diff --git a/.idea/.name b/.idea/.name
index e347a86c433b2ae0cc8e620d280a897a7d5ff770..c27efae63966199781b1f41c90e4c3b8eb81523c 100644
--- a/.idea/.name
+++ b/.idea/.name
@@ -1 +1 @@
-characterizationUseCase.py
\ No newline at end of file
+periodograms.py
\ No newline at end of file
diff --git a/hpc_case/periodograms.py b/hpc_case/periodograms.py
index 06e94cc27d6e1a465dd873873008a83a960c24dd..18ebb9497bd0c2c8c1baaeade8556ca4d376627b 100644
--- a/hpc_case/periodograms.py
+++ b/hpc_case/periodograms.py
@@ -20,7 +20,7 @@ def filterTime(series, filterTimeInSec):
     return seriesFiltered
 
 def differentiateSeries(series): # Differentiating a non-stationary time series with no trend
-    print("Differentiation")
+    print("A differentiation of the time series is necessary. There is no trend\n")
     seriesDiff = []
     for i in range(len(series) - 1):
         seriesDiff.append(series[i] - series[i + 1])
@@ -28,10 +28,13 @@ def differentiateSeries(series): # Differentiating a non-stationary time series
 
 def printPeriodogram(series): # Show periodogram and top 8 frequencies in time series.
 
+    print("Displaying the periodogram of the time series\n")
+
     # Periodogram
     freqencies, spectrum = periodogram(series)
     plt.plot(freqencies, spectrum, color='blue')
     plt.grid(True, linestyle='-', which='major', alpha=0.5, axis='both')
+    plt.title("Periodogram of the time series")
     plt.xlabel('Frequency (Hz)', fontsize=45)
     plt.ylabel('Power spectral density', fontsize=45)
     plt.xticks(fontsize=40)
@@ -50,6 +53,8 @@ def printPeriodogram(series): # Show periodogram and top 8 frequencies in time s
         print(val)
 
 def stationaryTestsResults(series, alpha): # Assessing the stationarity of a time series using ADF and KPSS tests
+    print("Testing the stationarity of the time series")
+
     # ADF test
     testAdf = adfuller(series)
     # p-value
@@ -61,35 +66,47 @@ def stationaryTestsResults(series, alpha): # Assessing the stationarity of a tim
     print("The p-value KPSS:", testKpss[1])
 
     if testAdf[1] <= alpha <= testKpss[1]:
-        print("The series is stationary")
+        print("The time series is stationary\n")
 
     else:
-        print("The series is not stationary")
+        print("The time series is not stationary\n")
 
 def removeTrend(series, granularity): # Removing the trend component from the time series if it is present
+    print("A trend component is present")
+    print("Displaying the time series with trend\n")
     x_abs = [i for i in range(len(series))]
     low = lowess(series, x_abs, frac=granularity)
     low = [v[1] for v in low]
 
     plt.plot(series)
+    plt.title("Time series with trend")
     plt.plot(low)
+    plt.xlabel("time (hour)")
     plt.show()
 
     series_without_trend = [val - tr for val, tr in zip(series, low)]
 
+    print("Displaying the time series without its trend\n")
+
     plt.plot(series_without_trend)
+    plt.title("Time series without trend")
+    plt.xlabel("time (hour)")
     plt.show()
 
     return series_without_trend
 
 def plotSeries(series):
     plt.plot(series)
+    plt.title("Time series")
+    plt.xlabel("time (hour)")
     plt.show()
 
 def execution(List):
     for l in List:
+        print("######################################")
         print(l[2])
         X = filterTime(l[0], l[1])
+        print("Displaying the time series\n")
         plotSeries(X)
         stationaryTestsResults(X, alphaUsed)
         if l[3] == "T":
@@ -97,6 +114,7 @@ def execution(List):
             stationaryTestsResults(X, alphaUsed)
         elif l[3] == "D":
             X = differentiateSeries(X)
+            print("Displaying the differentiate time series\n")
             plotSeries(X)
             stationaryTestsResults(X, alphaUsed)
         printPeriodogram(X)