test parameters

.gitignore

@@ -13,3 +13,4 @@ venv
 model_resutls.txt
 model
 metrics.txt
+metrics.png

Jenkinsfile

@@ -22,6 +22,7 @@ pipeline {
                             copyArtifacts filter: '*', projectName: 's444463-create-dataset'
                             sh 'python3 ./deepl.py $EPOCH'
                             archiveArtifacts artifacts: "model"
+                            build job: "s444380-evaluation/master"
                 }
             }
         }

evaluation.Jenkinsfile

@@ -3,12 +3,12 @@ pipeline {
 		dockerfile true
 	}
     parameters {
-        string (
-            defaultValue: '10',
-            description: 'Epochs number',
-            name: 'EPOCH',
-            trim: false
-        )
+	    gitParameter branchFilter: 'origin/(.*)', defaultValue: 'master', name: 'BRANCH', type: 'PT_BRANCH'
+		buildSelector(
+			defaultSelector: lastSuccessful(),
+			description: 'From which build copy content',
+			name: 'BUILD_SELECTOR'
+		)
     }
     stages {
         stage('checkout: Check out from version control') {
@@ -18,11 +18,11 @@ pipeline {
         }
         stage('bash script') {
             steps {
-                withEnv(["EPOCH=${params.EPOCH}"]) {
-                            copyArtifacts filter: '*', projectName: 's444463-training/master'
+                withEnv(["BRANCH=${params.BRANCH}"]) {
+                            copyArtifacts filter: '*', projectName: 's444463-training/$BRANCH'
                             copyArtifacts filter: '*', projectName: 's444463-create-dataset'
                             sh 'python3 ./evaluation.py'
-                            archiveArtifacts artifacts: "metrics.txt"
+                            archiveArtifacts artifacts: "metrics.txt" "metrics.png"
                 }
             }
         }

evaluation.py

@@ -3,6 +3,8 @@ import pandas as pd
 import numpy as np
 from sklearn.feature_extraction.text import TfidfVectorizer
 import scipy
+import matplotlib.pyplot as plt
+import re
 
 if __name__ == "__main__":
     data = pd.read_csv('fake_job_postings.csv', engine='python')
@@ -74,6 +76,18 @@ if __name__ == "__main__":
     f.write(f"Precision = {precision}\n")
     f.write(f"Recall = {recall}\n")
 
+
+    f_read = open("metrics.txt", "r")
+    content = re.findall('F-SCORE = [0-9.]+', f_read.read())
+    fscores = []
+    for c in content:
+        r = re.findall("\d+\.\d+", c)
+        fscores.append(r[0])
+
+    plt.plot(fscores) 
+    plt.ylabel('F score')
+    plt.xticks(np.arange(0, len(fscores)+1, 5))
+    plt.savefig('metrics.png')
     # f.write(f"TP descriptions:")
     # for i in TP:
     #     f.write(i+'\n')