Add a new notebook

lingyaw · Nov 24, 2016 · d8d91e1 · d8d91e1
1 parent 20a05f6
commit d8d91e1
Showing 1 changed file with 96 additions and 0 deletions.
diff --git a/tools/ipython_notebooks/python3/LogPlotter.ipynb b/tools/ipython_notebooks/python3/LogPlotter.ipynb
@@ -0,0 +1,96 @@
+{
+ "metadata": {
+  "name": "",
+  "signature": "sha256:04e93c75a12ec21f1ab4c75eb40d6cb9d455d9821f45edfe5f1146aa0d403d4b"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "APPS"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "from LogReader import PropertyUuidNameMapLog, CaseLog, SimulationLog, OptimizationLog, ProductionDataLog\n",
+      "from LogDataStructures import CaseContainer, Optimizer\n",
+      "\n",
+      "output_path=\"/home/einar/fo_out_20161122_apps/\"\n",
+      "name_map = PropertyUuidNameMapLog(output_path + \"log_property_uuid_name_map.csv\")\n",
+      "case_log = CaseLog(output_path + \"log_cases.csv\")\n",
+      "sim_log_1 = SimulationLog(output_path + \"rank1/log_simulation.csv\")\n",
+      "opt_log = OptimizationLog(output_path + \"log_optimization.csv\")\n",
+      "prod_log = ProductionDataLog(output_path + \"rank1/log_production_data.txt\")\n",
+      "\n",
+      "case_container = CaseContainer(case_log, name_map)\n",
+      "optimizer = Optimizer(opt_log, case_container)\n",
+      "\n",
+      "y1 = []\n",
+      "for case in optimizer.best_case_pr_iteration:\n",
+      "    y1.append(case.objective_function_value)\n",
+      "    \n",
+      "from matplotlib import pyplot as plt\n",
+      "plt.plot(y1)\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 11
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "output_path=\"/home/einar/fo_out_20161118/\"\n",
+      "name_map = PropertyUuidNameMapLog(output_path + \"log_property_uuid_name_map.csv\")\n",
+      "case_log = CaseLog(output_path + \"log_cases.csv\")\n",
+      "sim_log_1 = SimulationLog(output_path + \"log_simulation.csv\")\n",
+      "opt_log = OptimizationLog(output_path + \"log_optimization.csv\")\n",
+      "prod_log = ProductionDataLog(output_path + \"log_production_data.txt\")\n",
+      "\n",
+      "case_container = CaseContainer(case_log, name_map)\n",
+      "optimizer = Optimizer(opt_log, case_container)\n",
+      "\n",
+      "y2 = []\n",
+      "for case in optimizer.best_case_pr_iteration:\n",
+      "    y2.append(case.objective_function_value)\n",
+      "    \n",
+      "from matplotlib import pyplot as plt\n",
+      "plt.plot(y2)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 12,
+       "text": [
+        "[<matplotlib.lines.Line2D at 0x7f49ca7c0400>]"
+       ]
+      }
+     ],
+     "prompt_number": 12
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [],
+     "language": "python",
+     "metadata": {},
+     "outputs": []
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}