~= Delta heading

notebook.ipynb

@@ -126,6 +126,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "# $\\Delta$elta\n",
     "## Latency Criticality"
    ]
   },
 %% Cell type:markdown id: tags:
 
 # X-Lap in Action
 
 %% Cell type:code id: tags:
 
 ``` python
 %matplotlib inline
 ```
 
 %% Cell type:markdown id: tags:
 
 ## Data Retrieval
 
 %% Cell type:code id: tags:
 
 ``` python
 from xlap.parse import evaluate, parse_config
 config = parse_config()
 data_files = {
     "sender": "rtn2018/20180417_testbed/",
     "receiver": "rtn2018/20180417_testbed/"
 }
 df_1GHz = evaluate(data_files["sender"] + "sender-1000000.csv", data_files["receiver"] + "receiver-1000000.csv", config=config, kind=0)
 df_1GHz.name = "1GHz"
 df_2GHz = evaluate(data_files["sender"] + "sender-2000000.csv", data_files["receiver"] + "receiver-2000000.csv", config=config, kind=0)
 df_2GHz.name = "2GHz"
 df_3GHz = evaluate(data_files["sender"] + "sender-3000000.csv", data_files["receiver"] + "receiver-3000000.csv", config=config, kind=0)
 df_3GHz.name = "3GHz"
 dfs = [df_1GHz, df_2GHz, df_3GHz]
 ```
 
 %% Cell type:markdown id: tags:
 
 ## Individual Packet Traces
 
 %% Cell type:code id: tags:
 
 ``` python
 from xlap.analyse.trace import traces
 traces(df_1GHz, config, global_xaxis=True)
 ```
 
 %% Cell type:markdown id: tags:
 
 ## Trace Jitter Analysis
 
 %% Cell type:code id: tags:
 
 ``` python
 from xlap.analyse.jitter import multi_trace_jitter
 multi_trace_jitter(dfs, config)
 ```
 
 %% Cell type:markdown id: tags:
 
 ## Latency Distributions
 
 %% Cell type:code id: tags:
 
 ``` python
 from xlap.analyse.cdf import multi_cdf
 from xlap.analyse.util import colors
 import copy
 cfg = copy.deepcopy(config)
 list(map(cfg["durations"].pop, ("Decoding",
                                 "ReceiverIPC",
                                 "HandlePacket",
                                 "Feedback",
                                 "SenderIPC",
                                 "SenderEnqueued",
                                 "Enqueue")))
 multi_cdf(dfs, cfg, colors=colors)
 ```
 
 %% Cell type:markdown id: tags:
 
 ## Correlation with E2E Latency
 
 %% Cell type:code id: tags:
 
 ``` python
 from xlap.analyse.correlation import multi_correlation
 multi_correlation(dfs, config, colors=colors, figsize=(3.0,2.0), cols=4)
 ```
 
 %% Cell type:markdown id: tags:
 
+# $\Delta$elta
 ## Latency Criticality
 
 %% Cell type:code id: tags:
 
 ``` python
 from xlap.analyse.latency import analyse
 d = analyse(df_1GHz, config)
 ```
 
 %% Cell type:markdown id: tags:
 
 ### Correlations
 
 %% Cell type:code id: tags:
 
 ``` python
 d.corr.sort_values(ascending=False)
 ```
 
 %% Cell type:markdown id: tags:
 
 ### Control Flow Graph
 
 %% Cell type:code id: tags:
 
 ``` python
 d.cfg
 ```
 
 %% Cell type:markdown id: tags:
 
 ## Timing Behaviour
 
 %% Cell type:code id: tags:
 
 ``` python
 from xlap.analyse.timing import timing_behaviour
 timing_behaviour(df_1GHz, df_2GHz, config)
 ```
 
 %% Cell type:code id: tags:
 
 ``` python
 timing_behaviour(df_1GHz, df_3GHz, config)
 ```
 
 %% Cell type:code id: tags:
 
 ``` python
 timing_behaviour(df_2GHz, df_3GHz, config)
 ```