Merge branch 'inet-framework:master' into master

examples/mobility/MobileNetwork.ned

@@ -18,7 +18,7 @@ network MobileNetwork
         bool hasVisualizer = default(false);
         bool hasScenarioManager = default(false);
         bool hasEnvironment = default(false);
-        @display("bgb=600,400");
+        @display("bgb=600,600");
     submodules:
         visualizer: IntegratedCanvasVisualizer if hasVisualizer {
             parameters:

examples/mobility/omnetpp.ini

@@ -9,7 +9,7 @@ sim-time-limit = 1000s
 **.constraintAreaMinY = 0m
 **.constraintAreaMinZ = 0m
 **.constraintAreaMaxX = 600m
-**.constraintAreaMaxY = 400m
+**.constraintAreaMaxY = 600m
 **.constraintAreaMaxZ = 0m
 
 [Config Update]

python/inet/scave/plot.py

@@ -665,7 +665,7 @@ def add_to_dataframe(df, style_tuple_list=None, default_dict=None, order=None):
         or
     order = ['configname', 'Advanced_config', 'Default_config', 'Manual_config']
     
-    Note that the value parameter in style_tuple_list and the order can contain regex (e.g. .*foo). Make sure to escape regex characters such as [ and ] with \
+    Note that the value parameter in style_tuple_list and the order can contain regex (e.g. .*foo). Make sure to escape regex characters such as [ and ] with \\
     """
 
 
@@ -700,8 +700,8 @@ def remove_zero_index_if_present(df):
 
             for i in range(0,len(df)):
                 pattern = re.compile(value)
-                logger.debug(f"value: {value}, pattern: {pattern}, df[column][i] {df[column][i]}")
-                match = re.fullmatch(pattern, df[column][i])
+                logger.debug(f"value: {value}, pattern: {pattern}, df.loc[i, column] {df.loc[i, column]}")
+                match = re.fullmatch(pattern, df.loc[i, column])
                 logger.debug(f"match: {match}")
                 if match != None:
                     # if debug:
@@ -732,9 +732,9 @@ def remove_zero_index_if_present(df):
             logger.debug(f'order_column: {order_column}, order_dict {order_dict}')
             for i in order_dict.items():
                 for j in range(0,len(df)):
-                    # if df[order_column][j] == i[0]:
+                    # if df.loc[j, order_column] == i[0]:
                     pattern = re.compile(i[0])
-                    match = re.fullmatch(pattern, df[order_column][j])
+                    match = re.fullmatch(pattern, df.loc[j, order_column])
                     if match != None:
                         df.loc[j, 'order'] = i[1]
         else:
@@ -743,9 +743,9 @@ def remove_zero_index_if_present(df):
             logger.debug(f'order_column: {order_column}, order_list {order_list}')
             for order in range(0, len(order_list)):
                 for j in range(0,len(df)):
-                    # if df[order_column][j] == i[0]:
+                    # if df.loc[j, order_column] == i[0]:
                     pattern = re.compile(order_list[order])
-                    match = re.fullmatch(pattern, df[order_column][j])
+                    match = re.fullmatch(pattern, df.loc[j, order_column])
                     if match != None:
                         df.loc[j, 'order'] = order
 

showcases/tsn/combiningfeatures/invehicle/InVehicleNetworkShowcase.anf

@@ -4624,7 +4624,7 @@ if df.empty:
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
-df['legend'] = df['module'].map(lambda module: re.sub(".*\.(.*)\..*", "\\1", module))
+df['legend'] = df['module'].map(lambda module: re.sub(".*\\.(.*)\\..*", "\\1", module))
 
 # plot
 utils.plot_vectors(df, props)
@@ -5198,7 +5198,7 @@ if df.empty:
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
-df['legend'] = df['module'].map(lambda module: re.sub(".*\.(.*)\..*", "\\1", module))
+df['legend'] = df['module'].map(lambda module: re.sub(".*\\.(.*)\\..*", "\\1", module))
 
 # plot
 utils.plot_vectors(df, props)

showcases/tsn/gatescheduling/eager/EagerGateSchedulingShowcase.anf

@@ -5,7 +5,7 @@
         <input pattern="/inet/showcases/tsn/gatescheduling/eager/results/Eager-*.sca"/>
     </inputs>
     <charts>
-        <chart icon="icons/full/obj/linechart.png" id="1635758751" name="Application End-to-End Delay" template="linechart_native" type="LINE">
+        <chart icon="icons/full/obj/linechart.png" id="1057960291" name="Application End-to-End Delay" template="linechart_native" type="LINE">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -36,10 +36,10 @@ if df.empty:
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
 
-style_tuple_list = [('module', '.*app\[0\].*', {'marker': 'd', 'markersize': 4}), 
-                    ('module', '.*app\[1\].*', {'marker': 'x', 'markersize': 2}),
-                    ('module', '.*app\[2\].*', {'marker': 'd', 'markersize': 4}),
-                    ('module', '.*app\[3\].*', {'marker': 's', 'markersize': 2})]
+style_tuple_list = [('module', '.*app\\[0\\].*', {'marker': 'd', 'markersize': 4}), 
+                    ('module', '.*app\\[1\\].*', {'marker': 'x', 'markersize': 2}),
+                    ('module', '.*app\\[2\\].*', {'marker': 'd', 'markersize': 4}),
+                    ('module', '.*app\\[3\\].*', {'marker': 's', 'markersize': 2})]
 
 order = ['module', {'TsnDumbbellNetwork.server2.app[2].sink': 2,
                     'TsnDumbbellNetwork.server2.app[3].sink': 3,

showcases/tsn/gatescheduling/sat/SatShowcase.anf

@@ -36,10 +36,10 @@ if df.empty:
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
 
-style_tuple_list = [('module', '.*app\[0\].*', {'marker': 'd', 'markersize': 4}), 
-                    ('module', '.*app\[1\].*', {'marker': 'x', 'markersize': 2}),
-                    ('module', '.*app\[2\].*', {'marker': 'd', 'markersize': 4}),
-                    ('module', '.*app\[3\].*', {'marker': 's', 'markersize': 2})]
+style_tuple_list = [('module', '.*app\\[0\\].*', {'marker': 'd', 'markersize': 4}), 
+                    ('module', '.*app\\[1\\].*', {'marker': 'x', 'markersize': 2}),
+                    ('module', '.*app\\[2\\].*', {'marker': 'd', 'markersize': 4}),
+                    ('module', '.*app\\[3\\].*', {'marker': 's', 'markersize': 2})]
 
 order = ['module', {'TsnDumbbellNetwork.server2.app[2].sink': 2,
                     'TsnDumbbellNetwork.server2.app[3].sink': 3,
@@ -716,10 +716,10 @@ df_sat= utils.perform_vector_ops(df_sat, props["vector_operations"])
 
 #print(df_eager, df_sat)
 
-style_tuple_list = [('module', '.*app\[0\].*', {'marker': 'd', 'markersize': 4, 'color': '#1f77b4'}), 
-                    ('module', '.*app\[1\].*', {'marker': 'x', 'markersize': 2, 'color': '#ff7f0e'}),
-                    ('module', '.*app\[2\].*', {'marker': 'd', 'markersize': 4, 'color': '#2ca02c'}),
-                    ('module', '.*app\[3\].*', {'marker': 's', 'markersize': 2, 'color': '#d62728'})]
+style_tuple_list = [('module', '.*app\\[0\\].*', {'marker': 'd', 'markersize': 4, 'color': '#1f77b4'}), 
+                    ('module', '.*app\\[1\\].*', {'marker': 'x', 'markersize': 2, 'color': '#ff7f0e'}),
+                    ('module', '.*app\\[2\\].*', {'marker': 'd', 'markersize': 4, 'color': '#2ca02c'}),
+                    ('module', '.*app\\[3\\].*', {'marker': 's', 'markersize': 2, 'color': '#d62728'})]
 
 #style_tuple_list = []
 

showcases/tsn/streamfiltering/tokenbucket/TokenBucketPolicingShowcase.anf

@@ -602,7 +602,7 @@ if df.empty:
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
-df['title'] = df['title'].map(lambda title: re.sub("\, vector.*", "", title))
+df['title'] = df['title'].map(lambda title: re.sub("\\, vector.*", "", title))
 
 # plot
 utils.plot_vectors(df, props)
@@ -1239,7 +1239,7 @@ if df.empty:
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
-df['title'] = df['title'].map(lambda title: re.sub("\, vector.*", "", title))
+df['title'] = df['title'].map(lambda title: re.sub("\\, vector.*", "", title))
 
 # plot
 utils.plot_vectors(df, props)

showcases/tsn/streamfiltering/underthehood/PeekingUnderTheHoodShowcase.anf

@@ -30,7 +30,7 @@ if df.empty:
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
-df['title'] = df['title'].map(lambda title: re.sub("\, vector.*", "", title))
+df['title'] = df['title'].map(lambda title: re.sub("\\, vector.*", "", title))
 
 # plot
 utils.plot_vectors(df, props)
@@ -667,7 +667,7 @@ if df.empty:
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
-df['title'] = df['title'].map(lambda title: re.sub("\, vector.*", "", title))
+df['title'] = df['title'].map(lambda title: re.sub("\\, vector.*", "", title))
 
 # plot
 utils.plot_vectors(df, props)
@@ -1304,7 +1304,7 @@ if df.empty:
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
-df['title'] = df['title'].map(lambda title: re.sub("\, vector.*", "", title))
+df['title'] = df['title'].map(lambda title: re.sub("\\, vector.*", "", title))
 
 # plot
 utils.plot_vectors(df, props)

showcases/tsn/timesynchronization/clockdrift/ClockDriftShowcase.anf

@@ -48,8 +48,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -629,8 +629,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -1210,8 +1210,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -1791,8 +1791,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -2372,8 +2372,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -2953,8 +2953,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -3534,8 +3534,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -4117,8 +4117,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)
@@ -4698,8 +4698,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 
 df['legend'] = df['module']
 for i in range(0,len(df['legend'])):
-    df['legend'][i] = df['module'][i].replace('ClockDriftShowcase.','')
-    df['legend'][i] = df['legend'][i].replace('.clock','')
+    df.loc[i, 'legend'] = df.loc[i, 'module'].replace('ClockDriftShowcase.','')
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace('.clock','')
 
 # plot
 utils.plot_vectors(df, props)

showcases/tsn/timesynchronization/gptp/GptpShowcase.anf

@@ -41,8 +41,8 @@ if df.empty:
 df['legend'] = df['module']
 
 for i in range(0,len(df)):
-    df['legend'][i] = df['legend'][i].replace("OneMasterClockGptpShowcase.","")
-    df['legend'][i] = df['legend'][i].replace(".clock","")
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace("OneMasterClockGptpShowcase.","")
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace(".clock","")
 
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
@@ -628,8 +628,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 df['legend'] = df['module']
 
 for i in range(0,len(df)):
-    df['legend'][i] = df['legend'][i].replace("TwoMasterClocksTreeGptpShowcase.","")
-#    df['legend'][i] = df['legend'][i].replace(".clock","")
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace("TwoMasterClocksTreeGptpShowcase.","")
+#    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace(".clock","")
 
 # plot
 utils.plot_vectors(df, props)
@@ -1204,8 +1204,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 df['legend'] = df['module']
 
 for i in range(0,len(df)):
-    df['legend'][i] = df['legend'][i].replace("TwoMasterClocksTreeGptpShowcase.","")
-#    df['legend'][i] = df['legend'][i].replace(".clock[0]","")
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace("TwoMasterClocksTreeGptpShowcase.","")
+#    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace(".clock[0]","")
 
 # plot
 utils.plot_vectors(df, props)
@@ -1780,8 +1780,8 @@ df = utils.perform_vector_ops(df, props["vector_operations"])
 df['legend'] = df['module']
 
 for i in range(0,len(df)):
-    df['legend'][i] = df['legend'][i].replace("TwoMasterClocksTreeGptpShowcase.","")
-#    df['legend'][i] = df['legend'][i].replace(".clock[0]","")
+    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace("TwoMasterClocksTreeGptpShowcase.","")
+#    df.loc[i, 'legend'] = df.loc[i, 'legend'].replace(".clock[0]","")
 
 # plot
 utils.plot_vectors(df, props)