaluate metrics') {
+            sh "pip install matplotlib"
+            sh "cd train-eval && ./eval.py"
+            sh "./plot_metrics.py"
+     }
+ }
+
+ stage('artifacts') {
+         echo 'saving artifacts'
+         archiveArtifacts 'metrics.txt', 'prediction.tsv', 'metrics.png'
+}
+}
+}
+

train-eval/eval.py

@@ -45,7 +45,7 @@ print ("The accuracy is", acc)
 print ("The precission score is ", prec)
 print ("The recall score is ", recall)
 
-file = open('metrics.txt', 'w')
+file = open('metrics.txt', 'a')
 file.write(str(acc)  + '\t' + str(prec) + '\t' + str(recall))
 file.close()
 

train-eval/plot_metrics.py

@@ -0,0 +1,19 @@
+#!/usr/bin/python3
+import matplotlib
+import matplotlib.pyplot as plt 
+
+data = []
+with open('metrics.txt', 'r') as metrics:
+    for line in metrics:
+        data.append(line.strip().split('\t'))
+
+
+# print(acc)
+labels = ['accuracy','precision','recall']
+builds = [x for x in range(len(data))]
+fig = plt.figure()
+ax = fig.add_subplot(1,1,1)
+for i in range(3):
+    ax.plot(builds, [data[x][i] for x in range(len(data))], label=labels[i])
+plt.legend()
+plt.savefig('metrics.png')