image creation python update

testing-results/test_image_creator.py

@@ -2,28 +2,26 @@
 import sys
 import matplotlib.pyplot as plt
 
-def plot_read(read_res_file, threads, iterations):
 
+def plot_read(graph_name, threads, iterations):
     x = []
     y = []
+    i = 1
     dizionario = {}
-    for i in range(1, threads+1):
+    while i <= threads:
         dizionario[i] = 0.0
 
-
-    with open(read_res_file) as csv_file:
+    with open("read_test_" + graph_name + ".csv") as csv_file:
         csv_reader = csv.reader(csv_file, delimiter=',')
         line_count = 0
         for row in csv_reader:
-            if line_count == 0:
-                line_count += 1
-            else:
+            if line_count != 0:
                 dizionario[int(row[0])] += float(row[1])
                 line_count += 1
 
     for key in dizionario:
         x.append(key)
-        y.append(dizionario[key]/iterations)
+        y.append(dizionario[key] / iterations)
 
     # Creazione del grafico con linea che unisce i punti
     plt.plot(x, y, marker='o', linestyle='-')
@@ -34,18 +32,20 @@ def plot_read(read_res_file, threads, iterations):
     plt.title('loading time')
 
     # Mostra il grafico
-    plt.savefig(read_res_file + '.png')
+    plt.savefig("seq_test_"+ graph_name + '.png')
     plt.clf()
 
-def plot_seq(seq_res_file, iterations):
- # SEQUENTIAL PARTITION QUALITY
+
+def plot_seq(graph_name, iterations):
+    # SEQUENTIAL PARTITION QUALITY
     categorie = ['Min-partition', 'Max-partition', 'Median-partition']
     valori = {}
     allCategories = []
-    
-    with open(seq_res_file) as csv_file:
+
+    with open("seq_test_" + graph_name + ".csv") as csv_file:
         csv_reader = csv.reader(csv_file, delimiter=',')
         line_count = 0
+
         for row in csv_reader:
             if line_count == 0:
                 for a in row:
@@ -57,32 +57,34 @@ def plot_seq(seq_res_file, iterations):
                     valori[allCategories[i]] += float(row[i])
                 line_count += 1
 
-    valori_to_print = [valori['min_partition']/iterations, valori['max_partition']/iterations, valori['median_partition']/iterations]
+    for key in valori:
+        valori[key] = valori[key] / iterations
 
-    print(categorie)
-    print(valori_to_print)
+    valori_to_print = [valori['min_partition'], valori['max_partition'], valori['median_partition']]
+
+    print(allCategories)
+    print(valori)
 
     # Creazione del grafico a barre
-    plt.bar(categorie, valori_to_print, color=['blue','orange','green'])
+    plt.bar(categorie, valori_to_print, color=['blue', 'orange', 'green'])
 
     # Aggiunta di etichette agli assi e titolo al grafico
-    #plt.xlabel('Categorie')
-    #plt.ylabel('Valori')
+    # plt.xlabel('Categorie')
+    # plt.ylabel('Valori')
     plt.title('Partition quality in sequential mode')
 
     # Mostra il grafico
     plt.savefig("seq_quality_" + graph_name + '.png')
     plt.clf()
 
 
-def plot_par(path, threads, iterations):
-
+def plot_par(graph_name, threads, iterations):
     allCategories = []
     valori = []
     for i in range(threads):
         valori.append({})
 
-    with open(path) as csv_file:
+    with open("par_test_" + graph_name + ".csv") as csv_file:
         csv_reader = csv.reader(csv_file, delimiter=',')
         line_count = 0
         for row in csv_reader:
@@ -91,64 +93,59 @@ def plot_par(path, threads, iterations):
                     allCategories.append(a)
                     for t in range(0, threads):
                         valori[t][a] = 0.0
-                    
+
                 line_count += 1
             else:
-                for i in range(1, len(row)-1):
-                    valori[int(row[0])-1][allCategories[i]] += float(row[i])
+                for i in range(1, len(row)):
+                    valori[int(row[0]) - 1][allCategories[i]] += float(row[i])
                 line_count += 1
 
-
-
     for i in range(threads):
         for key in valori[i]:
-            valori[i][key] = valori[i][key]/iterations
+            valori[i][key] = valori[i][key] / iterations
 
     runTime = []
-    for i in range( threads):
+    for i in range(threads):
         runTime.append(valori[i][allCategories[1]])
 
-    plt.plot(range(1, threads+1), runTime, marker='o', linestyle='-')
+    plt.plot(range(1, threads + 1), runTime, marker='o', linestyle='-')
     plt.xlabel('threads')
     plt.ylabel('time (ms)')
     plt.title('partitioning time in parallel mode')
     plt.savefig("par_time_" + graph_name + '.png')
     plt.clf()
 
     min_partition = []
-    for i in range( threads):
+    for i in range(threads):
         min_partition.append(valori[i][allCategories[3]])
     max_partition = []
-    for i in range( threads):
+    for i in range(threads):
         max_partition.append(valori[i][allCategories[4]])
     median_partition = []
-    for i in range( threads):
+    for i in range(threads):
         median_partition.append(valori[i][allCategories[6]])
     # Creazione del grafico con due linee
-    plt.plot(range(1, threads+1), min_partition, label='Min-partition', marker='o', linestyle='-')
-    plt.plot(range(1, threads+1), max_partition, label='Max-partition', marker='s', linestyle='--')
-    plt.plot(range(1, threads+1), median_partition, label='Median-partition', marker='D', linestyle=':')
+    plt.plot(range(1, threads + 1), min_partition, label='Min-partition', marker='o', linestyle='-')
+    plt.plot(range(1, threads + 1), max_partition, label='Max-partition', marker='s', linestyle='--')
+    plt.plot(range(1, threads + 1), median_partition, label='Median-partition', marker='D', linestyle=':')
 
-    print("PARALELL: ",valori[3])
+    print("PARALELL: ", valori[3])
 
     # Aggiunta di etichette agli assi, titolo al grafico e legenda
     plt.xlabel('threads')
-    #plt.ylabel('Asse Y')
+    # plt.ylabel('Asse Y')
     plt.title('Partition quality in parallel mode')
-    #plt.legend(loc="best")
+    # plt.legend(loc="best")
 
     # Mostra il grafico
     plt.savefig("par_quality_" + graph_name + '.png')
 
+
 def plot_graphs(graph_name, threads, iterations):
-    plot_read("read_test_" + graph_name +".csv", threads, iterations)
-    plot_seq("seq_test_"+graph_name+".csv", iterations)
-    plot_par("par_test_"+graph_name+".csv", threads, iterations)
+    plot_read(graph_name, threads, iterations)
+    plot_seq(graph_name, iterations)
+    plot_par(graph_name, threads, iterations)
 
 
 if __name__ == '__main__':
-
-    graph_name = sys.argv[1]
-    threads = int(sys.argv[2])
-    iterations = int(sys.argv[3])
-    plot_graphs(graph_name.lower(), threads, iterations)
+    plot_graphs(sys.argv[1].lower(), int(sys.argv[2]), int(sys.argv[3]))