showcases: eliminate invalid escape sequence warning in anf files

inet-framework · Jul 18, 2024 · 6b53048 · 6b53048
1 parent 54d6840
commit 6b53048
Show file tree

Hide file tree

Showing 12 changed files with 98 additions and 98 deletions.
diff --git a/python/inet/scave/plot.py b/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 \\
     """
 
 

diff --git a/showcases/tsn/combiningfeatures/invehicle/InVehicleNetworkShowcase.anf b/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)

diff --git a/showcases/tsn/gatescheduling/eager/EagerGateSchedulingShowcase.anf b/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,

diff --git a/showcases/tsn/gatescheduling/sat/SatShowcase.anf b/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 = []
 

diff --git a/showcases/tsn/streamfiltering/tokenbucket/TokenBucketPolicingShowcase.anf b/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)

diff --git a/showcases/tsn/streamfiltering/underthehood/PeekingUnderTheHoodShowcase.anf b/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)

diff --git a/showcases/tsn/trafficshaping/asynchronousshaper/AsynchronousShaperShowcase.anf b/showcases/tsn/trafficshaping/asynchronousshaper/AsynchronousShaperShowcase.anf
@@ -5,7 +5,7 @@
         <input pattern="results/General-#0.vec"/>
     </inputs>
     <charts>
-        <chart createdWith="OMNeT++ 7.0.0.230207-439c415f65" icon="icons/full/obj/linechart.png" id="678787873" name="Client Application and Filter Incoming Data Rate" resultTypes="vector" template="linechart_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="678787873" name="Client Application and Filter Incoming Data Rate" template="linechart_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -37,8 +37,8 @@ if df.empty:
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
 
-inet.scave.plot.add_to_dataframe(df, style_tuple_list=[('module', '.*app\[0\]|.*filter\[0\]', {'color': default_colors[0]}),
-                                                       ('module', '.*app\[1\]|.*filter\[1\]', {'color': default_colors[1]}),
+inet.scave.plot.add_to_dataframe(df, style_tuple_list=[('module', '.*app\\[0\\]|.*filter\\[0\\]', {'color': default_colors[0]}),
+                                                       ('module', '.*app\\[1\\]|.*filter\\[1\\]', {'color': default_colors[1]}),
                                                        ('module', '.*client.*', {'linestyle': 'dotted'})])
 
 # plot
@@ -651,7 +651,7 @@ utils.export_data_if_needed(df, props)
             <property name="matplotlibrc" value="savefig.transparent : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="" icon="icons/full/obj/linechart.png" id="182658708" name="Filter incoming, outgoing and dropped data rate" resultTypes="" template="linechart_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="182658708" name="Filter incoming, outgoing and dropped data rate" template="linechart_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -684,8 +684,8 @@ if df.empty:
 df = utils.perform_vector_ops(df, props["vector_operations"])
     
 style_tuple_list = [('name','.*incoming.*', {'linestyle': 'dotted'}),
-                    ('module','.*(filter\[0\]|queue\[0\]).*', {'color': default_colors[0]}),
-                    ('module','.*(filter\[1\]|queue\[1\]).*', {'color': default_colors[1]}),
+                    ('module','.*(filter\\[0\\]|queue\\[0\\]).*', {'color': default_colors[0]}),
+                    ('module','.*(filter\\[1\\]|queue\\[1\\]).*', {'color': default_colors[1]}),
                     ('name','.*dropped.*', {'linestyle': 'dashed'})]
 
 inet.scave.plot.add_to_dataframe(df, style_tuple_list)
@@ -1314,7 +1314,7 @@ utils.export_data_if_needed(df, props)
             <property name="matplotlibrc" value="savefig.transparent : True&#10;figure.autolayout : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="OMNeT++ 7.0.0.230207-439c415f65" icon="icons/full/obj/linechart.png" id="983061138" name="Queue incoming and outgoing data rate" resultTypes="vector" template="linechart_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="983061138" name="Queue incoming and outgoing data rate" template="linechart_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -1346,8 +1346,8 @@ if df.empty:
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
 
-style_tuple_list = [('module','.*(app\[0\]|queue\[0\]).*', {'color': default_colors[0]}),
-                    ('module','.*(app\[1\]|queue\[1\]).*', {'color': default_colors[1]}),
+style_tuple_list = [('module','.*(app\\[0\\]|queue\\[0\\]).*', {'color': default_colors[0]}),
+                    ('module','.*(app\\[1\\]|queue\\[1\\]).*', {'color': default_colors[1]}),
                     ('name','incoming.*', {'linestyle': 'dotted'})]
 
 inet.scave.plot.add_to_dataframe(df, style_tuple_list)
@@ -1971,7 +1971,7 @@ utils.export_data_if_needed(df, props)
             <property name="matplotlibrc" value="savefig.transparent : True&#10;figure.autolayout : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="" icon="icons/full/obj/linechart.png" id="453153400" name="Queue incoming and outgoing data rate, zoomed" resultTypes="" template="linechart_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="453153400" name="Queue incoming and outgoing data rate, zoomed" template="linechart_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -2003,11 +2003,11 @@ if df.empty:
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
     
-style_tuple_list = [('source','throughput\(packetPushStarted\)', {'linestyle': 'dotted'}),
-                    ('module','.*(app\[0\]|queue\[0\]).*', {'color': default_colors[0]}),
-                    ('module','.*(app\[1\]|queue\[1\]).*', {'color': default_colors[1]}),
-                    ('module','.*(filter\[0\]).*', {'color': default_colors[0], 'linestyle': 'dashed'}),
-                    ('module','.*(filter\[1\]).*', {'color': default_colors[1], 'linestyle': 'dashed'})]
+style_tuple_list = [('source','throughput\\(packetPushStarted\\)', {'linestyle': 'dotted'}),
+                    ('module','.*(app\\[0\\]|queue\\[0\\]).*', {'color': default_colors[0]}),
+                    ('module','.*(app\\[1\\]|queue\\[1\\]).*', {'color': default_colors[1]}),
+                    ('module','.*(filter\\[0\\]).*', {'color': default_colors[0], 'linestyle': 'dashed'}),
+                    ('module','.*(filter\\[1\\]).*', {'color': default_colors[1], 'linestyle': 'dashed'})]
 
 inet.scave.plot.add_to_dataframe(df, style_tuple_list)
     
@@ -2638,7 +2638,7 @@ utils.export_data_if_needed(df, props)
             <property name="matplotlibrc" value="savefig.transparent : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="" icon="icons/full/obj/linechart.png" id="1095145658" name="Server Application and Queue Outgoing Traffic" resultTypes="" template="linechart_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="1095145658" name="Server Application and Queue Outgoing Traffic" template="linechart_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -2670,9 +2670,9 @@ if df.empty:
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
     
-style_tuple_list = [('module','TsnLinearNetwork.server.app\[.*\].sink', {'linestyle': '--'}),
-                    ('module','.*(app\[0\]|queue\[0\]).*', {'color': default_colors[0]}),
-                    ('module','.*(app\[1\]|queue\[1\]).*', {'color': default_colors[1]})]
+style_tuple_list = [('module','TsnLinearNetwork.server.app\\[.*\\].sink', {'linestyle': '--'}),
+                    ('module','.*(app\\[0\\]|queue\\[0\\]).*', {'color': default_colors[0]}),
+                    ('module','.*(app\\[1\\]|queue\\[1\\]).*', {'color': default_colors[1]})]
 
 inet.scave.plot.add_to_dataframe(df, style_tuple_list)
     
@@ -3295,7 +3295,7 @@ utils.export_data_if_needed(df, props)
             <property name="matplotlibrc" value="savefig.transparent : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="OMNeT++ 7.0.0.230207-439c415f65" icon="icons/full/obj/linechart.png" id="1118731091" name="Filter and queue incoming and outgoing traffic + drop rate, best effort" resultTypes="vector" template="linechart_separate_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="1118731091" name="Filter and queue incoming and outgoing traffic + drop rate, best effort" template="linechart_separate_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 import matplotlib.pyplot as plt
 from omnetpp.scave import results, chart, utils
@@ -3973,7 +3973,7 @@ utils.export_image_if_needed(props)
             <property name="matplotlibrc" value="savefig.transparent : True&#10;figure.autolayout : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="OMNeT++ 7.0.0.230207-439c415f65" icon="icons/full/obj/linechart.png" id="396641951" name="Filter and queue incoming and outgoing traffic + drop rate, video" resultTypes="vector" template="linechart_separate_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="396641951" name="Filter and queue incoming and outgoing traffic + drop rate, video" template="linechart_separate_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 import matplotlib.pyplot as plt
 from omnetpp.scave import results, chart, utils
@@ -4651,7 +4651,7 @@ utils.export_image_if_needed(props)
             <property name="matplotlibrc" value="savefig.transparent : True&#10;figure.autolayout : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="OMNeT++ 7.0.0.230207-439c415f65" icon="icons/full/obj/linechart.png" id="1893942980" name="Queue remaining eligibility time" resultTypes="vector" template="linechart_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="1893942980" name="Queue remaining eligibility time" template="linechart_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -5290,7 +5290,7 @@ utils.export_data_if_needed(df, props)
             <property name="matplotlibrc" value="savefig.transparent : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="" icon="icons/full/obj/linechart.png" id="1874158300" name="Queue remaining eligibility time, zoomed" resultTypes="" template="linechart_native" type="LINE">
+        <chart icon="icons/full/obj/linechart.png" id="1874158300" name="Queue remaining eligibility time, zoomed" template="linechart_native" type="LINE">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils, ideplot
 
@@ -5931,7 +5931,7 @@ utils.export_data_if_needed(df, props)
             <property name="legend_automatic" value="true"/>
             <property name="legend_format" value=""/>
         </chart>
-        <chart createdWith="" icon="icons/full/obj/linechart.png" id="1641514640" name="Traffic shaping" resultTypes="" template="linechart_separate_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="1641514640" name="Traffic shaping" template="linechart_separate_mpl" type="MATPLOTLIB">
             <script><![CDATA[import re
 import numpy
 import math
@@ -6004,7 +6004,7 @@ for i in df:
 #df = utils.perform_vector_ops(df, props["vector_operations"])
 #df["moduledisplaypath"].fillna(df["module"], inplace=True)
 #df["legend"] = df["moduledisplaypath"] + ", " + df["title"]
-#df["legend"] = df["legend"].apply(lambda legend: re.sub(".*\.(.*) dilated.*", "\\1", str(legend)))
+#df["legend"] = df["legend"].apply(lambda legend: re.sub(".*\\.(.*) dilated.*", "\\1", str(legend)))
 #df["title"] = df["legend"]
 
 # plot
@@ -6647,7 +6647,7 @@ utils.export_data_if_needed(df, props)]]></script>
             <property name="matplotlibrc" value="savefig.transparent : True"/>
             <property name="include_fields" value="false"/>
         </chart>
-        <chart createdWith="" icon="icons/full/obj/linechart.png" id="727250450" name="Traffic shaping, zoomed" resultTypes="" template="linechart_separate_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="727250450" name="Traffic shaping, zoomed" template="linechart_separate_mpl" type="MATPLOTLIB">
             <script><![CDATA[import re
 import numpy
 import math
@@ -6720,7 +6720,7 @@ for i in df:
 #df = utils.perform_vector_ops(df, props["vector_operations"])
 #df["moduledisplaypath"].fillna(df["module"], inplace=True)
 #df["legend"] = df["moduledisplaypath"] + ", " + df["title"]
-#df["legend"] = df["legend"].apply(lambda legend: re.sub(".*\.(.*) dilated.*", "\\1", str(legend)))
+#df["legend"] = df["legend"].apply(lambda legend: re.sub(".*\\.(.*) dilated.*", "\\1", str(legend)))
 #df["title"] = df["legend"]
 
 # plot

diff --git a/showcases/tsn/trafficshaping/cbsandats/CbsAndAtsShowcase.anf b/showcases/tsn/trafficshaping/cbsandats/CbsAndAtsShowcase.anf
@@ -5,7 +5,7 @@
         <input pattern="results/General-#0.vec"/>
     </inputs>
     <charts>
-        <chart createdWith="" icon="icons/full/obj/linechart.png" id="793412994" name="Shaper Incoming And Outgoing Traffic" resultTypes="" template="linechart_mpl" type="MATPLOTLIB">
+        <chart icon="icons/full/obj/linechart.png" id="587404414" name="Shaper Incoming And Outgoing Traffic" template="linechart_mpl" type="MATPLOTLIB">
             <script><![CDATA[import math
 from omnetpp.scave import results, chart, utils
 import os
@@ -37,9 +37,9 @@ if df.empty:
 # apply vector operations
 df = utils.perform_vector_ops(df, props["vector_operations"])
 
-style_tuple_list = [('source', 'throughput\(packetPushStarted\)', {'linestyle': 'dashed'}),
-                    ('module', '.*(app\[0\]|queue\[0\]).*', {'color': default_colors[0]}),
-                    ('module', '.*(app\[1\]|queue\[1\]).*', {'color': default_colors[1]})]
+style_tuple_list = [('source', 'throughput\\(packetPushStarted\\)', {'linestyle': 'dashed'}),
+                    ('module', '.*(app\\[0\\]|queue\\[0\\]).*', {'color': default_colors[0]}),
+                    ('module', '.*(app\\[1\\]|queue\\[1\\]).*', {'color': default_colors[1]})]
 
 inet.scave.plot.add_to_dataframe(df, style_tuple_list)
-Original file line number
+Diff line change
@@ Expand Up @@
             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 \\
         """
@@ Expand Down @@