add plot and new jenkinsfile

Jenkinsfile_evaluation

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+pipeline {
+   agent  any
+   parameters{
+         string(
+            defaultValue: 'master',
+            description: 'BRANCH',
+            name: 'BRANCH',
+            trim: false
+         )
+    }
+    stages {
+      stage('Clear_Before') {
+         steps {
+            sh 'rm -rf *'
+         }
+      }
+      stage('Clone') {
+         steps {
+            sh 'git clone https://git.wmi.amu.edu.pl/s444439/ium_z444439'
+         }
+      }
+      stage('copy_artifacts_from_training') {
+         steps {
+            copyArtifacts(projectName: 'z-s444439-training/master', fingerprintArtifacts: true)
+         }
+      }
+      stage('copy_artifacts_from_evaluation') {
+         steps {
+            copyArtifacts(projectName: 'z-s444439-evaluation/master', fingerprintArtifacts: true, optional: true)
+         }
+      }
+      stage('copy_artifacts_test') {
+         steps {
+            copyArtifacts(projectName: 'z-s444439-create-dataset', filter: 'X_test.csv,Y_test.csv', fingerprintArtifacts: true)
+         }
+      }
+      stage('Docker') {
+         agent {
+            dockerfile {
+               filename 'Dockerfile'
+               dir      'ium_z444439'
+               reuseNode true
+            }
+         }
+         steps {
+            sh 'ls -a'
+            sh 'python ./ium_z444439/prediction.py'
+            sh 'python ./ium_z444439/plot.py'
+            archiveArtifacts 'prediction.csv'
+            archiveArtifacts 'metrics.csv'
+            archiveArtifacts 'metrics.png'
+         }
+      }
+
+
+      stage('clear_after') {
+         steps {
+            sh 'rm -rf *'
+         }
+      }
+   }
+}

plot.py

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+import pandas as pd
+import matplotlib.pyplot as plt
+
+metrics = pd.read_csv('./metrics.csv')
+
+builds = metrics[metrics.columns[0]]
+accuracy = metrics[metrics.columns[1]]
+
+plt.plot(builds, accuracy)
+plt.savefig('metrics_.png')