Add minimal commandline interface.

README.md

 # X-Lap: A Systems Approach for Cross-Layer Profiling and Latency Analysis for Cyber-Physical Networks
+
+
+## How to use X-lap?
+
+### Step 0: Define your relevant timestamps across a packet trace.
+Define time- and cyclestamps:
+
+* Where data enters the sender app.
+* Where data leaves the sender app.
+* Where data enters the receiver app.
+* Where data leaves the receiver app.
+* Define additional cyclestamps wherever appropriate.
+* Define interesting durations inside xlap.yml.
+
+### Step 1: Instrument your code and generate traces
+* Define a Sender and Receiver Application (send arbitrary data around).
+* Initialize the xlap facility.
+* Add stamping code where-ever appropriate.
+* There are different mechanisms for adding timestamps.
+
+
+### Step 2: Use the provided xlap analysis tools
+* Write your xlap.yml file as follows:
+
+```yaml
+data_files: ads
+stamps: ads
+durations: asd
+```
+
+* Run one of the following analyses on the data set:
+    * Jitter Analysis (`jitter`)

xlap/command_line.py

+import argparse
 import yaml
+
 from xlap.parse import evaluate
 import xlap.analyse.jitter as jitter
 
+tasks = {
+    "jitter": None
+}
+
 def parse_config():
     contents = None
     with open("xlap.yml") as f:
@@ -11,7 +17,15 @@ def parse_config():
 def main():
     config = parse_config()
     data_files = config["data_files"]
-    df_data = evaluate(data_files["sender"], data_files["receiver"],kind=0)
 
+    parser = argparse.ArgumentParser()
+    parser.add_argument("tasks", metavar="T", type=str, nargs="+", help="analysis tasks to execute")
+    args = parser.parse_args()
+
+    for command in args.tasks:
+        if command not in tasks.keys():
+            print("{} is not a known analysis task.".format(command))
+            continue
 
-    jitter.analyse(df_data, config, "TraceJitter.pdf")
+        df_data = evaluate(data_files["sender"], data_files["receiver"],kind=0)
+        jitter.analyse(df_data, config, "TraceJitter.pdf")