From 26e1cbebb2a5149ad0b9e8cf96b160a203bce60f Mon Sep 17 00:00:00 2001
From: alphagammamle <lelandphd@gmail.com>
Date: Sun, 2 Apr 2017 02:11:38 -0400
Subject: [PATCH 1/2] State Transition Matrix update

A easier to read or possbile faster way to compute the state probability
transition matrix
---
 Data Generation and Likelihood Fit.ipynb | 35 +++++++-----------------
 1 file changed, 10 insertions(+), 25 deletions(-)

diff --git a/Data Generation and Likelihood Fit.ipynb b/Data Generation and Likelihood Fit.ipynb
index 22e3804..0136a1e 100644
--- a/Data Generation and Likelihood Fit.ipynb	
+++ b/Data Generation and Likelihood Fit.ipynb	
@@ -32,6 +32,7 @@
     "import random as rnd\n",
     "import scipy.stats as stats\n",
     "import scipy.optimize as opt\n",
+    "import scipy.sparse\n",
     "import json as json\n",
     "import matplotlib as mpl\n",
     "from math import exp\n",
@@ -526,17 +527,8 @@
     "    # Initialization of the state-transition matrices: describe the state-transition probabilities\n",
     "    # if the maintenance cost is incurred, and regenerate the state to 0 if the replacement cost\n",
     "    # is incurred.\n",
-    "    ST_mat = np.zeros((S, S))\n",
-    "    p = np.array(p) \n",
-    "    for i in range(S):\n",
-    "        for j, _p in enumerate(p):\n",
-    "            if i + j < S-1:\n",
-    "                ST_mat[i+j][i] = _p\n",
-    "                \n",
-    "            elif i + j == S-1:\n",
-    "                ST_mat[S-1][i] = p[j:].sum()\n",
-    "            else:\n",
-    "                pass\n",
+    "    ST_mat=scipy.sparse.diags(p, range(len(p)), shape=(S, S)).toarray()\n",
+    "    ST_mat[-2:,-1] = [1 - p[1], 1]\n",
     "    \n",
     "    R_mat = np.vstack((np.ones((1, S)),np.zeros((S-1, S))))        \n",
     "            \n",
@@ -1211,15 +1203,8 @@
     "        # A (SxS) matrix indicating the probability of a bus transitioning\n",
     "        # from a state s to a state s' (used to compute maintenance utility)\n",
     "        \n",
-    "        self.trans_mat = np.zeros((S, S))\n",
-    "        for i in range(S):\n",
-    "            for j, _p in enumerate(self.p):\n",
-    "                if i + j < S-1:\n",
-    "                    self.trans_mat[i+j][i] = _p\n",
-    "                elif i + j == S-1:\n",
-    "                    self.trans_mat[S-1][i] = p[j:].sum()\n",
-    "                else:\n",
-    "                    pass\n",
+    "        self.trans_mat=scipy.sparse.diags(p, range(len(p)), shape=(S, S)).toarray()\n",
+    "        self.trans_mat[-2:,-1] = [1 - p[1], 1]\n",
     "\n",
     "        # A second (SxS) matrix which regenerates the bus' state to 0 with\n",
     "        # certainty (used to compute the replacement utility)\n",
@@ -2141,21 +2126,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 2",
    "language": "python",
-   "name": "python3"
+   "name": "python2"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 3
+    "version": 2
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.4.3"
+   "pygments_lexer": "ipython2",
+   "version": "2.7.13"
   }
  },
  "nbformat": 4,

From 252987d3ed93aa6530559b189954260bfaa670bc Mon Sep 17 00:00:00 2001
From: alphagammamle <lelandphd@gmail.com>
Date: Sun, 2 Apr 2017 02:24:56 -0400
Subject: [PATCH 2/2] Update Data Generation and Likelihood Fit.ipynb

---
 Data Generation and Likelihood Fit.ipynb | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/Data Generation and Likelihood Fit.ipynb b/Data Generation and Likelihood Fit.ipynb
index 0136a1e..b65c144 100644
--- a/Data Generation and Likelihood Fit.ipynb	
+++ b/Data Generation and Likelihood Fit.ipynb	
@@ -2126,21 +2126,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 2",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "python2"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.13"
+   "pygments_lexer": "ipython3",
+   "version": "3.4.3"
   }
  },
  "nbformat": 4,