~= update notebook

notebook.ipynb

@@ -34,7 +34,9 @@
     "from xlap.analyse.latency import analyse\n",
     "import matplotlib.pyplot as plt\n",
     "import pandas as pd\n",
-    "%matplotlib inline"
+    "import copy\n",
+    "%matplotlib inline\n",
+    "colors = [\"#E69F00\", \"#009E73\", \"#56B4E9\",  \"#CC79A7\", \"#D55E00\"]"
    ]
   },
   {
@@ -52,29 +54,16 @@
    "source": [
     "config = parse_config()\n",
     "data_files = {\n",
-    "    \"sender\": \"~/Work/Publications/rtn-2018/eval/20180420_base1/\",\n",
-    "    \"receiver\": \"~/Work/Publications/rtn-2018/eval/20180420_base1/\"\n",
+    "    \"sender\": \"rtn2018/20180417_testbed/\",\n",
+    "    \"receiver\": \"rtn2018/20180417_testbed/\"\n",
     "}\n",
-    "x= 4050\n",
-    "original1 = evaluate(data_files[\"sender\"] + \"sender-1000000.csv\", data_files[\"receiver\"] + \"receiver-1000000.csv\", config=config, kind=0).iloc[0:x]\n",
+    "original1 = evaluate(data_files[\"sender\"] + \"sender-1000000.csv\", data_files[\"receiver\"] + \"receiver-1000000.csv\", config=config, kind=0)\n",
     "original1.name = \"1GHz\"\n",
-    "original2 = evaluate(data_files[\"sender\"] + \"sender-2000000.csv\", data_files[\"receiver\"] + \"receiver-2000000.csv\", config=config, kind=0).iloc[0:x]\n",
+    "original2 = evaluate(data_files[\"sender\"] + \"sender-2000000.csv\", data_files[\"receiver\"] + \"receiver-2000000.csv\", config=config, kind=0)\n",
     "original2.name = \"2GHz\"\n",
-    "original3 = evaluate(data_files[\"sender\"] + \"sender-3000000.csv\", data_files[\"receiver\"] + \"receiver-3000000.csv\", config=config, kind=0).iloc[0:x]\n",
+    "original3 = evaluate(data_files[\"sender\"] + \"sender-3000000.csv\", data_files[\"receiver\"] + \"receiver-3000000.csv\", config=config, kind=0)\n",
     "original3.name = \"3GHz\"\n",
-    "\n",
-    "data_files = {\n",
-    "    \"sender\": \"~/Work/Publications/rtn-2018/eval/20180420_changed/\",\n",
-    "    \"receiver\": \"~/Work/Publications/rtn-2018/eval/20180420_changed/\"\n",
-    "}\n",
-    "original4 = evaluate(data_files[\"sender\"] + \"sender-1000000.csv\", data_files[\"receiver\"] + \"receiver-1000000.csv\", config=config, kind=0).iloc[0:x]\n",
-    "original4.name = \"1GHz [2]\"\n",
-    "original5 = evaluate(data_files[\"sender\"] + \"sender-2000000.csv\", data_files[\"receiver\"] + \"receiver-2000000.csv\", config=config, kind=0).iloc[0:x]\n",
-    "original5.name = \"2GHz [2]\"\n",
-    "original6 = evaluate(data_files[\"sender\"] + \"sender-3000000.csv\", data_files[\"receiver\"] + \"receiver-3000000.csv\", config=config, kind=0).iloc[0:x]\n",
-    "original6.name = \"3GHz [2]\"\n",
-    "\n",
-    "dfs = [original1, original4, original2, original5, original3, original6]"
+    "dfs = [original1, original2, original3]"
    ]
   },
   {
@@ -90,7 +79,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "traces(original1, config)"
+    "traces(original1, config, global_xaxis=True)"
    ]
   },
   {
@@ -109,7 +98,7 @@
     "def multi_trace_jitter(dfs, config):\n",
     "    for df in dfs:\n",
     "        print(\"############################ {} ############################\".format(df.name))\n",
-    "        jitter.trace_jitter(df, config=config, threshold=500)\n",
+    "        jitter.trace_jitter(df, config=config, threshold=200)\n",
     "        \n",
     "multi_trace_jitter(dfs, config)"
    ]
@@ -127,7 +116,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "multi_cdf(dfs, config, export=True)"
+    "cfg = copy.deepcopy(config)\n",
+    "d = cfg[\"durations\"]\n",
+    "\n",
+    "l=(\"Decoding\",\"ReceiverIPC\",\"HandlePacket\", \"Feedback\", \"SenderIPC\",\"SenderEnqueued\",\"Enqueue\")\n",
+    "for e in l:\n",
+    "    if e in l:\n",
+    "        del d[e]\n",
+    "\n",
+    "multi_cdf(dfs, cfg, colors=colors)"
    ]
   },
   {
@@ -143,14 +140,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "multi_correlation(dfs, config, export=True)"
+    "multi_correlation(dfs, config, colors=colors, figsize=(3.0,2.0), cols=4)"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "source": [
     "## Latency Criticality"
    ]
@@ -265,7 +260,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.8"
   },
   "widgets": {
    "state": {