Remove jitter.prep. Add correlation export. Small fixes.

notebook.ipynb

@@ -17,9 +17,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "import logging\n",
@@ -29,10 +27,12 @@
     "import ipywidgets as widgets\n",
     "from xlap.parse import evaluate, evaluate_side, parse_config\n",
     "import xlap.analyse.jitter as jitter\n",
+    "from xlap.analyse.cdf import multi_cdf\n",
     "from xlap.analyse.regress import linear as linear_regression\n",
     "from xlap.analyse.trace import traces\n",
-    "from xlap.analyse.correlation import correlation\n",
+    "from xlap.analyse.correlation import correlation, multi_correlation\n",
     "from xlap.analyse.latency import analyse\n",
+    "import matplotlib.pyplot as plt\n",
     "import pandas as pd\n",
     "%matplotlib inline"
    ]
@@ -51,8 +51,17 @@
    "outputs": [],
    "source": [
     "config = parse_config()\n",
-    "data_files = config[\"data_files\"]\n",
-    "original = evaluate(data_files[\"sender\"], data_files[\"receiver\"], config=config, kind=0)"
+    "data_files = {\n",
+    "    \"sender\": \"~/Work/Publications/rtn-2018/eval/20180417_testbed/\",\n",
+    "    \"receiver\": \"~/Work/Publications/rtn-2018/eval/20180417_testbed/\"\n",
+    "}\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)\n",
+    "original2.name = \"2GHz\"\n",
+    "original3 = evaluate(data_files[\"sender\"] + \"sender-3000000.csv\", data_files[\"receiver\"] + \"receiver-3000000.csv\", config=config, kind=0)\n",
+    "original3.name = \"3GHz\"\n",
+    "dfs = [original1, original2, original3]"
    ]
   },
   {
@@ -68,7 +77,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "traces(original, config)"
+    "traces(original1, config)"
    ]
   },
   {
@@ -84,8 +93,28 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "df = jitter.prep(original, config=config)\n",
-    "jitter.trace_jitter(df, threshold=500)"
+    "def multi_trace_jitter(dfs, config):\n",
+    "    for df in dfs:\n",
+    "        print(\"############################ {} ############################\".format(df.name))\n",
+    "        jitter.trace_jitter(df, config=config, threshold=300)\n",
+    "        \n",
+    "multi_trace_jitter(dfs, config)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## CDFs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "multi_cdf(dfs, config, export=True)"
    ]
   },
   {
@@ -101,7 +130,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "correlation(df[df[\"EndToEnd_D\"] < 500], config)"
+    "multi_correlation(dfs, config, export=True)"
    ]
   },
   {
@@ -119,7 +148,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "d = analyse(original, config)"
+    "d = analyse(original1, config)"
    ]
   },
   {
@@ -153,6 +182,65 @@
    "source": [
     "d.cfg"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Kolmogorov\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy import stats\n",
+    "from xlap.analyse.util import extract_durations\n",
+    "import numpy as np\n",
+    "\n",
+    "def timing_behaviour(df1, df2, config, confidence=0.9):\n",
+    "    durations = [x + \"_D\" for x in extract_durations(config)]\n",
+    "    \n",
+    "    norm = lambda x: x / np.max(x)\n",
+    "    \n",
+    "    for duration in durations:\n",
+    "        rvs1 = norm(df1[duration])\n",
+    "        rvs2 = norm(df2[duration])\n",
+    "        stat, pvalue = stats.ks_2samp(rvs1, rvs2)\n",
+    "        result = \"CANNOT REJECT\"\n",
+    "        if pvalue < 1 - confidence:\n",
+    "            result = \"REJECT\"\n",
+    "        print(duration.ljust(20), \"{:.6f}\".format(pvalue), result, sep=\"\\t\\t\")\n",
+    "\n",
+    "timing_behaviour(original1, original2, config)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "timing_behaviour(original1, original3, config)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "timing_behaviour(original2, original3, config)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -171,7 +259,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.2"
+   "version": "3.6.3"
   },
   "widgets": {
    "state": {

xlap.yml

@@ -39,6 +39,14 @@ stamps:
         Source: sender
         Thread: app_send
         Type: time
+    PrrtSendPacketStart:
+        Source: sender
+        Thread: trans_send
+        Type: none
+    PrrtSendPacketEnd:
+        Source: sender
+        Thread: trans_send
+        Type: none
 
     PrrtTransmitStart:
         Source: sender