trigger other projects

Dockerfile

@@ -8,6 +8,7 @@ RUN pip3 install pandas
 RUN pip3 install kaggle
 RUN pip3 install tensorflow
 RUN pip3 install sklearn
+RUN pip3 install matplotlib
 COPY ./data_dev ./
 COPY ./evaluate_network.py ./
 RUN mkdir /.kaggle

JenkinsfileEval

@@ -19,7 +19,7 @@ node {
 
         }
         stage('Clone repo') {
-                    docker.image("karopa/ium:16").inside {
+                    docker.image("karopa/ium:20").inside {
                         stage('Test') {
                             checkout([$class: 'GitSCM', branches: [[name: '*/evaluation']], doGenerateSubmoduleConfigurations: false, extensions: [], submoduleCfg: [], userRemoteConfigs: [[url: 'https://git.wmi.amu.edu.pl/s434765/ium_434765']]])
                             copyArtifacts fingerprintArtifacts: true, projectName: 's434765-create-dataset', selector: buildParameter("BUILD_DATASET")

evaluate_network.py

@@ -2,6 +2,7 @@ import pandas as pd
 import numpy as np
 from sklearn.metrics import mean_squared_error
 from tensorflow import keras
+import matplotlib.pyplot as plt
 
 model = keras.models.load_model('model')
 data = pd.read_csv("data_dev", sep=',', error_bad_lines=False,
@@ -39,3 +40,11 @@ print(error)
 
 with open("rmse.txt", "a") as file:
     file.write(str(error) + "\n")
+
+with open("rmse.txt", "r") as file:
+    lines = file.readlines()
+    plt.plot(range(len(lines)), [line[:-2] for line in lines])
+    plt.tight_layout()
+    plt.ylabel('RMSE')
+    plt.xlabel('evaluation no')
+    plt.savefig('evaluation.png')