diff --git a/NewProtofish.ipynb b/NewProtofish.ipynb
index f532332..68d5f99 100644
--- a/NewProtofish.ipynb
+++ b/NewProtofish.ipynb
@@ -77,7 +77,22 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "┌ Info: Precompiling NLopt [76087f3c-5699-56af-9a33-bf431cd00edd]\n",
+ "└ @ Base loading.jl:1273\n",
+ "┌ Info: Precompiling DataFrames [a93c6f00-e57d-5684-b7b6-d8193f3e46c0]\n",
+ "└ @ Base loading.jl:1273\n",
+ "┌ Info: Precompiling SpecialFunctions [276daf66-3868-5448-9aa4-cd146d93841b]\n",
+ "└ @ Base loading.jl:1273\n",
+ "┌ Info: Precompiling PyPlot [d330b81b-6aea-500a-939a-2ce795aea3ee]\n",
+ "└ @ Base loading.jl:1273\n"
+ ]
+ }
+ ],
"source": [
"include(\"./src/WatchFish.jl\")\n",
"using .WatchFish"
@@ -97,11 +112,44 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 2,
"metadata": {
"scrolled": false
},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
Name Fit Interval_Low Interval_High String Float64 Float64 Float64 4 rows × 4 columns
1 Bkg 1 30.0 30.0 30.0 2 Bkg 2 40.0 1.0 67.0 3 Bkg 3 12.0015 1.00146 23.0015 4 Signal 17.9979 -23.0021 58.9979
"
+ ],
+ "text/latex": [
+ "\\begin{tabular}{r|cccc}\n",
+ "\t& Name & Fit & Interval\\_Low & Interval\\_High\\\\\n",
+ "\t\\hline\n",
+ "\t& String & Float64 & Float64 & Float64\\\\\n",
+ "\t\\hline\n",
+ "\t1 & Bkg 1 & 30.0 & 30.0 & 30.0 \\\\\n",
+ "\t2 & Bkg 2 & 40.0 & 1.0 & 67.0 \\\\\n",
+ "\t3 & Bkg 3 & 12.0015 & 1.00146 & 23.0015 \\\\\n",
+ "\t4 & Signal & 17.9979 & -23.0021 & 58.9979 \\\\\n",
+ "\\end{tabular}\n"
+ ],
+ "text/plain": [
+ "4×4 DataFrames.DataFrame\n",
+ "│ Row │ Name │ Fit │ Interval_Low │ Interval_High │\n",
+ "│ │ \u001b[90mString\u001b[39m │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m │\n",
+ "├─────┼────────┼─────────┼──────────────┼───────────────┤\n",
+ "│ 1 │ Bkg 1 │ 30.0 │ 30.0 │ 30.0 │\n",
+ "│ 2 │ Bkg 2 │ 40.0 │ 1.0 │ 67.0 │\n",
+ "│ 3 │ Bkg 3 │ 12.0015 │ 1.00146 │ 23.0015 │\n",
+ "│ 4 │ Signal │ 17.9979 │ -23.0021 │ 58.9979 │"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"m = CountingExperiment()\n",
"\n",
@@ -120,9 +168,35 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 3,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "Figure(PyObject )"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "(y[x .>= low])[1] = 0.6901178106433539\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "findfont: Font family ['Nimbus Roman Italic'] not found. Falling back to DejaVu Sans.\n",
+ "findfont: Font family ['Times New Roman Bold'] not found. Falling back to DejaVu Sans.\n"
+ ]
+ }
+ ],
"source": [
"using PyPlot\n",
"plt.style.use(\"fish.mplstyle\")\n",
@@ -138,9 +212,20 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 4,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "Figure(PyObject )"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
"source": [
"using PyPlot\n",
"\n",
@@ -151,7 +236,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
@@ -160,7 +245,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 6,
"metadata": {
"scrolled": false
},
@@ -196,9 +281,27 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 7,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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19fVqbm6O6v1ZF2INw6ADCwCAFJfuayC6r4hWsDwWbnQ2EOvEAgCQjeKw7msf3w0MWPcViZJ1I7EAAGS9OKz72ifUJC7WfcVwI8QCAJBt4tB9lcJvYED3FcONOgEAANnA5ZD2brTu+7qvvmLsvkrhJ3EBw40QCwBApgvsv+5+YcjdV6l/EpcvJnEhUagTAACQyUL1Xxdvt25D7L6ygQGShRALAEAmC9d/rZ0z5O4rk7iQLIRYAAAyyTCs/coGBkhFdGIBAMgUcVr7le4r0gEjsQAAZII4rf1K9xXpghALAEAmiMPar3RfkU4IsQAApCO6r8hydGIBAEg3dF8BRmIBAEgrdF8BSYRYAADSC91XQBIhFgCA9EL3FZBEJxYAgNTnckh7N1r3g+i+Sv79V7qvyASMxAIAkMq2runvwBo2K8DG0H2Vgvdf6b4i3RmmaZqRT0t/NTU1cjgcqq6uVlNTU7IvBwCAyFwOa/WBwOrA4u0Rg2sfp6tTs1ds8KsP2A1DDUvnSRLdV6SUWPIaI7EAAKSqSJO4ohCu/zqrrpzwirRFJxYAgFTh232V+idx+YowiYu1X5EtCLEAAKSCOGxgsHbLfs1esUHX/GazZq/YoLVb9quypEDLF06R3bCSLP1XZArqBAAAJFscNjBg7VdkG0IsAADJFocNDFj7FdmGOgEAAIlG9xUYMkIsAACJRPcViAvqBAAAJArdVyBuCLEAACQK3VcgbgixAAAMJ5fDCq9ldf3d18AduMJ0XyVr9HVvS4dqK4q83dfAHbjoviLbEGIBABguW9f01wcMm9V7XbDaqhCY7ojdV8nqv/bVB2yGtHzhFC1fOEXL1u2Q2zTpviJrGaZpmpFPS3+x7MULAMCQuRzWxK3AUdfF263HEbqvkjUCO3vFhgGjrg1L50kS3VdknFjyGiOxAAAMh3D919o5EbuvUvj+66y6csIrshpLbAEAEA+s/QokFCEWAIChYu1XIOGoEwAAMBSs/QokBSEWAIChYO1XICmoEwAAEIs4dF8D0X0FYkeIBQAgWnHovkoDJ3DRfQViR50AAIBoxKH7KgXfvGDRjPF0X4EYEWIBAIhGHLqv4SZw0X0FYpP2dYLu7m794Q9/0PTp0/XUU08l+3IAAJnEt/8ah+5ruAlcAGKTtiOxLS0teuihh/TAAw/I6XQm+3IAAJlm65r++oBhs3qvC1ZbFQLTHVX3VbJGX/e2dKi2osg7gStwG1kmcAGxS8sQu23bNj3++OM6cOAAARYAEH+h+q+Lt1u3KLqvUvD+6/KFU7Rs3Q65TZMJXMAQpGWInTZtmqZNmyZJevLJJ/Xxxx8n+YoAABklXP+1dk7E8CqF7r82LJ2nhqXzmMAFDFFahlhfhYX8FQwAYIhcDiu4ltVZAbWv/+obZOPYf51VV054BYYo7Sd2AQAwJMO09isbGADDK+1HYgEAGLRhXvuV/iswfAixAIDsNcxrv7KBATB8CLEAgOw1zN1XNjAAhg+dWABA9vDdvECi+wqkMUZiAQDZIdjmBdOvpfsKpClCLAAg84WbwEX3FUhLaR9iT5486X3c3d2dxCsBAKSsSBO4okD3FUgtce3EulwurVy5UrW1tXr22Wcjnu92u/Xwww9r5syZKigoUGlpqb7whS9o/fr1Uf283bt36/Dhw97nr7zyyqCvHQCQQQK7r30TuHxFMYHLt/9K9xVILXEJsbt27dJNN92k6upq/fCHP9S+ffsivqe1tVUXXXSRbrzxRo0ePVrbtm3TY489pi1btujSSy/VrbfeGvK9r776qqZOnapzzjlHHk//f1mvWrVKZ555pv7zP/8zHl8LAJCO4rR5wdot+zV7xQZd85vNmr1igzY2fqzlC6fIblhJlu4rkFyGaZpm5NMGMk1Tzz//vFatWqVnn31WgR/zv//7v/r85z8f9L0ej0cXX3yxXn75ZUnSzp07ddZZZ0mSli5dqp///OeSpJ/85Ce68847B3N5A9TU1MjhcKi6ulpNTU1x+UwAQIpxOazgGrhk1uLtVmB1OaKawOV0dWr2ig1+9QG7Yahh6TxJovsKDJNY8tqgR2KXLFmiDRs26Pzzz1dZWVlM733kkUe8Aba0tNQbYCVp5syZ3sfLly/X3r17B3uJAIBsE677KlnBtXZOxB5spP7rrLpyAiyQZIOe2HXvvfd6H0+aNEnXXXfdoN5bUVHh91p1df8/WHp6erRixQo99NBDg73MAZxOp2pqaiKet2TJEi1ZsiRuPxcAMExcDiu8ltUNevMCp6tTe1s6VFtRpMqSAm//NXAklv4rMDgrV67UypUrI57ndDqj/sy4rE4QTSjss3//fr377rve54WF/v9AGDFihN/zdevW6cEHH5Tdbh/aRZ7i8XjkcDginnfs2LG4/DwAwDAKtvbrgtXW8lmmO+ruK2u/AsPr2LFjUeWvWMQlxNps0bcSXnrpJb/neXl5fs8Dw2pLS4t27NihadOmDfr6fNlsNlVWVkY8b9SoUXH5eQCAYRJq7dfF261blN1X1n4Fht+oUaP8/rY9FKfT6TdpP5yErxPb0NDg9zw3N9fvebBA/Oabb8YtxFZWVjKxCwAyQbj+axS9V4m1X4FEibam2TexKxpxXSc2GoEXFjjyahgBi/BJUS3ZBQDIcHFY+9V33VdJrP0KpLGEh9gjR474X0AUVYTA9wAAskwc1n4NXPd17Zb9qiwpYO1XIE0lvE7Q2trq9zxw5DXYSKzv1rIAgCwTqvtaN1+afq11H6H/SvcVyDwJD7H5+flhX3e73QOOlZaWDtflAABSXbjua0l1/y0Muq9A5kl4nSDSxgjBZqSVl5cP1+UAAFIN3VcAUUj4SOyECRO0ceNG7/PA0BpsJLaqqipuP980TXV0dPgdKyoqitvnAwCGINi6r9OvjWntV9Z9BdJDYB6TrJwWrYSH2JkzZ2rNmjXe5729vX6vBxuJ/dSnPhW3n9/c3Kzi4mK/Y7H8gQEAhgndVyCrBOaxWCU8xM6ZM8fveWdnp9/zwJHYyspKTZo0adivCwCQZHRfAcQg4Z3YqVOn6pxzzvE+d7lcfq8HjsRedtllcf35VVVVam9v97sBAJLEt/86iO6r5N9/pfsKpI/APNbe3h5ThTQuI7HBlsDq6ekJef5tt92m6667TpJ06NAhmabpXVqrubnZe57dbtf3v//9eFyil2EYdGABIBUE67/G0H2Vgvdf6b4C6SFYHgu21GoocQmxH3300YBjBw4cCHn+N77xDf3pT3/S008/rRMnTujdd9/VueeeK0navHmz97xly5bp7LPPjsclAgBSSaj+6+Lt1i1C91UK3X9tWDpPDUvn0X0FMtyg6wRHjx7Vnj17tG7dOt11110DXr/77rv1xBNPaN++fQN6rzabTX/84x81f/58SdKtt96q999/Xy+99JIefvhhSdLNN9+sO++8c7CXBwBIZZH6r7Vzhtx/nVVXToAFMtigQ+w3v/lN1dXV6aqrrpLD4RjwusPh0BVXXKHa2lqtXbt2wOsjR47Uc889p1//+tc6cuSIZsyYoYULF+rCCy/Uc889p1WrVsU0pAwASGFxWPs1EP1XILsZZpasL1VTUyOHw6Hq6mo1NTUl+3IAIHuEWvt165qB/dfp14b8GKerU3tbOlRbUeQdYV27Zf+A/uuiGeMT9c0AxFkseS3hS2wBALJIHNZ+lUJvYMDar0D2yroQy45dAJBAcVj7NdwGBqz9CqSvtNuxK9nYsQsAhpHLYQXXsjornPZ1X32DbIzd10gTuACkp6Hu2JXwzQ4AABlq6xpp1bnSowus+61rrCC7YLUVXKWo1n713bxAYgIXgOCybiS2qqpKjY2Nyb4MAMgsw9x9ZQMDIPME2zW1vr7eb+OrcLIuxLJjFwAMg2HuvjKBC8g8KbFjFwAgC/n2XxPQfWUCFwBfhFgAQOyCrf26YPXAdV+jGH3tW/u1r/vqG2TpvgIIhRALAIhNqP7r4u3WLYruqxS8/0r3FUC0CLEAgNiE67/WzokYXqXQ/deGpfPUsHQe3VcAERFiAQCxGeb+66y6csIrgIhYJxYAEJ7LIe3daN1LrP0KICUwEgsACC3YBK7p17L2K4Cky7oQa5rmgL16WTcWAIIIt4EBa78CGKLAPCZZOS1aWRdim5ubB+zVG8sfGABkjUgbGESBtV8BhBKYx2JFJxYAYAnsvvZN4PIVYQIX3VcAiZJ1I7FVVVVqbGxM9mUAQGoJ1X2NYQMDuq8AYtHe3j7gWH19vZqbm6N6v2Fmyd+l19TUyOFwqLq6Wk1NTcm+HABIHS6HtOrcgUtmLd5uBVaXI+IELqerU7NXbBiw21bD0nmqLCmQ09VJ9xVARLHktawbiQUABIjUfY1iAhfdVwCJRogFgGzjcljBtazOCqeD3LzA6erU3pYO1VYUebuvgSOxdF8BDBdCLABkkzh0X6Xg/Ve6rwASiU4sAGSLOHRfpfD9V0l0XwEMGp1YAMBAcei+SuH7r7PqygmvABKCEAsAmcy3/xqH7mtlSQH9VwApgRALAJkqWP81Dt1X1n4FkAroxAJAJgrXf5WG3H1l7VcAw4FOLABku3D919o5Q+6+svYrgGTLuhBrmqY6Ojr8jhUVFSXpagAgTuKw9ivdVwCJFJjHJCunRSvrQmxzc7OKi4v9jmVJowJAporD2q90XwEkWmAei1XWdWKDyZI/AgCZKA5rv9J9BZAMhmGEfI1ObBBVVVVqbGxM9mUAQHzEYe1Xuq8AkqG9vX3Asfr6ejU3N0f1/qwLsYZh0IEFkL7ovgLIEMHyWLjR2UC2eF4MAGAYbV1jVQceXWDdb11jBdkFq63gKkXVfZ29YoOu+c1mzV6xQWu37FdlSYGWL5wi+6l/edB9BZAOsm4kFgDSksvRP3lLsu6fXCzVzbcmcdXNj6r72jd5S7JGXpet26G59WO0aMZ4za0fQ/cVQNogxAJAOqD7CgB+CLEAkKp8+6+D6L4GovsKIJPQiQWAVBTYf939Qkzd1z5OV6c27W6R09VJ9xVARmEkFgBSTaj+6+Lt1i1C97VPqA0M6L4CyASEWABINeH6r7VzIoZXKfwkLrqvADIBdQIASDaXQ9q70bqX+vuvvmLsv4abxAUAmYAQCwDJFIe1XyX/7qvUP4nLF5O4AGQS6gQAkCxxWPtVCt19Xb5wipat2yG3aTKJC8giHtMz4GbK7H9smvKo/7HbdPsdkym/1z2mR2eUnKFcW26yv5ofQiwAJEsc1n5lAwMgONM01evpVY+np//m7gn6vNfTa93MXuuY6XPM5+Y23erx9MjtcavX7PW/P/V6373vax7TM+Cxx/TI7XF7z3Wb1mu+926PW6askOnx9L/mkUcej8cbNN0et/exJ/CfKXGy/qr1qiyuHJbPHqysC7Gmaaqjo8PvWLC9ewEg7nzXfS2pjsvar2xggFTmMT066T6prt4udfV2qdPd6X3c5e7Syd6T1us+j/tu3e7uAY+73d3q9vg8PvXc97FvUEV4hgzZDJsMw5DdsMuQIcOwjtlkHTcMw/s43gLzmGTltGhlXYhtbm5WcXGx37FY/sAAYFC2rumvDhg2q/M6/Vrr/snF1ghslN3XvS0dqq0oUmVJARsYIG48pkedvZ1q725XR0+Hdeu17k/0nPAeO9F7Qid6Tqizt1Mnek+os+fUfW+n99b3epe7K9lfy8uQoTx7nnJtud5bji1HufZc5Rg5yrH13/pe83t+6hy7zW7dG8Hvc2w5shk25dpyZTNs3uMDHtvsshv9t77XbTbbwGOGze/m+5o3gJ66DzzX79YXTH3CazIF5rFYZV2IBYCEo/uKBPCYHh3vPq5j3cd07OQxubpdfs+PdR9Te3e7jncf1/Ge42rvbld7j/W8L6CaGr5BnTxbnkbkjNAI+wiNyBmh/Jz8/sd263F+Tr7y7fnKs+Up356v/Jz+x3n2/vs8e573eK491/u87z7Xfiqo2nOVZ8vzhktklqz7X7SqqkqNjY3JvgwA2YTuK2Lk9rjVdrJNR7uOqrWrVa0nW9XW1aa2kz63rja5Trrk6nbJddIKrPEIoXbDrqLcoqC3wpxC6z63UAU5BSrMKfQ+DnYbkTNChTmFyrfny26zx+FPBrTp9f4AACAASURBVJmkvb19wLH6+no1NzdH9f6sC7GGYdCBBZBYdF8hqcfToyOdR3Sk84haOlvU0tmiI11H1NrVah3vOqLWzla1drWq7WTboANpQU6BRuaN1Ki8UdYtf1T/47xRKs4rVnFusUbmjVRxXrFG5o5UUW6RivOKVZRbpBH2EUn/a2Zkh2B5LJbfvawLsQCQEIGTuGLsvkr+/Ve6r6nLNE21nWzTwY6DOnzisA6dOKTDJw57b4dOHNKRziM6evJoTJ9ryFBJfolGjxit0fmjVTaiTCX5JSrNL9XoEaO9j0vyS1SSV+INq3n2vGH6pkBqIcQCQLyFmsQVZfdVCt5/pfuaHCd6TsjZ4ZSzw6nm9mYd7DgoZ4dTh04c0sGOgzrUcUjdnu6oPivHyFFZQZkqCipUUVCh8hHlKhtRpvKCcutxQZnKRli30vxSepxAGIaZJVPza2pq5HA4VF1draampmRfDoBM5XJYO28FVgcWb48YXPs4XZ2avWLDgFHXhqXzJInua5z1eHp0sP2gmtqbrNvxU7f2JjnaHXKddEX1OeUjynVa4WkaWzhWpxWe5r2NLRyrikIrtJbml8oWuKUwAK9Y8hr/iQcA8RRpElcUwvVfZ9WVE14HobO3U/uP7de+Y/t04PgBv6Dq7HBGXCB+ZN5IVRZVem/jisZpXNE4jS0cq3FF43Ra4Wn8NT6QYIRYABiKOGxgwNqv8WGapo50HdGetj3a7dqtPW179NGxj7Tv2D45O5xh35tvz1dNcY1qRlq36uJq1RTXqHpktaqKqlScN7T1LAHEHyEWAAYrDhsYsPZr7EzT1OETh7W7bbc+bPtQe1x7tLttt/a49uhY97GQ7xuVN0oTSibojJFn6PSRp3sDa01xjSoKKpiRD6QZQiwADEYcNjBg7dfIjncf1wdHP9Cuo7u0q3WXFVrb9uh4z/Gg59sMm2qKa3RmyZmqLa1V7ahaTSiZoAmjJqg0v5SgCmQQQiwADEYcNjBg7dd+pmnK0e7QrtZd2nV0l95vfV+NRxvlaHcEPd9u2DV+1HjVldSprtS6nVlypiaUTFC+PT/BVw8gGQixABANuq9x4zE9+ujYR9rRskM7WnZ4A2t7z8DdeyRpbOFYTS6brMmjJ2vS6EmqK63ThFETmEgFZDlCLABEQvd1SD4+8bG2t2zXjpYd2t6yXe+2vBu0DpBry9XE0omqH13vDa31o+tVOqI0CVcNINURYgEgHLqvMTnRc0I7j+zU9pbt3tvBjoMDzsu35+ussrN0bsW5Orv8bE0um6zaklrl2nKTcNUA0hEhFgDCofsakmmaampv0raPt2nb4W3a9vE2NR5tlNt0+51nyFBdaZ2mVEzRlDFTNKViiupK6wisAIaEEAsAgXz7r4Povkr+/ddM6b6apqm9rr3acnCLthzaojcOvqEjXUcGnHdawWnesDp1zFSdXX62inKLknDFADIZIRYAfAXrv8bQfZWC91/TsftqmqY+OvaRNjs3a8uhLdpycItau1r9zsmx5ejssrM1dcxUTTttms4bc57GFY1L0hUDyCaGaZpm5NPSXyx78QLIUi6HtOrcgaOui7dbjyN0XyVrBHb2ig0DRl0bls6TpJTvvh7qOKTNBzdrs9O6HTpxyO/1fHu+zhtzni4Yd4EuGHuBpoyZwpJWAOImlryWdSOxpmmqo6PD71hREX/NBUDh+6+1cyJ2X6Xw/ddZdeUpF17butr0+sHX9frB17XZuVn7ju3zez3XlqvzTjtPM8bN0MxxMzWlYgpLWwGIi8A8Jlk5LVpZF2Kbm5tVXOy/B3aWDEYDCJSFa792u7v15qE3tal5kzY7N+v91vdlqv9ibYZNZ5edrQsrL9SFlRfqvNPOU0FOagVvAJkhMI/FKutCLABIyqq1X5vbm9XgaNArjle02blZnb2dfq9PLJ2oCysv1MxxM3XBuAs0Km9Ukq4UAKKXdZ3YqqoqNTY2+r1GnQDIMuG6ryXVp0ZoI6/9Gqr7WllSIKerM2n91x5Pj94+/LZeaXpFG5s2ardrt9/rYwrGaHb1bM2qnKWZlTNVUVCR0OsDACl4naC+vl7Nzc10YoMxDIPQCmS7DFz7ta2rTa84rND6t+a/6Xh3/45YdsOuaWOmaU7NHH26+tOaPHqyDMNI2LUBQDDB8lgs/2zKuhALIAvFofsaKBW6rweOH9CL+1/Uiwde1NbDW+Xx+T6l+aWaUz1Hc2vmalbVLJXklyTsugAgEQixADJbHLqv0sAJXJUlBQnvvpqmqV1Hd+mvH/1VLx54UY1H/atR9aPr9Zmaz2huzVxNqZgiu80+bNcCAMlGiAWQuVyO/gArWfdPLpbq5ltBtm5+VGu/hprAtWjGeM2tHzOs3VfTNLWjZYee3/+8nt/3vJra+ztidsOu88eer4vHX6yLTr9I1cWRlwADgExBiAWQueLQfXW6Or0BVrLqA8vW7dDc+jHD1n31mB698/E7Wv/Rev31o7/K2eH0vpZvz9enqz+t+ePna27NXGoCALIWIRZA5hiG7mukCVzx4va49fbHb2v9Piu4Hu487H2tIKdAn6n5jD57xmc1p3qOCnNTY81ZAEgmQiyAzBCn7qvk338dzglcpmnqnZZ39MyeZ7T+o/Vq6WzxvlacW6yLTr9Inz3js5pdNVsjckYM+ecBQCYhxAJIf3HqvkrB+6/xnsC1p22Pnt77tJ7Z84xfx3Vk7kjNGz9Pl5xxiWZVzWJ7VwAIgxALIP3Fofsqhe6/Niydp4al84Y0gauls0VP73laT+95Wu+1vuc9XpBToIvHX6wv1n5Rn6z8JMEVAKJEiAWQnnz7r3Hovkrh+6+z6spjDq8n3Sf14oEX9f8+/H/a1LxJbtMtScoxcjS7era+WPtFXXT6RXRcAWAQCLEA0k+w/usQu6+VJQVx6b+apqltH2/TE7uf0HN7n9Pxnv6ds6ZWTNWCugW6dMKlGj1idMxfGwDQjxALIL2E6r8u3m7dhtB9XTRj/KD7rwc7DurJ3U/qid1P6KNjH3mPjysapwVnLtCCugWqLakd0lcHAPQjxAJIL+H6r7VzhtR9nVs/JqYNDLp6u/TC/hf0xIdP6DXnazJlfWBBToE+d8bndFndZZoxboZshm3QXxcAEBwhFkBqS8Lar5E2MHi/9X2t+2CdntrzlI5399cFLhh7gS6feLk+d8bnVJRbFPX1AABiR4gFkLritPZrPLqvx7uP65k9z2jdh+u088hO7/GqoipdPvFyXVZ3mWpG1sTlawMAIiPEAkhNcVr7dajd1/eOvKe1u9bqmb3PqLO3U5KUY8vR/PHztXDSQn2y8pPUBQAgCQixAFJTHNZ+HWz3tau3S8/te05/2vUnvdPyjvd4XUmdrqq/Sl8+88usLgAASUaIBZCaktB93efapz83/llP7H5CrpMuSdao6+fGf05XT75a5489X4ZhDOlrAQDigxALIDUETuAqqU5I97XH3aMNBzboz7v+rM0HN3uPVxVV6auTv6orJl6hioKKYfnKAIDBI8QCSL5QE7iGsfvqaHfoscbHtO6DdTrSdUSSZDNsmls9V1+d/FXNrpotu82eqD8BAECMCLEAkivcBK44d19PL8/XnvatuumF/6uNTRu967qOKRijhZMW6qpJV6myuHI4vy0AIE6yLsSapqmOjg6/Y0VFrOcIJE2kCVxRiNR9zc/v1M4T/6M73/6zHO0O7zkXVl6oRZMX6aLTL1KuLXeo3wQAEIPAPCZZOS1aWRdim5ubVVxc7Hcslj8wAHHg238d5AQu3/5rqO6rJ9ehn/xttZ7e87S6Pd2SpJF5I3XFxCt0df3VmlAyYRi+HAAgGoF5LFaGmSUJrqamRg6HI+hrWfJHAKSGYP1XaeAErunXhvyIYP1XSae6r27ljdyl+vq39NGJ/uWxzi4/W1+b/DV9vvbzKsgJvRsXACAxwq32Ul1draampvDvz7YQW1VVpcbGRr/XqBMACeJySKvOHTjquni79TiKCVxOV6dmr9gwYNT1+Vs+qfX7n9SfGv8/fdzVfOq4XfPHz9c3z/6mpo2ZxvJYAJBCgtUJ6uvr1dzcHFWIzbo6gWEYhFYgWcL1X2vnRNWBDey/GjnHZB/9qv7+2Z/pRO9xSVZl4Cv1X9HfT/57JmoBQIoKlsdiGWzIuhALIIEC134dRP811NqvyjuovLJXlDPqbRk2t070SqePPF3fPPuburzuchXmFob8TABA+iPEAhgeodZ+jWEDg8Du691XnquJ4z/WtAv+og/b3/CeV1Nwtm658AZddPpFrO0KAFmCEAsg/sKt/RrlBgb+a796ZCt6T3dtfVD29/ZLkgwZ+rvyObrunOt0ce3MxHwvAEDKIMQCiL9Ia79GsYGB1X11K6fkLeWVvyx7/seSpBwjV1dOukLXn3O9xo8aP1zfAACQ4gixAIYuzt3X8mK7dravV1Hdr2XLOypJMt0j1Ht0lv77G7fqnLGnD/c3AgCkOEIsgKGJZ/dVPcorfUMVNX/T8d4W2fIks7dYJ4/Mkcf1Sd19xQUEWACAJEIsgKGIV/f1fzYrZ/QW5ZY1yJZ7XMd7pfIRY/TdKd/W7LFf0sE2jyZUFKqyhE0KAAAWQiyAwRti93X/sf36xebfqnDi0zJs1rawnp4SdR+5SHct/D+aO6lKklRbPmzfAACQpgixAGLj238dRPfVNE2t37NJf9j5B73TukmmTBk2yd01Tt2tn1av6zzZjVxNOm10Ar4MACBdEWIBRC9Y/zWG7usbB9/Q7a+s1P4T273HJhZfoAvLrtRv1tvlNq0tZO9eeC7VAQBAWIRYANEJ1X9dvN26hem+vn34bd3/9v3a7Nx86q129bjOV0/rp/VOz1g9uHSerpsu7Ws5QfcVABAVQiyA6ITrv9bOCRpe3/n4HT247UH9zfE3SZLdyFFn6wXqbrlIZm9p34doX8sJzaorJ7wCAKJGiAUQ3CDXfjVNUw2OBj3y7iPacnCLJMlu2HXFxCt0+YRv6qr73pdp9p9vNwxNqChMxDcCAGQQQiyAgQax9muvp1fP7XtOj+x4RLuO7pJkhdeZYz6nG6fdoPOrJkmSli/M1bJ1O+Q2TfqvAIBBM0zTd0wkc9XU1MjhcKi6ulpNTU3Jvhwgdbkc0qpzB464Lt5uBVaXw6//2uPp0eMfPK7f7/i9HO0OSVJBToGmjrpUL77+Cbl7SmUzpOULp2jRDGubWKerk/4rAGCAWPIaI7EA/EW59qvb49b/7nlKD779oA4cPyBJKhtRpms+cY0uqrpcX1j5pjyn/hPZY0rL1u3Q3Poxqiwp8N4AABgsQiyQ7WLsvpqmqRcPvKj73rpPH7Z9KMkKrzdMvUFXTbpKI3JGaNPuFm+A7eM2rQlchFcAQDwQYoFsFkP31RxVpVebN+mBtx7QOy3vSJJG5o3Ut8/9ti6uWqiDbR4d7TBVWSLVVhTJZsgvyDKBCwAQT4RYIFuFWve1br4VZOvme7uvb3Q6df9z39Kbh96UZHVev3HWN3TdOdfp2Xdc+uw9r8pjyq/7unzhFCZwAQCGDSEWyFZRdF/f6T6i+zffqVedr0qScm25WjR5kb4z5TuqKKiQ09WpH6/bHrT7umjGeM2tH8MELgDAsCDEAtnEt/8apvu6p22P7t16r1468JIkKcfI0cJJC/UPU/9B44rGeU/f29IRtvvKBC4AwHAhxALZIlj/NaD7euQL/6ZfvfeI/tL4F7lNt2yGTZfVXaYbp96ompE1kqzlsfa2dKi2oojuKwAgaQixQDYI1X9dvF1avF0nW3bpD61v67cfPKqOng5J0rzT5+kH5/9AtSW13o9Zu2W/tz7Q13+l+woASAZCLJANQvRfe1oa9ZSnTb/a9is5O5ySpLPKztKtM27VjHEz/E4P1X9tWDpPDUvn0X0FACQUIRbIRBHWfm03DP1l1Cj94Y07dbjriCRpbOFY3Tz9Zn3pzC/JZtgGfGS4/uusunLCKwAgoQixQKYJs/brx88s0X+OLNSfRo1Uu80mdR3RmIIx+ubZ39TXPvE1FeT0B1Hf7mtlSQH9VwBASiHEApkkRPfVdfpMPew+pD+eMV49nh5J0pklZ+r6c67Xl878kvLseX4fE6z7ytqvAIBUQogFMklA97VH0tqRhfr1+uvl6rUmbP3daX+nb5/7bc2tmRu0NsDarwCAdECIBTLJqe6raXr0YmGBVpaV6qPcXKm3QxNLJ+qWC27R7OrZYT+CtV8BAOmAEAuks8AJXCXVeuviW/XvO/9Db4zIlySV5RTqn2bcqismXqEc28D/y9N9BQCkI0IskK4CJnC9M/9HeqBzrzY1b5JG5CvflqtrJ16l71ywWEW5RUE/gu4rACBdZV2INU1THR0dfseKioL/Cx5IWT4TuN7Ny9WDo0u1cfd/SbK2iL1y0pW6YeoNflvEBqL7CgBIpsA8Jlk5LVpZF2Kbm5tVXFzsdyyWPzAgJbTu1gc5dt0/ukwbiqy/5rebpi4b9yndMPsn3i1iw6H7CgBIpsA8FqusC7FAWvLpvu433Hpwz1/0TPU4mYYhm2nqS+0ndKPruM648nZpZHXIj/Htv9J9BQCks6wLsVVVVWpsbEz2ZQDRO9V9PWgz9NDoEv3PyFHqlUcyDH2uo1M3HT2qM3tNacEqa3JXCMH6r3RfAQDJ0t7ePuBYfX29mpubo3p/1oVYwzDowCJ9uBw6+vQP9NvRo/TfI0eq22ZI8ujTY2fon2bcorNzSqTWPVLZmWEDbKj+a8PSeWpYOo/uKwAg4YLlMcMwon5/1oVYIF109HRozVv36dGaceqwWZsSTO/q0s2tLk2f+y2p/GzrxDDhtU+4/uusunLCKwAg7RBigRTT3bpXf965Rg8feF6t3S7JZtMnTnbr+0fb9OnOLhmG3Rp5DYO1XwEAmY4QC6QIt8etJ1/8sX6170k151j/1zwjb7RuGvtpXfLKr2Uz3ZJhH1T3lbVfAQCZhhALJJlpmvrr/r/q/jdXac/x/VJOjk7r7dU/trl0RbtDuV/8o3T+94bUfWXtVwBApiHEAklimqZebX5Vq99arZ1HdkqSStxufbftmBYdb1dB3/rFrXuk2jlD7r6y9isAIJMQYoEkaOls0b+8dIv+dvhNSVJhTqGurbtS167/vxrpcfefGKH/SvcVAJCtCLFAgm1q3qQfv/gDtfaeUJ7H1NeOt+s7n/yeymb+o5RXJT25WIqi/0r3FQCQzQixQIL0enr1wNsP6HfbfydTpupPdusXH7fozJ5e6X+XSZMXSNOvlermR+y/0n0FAGQ7QiyQAAc7Duq2jbfprcNvSZKuPnZct7a2aURf79V0W8G1pLr/FgbdVwBAtrMl+wKATNbj6dG6bb/TV/7nCr11+C0V5xbrnhnL9K+trv4AK0XVfd20u0VOV6ckebuvvui+AgCyCSOxwDDodnfrid1P6LdvrFJzzzFJ0jknu/WLyX+v08/+e2lBD91XAACGgBALxNFJ90k9/sHj+t2O3+lgx0FJUnmvW99yHdM1x44r13mHdNZVdF8BABgiQiwQB6Zp6qk9T2nV1lU6fOKwJOm0vBJ927lXVx3voPsKAECcEWKBIdrVukt3b75bWw9vlSSNzSvVdz/xdV15xqXKv2+6FEP3NRDrvgIAEBwhFhgk10mXHnj7Aa3dtVYe06MCI1c3tLbo2rb9ymvcIS0olBasjrr72idwAwO6rwAADESIBWLU2dupJ3c/qQfefkCtXa2SpEur5+qW19ZqXG+PdZLpscLr4u3WLUL3tU+oSVx0XwEA8EeIBaK0z7VPa3et1RO7n9Dx7uOSpLqSOv34wh/rwq6TUsN/+r+hr/9aOydieJXCT+Ki+woAgD9CLBCG2+PWS00vae37a/Wq81Xv8ZrCSn2jcrauPud65Y4+Q3I5JMNmjcD2ibH/GmkSFwAA6EeIBULYeWSnbt90u95vfV+SZMjQ3Jq5+lrOGH3qpVWyvbtZemGV1Xudfm3M/dfA7iuTuAAAiB4hFgjQ1dulB7c9qDXvrpHbdGtk3khdXX+1vjr5q6p2S1p1bv+Ia1/3tW5+1Gu/SmxgAADAUBFiAR9bDm7RHZvu0P7j+yVJn5/wef1o5o9UUVBhnbB3o39lQIp57Vc2MAAAYOgIsYCs5bLuffNePfbBY5Kk0wpP079+8l910ahJ0sGdUlmdFU7L6oa9+8okLgAAIiPEIqv1enr1l8a/6P6375frpEuSdHX91Vp8/mKN3PG49PsrrcBq2Oi+AgCQQgixyFqbnZu14vUV+rDtQ0nSxNKJ+ucL/1kXjLvAWm3gyZvpvgIAkKIIscg6Tceb9Ms3fqm/7v+rJKkkv0Q3nXeTvlL/FeXYTv1fonU33VcAAFIYIRZZw2N69Mf3/6hVb65Sl7tLdsOuRZMX6f+c939Ukl/ifzLdVwAAUhohFlnhYMdB/evf/lWvOV+TJM0cN1NLZy7VpNGT+k9yOawR2L5JXDF2XyX//ivdVwAAhg8hFhnNNE09vfdp3f3a3Trec1wj7CO05IIl+trkr8kwjP4Tt67p78D6TuKKsvsqBe+/0n0FAGB4GKZpmpFPS381NTVyOByqrq5WU1NTsi8HCXC066h++tpP9fxHz0uSplRM0d2fvlsTSib4n+hy+G9gIFkjr4u3RwyufZyuTs1esWHAqGvD0nmSRPcVAIAoxJLXGIlFxnF73Hrsg8f072/9u1wnXcoxcvSP0/5R35nynf6JW74iTeKKQrj+66y6csIrAABxRohFRtl6aKuWv75c77e+L0maNHqSfjr7pzqn/Jz+kwK7r4OYxMXarwAAJBchFhnh8InDWvnmSj2952lJ0si8kfreed/TosmL/EdfQ3VfY5jExdqvAAAkHyEWaa2tq01rdq7Rf733XzrRe0KGDC2ctFDfn/59lY0o8z85DhsYsPYrAACpgRCLtNTS2aI1767Rf+/6b3X2dkqSplZM1bILl+mcinOCvykOGxiw9isAAKmBEIu0cvjEYT2y4xH9pfEv6nJ3SZLOKjtLN0y9QRePv1g2w9Z/Mt1XAAAyFiEWaePZvc/qJ5t+4h15nVIxRTdOvVFza+b6r/kq0X0FACDDEWKR8twet+5/+379dvtvJUlTx0zV96Z9T7OqZg0MrxLdVwAAsgAhFintePdxLX1lqTY2bZQkfeucb+nm6TfLbrOHfhPdVwAAMh4hFilrr2uvvr/h+9p3bJ/y7fm641N36Mtnfjn4yb7910F0XyX//ivdVwAAUhshFimn19Or9fvW62ev/UzHe45rbOFYrZ63OvSqA8H6rzF0X6Xg/Ve6rwAApC7DNE0z8mmpZ+3atbrnnntkGIbcbrd++MMf6pprrgl5fix78SI5DnUc0mMfPKbHGh/T4c7DkqTzxpyne+fdq4qCiuBvcjmkVecOHHVdvN16HKH7KlkjsLNXbBgw6tqwdJ4k0X0FACBBYslraTkSu3z5ci1btkz33nuvFi9erDvvvFNf//rX1djYqDvuuCPZl4cYmKap15yvae2utXrpwEtym25JUtmIMn21/qu6YeoNyrPnhf6AcP3X2jkRu69S+P7rrLpywisAACko7ULszp079S//8i+SpMsuu0ySdOmll+qOO+7QXXfdpSuvvFLTpk1L5iUiSm1dbfrnv/2zd9KWJE0/bboWTV6kz57x2eDhlbVfAQCA0jDErl69Wh6PFVjKy8slSePGjZNkjeo98MADevjhh5N2fYjOto+36ZaXb9HBjoPKs+Vp4aSFunry1Zo0elLoN7H2KwAAOCXtQuwLL7zgfZyfnz/g9eeffz6Rl4MYmaapP+z8g+598171mr06Y9QZ+uVnfqnJZZPDv5G1XwEAgI+0CrFHjhzR7t27vc9zc3MHnLNv3z61tLSooiLERCAkzbHuY/rJ336iF/Zb/yFyyRmX6M5P3anivOLIb2btVwAA4COtQuyhQ4f8nttstqDnHT58mBCbYva07dH3XviemtqblGPL0W0zbtPXJn8t+I5bEt1XAAAQVlqF2KNHj/o9DxWA2traEnE5iNLbh9/WTRtukuukS9XF1brnM/fo3IpzQ7+B7isAAIggrUJsQUF0YWPUqFHDfCWI1ksHXtKtL9+qLneXplRM0QPzH9DoEaNDv4HuKwAAiEJahdjKykq/56ZpBh2NHTt2bKIuCWGs+2Cd7nr1LrlNt+ZUz9E9n7lHhbkR/uqe7isAAIhC8FJpiqqsrFRVVZX3eW9v74BzamtrNWbMmEReFgKYpqmHtj2k2zfdLrfp1uV1l2v1xauDB1iXQ9q70bqX+ruvviJ0XwP1dV990X0FACCzpFWIlaTPf/7z3sft7e0DXp8/f34iLwc+ejw92tS8Sbe8fIvuf/t+SdI/TPkH/XT2T5VrG7iShLausbaMfXSBdb91jTXKumC1FVyliN3XPk5XpzbtbpHT1anKkgItXzhF9lOj9HRfAQDIPGlVJ5Ck733ve3rkkUdkmqYOHjyo0aNH6/jx45KsiV433nhjkq8wu/R4evS683Wt/2i9NuzfoLaT1qQ6Q4Z+NPNH+vpZXw/+xjh0X/uEmsRF9xUAgMwVt5FYl8ullStXqra2Vs8++2zE891utx5++GHNnDlTBQUFKi0t1Re+8AWtX78+7PumT5+u22+/XZK8P+fFF1+UJC1btkwXXHDBEL8JorHzyE797LWfad6f5ukf//qPWvfBOrWdbFPZiDJ9tf6rWvOFNaEDrBS++ypZwbV2TlQjsMEmcfWNyM6qKyfAAgCQgYY8Ertr1y7dd999+o//+A91dHRE9Z7W1lZdfvnlamho0CWXXKJt27bpwIEDWrRokS699FLdcsst+sUvfhHy/bfffrvOOOMM3XPPPfr9738vm82m3//+9/rWt7411K+DMFwnXXpm7zN6/IPH9V7re97jZSPK9Nnxn9UlEy7R+WPPV44txK+V79qvg1j3YVGbXgAAG5ZJREFUNZhIk7gAAEBmGlSINU1Tzz//vFatWqVnn31WpmlGftMpHo9HCxcuVENDgyRp1apVqq+vV319vb773e/q5z//ue655x4VFhbqzjvvDPk5119/va6//vrBXD5idKTziFa+uVLP7XtOJ90nJUm5tlx9dvxndeWkKzVz3EzZbfbwHxJs7dcY1n3twwYGAABAGmSIXbJkifLz83X++efr9ddf15EjR6J+7yOPPKKXX35ZklRaWqqzzjrL+9rMmTO9j5cvX67rr79etbW1g7lExEnj0Ubd9MJNcnY4JUkTSyfqqklX6ctnflmlI0qj+5BQ/dfF263bELuvbGAAAED2GVSIvffee72PJ02apOuuu25Q7w3cGra6uj/E9PT0aMWKFXrooYcGc4khOZ1O1dTURDxvyZIlWrJkSVx/drp5+cDLum3jbTrRe0LjR47Xv3363zRtzLTQW8WGEq7/GkXvVWIDAwAA0tnKlSu1cuXKiOc5nc6oP3PIndhoAmGf/fv369133/U+Lyz0/yvfESNG+D1ft26dHnzwQdntEf6qOgYej0cOhyPieceOHYvbz0w3pmlqzc41+uUbv5QpUzPHzdTKi1aqJL8kug/w7b6WVMel/8oGBgAApK9jx45Flb9iMeQQa7NFv8DBSy+95Pc8Ly/P73lgWG1padGOHTs0bdq0QV9fIJvNNmDnr2CydevaHnePfvraT/X4h49Lkr5S/xUtu3BZ8HVegwnWfZ1+bcz9V7qvAABkjlGjRvn9jXsoTqdTHo8n4nlSgteJ7ZvM1Sc31z8YBQvEb775ZlxDbGVlpZqamuL2eZlkV+su/ey1n+ntj9+WzbDpthm36ZpPXBN9fSBOa7/SfQUAILNEW9OsqamJesQ2oSE28KICR16DhaV9+/YN5yVBUltXm+5/+379ufHP8pgeFeUW6Rdzf6E5NXNi+6Bw3deS6v5bGHRfAQBANBIaYgNXMYimihDLygeITa+nV2t3rdWDbz+oY91WB/iSMy7RDy/4oaqKq2L/QLqvAAAgQRIaYltbW/2eB468BhuJPXny5LBeU7Z689Cb+tlrP9OHbR9KkiaPnqwfzfyRZoybEf2HBE7gKqmm+woAABIioSE2Pz8/7Otut3vAsdLSKNciRVS63d2676379Oi7j8qUqdL8Uv3T3/2Trpp0VeQNC3yFmsBF9xUAACRAQkNsWVlZ2NeDzUYrLy+P6zWYpjlge9yioqK4/oxUtat1l37c8GN9cPQDSdLCSQu15Pwl0S+d1SfcBC66rwAAIAqBeUxSTLvAJjTETpgwQRs3bvQ+DwytwUZiq6oG0c0Mo7m5WcXFxX7HYvkDS0duj1trdq7RfW/dpx5Pj8pGlOmOWXdo3vh5g/vASBO4okD3FQCA7BaYx2IV/SKvceC7rawk9fb2+j0PNhL7qU99alivKdMd6Tyi76z/jla+uVI9nh5ddPpFWnfZutgDrMsh7d1o3fdN4PIVxQQup6tTm3a3yOnq9HZffdF9BQAA0UroSOycOf5LNnV2dvo9DxyJrays1KRJk+J6DVVVVWpsbIzrZ6aqXk+vbt14q9489KYKcwq1dOZSXTHxiti3jQ3Wf41xAlew/ivdVwAAsld7e/uAY/X19Wpubo7q/QkNsVOnTtU555zj3XrW5XL5vR44EnvZZZfF/RoMw8iaDuyvtv1KWw5uUWFOof7ri/+liaMnxv4hofqvi7dbtygmcIXqvzYsnaeGpfPovgIAkIWC5bFYBtqGXCcItgRWT09PyPNvu+027+NDhw759VF9k7fdbtf3v//9oV5e1mpwNOjhdx6WJN0+6/bBBVgpcv+1dk7EHmyk/uusunICLAAAiMmQQ+xHH3004NiBAwdCnv+Nb3xDX/rSlyRJJ06c8I7KStLmzZu9j5ctW6azzz57qJeXlQ52HNSPX/mxJOnq+qv1xTO/GP2bfbuv0qD6r77dV0n0XwEAQNwNKsQePXpUe/bs0bp163TXXXcNeP3uu+/WE088oX379g3ovdpsNv3xj3/U/PnzJUm33nqr3n//fb300kt6+GFr5PDmm2/WnXfeOZhLy3o9nh7dtvE2tZ1s01llZ+m2mbdFflOfrWukVedKjy6w7reu6d/AwDi1hmyE/uvaLfs1e8UGXfObzZq9YoPWbtmvypICLV84RfZTf0VA/xUAAAyVYQ5ifakvf/nLevrpp6M695FHHtH1118/4Ljb7dZvf/tb/e53v9N7772n3NxcXXjhhfrBD36gSy65JNZLiqimpkYOh0PV1dVqamqK++enipVvrNQj7z6i4txi/enLf9Lpo06P7o0uhxVcA7eMXbzdCqwuR8T+q9PVqdkrNgzYbath6TxVlhTI6eqk/woAAEKKJa8NamLXU089NagL82W32///9u4/OIr6/uP46xIhCUESjajJpZGARgRCp2DoV6IiRRBQ05k4A51CsbWd0hkdazMdQIa2DtXB0hahVccfAynS0jKtQgeZNraCaIy/BlrlRzCVEkJ+AE3AAEcgP26/f5w5cpfL5Zbc3e7mno+Zm2R3P7v72fAe8t7Nez8fLV68WIsXLx7wseCzq26Xyg+US5JWFq+MPIGV+q99jWACA8Z+BQAA8RLX0QkQXYZh6D+f/0dVDVWqbKzUnhN7JEkLb1momTfMDL9za4Mvcb16jC857a59DX4S20/t65Fmj/KvSVd2Rpq/9jX4SSy1rwAAINoSLol1+rSzFzov6N2Gd/VW/VuqaqjSybaTAdun5kxV2eSy8AcJNe7rpEWmxn4NNe7r/KI8xn4FAAARGei0s5dVE+tE3TUWodj9R9DW2abKhkq9UfuGdtfvVlvnpZflUpNTdev1t6o4p1hT3VOVPyI//Bhr1L4CAAAbCJevxKwmFrHX6e1UVWOV/vrZX/VOwzsBiWtOeo5m3DBDt7tv1+TrJislOSXyA1P7CgAABoGES2LtPu1s/dl6bf1sq7Z9tk0nz18qFXAPd2vWDbM084aZmnDNBHNTx/asf72M2lcpsP6V2lcAADBQjpp21g7sOu3s2/Vva9PBTXq/6X3/usyUTN03+j7dN/o+jcsaZy5x7Raq/tVE7asUuv6V2lcAADAQA512NuFqYu04TuxHxz/SQxUP+Zdvy75NpQWl+tqXvqahyUMv/8Dh6l+lfmtfpfD1r5KofQUAAFET83FiEV3r962XJN31pbu0tGipcq/Mjc6Bw9W/5t/Rb+2rFL7+9bYxWSSvAADAEpc17Syi59CpQ3q38V0lu5IHnsC2NkhH3vZ9lS7Vv/YUwdivVYeb1dTqe5Gsu/61J+pfAQCA1UhiLbZh3wZJ0qxRswaWwO59xVc6sPF+39e9r/ietN6/zpe4ShGN/Vr89E598+UPVPz0Tm35qE7ZGWlaVVqo5C9qVKh/BQAAdkA5gYWOnT2miqMVkqSHJjzUT+swWhsuvbwl+b5uf0waM8M3icGYGRGN/dr98pbkG3lg+Wv7dWfBSM0vytOdBSOpfwUAALZBEmuhjQc2ymt4VZxTrLFXj738AzH2KwAASDCUE1ikpa1F2z7bJukynsJGofY1GLWvAADASRIuiTUMQx6PJ+Bjhc2HNuti10VNyJqgouuLIt8xCrWvUu8XuKh9BQAA8RScj3k8HpkZ+TXhxokNJd4/Ak+HRzP/MlNn28/qmbue0d033B3ZjuHGfc1wfzEzV/9jv4aavGB+UZ4kX3JL7SsAAIi1cBMbME6sTf2l5i86235Wo0aM0vQvTY98xyjUvoZ7gYvaVwAA4BQJl8Tm5OSopqbGsvN3dHXolYOvSJK+Pf7bSk5KDr9Da4Mveb16zKXa1+AnsSZqX/t7gQsAACAezp0712tdQUGBGhsbI9o/4ZJYl8sVcq7eeNlxZIdOnj+pkWkjdf+Y+8M33vvKpaGzXEm+utf71/mGzzK6Iqp9lXxPX480e5R/Tbr/Ba7gaWR5gQsAAMRTqHwsXIlBsIRLYq30XuN7WrtnrSRp4biFGpo8tO/GfY39+tg+3yeC2lcpdP3rqtJCLX9tv7oMgxe4AACAI5HExkFbZ5vW7lmrzYc2S5JGZ4zWvIJ54XcKV/+af0e/yavUd/1r5bLpqlw2nRe4AACAY5HExtj+5v16/J3HVXumVpI0/+b5KptcpmFDgv5837P2NcMd8/rX28ZkkbwCAADHIomNkQ5vh17+5GW99MlL6jK6NDJtpH5e/HMVu4t7Nw5V+zppken61561r9kZadS/AgCAQYskNgYMw9Ajbz6iqsYqSdLsUbO14v9WKCMlo3fjvmpfx8zwJbJjZgxo7FfqXwEAwGBEEhsDLpdLJWNKtK95n1Z8dYXmjp7bd+MYj/06vyhPdxaMpP4VAAAMKiSxMTI3f66Kc4qVmZoZvmEcxn5lAgMAADDYJFndgcHK5XKFTmBbG6Qjb/u+Sr6nrPev8yWuUsS1r1WHm9XU2iZJ/trXnqh9BQAAg1nCPYk1DEMejydgXdwmP+jrBS5qXwEAQIIJzsckX54WKZdhprWD5ebmqqGhIeS2uPwIWhuktRN6lw08ti+iMV8l3xPY4qd39hptoHLZdGVnpKmptY3aVwAA4AjhZudyu92qr68Pu3/CPYm1TH8vcEWA2lcAAACfhEtic3JyVFNTE/sTRWnygp5jvzLuKwAAGCzOnTvXa11BQYEaGxsj2j/hkliXyxX7GtgoTV4Qqv6V2lcAADAYhMrHwpUY9GqbaDWxkdRYDEh/ta+tDRG9wBWu/lUSta8AAGDQMZOvJdyT2JiLwuQFUvj619vGZJG8AgCAhMY4sdHWXfvaU4S1r4z9CgAAEBmS2Gi7jMkLtnxUp+Knd+qbL3+g4qd3astHdcrOSNOq0kIlf1EbQv0rAADAJZQTxIKJyQuaWtv8L29JvpEHlr+2X3cWjNT8ojzdWTCS+lcAAIAgJLGxEoXaV8Z+BQAACI1ygjij9hUAAGDgeBIbR6HGfZ1flMfYrwAAACaRxMYJta8AAADRQxIbJ9S+AgAARA81sTFC7SsAAEDsJNyTWMMw5PF4AtaFmrt3IKh9BQAACC84H5N8eVqkXIaZ1g7WPRdvKNH8ETS1tqn46Z0BpQPJLpcql01XdkaamlrbqH0FAAAJz+Vy9bnN7Xarvr4+7P4J9yQ21qh9BQAAiL2ES2JzcnJUU1MTs+N3174GP4ml9hUAAOCSc+fO9VpXUFCgxsbGiPZPuBe7XC6X0tPTAz7RlJ2RplWlhUr+4hE5ta8AAAC9Bedj6enpYUsMgiXck9h4YNxXAACA2CKJjRFqXwEAAGIn4coJAAAA4HwksQAAAHAcklgAAAA4DkksAAAAHIckFgAAAI7D6AQxsmbNGp05c0YjRoxQWVmZ1d2BAxAzMIuYgVnEDMyyc8y4DMMw+m/mfLm5uWpoaIhoLl4nng/OR8zALGIGZhEzMMvO+RPlBAAAAHAcklgAAAA4DkksAAAAHCfhk1iPxyOXyyWXyyWPx2Nqe3/7OkE8riEa57jcY5jZL9K2xAwxY6btQNsQM/E7PjFjH8SMubYD+b00kOuwWsInsQAAAHAeklgAAAA4TsKNE2sYRsCjcic9NgcAABgsQuVgZkZ+TbgktrGxUcOHD7e6GwAAAAltoPlYwiSxJ0+e7LdNQUGBXC5XwLqedwTB28Nta2pq8n/Nzc297H7HWrhrsNM5LvcYZvaLtG1/7YgZe5zDLjEz0DbETPyOT8zYBzFjru1Afi/1t92qmIkkb0uYGbuSk5Pl9Xqt7gYAAAD6kZSUpK6urrBtEuZJbGpqqi5cuKDk5GRde+21VncHAAAAQU6ePKmuri6lpqb22zZhnsQCAABg8GCILRvasmWLioqKNGXKFE2ePFmbN2+2uktwiPb2dm3atEmTJk3S66+/bnV3YFPnz5/XsmXLlJeXp9TUVBUWFurFF1+0uluwsY6ODv32t7/VxIkTNXz4cN1888365S9/qc7OTqu7BodoaWlRXl6e7rrrrqgdkyTWZlatWqVvfOMbWrBggT788EOVlJRowYIFeuKJJ6zuGmysublZTz31lEaNGqVFixbpX//6l9Vdgk21t7dr5syZ+sUvfqFjx47p4sWL2r9/v37wgx+orKzM6u7Bhtrb21VaWqpHH31U+/btk8fjUU1NjZYsWaIlS5ZY3T04gNfr1YIFC3Ts2LGoHpck1kYOHjyoFStWSJJKSkokSffcc48kaeXKlfr4448t6xvs6+OPP9azzz6r//73v/63SIG+/OpXv1JVVZXcbrfS0tICtq1du1affvqpRT2DXT311FO66aab9OGHH2rHjh2aOHGif9vzzz+v9vZ2C3sHJ1i5cqUqKiqiflySWBtZt26dfwSFrKwsSdL1118vyTf8xXPPPWdZ32BfX/7yl/XEE09o/fr1GjlypNXdgY15vV5t375de/bsUX19vU6fPq3vfe97/u2GYaiqqsrCHsJuOjo6dOONN2rNmjUqKirS3LlztWPHDiUl+dKHixcvqq2tzeJews4qKiq0fv36mBybJNZG3nzzTf/3KSkpvbb/4x//iGd34EDDhg2zuguwsQsXLqi8vFyTJk2S5Pt/5tlnn/XfNEvSddddZ1X3YENDhgzRt771rYB1ubm5/pgpLS1VRkaGFV2DA9TV1Wnp0qVas2ZNTI5PEmsTLS0tOnz4sH95yJAhvdrU1taqubk5nt0CMIgMGzZMY8eODViXkpKi0aNHS5LS09M1depUK7oGB9m7d6/+97//qaSkROXl5VZ3BzbV3t6uBQsW6Pnnn4/ZXwlJYm3ixIkTAcvdf6oJFskMFgBgRn19vSTpu9/9rjIzMy3uDezKMAzt3LlT8+bNk+SLm7q6Oot7BbsqKytTaWlpTG+MSWJt4vTp0wHLfU1B9/nnn8ejOwASxCeffKKmpibl5+frySeftLo7sLEnn3xSc+bM8f/VcO/evZo2bRqJLHr54x//qOPHj+tHP/pRTM9DEmsTwW8J92XEiBEx7gmARPKb3/xG6enp2rZtm6688kqruwMb+8lPfqLGxkY98MAD/nWnTp3SunXrLOwV7Ka6ulqrV6/Whg0bYn4uklibyM7ODljuayI1XroAEC1VVVX6wx/+oFdffTVg2CSgL1lZWfrzn/+shQsX+tdVV1db2CPYzZYtW/Tvf/9bGRkZcrlccrlcmj59un/77t275XK5VFtbO+BzkcTaRHZ2tnJycvzLoWZByc/PZwglAFFx+vRpLVq0SL///e/941FL0tGjRxn3E2G5XC79+te/9r+AzOgEsApJrI3Mnj3b//25c+d6bZ8xY0Y8uwNgkPJ6vXrwwQe1evXqgD8N19bW6jvf+U7I0VGAnq699loVFhZKku6++26LewM7eeSRR1RdXR3w2bhxo397UVGRqqur5Xa7B3wuklgbefjhh/0vdB0/flySdPbsWUm+O9/Fixdb1jc4w8WLF/3f8zQNfXn88ce1fft2zZs3T1dccYWuuOIKJSUlKT8/X11dXX2+WIrEU1lZqdLSUm3durXXtra2No0bN67XOLJIbNdcc43Gjh0b8MnLy/Nv7x7qLxo3yySxEWhtbdWaNWuUn5+vv//97/227+rq0ksvvaQpU6YoLS1NmZmZmjNnjt54442w+02aNEk/+9nPJMl/nl27dkmSli9frltvvXWAV4J4ilfcdDt8+HDAEGzvvPPOZfcd8RevePnd736n1atX+4/R/emuw//KV74y8ItBXMQjZtavX6+tW7eqtLRUjz32mDwejyTpT3/6kwzD0I4dOzR06NCoXRNiK96/l2LOQJ8OHTpkPPzww0Z6erohyZBk/O1vfwu7T0tLi3H77bcbkoxZs2YZn376qfHPf/7TyMrKMiQZP/7xj/s9b3l5uTF+/HhjwoQJxsSJE40NGzZE65IQB/GOm6qqKqOwsNBISUnxn6/7k5+fb2zatCnal4goime8vPfee8aQIUN6xUnPT3l5eQyuEtEUz5ipra01vv71rxtZWVlGUlKSkZ2dbTz44IPGM888Y3g8nlhcHmLAqnym265du/znnTZt2gCv5hKS2CBer9eoqKgw5syZY7hcrl7/wYf7R+/q6jKmTZvmb3vw4EH/tqVLl/rX//SnP43HpSCOiBuYQbzALGIGZiVCzFBOEKSsrEw7d+7U5MmTdfXVV5vat7y8XLt375YkZWZm6pZbbvFvmzJliv/7VatW6ciRI9HpMGyBuIEZxAvMImZgVkLEjKUptM1t3LjR1J3L+PHj/e1uvPHGgG3vv/9+wHG+//3vx7r7sAhxAzOIF5hFzMCswRozPIkNIzc3N+K2dXV1OnDggH952LBhAdtTU1MDll977TV1dXUNrIOwJeIGZhAvMIuYgVmDNWZIYsNISor8x/PWW28FLAe/rZmcnByw3NzcrP37919232BfxA3MIF5gFjEDswZrzJDERkllZWXAcvD4Z6ECaM+ePTHtE+yPuIEZxAvMImZglpNihiQ2ShoaGgKWg+9UQg0eHo15g+FsxA3MIF5gFjEDs5wUMySxUdLS0hKwHMmj++B9kHiIG5hBvMAsYgZmOSlmSGKj5NSpUwHLwXcqoe5cek4RisRE3MAM4gVmETMwy0kxQxIbJSkpKWG3h3pzLzMzM1bdgUMQNzCDeIFZxAzMclLMkMRGSX8DCXu93l7rsrKyYtUdOARxAzOIF5hFzMAsJ8UMSWyUjBo1KmA5+B851J1LTk5OLLsEByBuYAbxArOIGZjlpJghiY2SntOwSVJnZ2fAcqg7l6lTp8a0T7A/4gZmEC8wi5iBWU6KGZLYKLnjjjsCltva2gKWg+9csrOzddNNN8W8X7A34gZmEC8wi5iBWU6KGZLYKJk4caLGjx/vX25tbQ3YHnznUlJSEpd+wd6IG5hBvMAsYgZmOSlmSGLDCDVkREdHR5/tlyxZ4v/+xIkTMgzDv9zY2Oj/Pjk5WY8++miUegm7IW5gBvECs4gZmDVYY4YkNoyjR4/2Wnfs2LE+2y9cuFD33nuvJOn8+fM6cOCAf9sHH3zg/3758uUaN25cFHsKOyFuYAbxArOIGZg1aGPGQIBTp04Zhw8fNl599VXD7XYbkgI+brfb2LZtm3HkyBHj/PnzvfY/c+aMMWPGDEOSMXv2bKO6utrYtWuXcdVVVxmSjB/+8IeG1+u14MoQS8QNzCBeYBYxA7MSIWZIYoPce++9vf6h+/qUl5eHPEZnZ6fxwgsvGEVFRcbw4cONq666ypg9e7ZRUVER34tB3BA3MIN4gVnEDMxKhJhxGUaPQgcAAADAAaiJBQAAgOOQxAIAAMBxSGIBAADgOCSxAAAAcBySWAAAADgOSSwAAAAchyQWAAAAjkMSCwAAAMchiQUAAIDjkMQCAADAcUhiAQAA4DgksQAAAHAcklgAAAA4DkksAAAAHIckFgAAAI5DEgsAAADH+X/X92YpOqUWzwAAAABJRU5ErkJggg==",
+ "text/plain": [
+ "Figure(PyObject )"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "sensitivity(\"Signal\", results_set[20]) = 0.8649683135820136\n"
+ ]
+ }
+ ],
"source": [
"using SpecialFunctions\n",
"sens = []\n",
@@ -246,7 +349,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
@@ -255,7 +358,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
@@ -264,7 +367,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
@@ -273,7 +376,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
@@ -282,7 +385,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
@@ -291,7 +394,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
@@ -300,7 +403,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
@@ -507,15 +610,15 @@
"lastKernelId": null
},
"kernelspec": {
- "display_name": "Julia 1.2.0",
+ "display_name": "Julia 1.3.1",
"language": "julia",
- "name": "julia-1.2"
+ "name": "julia-1.3"
},
"language_info": {
"file_extension": ".jl",
"mimetype": "application/julia",
"name": "julia",
- "version": "1.2.0"
+ "version": "1.3.1"
}
},
"nbformat": 4,
diff --git a/README.md b/README.md
index 0734f0b..bfe90e8 100644
--- a/README.md
+++ b/README.md
@@ -4,31 +4,31 @@
[](https://travis-ci.com/MorganAskins/watchfish)
[](https://morganaskins.github.io/watchfish)
-Given $M$ components, each with an estimated rate $\vec{\beta}$ determined by a
-normal distribution with uncertainty $\vec{\sigma}$, calculate the confidence
-itervals and perform a hypothesis tests for each parameter $b$.
+Given components, each with an estimated rate determined by a
+normal distribution with uncertainty , calculate the confidence
+itervals and perform a hypothesis tests for each parameter .
-Nominally each event corresponds to a set of observables $\vec{x}$ of $N$
+Nominally each event corresponds to a set of observables of
measurements, for any given measurement, the probability for that particular
measurement to come from a particular components is given by
-$$ P_i(\vec{x}) $$
+
The prior probability is then formed through a combination of these components
such that the total probability is
-$$ \mathbf{P} = \sum_i^M P_i(\vec{x}) $$
+
-The likelihood for a full data set of $N$ measurements is the product of each
+The likelihood for a full data set of measurements is the product of each
event total probability
-$$\mathcal{L}(\vec{x}) = \prod_j^N \left( \sum_i^M b_iP_i(\vec{x}) \right) / \sum_i^Mb_i $$
+
We can extend the likelihood by proclaiming that each components as well as the
sum of components are simply a stochastic process, produces the extended
likelihood:
-$$\mathcal{L}(\vec{x}) = \frac{\text{e}^{-\sum_i^Mb_i}}{N!} \prod_j^N \left( \sum_i^M b_iP_i(\vec{x}) \right) $$
+
Finally, we can claim that we have _a priori_ knowledge of the parameters,
whether it be through side-band analysis or external constraints, by including
@@ -37,27 +37,26 @@ the shape of that prior, we will consider the information we receive on the
variables to be normally distributed and multiply the likelihood by those
constraints
-$$\mathcal{L}(\vec{x}) = \frac{\text{e}^{-\sum_i^Mb_i}}{N!} \prod_j^N \left( \sum_i^M b_iP_i(\vec{x}) \right) \frac{1}{\sqrt{2\pi \sigma_j^2}}\text{exp}\left({\frac{-(\beta_i-b_i)^2}{2\sigma_i^2}}\right)$$
+
A few definitions to simplify things:
-$$ \lambda := \sum_i^Mb_i $$
+
-Then then our objective function $\mathcal{O} = -\text{Ln}\mathcal{L}$
+Then then our objective function
-$$\mathcal{O} = \lambda + \text{Ln}N! -\sum_j^N\text{Ln}\left( \sum_i^M b_iP_i(\vec{x}) \right) + \sum_i^M \left( \frac{(\beta_i-b_i)^2}{2\sigma_i^2} + \text{Ln}\sqrt{2\pi \sigma_i} \right)$$
+
Finally, for a counting analysis we assume that an optimal set of cuts has been
applied which optimizes the sensitivity to a particular parameter, which
simplifies the likelihood such that
-$$ P_i(\vec{x}) := 1 $$
+
Also, because the shape of the likelihood space is independent of constant
-parameters, we can drop the $\text{Ln}\sqrt{2\pi \sigma_i}$ terms. We could
-also remove the $\text{Ln}N!$ term as well, but for numerical stability we will
-keep it around, but use Sterling's approximation: $\text{Ln}N! \approx
-N\text{Ln}N - N$. The remaining objective function we will thus use is:
+parameters, we can drop the terms. We could
+also remove the term as well, but for numerical stability we will
+keep it around, but use Sterling's approximation: . The remaining objective function we will thus use is:
-$$\mathcal{O} = \lambda - N\text{Ln}\lambda + N\text{Ln}N - N + \sum_i^M \left( \frac{(\beta_i-b_i)^2}{2\sigma_i^2} \right)$$
+
-_Note: If the different values of $\beta$ differ by orders of magnitude, it
+_Note: If the different values of differ by orders of magnitude, it
might be worth forming an affine invariant form of the likelihood, otherwise
-the $\text{Ln}\sqrt{2\pi \sigma_i}$ term should not matter_
+the term should not matter_
diff --git a/readme_markdown.md b/readme_markdown.md
new file mode 100644
index 0000000..0734f0b
--- /dev/null
+++ b/readme_markdown.md
@@ -0,0 +1,63 @@
+# Watchfish
+
+[](https://mybinder.org/v2/gh/morganaskins/watchfish/master)
+[](https://travis-ci.com/MorganAskins/watchfish)
+[](https://morganaskins.github.io/watchfish)
+
+Given $M$ components, each with an estimated rate $\vec{\beta}$ determined by a
+normal distribution with uncertainty $\vec{\sigma}$, calculate the confidence
+itervals and perform a hypothesis tests for each parameter $b$.
+
+Nominally each event corresponds to a set of observables $\vec{x}$ of $N$
+measurements, for any given measurement, the probability for that particular
+measurement to come from a particular components is given by
+
+$$ P_i(\vec{x}) $$
+
+The prior probability is then formed through a combination of these components
+such that the total probability is
+
+$$ \mathbf{P} = \sum_i^M P_i(\vec{x}) $$
+
+The likelihood for a full data set of $N$ measurements is the product of each
+event total probability
+
+$$\mathcal{L}(\vec{x}) = \prod_j^N \left( \sum_i^M b_iP_i(\vec{x}) \right) / \sum_i^Mb_i $$
+
+We can extend the likelihood by proclaiming that each components as well as the
+sum of components are simply a stochastic process, produces the extended
+likelihood:
+
+$$\mathcal{L}(\vec{x}) = \frac{\text{e}^{-\sum_i^Mb_i}}{N!} \prod_j^N \left( \sum_i^M b_iP_i(\vec{x}) \right) $$
+
+Finally, we can claim that we have _a priori_ knowledge of the parameters,
+whether it be through side-band analysis or external constraints, by including
+those constraints via some prior probability. Given no specific knowledge of
+the shape of that prior, we will consider the information we receive on the
+variables to be normally distributed and multiply the likelihood by those
+constraints
+
+$$\mathcal{L}(\vec{x}) = \frac{\text{e}^{-\sum_i^Mb_i}}{N!} \prod_j^N \left( \sum_i^M b_iP_i(\vec{x}) \right) \frac{1}{\sqrt{2\pi \sigma_j^2}}\text{exp}\left({\frac{-(\beta_i-b_i)^2}{2\sigma_i^2}}\right)$$
+
+A few definitions to simplify things:
+$$ \lambda := \sum_i^Mb_i $$
+
+Then then our objective function $\mathcal{O} = -\text{Ln}\mathcal{L}$
+
+$$\mathcal{O} = \lambda + \text{Ln}N! -\sum_j^N\text{Ln}\left( \sum_i^M b_iP_i(\vec{x}) \right) + \sum_i^M \left( \frac{(\beta_i-b_i)^2}{2\sigma_i^2} + \text{Ln}\sqrt{2\pi \sigma_i} \right)$$
+
+Finally, for a counting analysis we assume that an optimal set of cuts has been
+applied which optimizes the sensitivity to a particular parameter, which
+simplifies the likelihood such that
+$$ P_i(\vec{x}) := 1 $$
+Also, because the shape of the likelihood space is independent of constant
+parameters, we can drop the $\text{Ln}\sqrt{2\pi \sigma_i}$ terms. We could
+also remove the $\text{Ln}N!$ term as well, but for numerical stability we will
+keep it around, but use Sterling's approximation: $\text{Ln}N! \approx
+N\text{Ln}N - N$. The remaining objective function we will thus use is:
+
+$$\mathcal{O} = \lambda - N\text{Ln}\lambda + N\text{Ln}N - N + \sum_i^M \left( \frac{(\beta_i-b_i)^2}{2\sigma_i^2} \right)$$
+
+_Note: If the different values of $\beta$ differ by orders of magnitude, it
+might be worth forming an affine invariant form of the likelihood, otherwise
+the $\text{Ln}\sqrt{2\pi \sigma_i}$ term should not matter_