{ "cells": [ { "cell_type": "markdown", "metadata": { "tags": [] }, "source": [ "# The Trigger Function\n", "\n", "## Transforming Continuous Preferences into Discrete Events\n", "\n", "This notebook is a mathematical deep dive into the derivation of the Trigger Function used in Conviction Voting for the 1Hive use case.\n", "\n", "The role of the trigger function in the conviction voting algorithm is to determine if a sufficient amount of conviction has accumulated in support of a particular proposal, at which point it passes from being a candidate proposal to an active proposal. \n", "\n", "In the 1Hive use case for conviction, proposals map to precise quantities of resources $r$ requested from a communal resource pool $R$ (which is time varying $R_t$ but we will drop the subscript for ease of reading). Furthermore, there is a supply of governance tokens $S$ which are being used as part of the goverance process. In the implementation the quantity $S$ will be the effective supply which is the subset of the total Supply for the governance token in question. \n", "\n", "We assume a time varying supply $S_t$ and thereforewe can interpret $S_t$ as the effective supply without loss of generality. From here forward, we will drop the subscript and refer to $S$ for ease of reading. The process of passing a proposal results in an allocation of $r$ funds as shown in the figure below.\n", "\n", "![](images/stockflow_cv_trigger.png)\n", "\n", "The trigger function is characterized by a set of parameters in addition to the current state of the system: $R$ and $S$. Those parameters are $\\alpha$, $\\beta$ and $\\rho$.\n", "\n", "* $\\alpha \\in (0,1)$ is the conviction rate parameter defined in the [Deriving Alpha notebook](https://nbviewer.jupyter.org/github/BlockScience/Aragon_Conviction_Voting/blob/master/models/v3/Deriving_Alpha.ipynb) and should be tuned according to a desired half life.\n", "\n", "* $\\beta\\in (0,1)$ is the asymptotic limit for trigger function. It is impossible to discharge more than $\\beta$ share of funds. \n", "\n", "* $\\rho \\in (0, \\beta^2)$ is a the scale factor for trigger function. Note that we require $0<\\rho <\\beta^2$ \n", "\n", "The trigger function is defined by: $y^*(r) = \\frac{\\rho S}{(1-\\alpha)\\left(\\beta^2 - \\frac{r}{R}\\right) }$\n", "\n", "The geometric properties of this function with respect to the parameter choices are shown here:\n", "\n", "![](images/trigger_geometry.png)\n", "\n", "On this plot we can see that there is a maximum conviction that can be reached for a proposal, and also a maximum achievable funds released for a single proposal, which are important bounds for a community to establish for their funding pool.\n", "\n", "Note that by requiring that: $0<\\rho <\\beta^2$ the following holds $0<\\frac{\\rho}{\\beta^2}<1$ and $0<\\beta - \\sqrt \\rho <\\beta <1$" ] }, { "cell_type": "code", "execution_count": 434, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "\n", "from cadCAD.configuration.utils import config_sim\n", "from model.parts.utils import *\n", "from model.parts.sys_params import * " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Reader Tutorial:\n", "\n", "Feel free to pull parameters out of the existing files or use this notebook to ovewrite them with your own choices to see how the plots are affected." ] }, { "cell_type": "code", "execution_count": 436, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "{'sentiment': 0.6, 'n': 30, 'm': 7, 'funds': 4867.21, 'supply': 22392.22}" }, "metadata": {}, "execution_count": 436 } ], "source": [ "initial_values" ] }, { "cell_type": "code", "execution_count": 438, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "{'beta': [0.2],\n 'rho': [0.0025],\n 'alpha': [0.7937005259840998],\n 'gamma': [0.001],\n 'sensitivity': [0.75],\n 'tmin': [1],\n 'min_supp': [1],\n 'base_completion_rate': [45],\n 'base_failure_rate': [180],\n 'base_engagement_rate': [0.3],\n 'lowest_affinity_to_support': [0.3]}" }, "metadata": {}, "execution_count": 438 } ], "source": [ "params" ] }, { "cell_type": "code", "execution_count": 440, "metadata": {}, "outputs": [], "source": [ "supply = initial_values['supply']\n", "funds = initial_values['funds']\n", "\n", "alpha = params['alpha'][0]\n", "beta = params['beta'][0]\n", "rho = params['rho'][0]\n" ] }, { "cell_type": "code", "execution_count": 442, "metadata": {}, "outputs": [], "source": [ "def trigger(requested, funds, supply, alpha, beta, rho):\n", " '''\n", " Function that determines threshold for proposals being accepted.\n", " Refactored slightly from built in to be explicit for demo\n", " '''\n", " share = requested/funds\n", " if share < beta:\n", " threshold = rho*supply/(beta-share)**2 * 1/(1-alpha)\n", " return threshold \n", " else: \n", " return np.inf" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Simple derivations:\n", "\n", "We can plug in some boundary conditions to determine our minimum required and maximum achievable conviction. We can also determine the maximum achievable funds a proposal is able to request, to understand the upper bounds of individual proposal funding.\n", "\n", "* min_required_conviction = $y^*(0) = \\frac{\\rho S}{(1-\\alpha)\\beta^2}$\n", "\n", "* max_achievable_conviction = $\\frac{S}{1-\\alpha}$\n", "\n", "* min_required_conviction_as_a_share_of_max = $\\frac{\\rho S}{(1-\\alpha)\\beta^2} \\cdot \\frac{1-\\alpha}{S} = \\frac{\\rho}{\\beta^2}$\n", "\n", "* To compute the max_achievable_request solve: $\\frac{S}{1-\\alpha} = \\frac{\\rho S}{(1-\\alpha)\\left(\\beta-\\frac{r}{R}\\right)^2}$\n", "\n", "* max_achievable_request = $r = (\\beta -\\sqrt\\rho)F$" ] }, { "cell_type": "code", "execution_count": 444, "metadata": { "tags": [] }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": "min_required_conviction =6783.893932236272\nmax_achievable_conviction =108542.30291578037\n\nmin_achievable_conviction_as_a_share_of_max_achievable_conviction =0.06249999999999999\n\nmax_achievable_request =730.0815000000001\ntotal_funds =4867.21\n\nmax_achievable_request_as_a_share_of_funds =0.15000000000000002\n" } ], "source": [ "min_required_conviction = trigger(0, funds, supply, alpha, beta, rho)\n", "print(\"min_required_conviction =\"+str(min_required_conviction))\n", "\n", "max_achievable_conviction = supply/(1-alpha)\n", "print(\"max_achievable_conviction =\"+str(max_achievable_conviction))\n", "print(\"\")\n", "print(\"min_achievable_conviction_as_a_share_of_max_achievable_conviction =\"+str(min_required_conviction/max_achievable_conviction))\n", "print(\"\")\n", "max_request = beta*funds\n", "max_achievable_request = (beta - np.sqrt(rho))*funds\n", "print(\"max_achievable_request =\"+str(max_achievable_request))\n", "print(\"total_funds =\"+str(funds))\n", "print(\"\")\n", "print(\"max_achievable_request_as_a_share_of_funds =\"+str(max_achievable_request/funds))\n", "\n", "granularity = 100 \n", "\n", "requests = np.arange(0,.9*max_request, max_request/granularity)\n", "requests_as_share_of_funds = requests/funds\n", "conviction_required = np.array([trigger(r, funds, supply, alpha, beta, rho) for r in requests])\n", "conviction_required_as_share_of_max = conviction_required/max_achievable_conviction\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot series 1: \"Absolute Terms\" \n", "\n", "These plots demonstrate the trigger function based on alpha, Supply and Funds as above." ] }, { "cell_type": "code", "execution_count": 446, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "Text(0, 0.5, 'Conviction Required to Pass')" }, "metadata": {}, "execution_count": 446 }, { "output_type": "display_data", "data": { "text/plain": "
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}, "metadata": { "needs_background": "light" } } ], "source": [ "plt.plot(requests, conviction_required)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request, 0, ax[3], 'g', '--')\n", "plt.hlines(max_achievable_conviction, 0, max_request, 'g', '--')\n", "plt.hlines(min_required_conviction, 0, max_request, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Absolute Terms; Linear Scale\")\n", "plt.xlabel(\"Resources Requested\")\n", "plt.ylabel(\"Conviction Required to Pass\")" ] }, { "cell_type": "code", "execution_count": 448, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "(0.0, 119396.53320735841)" }, "metadata": {}, "execution_count": 448 }, { "output_type": "display_data", "data": { "text/plain": "
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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "plt.figure(figsize=(10, 7))\n", "plt.plot(requests, conviction_required)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request, 0, ax[3], 'g', '--')\n", "plt.hlines(max_achievable_conviction, 0, max_request, 'g', '--')\n", "plt.hlines(min_required_conviction, 0, max_request, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Absolute Terms; Linear Scale\")\n", "plt.xlabel(\"Resources Requested\")\n", "plt.ylabel(\"Conviction Required to Pass\")\n", "plt.gca().set_ylim(0, max_achievable_conviction*(1.1))" ] }, { "cell_type": "code", "execution_count": 450, "metadata": {}, "outputs": [ { "output_type": "display_data", "data": { "text/plain": "
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0SqzmdTg/GzXKeYWIJQpjjOfCNVFMX7WTrVm53NGrpdehnMgShTHGhIe3vttE09rx9IvRRuxCliiMMaYYK7cdYP7GfdzRq4W3/TqFAUsUxhhTjLfnbCI+riKDU8OoEdsjliiMMaaIfYeP8XH6Vq4+qym1EuK8DsdzdnmsMcZzU26Z4nUIJ3h/wRaO5hVwR8+WXodSvCmhra+ITBQiMggY1LZtW69DMcaUg4S48Ok/6WhePm/P2UTvtvVIblTD63CKlxDa+orIU0/2hDtjosvLC17m5QUvex0GAJ8s2cbOA0e554I2XodSspdfdl4hEpGJwhgTXcavGM/4FeO9DoOCAuXVr9fTqXFNzm8XvneLM3688woRSxTGGOP6ctVONuw+zD0XtkYkti+J9WWJwhhjAFXl1dnrSaobzxVnNPY6nLBiicIYY4AFm/azZEsWd5/f2vtHnYYZqw1jjAFembWOutUqc/3Zsfeo09JE5OWxxpjoMittlqfb/yEji6/W7Obhy5KJr1zR01gCMmtWSDdnRxTGmJj3wowfqZ0Qx+09W3gdSliyRGGM8dzwOcMZPme4J9tempnlPMHuvFbUqBoh3XUMH+68QsQShTHGc5PXTmby2smebPuFGT9SKz4u/J454c/kyc4rRCxRGGNi1rLMbKavirCjCQ9YojDGxKz/zFhLzaqVuKN3S69DCWsRmShEZJCIjMzOzvY6FGNMhFq0eR/TV+1iyAWtqWlHE35FZKKwTgGNiS7xcfHEx8WHbHuqynNT15BYvQq/Oq9VyLZbbuLjnVeIlHofhYj8A3gayAWmAd2Aoao6JsixGWNixNRbpoZ0e7PW7ub7TfsYdlVnEipH4O1kU0NbX4EcUVyqqgeAgUAm0B54OKhRGWNMkBQUKP+YtobmdRMY3N0ecxqIQBJF4cm7AcB7qroviPEYY2LQsNnDGDZ7WEi2NWnpNlZtP8CDl7ancqWIPPsOw4Y5rxAJpJYmichqIBWYISL1gSPBDcsYE0tmbJzBjI0zgr6dI8fzGf7FGjo2rsmgrk2Cvr2gmTHDeYVIqYlCVR8BegKpqnocOAxcFezAjDGmvI2as4mMfbk8PqAjFSrY8yYCVWqiEJHrgTxVzReRJ4AxQASnYmNMLNpz6CgvzlxH3w4NOC+cn14XhgI59fSkqh4UkfOAy4C3gVeCG5YxxpSvf325liPH83nsio5ehxJxAkkU+e7fK4BXVPUToHLwQjLGxJp6CfWol1AvaOtfveMA73+/hdt6tqBN/epB207I1KvnvEIkkAuIt4rIa0A/4DkRqUKE3qhnjAlPE2+YGLR1qypPT15Fjapx/K5vu6BtJ6QmBq++ihPIF/4NwOfA5aqaBdTF7qMwxkSIact38O26Pfz+kvbUTrCTIacikKueclT1QyBbRJrj3FexOuiRGWNixqPTH+XR6Y+W+3pzjuXx18kr6dS4Jrf0iKKb6x591HmFSCBdeFwJPI9zpdMuoDlOougc3NCMMbFibubcoKz3vzPXsT37CC/efCaVKkbRGfO5wamvkgRSc8OAc4G1qtoKp63iu6BGZYwxp2ndrkP875sNXHd2M85uUdfrcCJaIIniuKruBSqISAVV/QpICW5Yxhhz6lSVpz5dTtW4ijzSv4PX4US8QK56yhKR6sDXwFgR2QXkBTcsY4w5dR8t2cp36/Yy7KrOJFav4nU4ES+QRHElTt9O/wfcAtQC/hrMoIwxsaVZzWbltq69h44ybPJKzmpem1t6tCi39YaVZuVXX4EoMVGISA9gJNAGWAbcqapvhyowf0RkEDCobdu2XodijCkHY64pv8fbPP3ZKg4dzePv13aN3v6cxoT2cUD+2iheAh4C6gH/Av4dkogCYE+4M8YUZ/ba3Xy0ZCv3XtiG9g1reB1O1PCXKCqo6peqelRVPwDqhyooY0xsGTptKEOnDT2tdRw+msfjHy2jdf1q/PqiKD/bMHSo8woRf20UtUXkmpLG3ZvwjDHmtKXvSD/tdfx96mq2ZuUybkhPqsZVPP2gwll6ekg35y9RzAYGlTCugCUKY0xYmLNuD6PnbeZXvVtxTiu7Z6K8lZgoVPWXoQzEGGNOxaGjefxh4lJaJVbj4cuSvQ4nKgVyeawxxoStZ6esYmtWLh/c05P4ylF+yskjliiMMZ5rX6/9KS331ZpdjJ2/hbvOa0Vqyxg65dT+1OrrVImqhnSD5Sk1NVUXLlzodRjGGA/sPXSUy0Z8Q71qlfnkgd7R34BdjkRkkaqmBvr+QHqPjQPuAy5wJ80GXlXV46cWojHGnB5V5ZEPl3Eg9zij7zzHkkSQBdIp4CvA2cDL7uss7JnZxphyNGTSEIZMGhLw+8ctyODLlTv5w+XJdGxcM4iRhakhQ5xXiATSRtFdVbv5jM8UkR+CFZAxJvas3bs24Peu332Iv05eSa829fhV71ZBjCqMrQ28vspDIEcU+SLSpnBERFoD+cELyRhjinfkeD6/HruYKpUq8K8bUqK3L6cwE8gRxcPAVyKyARCgBfCroEZljDHF+Ntnq1i94yBvpqXSqFZVr8OJGYEkim+BdkAyTqKw52UbY0Ju6rLtjJ63mbvPb8XFHRp6HU5MCSRRzFXVs4ClhRNEZDFOo7Yxxpy2lEYpfudv2ZvDHycupVtSbR6+zJ5YR0pKSDfn73kUjYCmQLyInIlzNAFQE0gIQWzGmBgx4vIRJc47cjyf+8YuAuDFm86kcqVAmlaj3IgRId2cvyOKy4A0oBnwPD8nigPAY8ENyxhjHE99soIV2w7wZloqSXXtN6oX/HUK+Dbwtohcq6oTQxiTMSbG3PrhrcDJT7obvyCDcQsz+M3Fba1dwtetTn2F6kl3pbZRWJIwxgRb5oHMk6Yty8zmyU+Wc17bRIb2C23fRmEv8+T6CiY72WeMCTu7Dx5lyOiFJFavwn9uTKGi3S/hKes91hgTVo7lFXD/2EXszznGhHt7Ua96Fa9Dinn+rnq6pqR5YI9CNcYEx18nr2DBpv3858YUujSt5XU4Bv9HFIWPPW0A9AJmuuMXAbOwR6EaY8pJz2Y9ARg9bzNj5m3hngtac1VKU4+jCmM9e4Z0c6U+j0JEJgN3q+p2d7wx8JKq+j3iCAV7HoUx0eObH3eT9tYCLmxfn9dvT7V2iSAq6/MoAmnMblmYJFw7AbsEwRhTbtbtOsT9YxfTrkF1XrjpTEsSYSaQxuxZIvI58B6gwI3AV0GNKgT6jOpz0rQbOt/A/d3vJ+d4DgPGDjhpflpKGmkpaezJ2cN14687af59qfcxuMtgMrIzuO2j206a/2DPBxmUPIg1e9Zwz+R7Tpr/xAVP0K91P9J3pDN02tCT5j/T9xl6JfViTsYcHptx8j2PIy4fQUqjFKZvmM7TXz990vzXBr5GcmIyk9ZM4vm5z580f/TVo0mqlcS45eN4ZeHJjxyZcMMEEhMSGZU+ilHpo06aP+WWKSTEJfDygpcZv2L8SfNnpc0CYPic4UxeO/mEefFx8Uy9ZSoAw2YPY8bGGSfMr5dQj4k3OFdqPzr9UeZmzj1hfrOazX66Bn/otKGk70g/YX77eu0ZOWgk4Dz7oGi31imNUn66O/jWD2896XLNns168my/ZwG4dvy17M3Ze8L8vq368uSFTwLQf2x/co/nnjB/YPuBPNTrIcD2vaL7Xn5ePDu23IoWVOEX52Yz8L1+Jy1v+16RfW/FCmZtuAAmhubuhVKPKFT1AeBVoBuQAoxU1d+UdyAi0kdEvhGRV0WkT3mv3xgTfgoKKrFr69UcP16NxKYTqVM9ch/NHFLHj8PevaW/r5wE9MxsEWkBtFPV6SKSAFRU1YMBLPcmMBDYpapdfKZfDvwHqAj8T1X/LiIXAo/gnNp6WlXXlbZ+a6MwJnLlFyi/HruYz1fuILHxJ1SrufanX/6mFH36OH9nzTqlxcu9jUJE7gYmAK+5k5oCHwe4/lHA5UXWVxF4CegPdAJuEpFOwDeq2h/4I/CXANdvjIlQf/tsFdNW7OCJKzpRrWZon9hmyiaQxuxfA71xOgNEVX/EuWS2VKr6NbCvyORzgHWqukFVjwHvA1epaoE7fz9gd9gYE8Ve/3oDb363kV/1bsWd58Xo40wjSCCN2UdV9ZiIcxWCiFTCadQ+VU2BDJ/xTKCHe4PfZUBt4MWSFhaRIcAQgObNm59GGMYYL0xclMnfpqziijMa8/gVHQHnYgBTBn1DW1+BJIrZIvIYznMpLgHuByadxjaLu+5N3Tu9S72JT1VHAiPBaaM4jTiMMSE2c/VO/jBxKb3b1uNfg7v9dBls4RVjJkBPhra+Ajn19EdgN7AMuAeYAjxxGtvMBJJ8xpsB205jfcaYCLBw0z7uH7uYjo1r8NptqVSpVNHrkEyA/B5RiEgFYKl7xdLr5bTNBUA7EWkFbMW5L+Pmclq3MSYMLd+azS/fWkDjWvG8lXYO1auc+NXTf2x/gJ/uZzCl6O/UF1NDU19+jyjcBuYfROSUGgNE5D1gLpAsIpkicqeq5gEPAJ8Dq4DxqrqijOsdJCIjs7OzTyUsY0wIrdt1kNvf/J6a8XGMuasH9WucfK1K7vHck25SNH7k5jqvEAmkjaIxsEJEvgcOF05U1StLW1BVbyph+hScU1inRFUnAZNSU1PvPtV1GGOCL2NfDrf+73sqiDDmrh40rR3vdUjmFASSKOyeBmNMmWXuz+HGkfM4kpfP+0POpVViNa9DMqcokEehzg5FIMaY6LE9O5ebX5/PwSPHeffuc+nQqKbXIZnT4O/BRd+q6nkicpAT75sQnMtZ7ZM3xpxk54Ej3Pz6fPYfPsbou3oE9PChge0HhiCyKDIwtPUVUF9P4cr6ejImvOzIPsJNr89j14EjvHPnOZzdoq7XIZlilLWvp1JPPZV0xZOqbilLYOVJRAYBg9q2betVCMaYIrZl5XLT6/PYe+iYJYkoE8gT7pb5jFYFWgFrVLVzMAMLhB1RGBMeMvfn/HS66Z07z+HM5nXKtHzhMzqs99gAhbj32EAas88osoGzcO7QNsYYNu45zC2vz+PQ0TzG3NWDbkm1vQ7JlLNALo89gaouFpHuwQjGGBNZ1uw4yK1vzCe/QHlvyLl0blJ6w7WJPIG0UfzeZ7QCcBZO30/GmBi2LDOb29+cT1zFCoy/51zaNqjhdUgmSAI5ovD99POAz4DQPKjVGBOW5qzfw91vL6R2QmXevbsHLerZzXTRLJA2irC7M9uuejLGO5+v2MFv3l1Cy8QE3vlVDxrVqnra67yh8w3lEFkMuSG09RXIVU+f+psfSJ9PwWJXPRkTWuMXZPDIh0vp2qw2o37ZndoJlb0OyZyCcr/qCdgINALGuOM3AZtwen81xsQAVeXFmet4/su1nN8ukVdvPZtqVcp8LUyJco7nAJAQl1Bu64xqOU59kRCa+grkkz5TVS/wGZ8kIl+r6mPBCsoYEz7yC5Q/fbKcsfO3cM2ZTfn7tV2pXCmQZ54FbsDYAYDdRxGwAU59nep9FGUVSKKoLyKtVXUDgPvAofrBDcsYEw5yjuXxu/fT+XLlTu69sA1/vDwZkeKeZmyiWSCJ4v+AWSKywR1vid1wZ0zU233wKHe9vYBlW7P586BOpPVu5XVIxiOBXPU0TUTaAR3cSatV9Whww/LPrnoyJrjW7TpI2lsL2HPoKK/dlsolnRp6HZLxUKknGkUkAXgYeEBVfwCai4infQKr6iRVHVKrlt0Fakx5++bH3Vz98hyOHM9n3JCeliRMQKee3gIWAT3d8UzgA2BysIIyxnhjzLzNPPXpCtrWr84baak0qxOaq2rSUtJCsp2okZYW0s0FkijaqOpgEbkJQFVzxVqzjIkqefkFPP3ZKkbN2cTFHRrwwk1nUr0cL38tjSWKMgrDRHFMROJxn3InIm0AT9sojDHlJyvnGA+8u4Rv1+3hzvNa8diAjlSsENrfgnty9gCQmJAY0u1GrD1OfZEYmvoKJFE8BUwDkkRkLNAbSAtmUMaY0Phx50Huemch27OO8M/runJ9apIncVw3/jrA7qMI2HVOfYXNfRSq+qWILAbOxXle9u8A6wHMmAg3bfkOHhyfTnzlSrw35FzOblG2hw2Z2OE3UYhIT6Ap8LWqfiYiXYEXgPMBb356GGNOS36BMmL6Wv47cx3dkmrz6q1n0bhWvNdhmTBW4uWxIvJP4E3gWuAzEXkK+BKYD7QLTXglxjZIREZmZ2d7GYYxEScr5xh3vr2A/85cx+DUJMbfc64lCVMqf0cUV+D083REROoA24CuqvpjaEIrmapOAialpqbe7XUsxkSKZZnZ3DtmEbsPHuXpX3Thlh7NrTsOExB/iSJXVY8AqOp+EVkTDknCGFM2qsq4BRn86dMVJFarzPh7e5ISZs+1vi/1Pq9DiCz3hba+/CWKNkWeRdHSd9zL51AYYwKTcyyPJz5azodLtnJe20ReuOlM6lYLv2dIDO4y2OsQIsvg0NaXv0RxVZHx54MZiDGmfP248yD3j13Mut2HGNqvHb+5uF3I748IVEZ2BgBJtewamYBkOPVFUmjqq8REoaqzQxKBMaZcqSofLMzkqU9XUK1KRcbc2YPebcP7RrbbProNsPsoAnabU19hcx+FMSZyHDxynCc+Xs4n6dvo1aYeIwan0KDm6T/T2sQ2SxTGRIn0jCx+9/4SMvbl8OAl7bn/orZhe6rJRBZLFMZEuPwC5dXZ6/n3l2tpWLMq7w/pyTmt6nodlokipSYKEWmP8zyKFr7vV9WLgxiXMSYAW7NyeXB8OvM27OOKro155uozqBUf53VYJsoEckTxAfAq8DqQH9xwAmNPuDMGPknfyhMfLye/QPnHtV25PrVZxN5A92DPB70OIbI8GNr6ElX1/waRRap6dojiKZPU1FRduHCh12EYE1LZOcd58pPlfPrDNs5qXpt/D06hRT3rp9MEzv1eTw30/YEcUUwSkfuBj/B5DoWq7juF+Iwxp2H22t38YcIP7D10jN9f0p77+7ShUsVSn2gc9tbsWQNAcmKyx5FEiDVOfZEcmvoKJFHc4f592GeaAq3LPxxjTHEOH83jmSmrGDt/C+0aVOd/t3fnjGbR88z4eybfA9h9FAG7x6mvsLmPQlVbhSIQY0zx5qzfwx8mLGVrVi53ndeKhy5LpmpcRa/DMjEkkKue4oD7gAvcSbOA11T1eBDjMibmHTqax3NTVzN63mZa1ktg/D096d7SLns1oRfIqadXgDjgZXf8NnfaXcEKyphY982Pu3lk4jK2Zefyq96tePiyZOIr21GE8UYgiaK7qnbzGZ8pIj8EKyBjYll2znH+NmUl4xdm0rp+NSbc25OzW9hRhPFWIIkiX0TaqOp6ABFpTZjcT2FMtFBVpizbwVOfrmB/zjHu69OG3/VtFzNtEU9c8ITXIUSWJ0JbX4EkioeBr0RkAyA4d2j/MqhRGRNDtmXl8qdPVjB91U7OaFqLUb/sTpem0XNFUyD6te7ndQiRpV9o6yuQq55miEg7IBknUaxW1aOlLGaMKUV+gfL2nE08/8Ua8lV5bEAHftW7VVTcF1FW6TvSAUhplOJpHBEjPd35m5ISks2VmChE5GJVnSki1xSZ1UZEUNUPgxybMVFraWYWj3+0nGVbs+mTXJ9hV3UhqW6C12F5Zui0oYDdRxGwoUOdv2FwH8WFwExgUDHzFLBEYUwZZeceZ/jnaxgzfzOJ1avw4s1ncsUZjSO2jyYTG/w94e4pd/CvqrrRd56IeHoTnnUKaCKNqvLRkq08M2U1+w4f5Y6eLfn9pe2pWdV6ejXhL5DG7InAWUWmTQA86yhQVScBk1JTU+/2KgZjArVq+wH+9MlyFmzaT0pS7ZhsrDaRzV8bRQegM1CrSDtFTcCerWhMKbJzjvPv6WsZPW8zNatW4rlrz+D6s5OoYE+dMxHG3xFFMjAQqM2J7RQHAfslb0wJ8guU8Qsz+Ofna8jKOcbNPZrz0KXJ1E6o7HVoYeuZvs94HUJkeSa09eWvjeIT4BMR6amqc0MYkzER6/uN+/jLpBWs2HaAc1rW5akrO9G5iZ1mKk2vpF5ehxBZeoW2vgJpo7hXRFapahaAiNQBnlfVXwU1MmMiSMa+HP4+bTWfLd1O41pV+c+NKVzZrYldzRSgORlzAEsYAZvj1FeoEkYgiaJrYZIAUNX9InJm8EIyJnIcPHKcl2et541vN1JBYGi/dtxzQRvrwK+MHpvxGGD3UQTsMae+wuE+ikIVRKSOqu4HEJG6AS5nTNTKyy9g/MJM/vXlGvYcOsbVZzbl4cuSaVI73uvQjCl3gXzhPw/MEZEJ7vj1wN+CF5Ix4UtVmbVmN89MWcWPuw7RvWUd3rijO92SansdmjFBE0hfT++IyELgYpy+nq5R1ZVBj8yYMLM0M4tnp6xm7oa9tKyXwKu3ns1lnRtaO4SJev7uo6ipqgfcU007gHd95tVV1X2hCNAYr23ee5jhX6xl0g/bqFutMn8e1Imbe7SgcqXY67zPxCZ/RxTv4txHsQinb6dC4o63DmJcxnhu18EjvDhzHe/O30JcxQr85uK2DLmgNTWs241yN+LyEV6HEFlGjAjp5vzdRzHQ/etpv07GhFp27nH+980G3vh2I0fzCrixexK/69uOBjWtQ4Jgse7FyyhE3YsXKrWNQkQ+Ad4HPlHVnOCHZIw3co/lM2rOJl6dvZ7s3ONc0bUxD12aTKvEal6HFvWmb5gO2AOMAjbdqa9QPcAokKue/gUMBv4uIt8D44DJqnokqJEZEyJH8/J5b/4WXvxqPXsOHeWi5Po8eGmyddwXQk9//TRgiSJgTzv1FTaJQlVnA7NFpCLOlU93A2/idA5oTMQ6llfAB4syeGnmOrZlH6FHq7q8cutZdG9Z1+vQjAkrAd04JyLxOB0DDsbpcvztYAZlTDAdzy9g4qJM/jtzHVuzcjmzeW3+eX03erWpZ5e6GlOMQNooxgE9gGnAS8AsVS0IdmDGlLfj+QV8uNhJEJn7c+nWrBZPX92FPu3rW4Iwxo9AjijeAm5W1fxgBxMoe8KdKYtjeQVMXJzJS185CaJrs1r85crOXNyhgSUIYwIgqlr6m0R6AS3xSSyq+k7wwgpMamqqLly40OswTJg6cjyf8QszeHXWerZlH6Fbs1oM7deePsl2BBFu1uxZA0ByYrLHkUSINU59kXxq9SUii1Q1NdD3B3LqaTTQBkgHCo8qFPA8URhTnMNH83h3/hZe/2YDuw4e5ewWdXj22q5c0C7REkSYsgRRRqeYIE5VIKeeUoFOGsihhzEeys45zttzN/HWdxvZn3Ocnq3rMWJwCj2tkTrsTVozCYBByYNKeacBYJJTXwwKTX0FkiiWA42A7UGOxZhTsuvAEd74diNj5m3m8LF8Lu7QgF9f1JazW9TxOjQToOfnPg9YogjY8059hVOiSARWujfbHS2cqKpXBi0qYwKwcc9hRn69nomLtpJXUMDArk24r08bOja2W3yMKU+BJIo/BzsIY8oiPSOL12avZ9qKHcRVrMD1qc24+/zWtLSuNowJioDuzBaRhkB3d9L3qroruGEZc6KCAmXW2l28NnsD8zfuo0bVStx3YRt+2bsV9WtU8To8Y6JaIFc93QD8E5iF08X4f0XkYVWd4HdBY8rBkeP5fLxkK69/s4H1uw/TpFZVnriiIzee05zqVeyJvMaEQiD/aY8D3QuPIkSkPjAdsERhgmbPoaOMmbeZMfM2s+fQMTo3qcl/bkxhwBmNiatoDwyKNqOvHu11CJFldGjrK5BEUaHIqaa9gP2nmqBYs+Mgb323kQ+XbOVYXgEXd2jAXee1sktco1xSrSSvQ4gsSaGtr0ASxTQR+Rx4zx0fDEwNXkgm1hS2P7z57Sa+XbeHqnEVuO7sZvyqdyvaNqjudXgmBMYtHwfA4C6DPY4kQoxz6ovBoamvQBqzHxaRa4DzcNooRqrqR0GPzES9g0eOM2FRJm/P2cSmvTk0qlmVP1yezE3dm1OnWmWvwzMh9MrCVwBLFAF7xakvzxOFiLQFGqrqd6r6IfChO/0CEWmjqutDEqGJOut3H+KdOZuYuHgrh47mcXaLOjx4aTKXd2lk7Q/GhCF/RxQjgMeKmZ7jzrNbKE3A8guUmat38c7cTXzz4x4qV6zAwK6NuaNXS7ol1fY6PGOMH/4SRUtVXVp0oqouFJGWwQvJRJO9h44ybmEGY+dtYWtWLo1qVuWhS9tz4znNSaxu9z8YEwn8JYqqfubFl3cgJnqoKou37GfMvC18tnQ7x/IL6Nm6Hk8O7Ei/jg2pZKeXjIko/hLFAhG5W1Vf950oIncCi4IblolEB48c5+P0bYydt5nVOw5So0olbu7RnFt6NKddwxpeh2fC2IQb7LasMpkQ2vrylyiGAh+JyC38nBhSgcrA1UGOy0SQZZnZvPv9Zj5J30bOsXw6N6nJM1efwVUpTahmd0+bACQmJHodQmRJDG19lfhfrKo7gV4ichHQxZ38marODElkJqwdPHKcT3/Yxnvfb2H51gNUjavAoK5NuOXcFnRrVstujjNlMip9FABpKWmexhExRo1y/qalhWRzgdxH8RXwVQhiMWFOVUnPyOL97zOYtNQ5eujQqAZ/ubIzvzizKbXi47wO0UQoSxRlFG6Jwpj9h4/x0ZKtjFuQwZqdB4mPq8igbo256ZzmpCTVtqMHY6KcJQpTrPwC5dt1exi/IIMvV+7kWH4B3ZJq8+w1ZzCwa2NqVLWjB2NihSUKc4LNew8zYVEmExZlsj37CLUT4rjl3ObckJpkT44zJkZZojAcPprHlGXbmbAok/kb91FB4Px29Xn8io5c0qkhVSpV9DpEY4yHLFHEqIICZd6GvUxYnMm05TvIOZZPq8RqPHxZMtec1ZTGteyeShM6U26Z4nUIkWVKaOvLEkWMWb/7EB8t3spHS7ayNSuXGlUqcWW3Jlyf2oyzmtexhmnjiYS4BK9DiCwJoa2vsEoUIlIN+Bp4SlUnex1PtNh76CiTl27nwyVb+SEj66dTS3/s34FLOzWkapydWjLeennBywDc3/1+jyOJEC879cX9oamvoCYKEXkTGAjsUtUuPtMvB/4DVAT+p6p/d2f9ERgfzJhiRe6xfKav2snHS7Yye+1u8gqUjo1r8sQVHbmyWxMa1PTXlZcxoTV+hfNvb4kiQOPdr8loSBTAKOBF4J3CCSJSEXgJuATIxOlT6lOgCbAS/50RGj/yC5Q56/fw8ZJtfL5iB4eO5tGoZlXuPL8VV5/ZlA6N7KolY0zZBTVRqOrXxXRJfg6wTlU3AIjI+8BVQHWgGtAJyBWRKapaEMz4ooGq8kNmNp+kb2XSD9vZc+goNapUYsAZjfjFmU3p0aoeFStYu4Mx5tR50UbRFMjwGc8EeqjqAwAikgbsKSlJiMgQYAhA8+bNgxtpGFu78yCfpm9j0tJtbN6bQ+WKFbi4QwOuSmnCRR0aWLuDMabceJEoivt5qz8NqI7yt7CqjgRGAqSmpqq/90abzXsPM3npdj5N38aanQepINC7bSK/vqgtl3VuZH0tGWOCwotEkQkk+Yw3A7Z5EEdEyNyfw2dLtzN56XaWbc0GILVFHf5yZWf6n9GIBjWsScdEvllps7wOIbLMmhXSzXmRKBYA7USkFbAVuBG42YM4wtb27Fw+W7qdz5ZtZ8mWLAC6NqvFYwM6MOCMxjSrY9ecG2NCJ9iXx74H9AESRSQT5/6IN0TkAeBznMtj31TVFWVc7yBgUNu2bcs7ZM9sy8plyrLtTFm2ncVucujcpCZ/uDyZK85oTIt61bwN0JggGj5nOAAP9XrI40gixHCnvngoNPUlqpF7mj81NVUXLlzodRinLGNfDtOW72DK8p+PHDo2rskVZzRiwBmNaV2/urcBGhMifUb1AewUVMD69HH+nuIpKBFZpKqpgb4/rO7MjgUbdh9i6vIdTFu+46c2hy5Na/LwZcn079LIkoMxJuxYoggyVWX1joNMc5PDmp0HAeiWVJtH+negf5dGdlrJGBPWLFEEQUGBsiQji89X7ODzFTvYvDcHEejesi5PDuzE5V0a0bS29c5qjIkMlijKybG8AuZu2MvnK3bw5cqd7D54lLiKQq82idxzQRsu6dSQ+jWqeB2mMWEpPs5+OJVJfGjrKyIbs32uerr7xx9/9CyOA0eOM2vNbr5YsYNZa3Zz6GgeCZUrclFyAy7p1JCLOzagpj0y1BgTZsramB2RiaKQF1c9bc3KZfrKnXy5cifzNuwlr0BJrF6Zfh0bckmnhvRum2jdZxhjwppd9VTOCgqU5duymb5yJ9NX7WLl9gMAtK5fjTvPb8WlnRqSklTHOt4z5jQMmz0MgCcvfNLjSCLEMKe+eDI09WWJohi5x/L5bt0eZqzeyYxVu9h18CgVBM5uUYfHBnSgb8eGtLHLWI0pNzM2zgAsUQRshlNflihCbGtWLjNX7+Kr1bv4bt0ejuYVUK1yRS5Mrk/fDg25qEMD6lar7HWYxhgTcjGbKPLyC1iSkcVXq3cxc/UuVu9w7m9oXjeBm3s0p2+HhpzTqi6VK1XwOFJjjPFWRCaK0+3rafTcTTw1YSEFcfGgBVQ5mEmd/Ru45tx2PPHbu8nNzWXAgAEnLZeWlkZaWhp79uzhuuuuO2n+fffdx+DBg8nIyOC22247af6DDz7IoEGDWLNmDffcc89J85944gn69etHeno6Q4cOPWn+M888Q69evZgzZw6PPfbYSfNHjBhBSkoK06dP5+mnnz5p/muvvUZycjKTJk3i+eefP7leRo8mKSmJcePG8corr5w0f8KECSQmJjJq1ChGjRp10vwpU6aQkJDAyy+/zPjxJz/Rdpbb3cDw4cOZPPnER6LHx8czdepUAIYNG8aMwkNrV7169Zg4cSIAjz76KHPnzj1hfrNmzRgzZgwAQ4cOJT09/YT57du3Z+TIkQAMGTKEtWvXnjA/JSWFESNGAHDrrbeSmZl5wvyePXvy7LPPAnDttdeyd+/eE+b37duXJ93TAP379yc3N/eE+QMHDuQht1+ePoXdL/i44YYbuP/++8nJyYnJfe/IoCNUrVfV9r1A9730dGalpJxUzmCJyEShqpOASampqXefyvINa1YlPms9Cfs3UDV7ExXzjwJQL64VItYobUyo1YmvQ0JCgs+TaYxfcXFQr17INmeXxxpjTIwp6+WxdgLeGGOMX5YojDGee3T6ozw6/VGvw4gcjz7qvEIkItsojDHRZW7m3NLfZH42N7T1FZFHFCIySERGZmdnex2KMcZEvYhMFKo6SVWH1KpVy+tQjDEm6kVkojDGGBM61kZhjPFcs5rNvA4hsjQLbX3ZfRTGGBNjYup5FCKyG9h8iosnAnvKMZxIEqtlj9VyQ+yWPVbLDf7L3kJV6we6oohOFKdDRBaWJaNGk1gte6yWG2K37LFabijfsltjtjHGGL8sURhjjPErlhPFSK8D8FCslj1Wyw2xW/ZYLTeUY9ljto3CGGNMYGL5iMIYY0wALFEYY4zxKyYThYhcLiJrRGSdiDzidTzlSUSSROQrEVklIitE5Hfu9Loi8qWI/Oj+reOzzKNuXawRkcu8i/70iUhFEVkiIpPd8Vgpd20RmSAiq93PvmcslF1E/s/dz5eLyHsiUjVayy0ib4rILhFZ7jOtzGUVkbNFZJk77wUJ5LGeqhpTL6AisB5oDVQGfgA6eR1XOZavMXCWO1wDWAt0Av4BPOJOfwR4zh3u5NZBFaCVWzcVvS7HaZT/98C7wGR3PFbK/TZwlztcGagd7WUHmgIbgXh3fDyQFq3lBi4AzgKW+0wrc1mB74GegABTgf6lbTsWjyjOAdap6gZVPQa8D1zlcUzlRlW3q+pid/ggsArnH+oqnC8T3L+/cIevAt5X1aOquhFYh1NHEUdEmgFXAP/zmRwL5a6J8yXyBoCqHlPVLGKg7Dj91cWLSCUgAdhGlJZbVb8G9hWZXKayikhjoKaqzlUna7zjs0yJYjFRNAUyfMYz3WlRR0RaAmcC84GGqrodnGQCNHDfFk31MQL4A1DgMy0Wyt0a2A285Z52+5+IVCPKy66qW4HhwBZgO5Ctql8Q5eUuoqxlbeoOF53uVywmiuLOx0XdNcIiUh2YCAxV1QP+3lrMtIirDxEZCOxS1UWBLlLMtIgrt6sSzimJV1T1TOAwzmmIkkRF2d3z8VfhnFppAlQTkVv9LVLMtIgrd4BKKusp1UEsJopMIMlnvBnO4WrUEJE4nCQxVlU/dCfvdA87cf/ucqdHS330Bq4UkU04pxMvFpExRH+5wSlLpqrOd8cn4CSOaC97P2Cjqu5W1ePAh0Avor/cvspa1kx3uOh0v2IxUSwA2olIKxGpDNwIfOpxTOXGvYLhDWCVqv7LZ9anwB3u8B3AJz7TbxSRKiLSCmiH09gVUVT1UVVtpqotcT7Tmap6K1FebgBV3QFkiEiyO6kvsJLoL/sW4FwRSXD3+744bXLRXm5fZSqre3rqoIic69bZ7T7LlMzrlnyPrh4YgHM10Hrgca/jKeeynYdzKLkUSHdfA4B6wAzgR/dvXZ9lHnfrYg0BXAER7i+gDz9f9RQT5QZSgIXu5/4xUCcWyg78BVgNLAdG41zlE5XlBt7DaYs5jnNkcOeplBVIdetrPfAibg8d/l7WhYcxxhi/YvHUkzHGmDKwRGGMMcYvSxTGGGP8skRhjDHGL0sUxhhj/LJEYcKCiOSLSLrbC+gkEantdUzlIdzKJSJ9RKTXKSy3SUQSgxGTCX+WKEy4yFXVFFXtgtPx2a9DHYCIVAzCaj0vVxF9cO5eNiZglihMOJqL21GZiLQRkWkiskhEvhGRDu70691f6T+IyNfutKoi8pbb1/4SEbnInZ4mIi8WrlxEJotIH3f4kIj8VUTmAz1F5HYRWequd7T7nvoiMlFEFriv3u70C92jhXR3ezXKoVytRGSuu51hInLInd5H3GdsuOMvikiaO3y2iMx21/W5T5cOvxWRlW553nc7ibwX+D835vP9lK2eiHzhlus1iu8jyMQKr+82tJe9VBXgkPu3IvABcLk7PgNo5w73wOmaA2AZ0NQdru3+fRB4yx3ugNPFQ1WcZxS86LOtyUAfd1iBG9zhzjh3sSa643Xdv+8C57nDzXG6RwGYBPR2h6sDlcqhXJ8Ct7vDv/ZZvg/u3ebu+ItuueKAOUB9d/pg4E13eBtQpUgd/Rl4yGc9JZXtBeBP7vAVbj0ler2f2MubV6USM4gxoRUvIulAS2AR8KU4PeD2Aj6Qnx/CVcX9+x0wSkTG43QGB073Jf8FUNXVIrIZaF/KdvNxOlAEuBiYoKp73HUU9v3fD+jkE0NN9+jhO+BfIjIW+FBVfbtvPtVy9QaudYdHA8+VEn8y0MVdLzgJabs7bykwVkQ+xunWozglle0C4BoAVf1MRPaXEoeJYpYoTLjIVdUUEamF84v/18AoIEtVU4q+WVXvFZEeOL9200UkhZJPj+Rx4mnWqj7DR1Q13x0Wiu9yuQLQU1Vzi0z/u4h8htOX1jwR6aeqq0+nXIXFK0MZBFihqj2LWeYKnC/8K4EnRaRzoGVzE4f172MAa6MwYUZVs4HfAg8BucBGEbkenJ5xRaSbO9xGVeer6p+APThdKn8N3OLOb49zKmUNsAlIEZEKIpJEyU81mwHcICL13HXUdad/ATxQ+CY3KRXGsExVn8PpkK/D6ZYL5yjlRnf4Fp9VbMb55V/FTTp93elrgPoi0tNdV5yIdBaRCkCSqn6F8zCn2jinxw7iPCK3ULFl48S67I/TyaCJUZYoTNhR1SU4z/u9EefL6k4R+QFYwc+Prf2n22i9HOdL7QfgZaCiiCwDxgFpqnoU58t3I067xnBgcQnbXQH8DZjtbq+wm/bfAqluo/BKnAZhgKHiNqjjfPlPLYdy/Q74tYgsAGr5LJuB80zopcBYYIk7/RhwHfCcu650nNNaFYExbl0sAf6tzuNRJwFXFzZm+ynbX4ALRGQxcClOe4+JUdZ7rDFhTEQOqWp1r+Mwsc2OKIwxxvhlRxTGGGP8siMKY4wxflmiMMYY45clCmOMMX5ZojDGGOOXJQpjjDF+/T+dQTN5EULgqwAAAABJRU5ErkJggg==\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "plt.plot(requests, conviction_required)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request, 0, ax[3], 'g', '--')\n", "plt.hlines(max_achievable_conviction, 0, max_request, 'g', '--')\n", "plt.hlines(min_required_conviction, 0, max_request, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Absolute Terms; Log Scale\")\n", "plt.xlabel(\"Resources Requested\")\n", "plt.ylabel(\"Conviction Required to Pass\")\n", "plt.gca().set_yscale('log')" ] }, { "cell_type": "code", "execution_count": 451, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "(3391.946966118136, 217084.60583156074)" }, "metadata": {}, "execution_count": 451 }, { "output_type": "display_data", "data": { "text/plain": "
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\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "plt.figure(figsize=(10, 7))\n", "plt.plot(requests, conviction_required)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request, 0, ax[3], 'g', '--')\n", "plt.hlines(max_achievable_conviction, 0, max_request, 'g', '--')\n", "plt.hlines(min_required_conviction, 0, max_request, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Absolute Terms; Log Scale\")\n", "plt.xlabel(\"Resources Requested\")\n", "plt.ylabel(\"Conviction Required to Pass\")\n", "plt.gca().set_yscale('log')\n", "plt.gca().set_ylim(min_required_conviction/2, max_achievable_conviction*2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot series 2: \"Relative Terms\" \n", "\n", "This set of plots looks at what happens when we knock out the dependence on alpha and supply, as well as treating requests as share of total funds." ] }, { "cell_type": "code", "execution_count": 452, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "Text(0, 0.5, 'Conviction Required to Pass as share of max achievable')" }, "metadata": {}, "execution_count": 452 }, { "output_type": "display_data", "data": { "text/plain": "
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}, "metadata": { "needs_background": "light" } } ], "source": [ "plt.plot(requests_as_share_of_funds, conviction_required_as_share_of_max)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request/funds, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request/funds, 0, ax[3], 'g', '--')\n", "plt.hlines(1, 0, max_request/funds, 'g', '--')\n", "plt.hlines(min_required_conviction/max_achievable_conviction, 0, max_request/funds, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Relative Terms; Linear Scale\")\n", "plt.xlabel(\"Resources Requested as a share of Total Funds\")\n", "plt.ylabel(\"Conviction Required to Pass as share of max achievable\")" ] }, { "cell_type": "code", "execution_count": 453, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "(0.0, 1.1)" }, "metadata": {}, "execution_count": 453 }, { "output_type": "display_data", "data": { "text/plain": "
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}, "metadata": { "needs_background": "light" } } ], "source": [ "plt.figure(figsize=(10, 7))\n", "plt.plot(requests_as_share_of_funds, conviction_required_as_share_of_max)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request/funds, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request/funds, 0, ax[3], 'g', '--')\n", "plt.hlines(1, 0, max_request/funds, 'g', '--')\n", "plt.hlines(min_required_conviction/max_achievable_conviction, 0, max_request/funds, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Relative Terms; Linear Scale\")\n", "plt.xlabel(\"Resources Requested as a share of Total Funds\")\n", "plt.ylabel(\"Conviction Required to Pass as share of max achievable\")\n", "plt.gca().set_ylim(0, 1.1)" ] }, { "cell_type": "code", "execution_count": 454, "metadata": {}, "outputs": [ { "output_type": "display_data", "data": { "text/plain": "
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z7S7ITx/mFVX1uxyPUCR0xWazZs2YNWtW2GEYY0zSEJEfo83zU/S0VVwvnept7DJcm2FjjDElgJ87ijuA4UA7EVmHeybgmtirGGOMKS7yzChUdSXu0fJKuB4Zk30sCmOMMfkQNaMQkWtU9Q0R+W2O6QCo6j8Djs0YY0wCiHVHUcn7W6UoAokHEekH9GvVqlXYoRhjTLGRr76ekkVaWppaqydjjPFPRGaralpu8/x04VEbuBk3ktLPy6vqDfEK0BhjTOLy0+rpA9w4u5Pw+nY3xhhTcvh94O6+wCMxxpgI3Ud0B2DqoKmhxpE0und3f6dOjfum/TxwN15E+uS9mDHGlExjZ2ewYsuesMMITNSMQkR2eyOY3YPLLPaLyK6I6cYYE5iaFWtSs6KvIahDtWX3Qe4bO5+3ZqwJN5CaNd0rAFGLnlQ1aZrFGmOKn7EDxoYdgi9j52RwJEu58ozGIQcSXHrlWfTkjXZWLeJzdRH5VWARFYI32tTwnTt3hh2KMaYEUFXembmWTs1OoFWd4ntt7aeO4k+q+vMvr6ruAP4UWESFoKrjVHVwtWrxGqvdGBOW+yfdz/2T7g87jJi+XfkTq7bu5cpOTcIOBe6/370C4KfVU26ZiZ/1jDGmwKZnTA87hDy9PXMNVSqUoc/J9cMOBaYHl15+7ihmicg/RaSliLQQkaeB2YFFZIwxSWDHvkNMWLiRS05rSEq50mGHEyg/GcVdwCHgHeBd4ACu63FjjCmx3puzjkNHshKj2ClgfroZ3wv8oQhiMcaYpKCqvD1zDac2qsZJDaqGHU7g/Pb19HugPVAhe7qqnhdgXMaYEq5R1UZhhxDVjFU/sWzTHp7of3LYoRzVKLj08lMpPQpX7NQXuBW4DtgSWETGGAO8cekbYYcQ1YivV1O9YlkuTm0YdihHvRFcevmpo6ipqv8BDqvqNK/X2C6BRWSMMQksY/s+Pl28kavOaEKFssW7EjubnzuKw97fDSLyS2A9kLj3hMaYYmHIxCEADOs1LNQ4chr57Y8AXNOlaciR5DBkiPs7bFjcN+0no3jMezJ7KPBvoCrwm7hHEgc2wp0xxUf6xvSwQzjO/kOZvP3dWi5sX4+G1VPCDudY6emBbdpPq6fx3tudwLmBRRIHqjoOGJeWlnZz2LEYY4qf/6WvY+f+wwzq1izsUIqUnzoKY4wp8VSVEV+v5sT6VTmjeY2wwylSllEYY4wPXy7fytJNu7n+F80QkbDDKVLWZ5MxJiG1qdkm7BCO8eK0FdStWp6LUxuEHUru2gSXXn4euBsJ3Jndg6yINAVeVdUegUVljCnxhvcbHnYIP5ufsYNvVmzj/t7tKF8mQZvEDg8uvfwUPX0FzBCRPiJyM/AZMCywiIwxJsG8NG0lVSqU4dedi3+/Trnx0+rpJRFZBEwBtgKnqerGwCMzxpRog8cNBsK/s1i9dS8TFm7glnNaUqVC2VBjiWmwS68g7iz8FD0NBB4GrgVOAT4WketVdV7cozHGGM+ybcvCDgGAl79cSZlSpbg+0ZvELgsuvfxUZvcHzlTVzcBbIvI+8DqQGlhUxhiTADbvPsC7szPof3pD6lStkPcKxZSfoqdf5fj8nYicEVhExhiTIF6atpLMLOWWs1uGHUqo/BQ9VQBuJEc348ANQQVljDFh27z7AKNm/MivUhvSrFalsMMJlZ+ip5HAEuBC4C/A1cD3QQZVUNbXkzHFR2q91FD3P3zaSg5nKnedlyS/J6mpgW1aVDX2AiJzVfU0EZmvqqeISFngk0QeuCgtLU1nzZoVdhjGmCS1ZfdBzvrH5/Q5uT7/HJAadjhFQkRmq2pabvP8PEeR3c34DhHpAFQDmsUpNmOMSTjDv1jBoSNZ3HVe67BDSQh+ip6Gi8gJuCayHwKVgT8GGpUxpsS75r1rgKIf6W7L7oOM/NbVTTRPprqJa1x6BTHSnZ9WT694b6cBLeIegTHG5CJjV0Yo+3328+WubqJHkt1NZASXXn5aPVXHPWzXLHJ5Vb07sKiMMSYEa7bt483v1nBlp8bJdTcRMD9FTx8D3wILgKxgwzHGmPD887OllC4l3J1sdxMB85NRVFDV3wYeiTHGhGjx+l18MG89t57Tkrol+Cns3Ph6jsLrNXY8cDB7oqr+FFhUxpgSr2ujrkW6v//7ZAlVypfh1mR9CrtrcOnlJ6M4BPwf8CCQ/dCFYhXbxpgAPd7z8SLb1/QV25iydAv39WpHtYoJ3ENsLI8Hl15+MorfAq1UdWtgURhjTEgys5RHxy+mYfUUrv9Fs7DDSUh+HrhbBOwLOhBjjInUf3R/+o/uH/h+xs7OYPGGXfy+V1sqlE3Q0ev86N/fvQLg544iE0gXkSkcW0dhzWONMYHZtm9b4PvYc/AI//fpUk5rUp2LTk3QsbD92hZcevnJKP7nvYwxplh5ceoKtuw+yPCBpyMiYYeTsPw8mf16UQRijDFFKWP7Pl7+ciUXpzbgtCYnhB1OQvNTR2GMMcXOo+MXU0qE+3q1CzuUhOen6MkYY4pcj+Y9Atv2lKWb+WTRJn7fqy0NqqcEtp8i1SO49Io6HoWIjFTVgSJyj6r+K7AIAmDjURhjojl4JJMLn/6CUqWEifecTbkyVrACBR+P4nQRaQrcICIniEiNyFcwoRaOiPQTkeE7d+4MOxRjTIJ6+YuVrN62jz9f1N4yCZ9ipdKLwESgHTA7xyshL9dVdZyqDq5WrVrYoRhjCqn3qN70HtU7rttc+9M+np3yA788uT5nta4d122Hrndv9wpA1DoKVX0GeEZEXlDV2wLZuzHGRLH/8P64bk9Veeh/CyktwoO/PDGu204I++ObXpH8NI+9TUROBc7yJn2hqvMDi8gYYwLw4bz1TFu2hUf6nVR8KrCLSJ4FdCJyNzAKqOO9RonIXUEHZowx8bJ97yH+Mm4xqY2rM7Brs7DDSTp+msfeBHRW1b0AIvIEMB34d5CBGWNMvDz20ffs3H+YNy49mdKl7Ans/PKTUQiuv6dsmd40Y4wJTN82feOynS+Xb2HsnAxu796SE+tXjcs2E1Lf+KRXbvxkFK8BM0Tkfe/zr4D/BBaRMcYA93a7t9Db2H3gMPeNmU+L2pWK//Cm9xY+vaLxU5n9TxGZCpyJu5O4XlXnBhaRMcbEyd8+/p6Nuw4w5rZuyd2FeMh8deGhqnOAOQHHYowxP+s+ojsAUwdNLdD605Zt4a3v1nLLOS3oWBI6/eve3f2dOjXum7bHEo0xxc6uA4f5w9j5tKpTmd/0bBN2OEnPOgU0xhQ7j3ywiM27DzLm6o5W5BQHvu4oRKSpiPT03qeISJVgwzLGmIIZN289781dx53ntrJxJuLEzwN3NwNjgJe8SY2wEe+MMQlow879PPj+AlIbV+fO81qFHU6x4afo6Q7gDGAGgKouF5E6gUZljCnxBrQfkK/ls7KUoaPncSRLGXZFKmVLl7Aq2AH5S6/88JNRHFTVQ9njyYpIGSD3QSyMMSZObu90e76Wf/nLlXyzYhtP9D+ZZrUqBRRVArs9f+mVH36y3Gki8gCQIiLnA+8C4wKLyBhjgH2H97Hv8D5fy85Zs53/+2QpvTvUY0Ba44AjS1D79rlXAPxkFPcBW4AFwC3Ax8BDgURjjDGePqP60GdUnzyX27nvMHe9OZd61Srw9/6nkF36UeL06eNeAYhZ9CQipYD5qtoBeDmQCIwxpoBUlfvGzmeT9/R1tZSyYYdULMW8o1DVLGCeiDQponiMMca3/07/kYmLNvL7Xm1JbVw97HCKLT+V2fWBRSLyHbA3e6KqXhRYVMYYk4c5a7bz2EeL6dGuDjed2SLscIo1PxnFnwOPwhhj8mHbnoPcMWoO9apV4J8DUillY0wEyk/vsdOKIhBjjIk0KHVQrtMzs5R73k5n295DvHdbN6pVtHoJAAYNCmzTeWYUItIFN5rdiUA5oDSwV1WL8QggxpiwRcso/vnZUr76YSt/v/RkOjSsVrRBJbIAMwo/zWOfBa4ClgMpuKFRnw0sImOMAbbu28rWfVuPmfbR/A08N2UFV3ZqzBWdSujzEtFs3epeAfA7HsUPIlJaVTOB10Tkm0CiMcYYz2WjLwOOjkfx/YZd3PvuPDo2qc6fL25fcp+XiOYyl15BjEfhJ6PYJyLlgHQR+QewASiBz8cbY8Kyfe8hBo+cRdWUMrx4zemUL2NdhxclP0VPA73l7sQ1j20M9A8yKGOMyXboSBa3j5rDpp0HefGa06lTtULYIZU4flo9/ei9PUAITWVFpBLwPHAImKqqo4o6BmNMOFThjx8sZPrKbTx9xak2vkRI/IxH8QsR+UxElonIyuxXYXYqIq+KyGYRWZhjei8RWSoiP4jIH7zJlwJjVPVmwB7yM6YE2bU9jbdnruXOc1txyWmNwg6nxPJTR/Ef4DfAbCAzTvsdgWs59d/sCSJSGngOOB/IAGaKyIe4gZIWeIvFa/9RZQ/oHmlA+wHc3ul29h3el2snZYNSBzEodRBb9239uQIu0m1pt3FFhytYu3MtA98feNz8oV2H0q9tP5ZuXcot4285bv5DZz9EzxY9Sd+YzpCJQ46b/7cef6Nb4258s/YbHpj8wHHzh/UaRmq9VCatnMRjXzx23PyX+r5E21ptGbd0HE9Nf+q4+SMvGUnjao15Z+E7vDDrhePmjxkwhloVazEifQQj0kccN//jqz+mYtmKPD/zeUYvGn3c/OzKyie/eZLxy8YfMy+lbAoTrp4AwKPTHmXyqsnHzK9ZsSZjB4wF4P5J9zM9Y/ox8xtVbcQbl74BwJCJQ0jfmH7M/DY12zC833AABo8bzLJty46Zn1ovlWG9hgFwzXvXkLEr45j5XRt15fGejwPQf3R/tu3bdsz8Hs178PA5DwPQe1Rv9h/ef8z8vm36cm+3ewE793Kee+u31uTQ1u70ObkeDRuk033E8fHZuRdx7vXZzNSmfzruGOPBTx3FTlWdoKqbVXVb9qswO1XVL4Cfckw+A/hBVVeq6iHgbeBiXKaRfSkRNV4RGSwis0Rk1pYtWwoTnjEmZAf31+PwtmtoV68iT12eij147UOdOnDFFYFsWlRzH4NIRDp6bwfgHrJ7DziYPV9V5xRqxyLNgPFez7SIyGVAL1W9yfs8EOiM6+b8WVwdyVd+6ijS0tJ01qxZhQnPGBOSNdv2cekLX1O2tPLida04tYH14+TL2rXub+OCPV8iIrNVNS23ebGKnnKWQURuQIHzChRNdLldM6iq7gWuj/O+jDEJaPveQwwa8R2HM5VytV/knk9/+rl4yORhoFe0WJTPUajquXHfW2wZuKa32RoB64s4BmNMSPYfyuSm/84i46f9vHFTZ34/LWfptAmLn1ZP94hIVXFeEZE5InJBALHMBFqLSHPvAb8rgQ8D2I8xJsEczszizjfnMGfNdoZdmcoZzWuEHZKJ4Kcy+wZV3QVcANTBFQP9vTA7FZG3gOlAWxHJEJEbVfUI7qG+T4DvgdGquiif2+0nIsN37txZmPCMMUVIVbn/vQVMXrKZv1zcgT4n1w87JJODn+ax2XUHfYDXVHWeFLKTFVW9Ksr0j3Fjchd0u+OAcWlpaTcXdBvGmKKjqvx9whLGzM5gSM/WDOzSNOyQTC78ZBSzReRToDlwv4hUAbKCDcsYUxI8N+UHXvpiJQO7NOWeHq2PmTe069CQokpSQ4NLr6jNY39eQKQUkAqsVNUdIlITaKiq8wOLqpCseawxie+1r1fx53GLufS0hjx5+ak2Sl3ICto8FgBVzQLmRHzeBhTqgTtjTMk2etZa/jxuMRe2r8s/Ljsl10xi6dalALSt1baow0tOS1160Tb+6eVrPIpkISL9gH6tWrUKOxRjTBTvz83gvrHzOat1LZ656jTKlM69TU12lyL2HIVPt3hdnATwHIWfVk9JQ1XHqergatVseERjEtG4eesZOnoeXZrXZPjANBtXIkn4eY6ipYiU9953F5G7RaR64JEZY4qVCQs2MOSddNKa1eA/g9JIKWeZRLLwc0cxFsgUkVa4nmSbA28GGpUxplj5aP4G7nxrLqmNq/PqoE5ULFesSr2LPT8ZRZb3MNwlwDBV/Q1gT8QYY3wZN289d789l45NqvP6DWdQubxlEsnGzzd2WESuAq4D+nnTygYXkjGmuPggfR2/8YqbXhvUiUr5yCQeOvuhACMrhh4KLr38fGvXA7cCf1XVVSLSHHgjsIgKwVo9GZM43pm5hj+8t4DOzWsUqLipZ4ueAUVWTPUMLr3yfOAuGdkDd8aE69WvVvGX8Ys5p01tXrzm9AJVXGePCJdaLzW+wRVX6enub2pqgVYv1AN3ItIaeBw4CaiQPV1VbTQRY8wxVJXnpvzAk58u48L2dXnmqtMK3AQ2e+hVe47CpyFD3N+QnqN4DXgBOAKcixvnemTcIzHGJLWsLOWvH33Pk58u41epDXju1x3tOYliwk9GkaKqk3HFVD+q6iPEf3Q7Y0wSO5KZxe/GzOeVr1YxqFsz/jkgNeoT1yb5+KldOuB1DLhcRO4E1uHGpTDGGA4czuSut+by2eJNDOnZmnt6tKaQIxGYBOMnoxgCVATuBh7FFT9dF2BMxpgksWPfIW58fRZz1mznzxe157puzcIOyQTAT++xM723e3BNZROWNY81puis27Gf6179jjXb9vHcrzvGfWS6v/X4W1y3V+z9Lbj0suaxxph8W7R+JzeMmMm+Q5m8fG0aXVrUDDskU0iFah5rjDGRpizdzJ2j5lAtpSzv3tqVdvWqBrKfb9Z+A0C3xt0C2X6x841LL7rFP70sozDG+PbmjDU8/MFC2tatwmvXd6Ju1Qp5r1RAD0x+ALDnKHx7wKVXKM9RiMg/RKSqiJQVkckislVErol7JMaYhJWZpTw2fjEPvL+As1rXYvStXQPNJExi8dPQ+QJV3QX0BTKANsDvAo3KGJMw9h48wi0jZ/38jMQr16ZZD7AljJ9vO7un2D7AW6r6k7WRNqZkyNi+j5ten8XyzXv4y8XtubZrs7BDMiHwk1GME5ElwH7gdhGpDRwINixjTNi+W/UTt74xm8OZWbw6qBPntKkddkgmJL6ax4rICcAuVc0UkYpAVVXdGHh0+RTxHMXNy5cvDzscY5LWmzPW8McPFtKkZkVevjaNlrUrF3kM1ntsPgXYe2yeGYWIXA5MVNXdIvIQ0BF4TFXnFCiaImDPURhTMIeOZPHIuEW8OWMN57SpzTNXnUa1FBunrCSIlVH4qcx+2MskzgQuBF7H9SZrjClGNu86wFUvf8ubM9ZwW/eWvDqoU6iZxKSVk5i0clJo+086kya5VwD81FFken9/Cbygqh+IyCOBRGOMCcXM1T9xx6g57Dl4hOd+3ZFfnhLf7jgK4rEvHgNspDvfHnPpFcRId34yinUi8hLQE3hCRMrj707EGJPgVJX/fLWKxycsoUmNioy8sTNt61UJOyyTYPxkFAOAXsCTqrpDROpjz1EYk/T2HDzCfWPn89H8DVzYvi7/d/mpVK1g9RHmeH56j90HvCcidUSkiTd5SbBhGWOC9P2GXdwxag6rt+3lD73bccvZLWwMCROVnzGzLwKeAhoAm4EmuIyifbChGWPiTVV5d1YGD3+wkGopZXnr5i50tp5fTR78FD09CnQBJqnqaSJyLnBVsGEZY+Jtz8EjPPj+Aj5IX8+ZrWox7MpUalUuH3ZYUb3U96WwQ0guLwWXXn4yisOquk1ESolIKVWdIiJPBBaRMSbuFmTs5K635rDmp30MPb8Nt5/bitKlEruoqW2ttmGHkFzaBpdefjKKHSJSGfgCGCUim4EjgUVUCDbCnTHHyspSXv16FU9MXEKtyuV5e3BXzmheI+ywfBm3dBwA/dr2CzmSJDHOpRf94p9efp7Mrojr26kUcDVQDRilqtviHk2c2JPZxsDm3QcYOnoeXy7fyvkn1eUf/U/hhErlwg7Lt+4jugM2HoVv3bu7vwUcj6JAI9yJSGdgONASWADcqKqvFygCY0yRmrR4E/eNnc/eQ0f46yUd+PUZTaxVkymwWEVPzwH34oqcLgKexnXhYYxJUPsOHeHR8d/z1ndrOLF+VZ65MpXWde0BOlM4sTKKUqr6mff+XRG5vygCMsYUzJw12xk6eh6rt+3llnNa8Nvz21C+TOmwwzLFQKyMorqIXBrts6q+F1xYxhi/Dh3J4pnJy3l+6g/Ur5bCmzd1oWtLezbCxE+sjGIa0C/KZwUsozAmZN9v2MXQ0fNYvGEXl5/eiIf7nVRsuuEYecnIsENILiODS6+oGYWqXh/YXo0xhXI4M4sXp67gmc+XUy2lLC9fm8b5J9UNO6y4alytcdghJJfGwaWXjZBuTJJZsnEX9747j4XrdtHv1Ab8+aL21EiiZq9+vbPwHQCu6HBFyJEkiXdcenFF/NPLMgpjksShI1k8N+UHnp/6A1UrlOXFazrSq0P440YE5YVZbnw0yyh8esEbT84yCmNKpvS1O7hvzHyWbtrNJac15I99T0qqh+dMcvPTe2xZ4DbgbG/SNOBFVT0cZGDGGNh78AhPfbqM175ZRZ0q5fnPdWn0OLF41UWYxOfnjuIFoCzwvPd5oDftpqCCKijr68kUJ1OWbuah9xeybsd+runShN/3aldsWjSZ5OIno+ikqqdGfP5cROYFFVBhqOo4YFxaWtrNYcdiTEFt3n2Av4xbzPj5G2hZuxLv3tqVTs2SoyM/Uzz5ySgyRaSlqq4AEJEWQGawYRlT8mRmKW99t4YnJi7h4JEsfnt+G245p0WJfbp6zIAxYYeQXMYEl15+MorfAVNEZCUgQFPghsAiMqYEWrhuJw++v4B5GTvp1rImj/2qAy1qVw47rFDVqlgr7BCSS63g0stPRvEV0Bpoi8sobLxsY+Jk5/7D/PPTpYz89kdqVCrPv65M5aJTG1hPr8CI9BEADEodFGocSWPECPd30KC4b9pPRjFdVTsC87MniMgcoGPcozGmhMjKUsbOyeDvE5awfd8hBnZpytAL21pldQTLKPIpjIxCROoBDYEUETkNdzcBUBWoGPdIjCkhFmTs5E8fLmTOmh10bFKd/954Bu0bVAs7LGOiinVHcSEwCGgEPMXRjGIX8ECwYRlT/Gzbc5AnP13K2zPXUrNSOf5x2Slc1rERpRJ87GpjYnUK+Drwuoj0V9WxRRiTMcXKoSNZ/Hf6av41eTn7D2Vy4y+ac3fP1lbMZJJGnnUUlkkYUzCqypSlm3nso+9ZuWUvZ7epzR/7nkirOjbinEku1teTMQFYunE3j320mC+Xb6VFrUq8OiiNc9vWsdZM+fDx1R+HHUJy+Ti49LKMwpg42rz7AMMmLeft79ZQuXwZHu57EgO7NKVcmVJhh5Z0Kpa1NjP5UjG49IrV6unSaPPAhkI1JtL+Q5m88uVKXpy2goNHsri2azPu6dHaengthOdnuu7lbu90e8iRJInnve74bo9/esW6o8ge9rQO0A343Pt8LjAVGwrVGI5kZjFmdgZPT1rGpl0H6dW+Hvf1bkfzWpXCDi3pjV40GrCMwrfRLr2KNKPIHgpVRMYDJ6nqBu9zfeC5uEdiTBJRVSZ/v5knJi5h+eY9nNakOs/+uqN13meKJT91FM2yMwnPJqBNQPEYk/Bmrv6JJyYsYdaP22lRqxIvXtORC9vXs4pqU2z5ySimisgnwFuAAlcCUwKNypgE9P2GXTz5yVImL9lMnSrl+dslJ3N5WiPKlraKalO8+XmO4k4RuYSjI9wNV9X3gw3LmMSxautenv5sGR/OW0/VCmX4fa+2XN+tOSnlSmb336bkEVXNeyGRpkBrVZ0kIhWB0qq6O/Do8ilihLubly9fHnY4JsllbN/Hvyf/wJg5GZQrXYobzmzG4LNaUq2iPVFtih8Rma2qabnN8zNm9s3AYKAG0BLXUeCLQI94BhkPNsKdiYeNOw/w/NQfeOu7NQjCwC5Nuf3cltSpUiHs0IwJhZ86ijuAM4AZAKq6XETqBBqVMSHYvOsAz09dwZvfrSErS7k8rTF3ndeKBtVTwg6tRHrymycBuLfbvSFHkiSedOnFvfFPLz8ZxUFVPZTdokNEyuAqtY0pFjbvOsAL01bw5ow1HMlS+ndsyF3ntaZxDXsyOEzjl40HLKPwbbxLr7Ayimki8gBuXIrzgduBcXGPxJgitnHnAV6ctoK3vnMZxKWnNeTO81rRtKY9LGdMJD8ZxX3ATcAC4BbgY+CVIIMyJkgZ2/fxwtQVvDsrgyxVLu3YkDvOtQzCmGhiZhQiUgqYr6odgJeLJiRjgrFyyx5emLqC9+euQwQuO70xt3dvaUVMxuQhZkahqlkiMk9EmqjqmqIKyph4Wrx+F89P/YGPF2ygbOlSXN25Cbec09IqqRNcSln7fvIlJbj08lP0VB9YJCLfAXuzJ6rqRYFFZUwczFr9E89N+YEpS7dQqVxpBp/dkhvPbE7tKuXDDs34MOHqCWGHkFwmBJdefjKKPwe2d2PiLCtL+XzJZl6ctoJZP26nRqVy3HtBGwZ2aWYPyhlTQH668JhWFIEYUxiHjmTx4bz1DP9iBcs27aFh9RQe6XcSV3RqYl1tJKlHpz0KwMPnPBxyJEniUZdePBz/9Io1cNFXqnqmiOzm2OcmBFBVrRr3aIzJp10HDvP2d2t49avVbNx1gHb1qvD0FafS95QG1llfkpu8ajJgGYVvk116FWlGoapnen9tJHiTcNbt2M9rX63i7Zlr2XPwCN1a1uTv/U/mnDa1rbtvY+LMT19PTXKbbq2gTBjS1+7gP1+t4uMFboiUvqfU5+azWtChYbWQIzOm+PJTmf1RxPsKQHNgKdA+kIiMyeFIZhafLd7Eq1+vYubq7VQpX4YbftGMQb9oTkNr4mpM4PxUZp8c+VlEOuKe0DYmUDv3H2b0zLWM+GY163bsp3GNFP7Y9yQGdGpM5fJ+rnFMMqtZsWbYISSXmsGll6/xKI5bSWSOqnYMIJ64SEtL01mzZoUdhimgHzbvYcQ3qxg7ex37D2fSuXkNbjizOT1PrEvpUlb/YEwQCjsexW8jPpYCOgJb4hSbMQBkZilTl25mxDer+XL5VsqVLsVFqQ0Y1K2Z1T8YEzI/9++RrZ6O4OosxgYTjilpduw7xLuzMhj57Y+s+WkfdauWZ+j5bbiqcxNqVbYnqEuy+yfdD8DjPR8POZIkcb9LLx6Pf3r5qaOwJ7NN3C3I2Ml/p6/mw3nrOXgkizOa1eC+Xu24oH1de/7BADA9Y3rYISSX6cGll5+ipw9jzbc+n4xfBw5nMn7+BkZ++yPz1u4gpWxp+p/eiGu7NqVdPXt+05hE5afoaRVQD3jD+3wVsBr4JKCYTDGzcsseRs1Yw5jZGezcf5iWtSvxSL+TuKRjI6qlWP9LxiQ6PxnFaap6dsTncSLyhao+EFRQJvkdPJLJp4s28eaMNUxfuY0ypYQLO9Tj6s5N6Nqipj09bUwS8ZNR1BaRFqq6EkBEmgO1gw3LJKuVW/bw9sy1jJmdwU97D9HohBR+d2FbLk9rRJ0qFcIOzySRRlUbhR1CcmkUXHr5ySh+A0wVkZXe52bYA3cmwoHDmUxcuJG3vlvDjFU/UbqU0PPEOvy6c1POalWLUvbsgymANy59I++FzFFvBJdeflo9TRSR1kA7b9ISVT0YWEQmaSxev4t3Zq7h/bnr2HXgCI1reHcPpzeiTlW7ezCmuPDT6qki8FugqareLCKtRaStqo4PPjyTaHbuP8yH6et4Z9ZaFq7bRbnSpejVoR5XdmpMlxY17e7BxM2QiUMAGNZrWKhxJI0hQ9zfYcPivmk/RU+vAbOBrt7nDOBdoEgyChFpATwIVFPVy4pin+ZYWVnKNyu2MXrWWiYu2sihI1mcWL8qj/Q7iYtTG3JCpXJhh2iKofSN6WGHkFzS0wPbtJ+MoqWqXiEiVwGo6n7x2WRFRF4F+gKbVbVDxPRewL+A0sArqvr3aNvwKtFvFJExfvZp4ufHbXsZOzuDsXPWsW7HfqpWKMMVaY0ZkNaYDg2rWsslY0oIPxnFIRFJwRvlTkRaAn7rKEYAzwL/zZ4gIqWB54DzcXcnM72H+koDOZ89v0FVN/vcl4mDXQcO8/H8DYydk8HM1dsRgbNa1+a+3u244KS6VChrw4oaU9L4ySj+BEwEGovIKOAXwCA/G1fVL0SkWY7JZwA/RDS3fRu4WFUfx919mCJ2JDOLr37Yyntz1vHJoo0cPJJFi9qV+N2Fbbm0Y0PqV7MxH4wpyfy0evpMROYAXXDjZd8DVCrEPhsCayM+ZwCdoy0sIjWBvwKnicj9XoaS23KDgcEATZrkOiifiaCqLN6wi//NXcf/0tezZfdBqqWU5fK0RvTv2IjUxtWtaMmEqk3NNmGHkFzaBJdeMTMKEemK+2H/QlU/EpFTgGeAs4DGBdxnbr8+UQfFUNVtwK15bVRVhwPDwY1HUcDYir11O/bzYfp63p+bwbJNeyhbWji3bR0u7diIc9vVpnwZK1oyiWF4v+Fhh5BchgeXXlEzChH5P1xRUDpwn4iMB24H/gbcUIh9ZnBsJtMIWF+I7Zk87Nx3mI8XbuB/c9cxY9VPAJze9AQe+1UH+p5Sn+oVrdWSMSa6WHcUv8T183RARE7A/ZifoqrLC7nPmUBrryuQdcCVwK8LuU2Tw/5DmUxesokP0tczdelmDmcqLWpXYuj5bbg4tSFNalYMO0RjYho8bjBgdxa+DXbpFcSdRayMYr+qHgBQ1e0isjS/mYSIvAV0B2qJSAbwJ1X9j4jciet9tjTwqqouKlj4JtLhzCy+Wr6VD+et59NFG9l7KJM6VcpzXddmXJTagJMbVrN6B5M0lm1bFnYIyWVZcOkVK6NomWMsimaRn/2MQ6GqV0WZ/jHwse8ofRKRfkC/Vq1axXvTCSszS5mxchvj5q9nwsKN7Nh3mGopZel3agMuOrUBnVvUtHGmjTGFEiujuDjH56eCDCQeVHUcMC4tLe3msGMJUlaWMnvNdsbPW8/HCzeyZfdBKpYrzfkn1aXvKQ04u00tq5Q2xsRN1IxCVacVZSAmtqwsZe7aHXw0fwMfL9jAxl0HKF+mFOe2rUPfU+tzXrs6VCzn57EYY4zJH/tlSWAuc9jOR/M3MmHhBjbsPEC50qU4p21t/nByO3qeVJfK5e0rNMVTar3UsENILqmpgW1aVIvfIwdpaWk6a9assMMokMwsZfaP2/l4wQYmLtzIxl0uczi7TS36nFyfnifVpWoFGz7UGBNfIjJbVdNym1esLkeTtTL7SGYWM1b9xISFG/hk0Sa27D5IuTKlOKdNbe47uS09TrTMwRgTHj/jUbQBfgc0jVxeVc8LMK4CSabK7INHMvn6h61MXLiRzxZvYvu+w6SULc257WrTq4Orc7BiJVOSXfPeNYCNdOfbNS69ghjpzs8v0bvAi8DLQGbcIyhB9hw8wtSlm5m4cCNTl25hz8EjVClfhh4n1qFXh3qc06YOKeWstZIxABm7MsIOIblkBJdefjKKI6r6QmARFHNb9xxk0uJNfLJoI1//sI1DmVnUrFSOvqfU58L29ejWqqY1ZTXGJDQ/GcU4EbkdeJ+IcShU9afAokpyq7bu5dNFrkhp9prtqEKjE1IY2LUpF5xUl7RmNewhOGNM0vCTUVzn/f1dxDQFWsQ/nOSUmaWkr93BZ4s38dnijazYsheA9g2qMqRHG84/qS4n1q9i3WcYY5KSn/EomhdFIPFQlK2e9h06wpfLtzL5+018vmQzW/ccokwpoXOLGgzs0pQeJ9alcQ3reM+YguraqGvYISSXrsGlV57PUYhIWeA24Gxv0lTgJVU9HFhUhRTUcxTrd+zn8yWbmfz9Jr5esY1DR7KoUr4M3dvVoeeJdejepg7VKlozVmNM8inscxQvAGWB573PA71pN8UnvMSVmaXMy9jBlCWbmfz9ZhZv2AVAkxoVubpzE3qeWJdOzWpQrkypkCM1xpjg+MkoOqnqqRGfPxeReUEFFLad+w/z5fItfL5kM9OWbmHb3kOULiWc3uQE7u/djh4n1qFl7cpW32BMwPqP7g/A2AFjQ44kSfR36cXY+KeXn4wiU0RaquoKABFpQTF8nkJVuX7ETKYu2QRSilJH9pOyYxW1tq/gqu6pDL21D/v27aNPnz7HrTto0CAGDRrE1q1bueyyy46bf9ttt3HFFVewdu1aBg4ceNz8oUOH0q9fP5YuXcott9xy3PyHHnqInj17kp6ezpAhQ46b/7e//Y1u3brxzTff8MADDxw3f9iwYaSmpjJp0iQee+yx4+a/9NJLtG3blnHjxvHUU8d3Ejxy5EgaN27MO++8wwsvHN9SesyYMdSqVYsRI0YwYsSI4+Z//PHHVKxYkeeff57Ro0cfN3/q1KkAPPnkk4wfP/6YeSkpKUyYMAGARx99lMmTJx8zv2bNmoz1/jHuv/9+pk+ffsz8Ro0a8Yb3ANKQIUNIT08/Zn6bNm0Y7g30MnjwYJbl6NM/NTWVYcOGAXDNNdeQkaOteteuXXn8cTeMe//+/dm2bdsx83v06MHDDz8MQO/evdm/f/8x8/v27cu9994LQPfu3clpwIAB3H777SXy3EvfmE67m9sB2Lnn59ybPJmpAfX35Cej+B0wRURW4sa7bgpcH0g0IRIRmteqxNz135GyYyXld69HvKG8U0qfEnJ0xhgTHl+dAopIeaAtLqNYoqoH81glVMncKaAxxuk+ojsAUwdNDTWOpJF9R+rdJeVXgSqzReQ8Vf1cRC7NMauliKCq7xUomgAla6eAxhiTyGIVPZ0DfA70y2WeAgmXUSRTp4DGmNh6NO8RdgjJpUdw6eXnOYrmqroqr2mJxIqejDEmf2IVPfl5ACC3tlZjCheSMcaYZBGrjqId0B6olqOeoipQIejAjDElW+9RvQGYcPWEkCNJEr1dejEh/ukVq46iLdAXqM6x9RS7AasDMMYEav/h/XkvZI7aH1x6Rc0oVPUD4AMR6aqq06MtZ4wxpnjzU0dxq4hUz/4gIieIyKvBhWSMMSaR+Gn1NFdVT8trWiIRkS3AjwVcvRawNY7hxIvFlT8WV/5YXPlTHONqqqq1c5vhpwuPUiJygqpuBxCRGj7XC020g/VDRGZFayIWJosrfyyu/LG48qekxeXnB/8p4BsRyW4Seznw13gHYowxJjH5GeHuvyIyCzgP19fTpaq6OPDIjDHGJIRYz1FUVdVdXlHTRuDNiHk1VPWnoggwBMPDDiAKiyt/LK78sbjyp0TFFbUyW0TGq2pfEVkFRC4kgKpqiyACMsYYk1h8dTNujDGm5MrzOQoR+UBErhKRikURUDyJSC8RWSoiP4jIH3KZLyLyjDd/voh0zGtdEakhIp+JyHLv7wlFFZeINBaRKSLyvYgsEpF7ItZ5RETWiUi69zp+OLSA4vLmrRaRBd6+Z0VMDzO92kakR7qI7BKRId68okivdiIyXUQOisi9ftYtovTKNa4EOL9ipVeY51e09Ar0/PIZ29XeOT9fRL4RkVPzWrdAaaaqMV+47safxz2X8C5wGVAhr/XCfgGlgRVAC6AcMA84KccyfYAJuOK0LsCMvNYF/gH8wXv/B+CJIoyrPtDRe18FWBYR1yPAvWGklzdvNVArl+2Gll65bGcjrq14UaVXHaATrpXgvX7WLaL0ihZX2OdXrnElwPkVNa6gzq98xNYNOMF735uAfsPyvKNQ1Wmqeru3w+HAAGBzXuslgDOAH1R1paoeAt4GLs6xzMXAf9X5FqguIvXzWPdi4HXv/evAr4oqLlXdoKpzAFR1N/A90DCf+497XHlsN7T0yrFMD2CFqhb0Qcx8x6Wqm1V1JnA4H+sGnl7R4gr7/IqRXrGEll45xPv88hvbN+o94wZ8CzTysW6+08xPFx6ISArQH7gVl7O+HnuNhNAQWBvxOYPjT/poy8Rat66qbgD3j4W72iiquH4mIs2A04AZEZPv9G5BXy3ALXhh41LgUxGZLSKDI5ZJiPQCrgTeyjEt6PQqyLpFkV55Cun8iiXM88uPeJ9fBYntRtyddV7r5jvN/NRRvIO7sjgPeA5oqap35bVeApBcpuWsuY+2jJ91C6owcbmZIpVx44QMUdVd3uQXgJZAKrAB96BkUcb1C1XtiLv9vUNEzs7n/oOKCxEpB1yEKzrNVhTpFcS6gW87xPMrljDPr9gbCOb8yldsInIuLqO4L7/r+uHnjuI1XOZwq6p+rqpZBd1ZEcsAGkd8bgSs97lMrHU3ZRdreH/zWwxXmLgQkbK4f+JRGjFuuapuUtVM7/t5GXfrWWRxqWr2383A+xH7DzW9PL2BOaq6KXtCEaVXQdYtivSKKuTzK6qQz6+8BHF++Y5NRE4BXgEuVtVtPtbNd5r5qaOYCHQWkV+LyLXZr7zWSwAzgdYi0tzL8a8EPsyxzIfAteJ0AXZ6t2Kx1v0QuM57fx3wQVHFJSIC/Af4XlX/GblCjjL5S4CFRRhXJRGp4sVRCbggYv+hpVfE/KvIUSxQROlVkHWLIr1ylQDnV7S4wj6/8hLE+eUrNhFpArwHDFTVZT7XzX+a5VXbDYwEvsG1fPq393omr/US4YVrDbMMV/v/oDftVuBW773gitNWAAuAtFjretNrApOB5d7fGkUVF3Am7vZxPpDuvfpEfE8LvHkfAvWLMK4WuFYV84BFiZJe3ryKwDagWi7nddDpVQ93ZbcL2OG9r5oA51eucSXA+RUtrrDPr1jfY2Dnl8/YXgG2R3xfs2KtW9A089PN+Pe4ZlXxKkM1xhiTRPzUUSzE5ajGGGNKID/djNcCFovId8DB7ImqelFgURljjEkYfjKKR4IOwhhjTOLy1SmgiNTFPWgH8J26JmrGGGNKAD8P3A0AvsONbDcAmCEilwUdmDHGmMTgpzL7QaCTql6nqtfiHhx5ONiwTDYRyRTX++RCERknItXDjikeEu24RKS7iHQrwHqrRaRWEDHll4jsCXn/b3ldVvwmYtqDcrQH1cyI93fnsn6q+Ohl1fuuxkeZvjNiH5MKf1QgIlNFJOHGxy5KfjKKUjmKmrb5XM/Ex35VTVXVDsBPwB1FHYCIlA5gs6EfVw7dcT1xlkgi4qe+Mtb69YBuqnqKqj6dPV1V/+p9z6kc/c5TVfWZXDaTimv7XxhfRuyjZyG3ZTx+fvAnisgnIjJIRAYBH3G04ylTtKbjdewlIi1FZKK4TtK+FJF23vTLvav0eSLyhTetgoi8Jq4//7ni+oXB+06fzd64iIwXke7e+z0i8hcRmQF0FfdE/nxvuyO9ZWqLyFgRmem9fuFNPyfiqm5u9lO1hTyu5uLGBJgpIo9mXz3nvLoUkWe98xQROV1Epnnb+kSOdltwt4gs9o7nbXEd4N0K/MaL+awYx1ZTRD71juslcu9TBxF5QURmiRvX4c8R0/8ese8nc1nvDHHjCsz1/rbNZZn6IvJFxB3ZWRHz/up9R9+Kq1tERPqJyAxvm5Mipj8iIsNF5FPgv9GOOce+cz2XgE+BOtnpF+V7jroNcU8P/wW4wtvGFX7SIi8i0kxEFkZ8vldEHvHeTxWRJ0TkOxFZlh23iKR458V8cX3dpXjTS4vICC/NF0jEnVOx5/PpwEuBfwJPA5cU5AlDexXsBezx/pbGdTrWy/s8GWjtve8MfO69XwA09N5X9/4OBV7z3rcD1gAVgEHAsxH7Gg90994rMMB73x5YijceAN6TnLhx1M/03jfBdf0AMA7XiRtAZaBMHI7rQ+Ba7/0dEet3B8ZHbPdZ77jK4noUqO1NvwJ41Xu/HiifI40e4dixGaId2zPAH733v/TSKbdxEmpEHN9U4BSghpeOErnvHOtVzU4voCcwNpdlhnL0Kd3SQJWI76yf9/4fwEPe+xMi9nkT8FTEMc8GUmIdcy77zu1cagYs9Hku+z0fc02LnN95xPLdgZ0cfUr5wZxxAfcCj3jvp0akRR9gkvf+txHnyinAESANOB34LGJbx31/xfUV9XZTRFrhuqP9Wl3nYO95088WkZaquiLauiauUkQkHXfCzwY+E9e7ZzfgXZGfL2jLe3+/BkaIyGi87wzXNcO/AVR1iYj8CLTJY7+ZuM7hwPUcPEZVt3rb+Mmb3hM4KSKGqt7dw9fAP0VkFPCeqmbE4bh+gevqHlz3CE/kEX9boIO3XXA/qNn9P80HRonI/4D/RVk/2rGdjbtwQlU/EpHtUdYfIK477DK4AYFOAhYDB4BXROQjXMacUzXgdRFpjfvhL5vLMjOBV8V14Pc/VU33ph+K2OZs4HzvfSPgHe+OqhywKmJbH6rq/ljHrG5simzRzqVd+Of3fPSTFjl9qap9sz94d4uxZP+PzMadi+C+42e8+OaLyHxv+kqghYj8G1ey8qmPeIqFWEVPw4DduUzf580zRWO/uvLdprh/8jtw39sOPVoWm6qqJwKo6q3AQ7ieI9NFpCZRikdwV0qR50CFiPcHVDXTey/k3kVxKaBrRAwNVXW3qv4dd+WaAnwrXvFRYY7Lk1sM0Y5BgEUR2zlZVS/w5v0S1zfU6cBsyb18PtdjixHHz0SkOe7KtYeqnoL7UamgqkdwjUHG4gaLmZjL6o8CU9TV3fTj2O/E7Vz1C9yP2TpgpBztpPOwepe6uIw++7j+jbtSPxm4Jcc29/o85p8PL9ax++R3G3mmhQ+xznE4+hBxZHpBLt+xugGCTsXdidyB62epRIiVUTRT1fk5J6rqLI7mvKaIqOpO4G7cD9B+YJWIXA6u10/xxsr17vZmqOofga24DOML4GpvfhtcscJS3PCSqSJSSkQaE70r5Mm4K+Sa3jZqeNM/Be7MXkhEUiNiWKCqTwCzcMULhTou3F3Kld77qyM28SPuKri8iFTDjTSGd3y1RaSrt62yItJeREoBjVV1CvB7oDqueGw3bvjPbLkeG8emZW9csU5OVXE/wDu9+oDe3vKVcZ3HfQwMwVXe5lQNlwGAK4o5jog0BTar6su43l475rZclG1eF2O5aMccKdq5lB/RtpHzO8gzLXzYhKs7qSki5YG+ea2QI74OuOInxLVuK6WqY3EtP/NK92IjVkYRK/dOiXcgJm+qOhfXg+aVuBP5RhHJ7lHzYm+x//Mq2hbiTvh5uJ5/S4vIAuAdYJCqHsT9+K7C1Ws8CcyJst9FuPGCp3n7y+6C+m4gzav0W4yrEAYY4lX4zcP9+Mds/ODzuO7BDVgzE/cDkr3uWmA0XnESMNebfgg3vvsT3rbSccVapYE3vLSYCzytqjtw9SqXRFTGRju2PwNni8gcXHfXa3I5nnnethcBr+LSGdyP4HivKGMakFtl6D+Ax0Xkay/W3HTH3S3OxRXH/SvKctkewRXnfYm7eIgm2jFHinYu5Ue0bUzBZfrpInIF/tIiJlU9jKskn4ErllviY7UXgMre9/R73HNk4BpcTPWKTEcA9xckpmQU9clsEXkLV5H4co7pNwIXqOoVRRCfMbkSkT2qWjnsOIwpCWJlFHVxI0kdwlX0gKv5L4dr+bSxSCI0JheWURhTdPyMR3EurvUIuMrBzwOPyhhjTMLw1SmgMcaYksu64jDGGBOTZRTGGGNisozCGGNMTJZRGGOMickyCmOMMTH9P2sKXFcN8J4+AAAAAElFTkSuQmCC\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "plt.plot(requests_as_share_of_funds, conviction_required_as_share_of_max)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request/funds, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request/funds, 0, ax[3], 'g', '--')\n", "plt.hlines(1, 0, max_request/funds, 'g', '--')\n", "plt.hlines(min_required_conviction/max_achievable_conviction, 0, max_request/funds, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Relative Terms; Log Scale\")\n", "plt.xlabel(\"Resources Requested as a share of Total Funds\")\n", "plt.ylabel(\"Conviction Required to Pass as share of max achievable\")\n", "plt.gca().set_yscale('log')" ] }, { "cell_type": "code", "execution_count": 455, "metadata": {}, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "(0.031249999999999997, 2)" }, "metadata": {}, "execution_count": 455 }, { "output_type": "display_data", "data": { "text/plain": "
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}, "metadata": { "needs_background": "light" } } ], "source": [ "plt.figure(figsize=(10, 7))\n", "plt.plot(requests_as_share_of_funds, conviction_required_as_share_of_max)\n", "ax= plt.gca().axis()\n", "plt.vlines(max_request/funds, 0, ax[3], 'r', '--')\n", "plt.vlines(max_achievable_request/funds, 0, ax[3], 'g', '--')\n", "plt.hlines(1, 0, max_request/funds, 'g', '--')\n", "plt.hlines(min_required_conviction/max_achievable_conviction, 0, max_request/funds, 'k', '--')\n", "plt.title(\"Sample Trigger Function in Relative Terms; Log Scale\")\n", "plt.xlabel(\"Resources Requested as a share of Total Funds\")\n", "plt.ylabel(\"Conviction Required to Pass as share of max achievable\")\n", "plt.gca().set_yscale('log')\n", "plt.gca().set_ylim(min_required_conviction/max_achievable_conviction/2,2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plot series 3: Heat Maps\n", "\n", "The next set of plots show the simultaneous variation of multiple parameters with a focus on alpha and supply.\n", "\n", "Note: that i am using params stored in the supporting files, this won't have changed even if you have edited the plots above" ] }, { "cell_type": "code", "execution_count": 456, "metadata": { "tags": [] }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": "{'beta': [0.2],\n 'rho': [0.0025],\n 'alpha': [0.7937005259840998],\n 'gamma': [0.001],\n 'sensitivity': [0.75],\n 'tmin': [1],\n 'min_supp': [1],\n 'base_completion_rate': [45],\n 'base_failure_rate': [180],\n 'base_engagement_rate': [0.3],\n 'lowest_affinity_to_support': [0.3]}" }, "metadata": {}, "execution_count": 456 } ], "source": [ "params" ] }, { "cell_type": "code", "execution_count": 457, "metadata": {}, "outputs": [], "source": [ "supply_sweep = trigger_sweep('effective_supply',trigger, params, supply)" ] }, { "cell_type": "code", "execution_count": 458, "metadata": {}, "outputs": [], "source": [ "alpha_sweep = trigger_sweep('alpha',trigger, params, supply)" ] }, { "cell_type": "code", "execution_count": 459, "metadata": {}, "outputs": [ { "output_type": "display_data", "data": { "text/plain": "
", "image/svg+xml": "\r\n\r\n\r\n\r\n \r\n \r\n \r\n \r\n 2020-08-20T19:03:59.091972\r\n image/svg+xml\r\n \r\n \r\n Matplotlib v3.3.0, https://matplotlib.org/\r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n 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+OcnJy9peujD9hCRP2NV1AQAAsGdzGQsAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcAAAAwFGEHAAAAMBRhBwAAADAUYQcbpqqOqqpzq+q8qnrGCvOrql40z/9IVd1zI+oEAABgzyLsYENU1V5J/izJQ5McmuTRVXXossUemuSQ+XFckpfs0iIBAADYIwk72ChHJDmvuz/V3d9K8tokRy9b5ugkr+zJ+5PcrKpuu6sLBQAAYM+y90YXwKZ1YJLzF55fkOTea1jmwCQXLS5UVcdlGvmRJFckv/HR9S2VTe6WSb680UUwFMcU623POKa+sZut65J1WMe49oxjiuvkW9ex/Wvrt2nHE+vtLmtZSNjBRqkV2no7lkl3H5/k+CSpqjO6+/AdLw8mjinWm2OK9eaYYr05plhPjifWW1WdsZblXMbCRrkgycELzw9KcuF2LAMAAABbEHawUU5PckhV3aGq9klyTJKTli1zUpLHzr/Kcp8kX+3ui5avCAAAABa5jIUN0d1XVtVTk7w9yV5JTujus6vqSfP8lyY5OcnDkpyX5OtJfnYNqz5+J5XM5uWYYr05plhvjinWm2OK9eR4Yr2t6Ziq7mvdAgEAAABgj+UyFgAAAGAowg4AAABgKMIOdmtVdVRVnVtV51XVM1aYX1X1onn+R6rqntvqW1U3r6pTquoT898DdtX+sLG293iqqoOr6t1VdU5VnV1Vv7TQ59lV9fmqOnN+PGxX7hMbawfPUZ+pqrPm4+aMhXbnqE1sB85Td1k4D51ZVZdW1dPmec5Tm9gajqnvqapTq+qKqvqVtfR1ntrctveY8n6KlezgOWrV91LCDnZbVbVXkj9L8tAkhyZ5dFUdumyxhyY5ZH4cl+Qla+j7jCTv7O5Dkrxzfs7gduR4SnJlkl/u7u9Ncp8kT1nW94Xdfdj8OHln7ge7jx08ppY8aD5uDl9oc47apHbkmOruc5fOQ0nulenG3m9Z6Oc8tQmt8Zi6OMkvJvn969DXeWqT2pFjKt5PscwOHk9LtvpeStjB7uyIJOd196e6+1tJXpvk6GXLHJ3klT15f5KbVdVtt9H36CQnztMnJnn4Tt4Pdg/bfTx190Xd/aEk6e7LkpyT5MBdWTy7pR05R63GOWrzWq9j6sgkn+zuz+78ktnNbfOY6u4vdffpSf7zOvR1ntq8tvuY8n6KFezIOWo1Ryc5UdjB7uzAJOcvPL8g1z4hbm2Z1freprsvSqaTbpJbr2PN7L525Hi6WlXdPsn3Jzltofmp83DyEwzl3VR29JjqJO+oqg9W1XELyzhHbV7rcp5KckyS1yxrc57anNZyvGxPX+epzWtHjqmreT/FbEePp1XfSwk72J3VCm3Lfyt5a8uspS+by44cT9PMqhsleVOSp3X3pXPzS5LcKclhSS5K8gc7XCl7ih09pn6ou++ZaejmU6rq/utZHHuk9ThP7ZPkx5K8YWG+89TmtSPvh7yXYiU7fFx4P8WCHT2eVn0vJexgd3ZBkoMXnh+U5MI1LrNa3y8uDfmd/35pHWtm97Ujx1Oq6vqZ/sf86u5+89IC3f3F7r6qu7+d5GWZhuOxOezQMdXdS3+/lOneCkvHjnPU5rVDx9TsoUk+1N1fXGpwntrU1nJMbU9f56nNa0eOKe+nWG6HjqdtvZcSdrA7Oz3JIVV1h/mbqmOSnLRsmZOSPHa+O/19knx1Hk65Wt+Tkhw7Tx+b5K07e0fYLWz38VRVleTlSc7p7j9c7LDsWvlHJPnoztsFdjM7ckztX1U3TpKq2j/Jg3PNseMctXntyP/3ljw6yy5hcZ7a1NZyTG1PX+epzWu7jynvp1jBjhxP23wvVd1Go7H7mn926o+S7JXkhO5+XlU9KUm6+6XzSfNPkxyV6c7zP9vdZ2yt79x+iySvT3K7JJ9L8qjuvnhX7hcbY3uPp6q6b5J/THJWkm/Pq/u17j65ql6VachlJ/lMkicu++DBwHbgmLpjrvmljL2T/JVzFMkO/3/vhpmufb5jd391YZ3OU5vYGo6p70hyRpKbZPp/3NeSHNrdl3ovxUq295hKcvd4P8UyO3A83TLbeC8l7AAAAACG4jIWAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AYI9WVb9eVWdX1Ueq6syquvfc/pmquuUG1vWCua4XLGt/XFX9+1zrmVX1ynXa3pr3t6peUVWfnrf/4ao6cj1q2F5VdbOq+vnt6PfsqvqVnVETAHu2vTe6AACA7VVVP5jkR5Lcs7uvmD/s77MO6927u6/cwdU8McmtuvuKFea9rrufuoPr31FP7+43VtWDkhyf5JANrOVmSX4+yYs3sAYABmJkBwCwJ7ttki8vBQrd/eXuvnBh/i9U1Yeq6qyq+p4kqaojqupfqupf5793mdsfV1VvqKq/SfKOqtq/qk6oqtPnZY9evvGavKCqPjpv4yfn9pOS7J/ktKW21VTVA6vqbxee/2lVPW6e/kxV/dYK+3GLqnrHXNufJ6m5ff+q+rt5xMZH17D9U5McOPfda96f0+eRMk9c2M8/raqPzes+uaoeuVDfLefpw6vqPQt1XOv1q6q7VtUH5lElH6mqQ5L8bpI7zW0vmJd7+kIdv7Xw2vx6VZ1bVf+Q5C7bem0B2JyM7AAA9mTvSPKbVfXxJP+QacTEexfmf7m77zlfIvErSZ6Q5N+S3L+7r6yq/5bkt5P8xLz8Dya5e3dfXFW/neRd3f1zVXWzJB+oqn/o7ssX1v/jSQ5Lco8kt0xyelW9r7t/rKq+1t2HbaXun6yq+87Tf5zk09vYz5X241lJ/qm7n1NVP5zkuHnZo5Jc2N0/nCRVddNtrPuoJH89Tz8+yVe7+weqat8k/1xV70jy/ZmChe9LcpskH0tywjbW++tZ4fVL8qQkf9zdr66qfZLsleQZSe629HpV1YMzjTQ5IlOIc1JV3T/J5UmOmevZO8mHknxwG3UAsAkJOwCAPVZ3f62q7pXkfkkelOR1VfWM7n7FvMib578fzBRMJMlNk5w4jyjoJNdfWOUp3X3xPP3gJD+2cE+IGyS5XZJzFpa/b5LXdPdVSb5YVe9N8gNJTtpG6VtcxlJVD9zG8ivtx/2Xprv776rqkrn9rCS/X1XPT/K33f2PW1nnC6rq95LcOsl95rYHJ7n70qiNTK/VIfO2lvbzwqp61zbqXVrXSq/fqUl+vaoOSvLm7v5EVa3U98FJ/nV+fqO5jhsneUt3fz25egQNAFyLsAMA2KPNH8Dfk+Q9VXVWkmOTvGKevXS/jKtyzfue5yZ5d3c/oqpuP/ddsjhqo5L8RHefu8rmr/UpfTtdmS0vL77Bsvkr7UcyhTVb6O6PzwHQw5L8TlW9o7ufs8I2n54pRPnFJCcmuVem/fmF7n774oJV9bCVtrVC7Yt1b+31O6eqTkvyw0neXlVPSPKpZctUkt/p7j9fVsfTVqkDAK7mnh0AwB6rqu4yj9BYcliSz26j202TfH6eftwqy7090z0/lu6F8f0rLPO+TJek7FVVt8o0AuIDayh9uc8mObSq9p0vO1nLr6O8L8lj5toemuSAefo7k3y9u/8yye8nuefWVtDd3850Gc31quohmfb5yVV1/Xld311V+8/bOmbez9tmGkWz5DOZgpLkmsuBkq28flV1xySf6u4XZRoBc/ckl2UatbHY9+eq6kZznwOr6tZzHY+oqv2q6sZJfnQNrxMAm5CRHQDAnuxGSf5kvifElUnOyzX3rtia38t0Gcv/SrLa5RjPTfJHST4yf2D/TKZffln0lkz3+fhwphEHv9rdX7huu5B09/lV9fokH0nyiVxz+cZqfivJa6rqQ0nem+Rzc/v3ZbpE5dtJ/jPJk7ex7a6q/5vkV5P89yS3T/KheZ//PcnDM+3nf810iczH5+0t1vHyqvq1JKcttG/t9fvJJD9dVf+Z5AtJnjPfI+Wfq+qjSd7W3U+vqu9NcuqclXwtyU9394eq6nVJzswUEG3tEh0ANrnqNhIQAIC1q6pXZLofyBs3uhYAWInLWAAAAIChGNkBAAAADMXIDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgD2eFV1v6o6d6Pr2F1U1duq6tiNrmN0VfWeqnrCRtexu6iqx1XVP633sgCwPYQdAOyWquprC49vV9U3Fp4/ZnHZ7v7H7r7LRtW6aP4Qd9Wy+v90J27v2VX1l4tt3f3Q7j5xJ2zrFVXVVfVjy9r/aG5/3Hpvc411Pb6q/q2qLquqL1bV31XVjTeiFnYvVXXkfGx8vareXVXftcqyX1v2uKqq/mRh/hOq6rx53t9X1XcuzHtaVX2qqi6tqgur6oVVtfc873YrrLur6pcX+v9UVX22qi6vqr+uqpsvzNu3qk6Y1/2Fqvpfy+ruud/Suv9iYd6xVfXBue8FVfV7S3XN899TVd9c6HvusnWvts/7VtVL5//mLq6qv6mqA1d4XR8w1/h/l7Wvts8HVtVb5/VeUFVPWtb3R6vqo3Nd/1JVhy7Mq6r6v1X1+ar66ryPd13p3xwYm7ADgN1Sd99o6ZHkc0l+dKHt1UvLLb5x39VW2fapi/V391N3aWE718eTXD1qZH4NHpXkkxtRTFU9IMlvJ3l0d984yfcmef1G1MLupapumeTNSf5PkpsnOSPJ67a2/LJzzm2SfCPJG+Z1LR1nR8/r+nSS1yx0/5sk9+zumyS5W5J7JPnFeb2fW7bu70vy7SRvmtd91yR/nuRn5u1+PcmLF9b97CSHJPmuJA9K8qtVddSy8u+xsI3F0UY3TPK0JLdMcu8kRyb5lWV9n7rQ9+rQeA37/EtJfjDJ3ZN8Z5L/SPInC/NTVddP8sdJTlvWvq19/st5e7dJ8sNJfruqHjT3PSTJq5M8KcnNMr32Jy2cjx+V5OeS3G+u+9Qkrwqw6Qg7ANijVNUD52/6/ndVfSHJ/1tqW1jmnlX1r/M3/W+oqtctfqtYVb9aVRfN38A+Yf7W8c7zvH2r6ver6nPzN5Yvrar9trbt61D3tYbtL9vuK6rqz2oalXBZVZ1WVXdaWPauVXXK/E3nF6vq1+YPPL+W5Cfnbzg/PC979eUVVXW9qvqN+RvUL1XVK6vqpvO82881HDvv75er6te3sSt/k+SHquqA+flRST6S5AsLtd6pqt5VVV+Z1/nqqrrZwvzPVNUzq+pjVXVJVf2/qrrBWl/LZX4gU7j0r0nS3Rd394ndfdny12J+vsW/w7z/v1jTt/JfrqoXVNX1Fpb956r6k/kb4n+rqiOXFzAfMxdX1fcttN26ptFIt1ph+TtX1XvndX65ql43t/9WzSMJqur6NX3j/Xvz8/1q+gb+gPn5fWr6Rvs/qurDVfXAhfXftKpePh/jn6/pW+691rJPVfWMqvrbrb3Y8/xPzsfox6rqEassu9XXdmGZ35+PgU9X1UMX2n+2qs6Zt/Opqnri1razih9PcnZ3v6G7v5kpNLhHVX3PGvo+MsmXkvzj/PxHk7yhu8/u7m8leW6S+y/9N9rdn+zu/1gqP1OYceetrPuxSd7X3Z+Znz8myd909/u6+2uZwpkfr2tGJz02yXO7+5LuPifJy5I8bg37kO5+yTzy7Vvd/flMIcEPraXvtvY5yR2SvL27vzi/vq9NsnwExS8neUeSf1vWvtV9rqobJXlgkud1939294eTvDFTgJEkD0nyj939T919ZZLnJzkwyQMW6vqn7v5Ud1+VKTi5euQHsHkIOwDYE31Hpm/svivJcYszqmqfJG9J8op5mdckecTC/KOS/K8k/y3Th5EHZEvPT/LdSQ6b5x+Y5DfXsu118Ogkv5XkgCTnJXneXPONk/xDkr/P9A3qnZO8s7v/PtM3r6+bv5W9xwrrfNz8eFCSOya5UZLll9XcN8ldMn3r+5tV9b2r1PjNJCclOWZ+/tgkr1y2TCX5nbnW701ycKYPmosek+lDy50yvd6/sco2V3NakofMQcEPVdW+27GORyQ5PMk9M32L/XML8+6d5FOZvhl/VpI318Jw+yTp7isyfdD76YXmRyf5h+7+9xW299xMHwAPSHJQrvk2/L2ZPuQlU4jzhVxzfP5gknO7+5KaLhX4uyT/N9Ox+CtJ3rQQrJyY5MpMx8n3J3lwksVv+7e6T939u939Iyu9SLNPZvrG/KaZjtW/rKrbrrL8tl7bc+c6fi/Jy6uq5nlfSvIjSW6S5GeTvLCq7plcfVnIf6zy+Kl5HXdN8uGljXX35XP9a7mk4dgkr+zunp/X/MjC82QaxZG5rp+qqkuTfDnTyI4/38q6H5vp32jJ8jo/meRbSb57Dre+c3H+PL18H95X0yUub66q26+yX/dPcvaytt+Zw6h/XgzNsu19fnmm4PM7q+qGmf6bftvVC0+XDP1ckuesUMdW93lhO8u3fbeF6eXzFue/Nsmdq+q7axpZcmymcyewyQg7ANgTfTvJs7r7iu7+xrJ590myd5IXzd8KvjnJBxbm/39J/t/8beXXM31gSzJd653kfyT5n/MIgcsyhQnHLPRfbdtX17Dsw9d91rhfb+7uD8zfVr46U+CSTB/6vtDdf9Dd3+zuy7r7tK2uZUuPSfKH87ecX0vyzCTH1JaX4PxWd39j/gb1w5k+qK3mlUkeW9MIkQck+evFmd19XnefMr9G/57kD3PtUOlPu/v87r44U6jz6DXuzxa6+x8zfYN/z0wBwFeq6g+XRjKs0fPnf+/PJfmjZbV8KckfzcfS6zJ9OP/hFdZxYpKfWhi58DPZ+tD5/8wUln3n/O+5NNLk1CSHVNUtMn0ofXmSA+dvuh+QKQxJplDl5O4+ubu/3d2nZLpE42FVdZskD03ytO6+vLu/lOSF2fIYXus+Xcs8SuLCebuvS/KJJEes0mW11/az3f2y+dv3E5PcNtNlC+nuv5tHS3R3vzdTOHS/ed7nuvtmqzz+al7/jZJ8dVk9X02y6v1cqup2mV7vxUDi5CT/X1XdvaaRXr+ZpDNdJrL02vzVfBnLdyd5aZIvrrDu+837+MaF5tXqvNHC863twwOS3D7J9yS5MMnf1gqX2FXVz2YKnn5/ofl/ZwpBD0xyfJK/WRi5sa19/nimSww/n+TSTMHmYrDxoiT/Zz7vLLfVfZ7Pu/+c5P9U1Q3mkOsnFrZ7SpIH1DTSbp9Mo9v2WZh/UaYROedmuhTpUUn+5wo1AIMTdgCwJ/r3edj0Sr4zyecXvpFNkvOXzT9/K/NulekN8weXgopM3wguXoqw2raXvH/Zh6/3b2P5JV9YmP56rvmgc3C2/54Y35nkswvPP5spDLrNGra7ovnD+a0yjcb42+WhT02XcLx2voTi0kzDyG+5bDWLr/tn5zqvparOrmtunni/rdTztu7+0UyjHI7ONJLluvxKymq1LD+WVqx1Dp8uz/Qh7Hsyjao4aSvb+9VM30R/YN6/n5vX8Y1MocUDMoUd703yL5kuO1gMO74ryaMWA7VMo3NuO8+7fpKLFub9eZJbX9d9WklVPbaqzlxY991y7X/bRau9tlcfd3PwmMzHXlU9tKreX9PlQf+R5GHb2M5KvpZpZMiimyS5bBv9HpvpMohPL9T3zkyjYN4078dn5vVcsLxzd38i0+iJFy+fl2mUwZuWBQCr1fm1hecr7sN8Kci3erqM5pcyXcaxxeisqnp4kt9N8tDu/vJC39Pm8PSKnm5q/M+ZXuu17PNLktwgyS2S7J/p/ihvm7f3o5mCi63dI2Vb/zaPmffj/Hk7r17abnf/W6bX8U8zBRu3TPKxhbqelWlk1MFzfb+V5F3z6BNgExF2ALAn6lXmXZTp2/DFYc4HL5t/0FbmfTnTN4F3XQgqbtrTTQXXsu3VXJ6Fb4Gr6juuQ9/zM13usZJt1XNhpg/AS26X6RKHa33rfB39Zabr8ZdfwpJMl7B0krvP33T/dLYcdp5s+brfbq7zWrr7rn3NzRP/caVlFpb99vwB7V25Zkj7Fq97psuQllutluXH0lZrzTQS4Kczjep449ZCse7+Qnf/j+7+ziRPTPLimu/dkinQ+K+ZLj85fX7+kEyjJ943L3N+klctC9T27+7fneddkeSWC/Nu0t2Llz1cl3262nxZwsuSPDXJLbr7Zkk+mmv/2y5a07/zsu3sm+kD9u8nuc28nZOXtlMr/7rJ4mPp15rOzsIoparaP9N/R8sv41hu+WUmSZLu/rPuPqS7bz3Xt3em/V/J3ln23+w8OuJRK6x7eZ13TLJvko939yWZzlmLo63usY196Cz8m8yX7r0s002ez1ql37X6bmOf75HkFfPInSsyXY51RE03hj0yyeHzpTVfSPKTSZ5WVW/d1j7P2/1sd/9Id9+qu++dKVC5eoRed7+xu+/W3bfIFG58V6b/Xpbqel13X9DdV3b3KzJdMua+HbDJCDsAGM2pSa5K8tSq2ruqjs6Ww+xfn+Rnq+p752/6rr4fR3d/O9OHghdW1a2Tq38C8SHrUNeHk9y1qg6r6Wacz74Off82yXfU9POW+9Z0E797z/O+mOT2tezGjwtek+R/VtUd5sshlu7xceV27seSFyX577nmA/iiG2f65vY/arq/xNNXWOYpVXVQTfeK+LWs8isZq6mqo6vqmKo6oCZHZBoFsTSa5sxMNz684RwoPH6F1Tx97n9wpm/GF2u5dZJfrOmGoY/K9I35yVsp51WZ7lHx01k5BFqq+VFVtRS4XZLpA+ZV8/P3Zvqw/bGebgr5nkyjVD7d19z/4y+T/GhVPaSq9pqH+j+wqg7q7osyXfLxB1V1k5puUHunmn5ZY5v7VNNPGb9nK6XvP9f67/OyP5uFe1ZsxWqv7dbsk+mD778nubKmG5c+eGlmL/t1kxUeS7/W9JYkd6uqn5j/m/vNJB+ZRwasqKr+S6ZLOt6wrP0GVXW3+Ri7XaZLPv54DiOWfqJ16ZxxaKbLxd65bPWPyPSLJe9e1v7qTP+e95sDmedkuqRtaZTDK5P8xvw6fk+mS+1eMW9r6Zyy1/zf9x9kuqzknHn+f53X/xPdvXg5X6rqZvMxdIP5XPmYTCOK3r6Wfc4ULjy2phviXj/Jzye5cB458n9yzb2PDss0yullme6/ss19ns/PN66qfarqpzP9+//hQu33mvf5VplGLv3Nwr/r6ZlGPt1mPv5/JtNop/MCbCrCDgCGMn9A/PFMH2r/I9MHz7/N9G13uvttmT6ovzvTm99T565XzH//99z+/pouwfiHTDfv3NG6Pp7pDf0/ZLrPwT+t3mOLvpdlChZ+NNPQ/09kuuFocs2Hsq9U1YdW6H5Cpg/h78v0U47fTPIL27ELy2u6uLvfuexyiCW/lekeGl/NdB+NN6+wzF9l+lD+qfnxf1dYZi0uyfTh7xOZ7hvwl0lesPCB94WZbnz4xUzfqL96hXW8NckHMwUjf5fpXhlLTsv0s59fznRvkUd291dWKqS7L0jyoUyBwGqjUH4gyWlV9bVMHwJ/aeGSiX9Jsl+uCZE+lunf7OpQqbvPz3S5zq9lCgTOzxQoLb2ve2ymwOBjmV6fN2a6xGUt+3RwpksZVtq/j2X6MH1qptfz+7a27ILVXtsVzcf7L2YKJi9J8lPZ+iVBq63n3zPd6+F583runYV7l9T0i0ZvW9bt2GwZNCy5QaZj9muZRhicmukD/ZIfSnJWVV2eKTg6OdO/z/J1v3L5fzPdfXamn1F9dab7qdw4U3Cw5FmZLmP7bKYw7AU93Zw4mS5He12mY/9Tme7d8SPd/Z/z/P+T6WayJy+MfFna5+tn+u/u3zMdC7+Q5OHdfe4a9/lXMh2bn5jX8bDMN4OeL435wtIj04i5y3u6R89a9vkh8/5cMi93VG95s98/znR+P3f++z8W5j0/U7h85jzvf2YKe/4jwKZSK79HAYBxVNVpSV7a3df6qdiafnnko0n2XYfRDqxBVX0myRO6+x92g1o6ySHdfa1vfavqcZnqvO91WN8Jmb7d3t5fl9mptrVPVXVmkiO3Fuhcx21t9bUFgJ3NyA4AhlNVD6iq75iHZh+b5O5Z+OnBqnrEPDz6gEzfAv6NoIMdVdNPfv541jB6YXfV3YetR9ABABtN2AHAiO6SaRjzVzPdRPOR870Mljwx07DrT2a6V8KTd3mFDKWqnptphNALFi5JAQA2iMtYAAAAgKEY2QEAAAAMZe+NLgDWU9X+ndxso8vYYHttdAF7gM2W8450TOxp/3a7a727yzGxUXXsyn+Xnb2t3eXfcg1qHde1Hi/rjq5jR1767X0ttmeb13U/r+s2rsu+rHXda615LetbS33bWs+26tmR+atte7V+q85beeR+Xe/bW2lfefnrrbD89bK2tiSpXHu9y5dd6/qWr2t71rP4/Lqub/H58nmL69raclvb9nVe/qppuhZLWGl6tbaV5i39+HmvYdnlfxf7XrVs3vL1zfOv+nby7b72rOXdv72sbWn6wuTL3X2rbIOwg8HcLFv+ctlmdJONLmAPsN9GF7CL3XijC1hHe9rxvbsea7vL67hRx+au3P+dfQzsLv+Wa3CD3WxdN9rA/ttb//Zs87r22f86Ln9dDvG11rLWGtZyCtl3Hdazrbq3tY3V1r/aulebt9oxdKOV77d9/Rt9fcX2fW7wrRXbb3jDay+/X67ddsN8Y8X++179i+6L/bdc9oYrru/abfvkW6sus1Jd+67SZ1t17LOs9sV9vPay31px3ta2t/i67LfF8itvY5+rFtZ/+TS99+ULBXxzYfryZX8Xp69YYd7XtrHMSttZPm+x7xrXd+nlyTfm9V06z7psYXrplbh0bl9qW5r/G9NPcW/T7vqVEwAAAMB2EXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2AAAAAEMRdgAAAABDEXYAAAAAQxF2sKqqOriq3l1V51TV2VX1S3P7zavqlKr6xPz3gIU+z6yq86rq3Kp6yEL7varqrHnei6qq5vZ9q+p1c/tpVXX7hT7Hztv4RFUduwt3HQAAgD2UsINtuTLJL3f39ya5T5KnVNWhSZ6R5J3dfUiSd87PM887JsldkxyV5MVVtde8rpckOS7JIfPjqLn98Uku6e47J3lhkufP67p5kmcluXeSI5I8azFUAQAAgJUIO1hVd1/U3R+apy9Lck6SA5McneTEebETkzx8nj46yWu7+4ru/nSS85IcUVW3TXKT7j61uzvJK5f1WVrXG5McOY/6eEiSU7r74u6+JMkpuSYgAQAAgBUJO1iz+fKS709yWpLbdPdFyRSIJLn1vNiBSc5f6HbB3HbgPL28fYs+3X1lkq8mucUq6wIAAICt2nujC2DPUFU3SvKmJE/r7kvn222suOgKbb1K+/b2WaztuEyXxyS56dbqAgAAYJMwsoNtqqrrZwo6Xt3db56bvzhfmpL575fm9guSHLzQ/aAkF87tB63QvkWfqto7U2Jx8Srr2kJ3H9/dh3f34cn+27ubAAAADELYwarme2e8PMk53f2HC7NOSrL06yjHJnnrQvsx8y+s3CHTjUg/MF/qcllV3Wde52OX9Vla1yOTvGu+r8fbkzy4qg6Yb0z64LkNAAAAtsplLGzLDyX5mSRnVdWZc9uvJfndJK+vqscn+VySRyVJd59dVa9P8rFMv+TylO6+au735CSvSLJfkrfNj2QKU15VVedlGtFxzLyui6vquUlOn5d7TndfvJP2EwAAgEEIO1hVd/9TVr53RpIcuZU+z0vyvBXaz0hytxXav5k5LFlh3glJTlhrvQAAAOAyFgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg5WVVUnVNWXquqjC22vq6oz58dnqurMuf32VfWNhXkvXehzr6o6q6rOq6oXVVXN7fvO6zuvqk6rqtsv9Dm2qj4xP47ddXsNAADAnmzvjS6A3d4rkvxpklcuNXT3Ty5NV9UfJPnqwvKf7O7DVljPS5Icl+T9SU5OclSStyV5fJJLuvvOVXVMkucn+cmqunmSZyU5PEkn+WBVndTdl6zfrgEAADAiIztYVXe/L8nFK82bR2f8f0les9o6quq2SW7S3ad2d2cKTh4+zz46yYnz9BuTHDmv9yFJTunui+eA45RMAQkAAACsStjBjrhfki929ycW2u5QVf9aVe+tqvvNbQcmuWBhmQvmtqV55ydJd1+ZaZTILRbbV+gDAAAAW+UyFnbEo7PlqI6Lktyuu79SVfdK8tdVddcktULfnv9ubd5qfbZQVcdlukQmyU3XVDgAAADjMrKD7VJVeyf58SSvW2rr7iu6+yvz9AeTfDLJd2calXHQQveDklw4T1+Q5OCFdd4002UzV7ev0GcL3X18dx/e3Ycn++/4zgEAALBHE3awvf5bkn/r7qsvT6mqW1XVXvP0HZMckuRT3X1Rksuq6j7z/Tgem+Stc7eTkiz90sojk7xrvq/H25M8uKoOqKoDkjx4bgMAAIBVuYyFVVXVa5I8MMktq+qCJM/q7pcnOSbXvjHp/ZM8p6quTHJVkid199LNTZ+c6Zdd9sv0Kyxvm9tfnuRVVXVephEdxyRJd19cVc9Ncvq83HMW1gUAAABbJexgVd396K20P26FtjcledNWlj8jyd1WaP9mkkdtpc8JSU64DuUCAACAy1gAAACAsQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIO1hVVZ1QVV+qqo8utD27qj5fVWfOj4ctzHtmVZ1XVedW1UMW2u9VVWfN815UVTW371tVr5vbT6uq2y/0ObaqPjE/jt1FuwwAAMAeTtjBtrwiyVErtL+wuw+bHycnSVUdmuSYJHed+7y4qvaal39JkuOSHDI/ltb5+CSXdPedk7wwyfPndd08ybOS3DvJEUmeVVUHrP/uAQAAMBphB6vq7vcluXiNix+d5LXdfUV3fzrJeUmOqKrbJrlJd5/a3Z3klUkevtDnxHn6jUmOnEd9PCTJKd19cXdfkuSUrBy6AAAAwBaEHWyvp1bVR+bLXJZGXByY5PyFZS6Y2w6cp5e3b9Gnu69M8tUkt1hlXddSVcdV1RlVdUZy+Y7tFQAAAHs8YQfb4yVJ7pTksCQXJfmDub1WWLZXad/ePls2dh/f3Yd39+HJ/quUDQAAwGYg7OA66+4vdvdV3f3tJC/LdE+NZBp9cfDCogcluXBuP2iF9i36VNXeSW6a6bKZra0LAAAAViXs4Dqb78Gx5BFJln6p5aQkx8y/sHKHTDci/UB3X5Tksqq6z3w/jscmeetCn6VfWnlkknfN9/V4e5IHV9UB82UyD57bAAAAYFV7b3QB7N6q6jVJHpjkllV1QaZfSHlgVR2W6bKSzyR5YpJ099lV9fokH0tyZZKndPdV86qenOmXXfZL8rb5kSQvT/Kqqjov04iOY+Z1XVxVz01y+rzcc7p7rTdKBQAAYBMTdrCq7n70Cs0vX2X55yV53grtZyS52wrt30zyqK2s64QkJ6y5WAAAAIjLWAAAAIDBCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOzaJqnpqVR2w0XUAAADAzibs2Dy+I8npVfX6qjqqqmqjCwIAAICdQdixSXT3byQ5JMnLkzwuySeq6rer6k4bWhgAAACsM2HHJtLdneQL8+PKJAckeWNV/d6GFgYAAADraO+NLoBdo6p+McmxSb6c5C+SPL27/7OqrpfkE0l+dSPrAwAAgPUi7Ng8bpnkx7v7s4uN3f3tqvqRDaoJAAAA1p2wY3BVdfN58o+WPU+SdPfF3X3Orq4LAAAAdhb37BjfB5OcMT8+uOxxxrY6V9UJVfWlqvroQtsLqurfquojVfWWqrrZ3H77qvpGVZ05P1660OdeVXVWVZ1XVS9a+jWYqtq3ql43t59WVbdf6HNsVX1ifhy7Lq8GAAAAwxN2DK6779Ddd5wfd1j2uOMaVvGKJEctazslyd26++5JPp7kmQvzPtndh82PJy20vyTJcZl+EeaQhXU+Pskl3X3nJC9M8vzk6hEoz0py7yRHJHlWVR1wHXYdAACATUrYsYlU1Y9X1R9W1R9U1cPX0qe735fk4mVt7+juK+en709y0Da2e9skN+nuU+dfhHllkqXtH53kxHn6jUmOnEd9PCTJKfNlNpdkCliWhy4AAABwLcKOTaKqXpzkSUnOSvLRJE+qqj9bh1X/XJK3LTy/Q1X9a1W9t6ruN7cdmOSChWUumNuW5p2fJHOA8tUkt1hsX6HPFqrquKo6o6rOSC7f0f0BAABgD+cGpZvHAzJdetJJUlUnZgo+tltV/XqSK5O8em66KMntuvsrVXWvJH9dVXdNUit076XVbGXean22bOw+PsnxU00HrrgMAAAAm4eRHZvHuUlut/D84CQf2d6VzTcM/ZEkj1kKULr7iu7+yjz9wSSfTPLdmUZlLF7qclCSC+fpC+ZaUlV7J7lppstmrm5foQ8AAABslbBj87hFknOq6j1V9Z4kH0tyq6o6qapOui4rqqqjkvzvJD/W3V9faL9VVe01T98x041IP9XdFyW5rKruM9+P47FJ3jp3OynJ0i+tPDLJu+bw5O1JHlxVB8w3Jn3w3AYAAACrchnL5vGb29Opql6T5IFJbllVF2T6hZRnJtk3ySnzL8i+f/7llfsneU5VXZnkqiRP6u6lm5s+OdMvu+yX6R4fS/f5eHmSV1XVeZlGdByTJN19cVU9N8np83LPWVgXAAAAbJWwY5Po7vdW1Xdk+hnXTnJ6d39hDf0evULzy7ey7JuSvGkr885IcrcV2r+Z5FFb6XNCkhO2VSMAAAAschnLJlFVT0jygSQ/nulykfdX1c9tbFUAAACw/ozs2DyenuT7l24gWlW3SPIvMXICAACAwRjZsXlckOSyheeXJTl/g2oBAACAncbIjs3j80lOq6q3Zrpnx9FJPlBV/ytJuvsPN7I4AAAAWC/Cjs3jk/NjydJPv954A2oBAACAnUbYsUl0929tdA0AAACwKwg7Nomqenemy1e20N3/dQPKAQAAgJ1G2LF5/MrC9A2S/ESSKzeoFgAAANhphB2bRHd/cFnTP1fVezekGAAAANiJhB2bRFXdfOHp9ZLcK8l3bFA5AAAAsNMIOzaPD2a6Z0dlunzl00kev6EVAQAAwE4g7NgkuvsOG10DAAAA7ArX2+gC2Lmq6geq6jsWnj+2qt5aVS9admkLAAAADEHYMb4/T/KtJKmq+yf53SSvTPLVJMdvYF0AAACwU7iMZXx7dffF8/RPJjm+u9+U5E1VdebGlQUAAAA7h5Ed49urqpZCrSOTvGthnrALAACA4fiwO77XJHlvVX05yTeS/GOSVNWdM13KAgAAAEMRdgyuu59XVe9Mctsk7+junmddL8kvbFxlAAAAsHMIOzaB7n7/Cm0f34haAAAAYGdzzw4AAABgKMIOAAAAYCjCjk2kqr6rqv7bPL1fVd14o2sCAACA9Sbs2CSq6n8keWOSP5+bDkry1xtWEAAAAOwkwo7N4ylJfijJpUnS3Z9IcusNrQgAAAB2AmHH5nFFd39r6UlV7Z2kV1keAAAA9kjCjs3jvVX1a0n2q6r/nuQNSf5mg2sCAACAdSfs2DyekeTfk5yV5IlJTk7yGxtaEQAAAOwEe290AewyRyd5ZXe/bKMLAQAAgJ3JyI7N48eSfLyqXlVVPzzfswMAAACGI+zYJLr7Z5PcOdO9On4qySer6i82tioAAABYf77d30S6+z+r6m2ZfoVlv0yXtjxhY6sCAACA9WVkxyZRVUdV1SuSnJfkkUn+IsltN7QoAAAA2AmM7Ng8HpfktUme2N1XbHAtAAAAsNMIOzaJ7j5mo2sAAACAXUHYMbiq+qfuvm9VXZbpXh1Xz0rS3X2TDSoNAAAAdgphx+C6+77z3xtvdC0AAACwK7hB6SZRVa9aSxsAAADs6YQdm8ddF59U1d5J7rVBtQAAAMBOI+wYXFU9c75fx92r6tL5cVmSLyZ56waXBwAAAOtO2DG47v6d+X4dL+jum8yPG3f3Lbr7mRtdHwAAAKw3Ycfm8YGquunSk6q6WVU9fAPrAQAAgJ1C2LF5PKu7v7r0pLv/I8mzNq4cAAAA2DmEHZvHSv/WfnoYAACA4Qg7No8zquoPq+pOVXXHqnphkg9udFEAAACw3oQdm8cvJPlWktcleX2SbyR5yoZWBAAAADuByxg2ie6+PMkzqupG3f21ja4HAAAAdhYjOzaJqvovVfWxJB+bn9+jql68hn4nVNWXquqjC203r6pTquoT898DFuY9s6rOq6pzq+ohC+33qqqz5nkvqqqa2/etqtfN7adV1e0X+hw7b+MTVXXs+rwSAAAAjE7YsXm8MMlDknwlSbr7w0nuv4Z+r0hy1LK2ZyR5Z3cfkuSd8/NU1aFJjkly17nPi6tqr7nPS5Icl+SQ+bG0zscnuaS77zzX+Px5XTfP9Gsx905yRJJnLYYqAAAAsDXCjk2ku89f1nTVGvq8L8nFy5qPTnLiPH1ikocvtL+2u6/o7k8nOS/JEVV12yQ36e5Tu7uTvHJZn6V1vTHJkfOoj4ckOaW7L+7uS5KckmuHLgAAAHAt7tmxeZxfVf8lSVfVPkl+Mck527mu23T3RUnS3RdV1a3n9gOTvH9huQvmtv+cp5e3L/U5f17XlVX11SS3WGxfoc8Wquq4TKNGktx0O3cJAACAURjZsXk8KdOvrxyYKTg4LOv/ayy1Qluv0r69fbZs7D6+uw/v7sOT/ddUKAAAAOMSdgyuqp4/Tz6oux/T3bfp7lt3909391e2c7VfnC9Nyfz3S3P7BUkOXljuoCQXzu0HrdC+RZ+q2jvT0IyLV1kXAAAArErYMb6HVdX1kzxzHdd5UpKlX0c5NslbF9qPmX9h5Q6ZbkT6gfmSl8uq6j7z/Tgeu6zP0roemeRd83093p7kwVV1wHxj0gfPbQAAALAq9+wY398n+XKS/avq0kyXhyxdJtLdfZPVOlfVa5I8MMktq+qCTL+Q8rtJXl9Vj0/yuSSPyrSys6vq9Zl+3vbKJE/p7qWboD450y+77JfkbfMjSV6e5FVVdV6mER3HzOu6uKqem+T0ebnndPfyG6UCAADAtQg7xvcb3f30qnprdx99XTt396O3MuvIrSz/vCTPW6H9jCR3W6H9m5nDkhXmnZDkhDUXCwAAAHEZy2Zw6vz30g2tAgAAAHYRIzvGt09VHZvkv1TVjy+f2d1v3oCaAAAAYKcRdozvSUkek+RmSX502bxOIuwAAABgKMKOwXX3PyX5p6o6o7tfvtH1AAAAwM7mnh2Dq6pfTZLufnlVPWrZvN/emKoAAABg5xF2jO+YhelnLpt31K4sBAAAAHYFYcf4aivTKz0HAACAPZ6wY3y9lemVngMAAMAezw1Kx3ePqro00yiO/ebpzM9vsHFlAQAAwM4h7Bhcd++10TUAAADAruQyFgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDgAAAGAowg4AAABgKMIOAAAAYCjCDrZLVd2lqs5ceFxaVU+rqmdX1ecX2h+20OeZVXVeVZ1bVQ9ZaL9XVZ01z3tRVdXcvm9VvW5uP62qbr8BuwoAAMAeRtjBdunuc7v7sO4+LMm9knw9yVvm2S9cmtfdJydJVR2a5Jgkd01yVJIXV9Ve8/IvSXJckkPmx1Fz++OTXNLdd07ywiTP3/l7BgAAwJ5O2MF6ODLJJ7v7s6ssc3SS13b3Fd396STnJTmiqm6b5CbdfWp3d5JXJnn4Qp8T5+k3JjlyadQHAAAAbI2wg/VwTJLXLDx/alV9pKpOqKoD5rYDk5y/sMwFc9uB8/Ty9i36dPeVSb6a5BbrXz4AAAAjEXawQ6pqnyQ/luQNc9NLktwpyWFJLkryB0uLrtC9V2lfrc/yGo6rqjOq6ozk8rUXDwAAwJCEHeyohyb5UHd/MUm6+4vdfVV3fzvJy5IcMS93QZKDF/odlOTCuf2gFdq36FNVeye5aZKLlxfQ3cd39+HdfXiy/7rtGAAAAHsmYQc76tFZuIRlvgfHkkck+eg8fVKSY+ZfWLlDphuRfqC7L0pyWVXdZ74fx2OTvHWhz7Hz9COTvGu+rwcAAABs1d4bXQB7rqq6YZL/nuSJC82/V1WHZbrc5DNL87r77Kp6fZKPJbkyyVO6+6q5z5OTvCLJfkneNj+S5OVJXlVV52Ua0XHMTtwdAAAABiHsYLt199ez7Iah3f0zqyz/vCTPW6H9jCR3W6H9m0keteOVAgAAsJm4jAUAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirCD7VZVn6mqs6rqzKo6Y267eVWdUlWfmP8esLD8M6vqvKo6t6oestB+r3k951XVi6qq5vZ9q+p1c/tpVXX7Xb6TAAAA7HGEHeyoB3X3Yd19+Pz8GUne2d2HJHnn/DxVdWiSY5LcNclRSV5cVXvNfV6S5Lgkh8yPo+b2xye5pLvvnOSFSZ6/C/YHAACAPZywg/V2dJIT5+kTkzx8of213X1Fd386yXlJjqiq2ya5SXef2t2d5JXL+iyt641Jjlwa9QEAAABbI+xgR3SSd1TVB6vquLntNt19UZLMf289tx+Y5PyFvhfMbQfO08vbt+jT3Vcm+WqSW+yE/QAAAGAge290AezRfqi7L6yqWyc5par+bZVlVxqR0au0r9ZnyxVPQcscttx0tXoBAADYBIzsYLt194Xz3y8leUuSI5J8cb40JfPfL82LX5Dk4IXuByW5cG4/aIX2LfpU1d6ZkoyLV6jj+O4+fLpvyP7rs3MAAADssYQdbJeq2r+qbrw0neTBST6a5KQkx86LHZvkrfP0SUmOmX9h5Q6ZbkT6gflSl8uq6j7z/Tgeu6zP0roemeRd8309AAAAYKtcxsL2uk2St8z3C907yV91999X1elJXl9Vj0/yuSSPSpLuPruqXp/kY0muTPKU7r5qXteTk7wiyX5J3jY/kuTlSV5VVedlGtFxzK7YMQAAAPZswg62S3d/Ksk9Vmj/SpIjt9LneUmet0L7GUnutkL7NzOHJQAAALBWLmMBAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7AAAAACGIuwAAAAAhiLsAAAAAIYi7GC7VNXBVfXuqjqnqs6uql+a259dVZ+vqjPnx8MW+jyzqs6rqnOr6iEL7feqqrPmeS+qqprb962q183tp1XV7Xf5jgIAALDHEXawva5M8svd/b1J7pPkKVV16Dzvhd192Pw4OUnmecckuWuSo5K8uKr2mpd/SZLjkhwyP46a2x+f5JLuvnOSFyZ5/i7YLwAAAPZwwg62S3df1N0fmqcvS3JOkgNX6XJ0ktd29xXd/ekk5yU5oqpum+Qm3X1qd3eSVyZ5+EKfE+fpNyY5cmnUBwAAAGyNsIMdNl9e8v1JTpubnlpVH6mqE6rqgLntwCTnL3S7YG47cJ5e3r5Fn+6+MslXk9xihe0fV1VnVNUZyeXrs1MAAADssYQd7JCqulGSNyV5WndfmumSlDslOSzJRUn+YGnRFbr3Ku2r9dmyofv47j68uw9P9r9uOwAAAMBwhB1st6q6fqag49Xd/eYk6e4vdvdV3f3tJC9LcsS8+AVJDl7oflCSC+f2g1Zo36JPVe2d5KZJLt45ewMAAMAohB1sl/neGS9Pck53/+FC+20XFntEko/O0yclOWb+hZU7ZLoR6Qe6+6Ikl1XVfeZ1PjbJWxf6HDtPPzLJu+b7egAAAMBW7b3RBbDH+qEkP5PkrKo6c277tSSPrqrDMl1u8pkkT0yS7j67ql6f5GOZfsnlKd191dzvyUlekWS/JG+bH8kUpryqqs7LNKLjmJ26RwAAAAxB2MF26e5/ysr31Dh5lT7PS/K8FdrPSHK3Fdq/meRRO1AmAAAAm5DLWAAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDsAAACAoQg7AAAAgKEIOwAAAIChCDvY7VXVUVV1blWdV1XP2Oh6AAAA2L0JO9itVdVeSf4syUOTHJrk0VV16MZWBQAAwO5M2MHu7ogk53X3p7r7W0lem+ToDa4JAACA3djeG10AbMOBSc5feH5BknsvLlBVxyU5bn56RfIbH91FtbE53DLJlze6CIbimGK97RnH1Dd2s3Vdsg7rGNeecUxxnXzrOrZ/bf027Xhivd1lLQsJO9jd1QptvcWT7uOTHJ8kVXVGdx++Kwpjc3BMsd4cU6w3xxTrzTHFenI8sd6q6oy1LOcyFnZ3FyQ5eOH5QUku3KBaAAAA2AMIO9jdnZ7kkKq6Q1Xtk+SYJCdtcE0AAADsxlzGwm6tu6+sqqcmeXuSvZKc0N1nr9Ll+F1TGZuIY4r15phivTmmWG+OKdaT44n1tqZjqrp720sBAAAA7CFcxgIAAAAMRdgBAAAADEXYwW6tqo6qqnOr6ryqesYK86uqXjTP/0hV3XNbfavq5lV1SlV9Yv57wK7aHzbW9h5PVXVwVb27qs6pqrOr6pcW+jy7qj5fVWfOj4ftyn1iY+3gOeozVXXWfNycsdDuHLWJ7cB56i4L56Ezq+rSqnraPM95ahNbwzH1PVV1alVdUVW/spa+zlOb2/YeU95PsZIdPEet+l5K2MFuq6r2SvJnSR6a5NAkj66qQ5ct9tAkh8yP45K8ZA19n5Hknd19SJJ3zs8Z3I4cT0muTPLL3f29Se6T5CnL+r6wuw+bHyfvzP1g97GDx9SSB83HzeELbc5Rm9SOHFPdfe7SeSjJvZJ8PclbFvo5T21CazymLk7yi0l+/zr0dZ7apHbkmIr3Uyyzg8fTkq2+lxJ2sDs7Isl53f2p7v5WktcmOXrZMkcneWVP3p/kZlV12230PTrJifP0iUkevpP3g93Ddh9P3X1Rd38oSbr7siTnJDlwVxbPbmlHzlGrcY7avNbrmDoyySe7+7M7v2R2c9s8prr7S919epL/vA59nac2r+0+pryfYgU7co5azdFJThR2sDs7MMn5C88vyLVPiFtbZrW+t+nui5LppJvk1utYM7uvHTmerlZVt0/y/UlOW2h+6jyc/ARDeTeVHT2mOsk7quqDVXXcwjLOUZvXupynkhyT5DXL2pynNqe1HC/b09d5avPakWPqat5PMdvR42nV91LCDnZntULb8t9K3toya+nL5rIjx9M0s+pGSd6U5Gndfenc/JIkd0pyWJKLkvzBDlfKnmJHj6kf6u57Zhq6+ZSquv96FsceaT3OU/sk+bEkb1iY7zy1ee3I+yHvpVjJDh8X3k+xYEePp1XfSwk72J1dkOTghecHJblwjcus1veLS0N+579fWsea2X3tyPGUqrp+pv8xv7q737y0QHd/sbuv6u5vJ3lZpuF4bA47dEx199LfL2W6t8LSseMctXnt0DE1e2iSD3X3F5canKc2tbUcU9vT13lq89qRY8r7KZbboeNpW++lhB3szk5PckhV3WH+puqYJCctW+akJI+d705/nyRfnYdTrtb3pCTHztPHJnnrzt4RdgvbfTxVVSV5eZJzuvsPFzssu1b+EUk+uvN2gd3MjhxT+1fVjZOkqvZP8uBcc+w4R21eO/L/vSWPzrJLWJynNrW1HFPb09d5avPa7mPK+ylWsCPH0zbfS1W30WjsvuafnfqjJHslOaG7n1dVT0qS7n7pfNL80yRHZbrz/M929xlb6zu33yLJ65PcLsnnkjyquy/elfvFxtje46mq7pvkH5OcleTb8+p+rbtPrqpXZRpy2Uk+k+SJyz54MLAdOKbumGt+KWPvJH/lHEWyw//fu2Gma5/v2N1fXVin89QmtoZj6juSnJHkJpn+H/e1JId296XeS7GS7T2mktw93k+xzA4cT7fMNt5LCTsAAACAobiMBQAAABiKsAMAAAAYirADAAAAGIqwAwAAABiKsAMAAAAYirADANijVdWvV9XZVfWRqjqzqu49t3+mqm65gXW9YK7rBcvaH1dV/z7XemZVvXKdtrfm/a2qV1TVp+ftf7iqjlyPGrZXVd2sqn5+O/o9u6p+ZWfUBMCebe+NLgAAYHtV1Q8m+ZEk9+zuK+YP+/usw3r37u4rd3A1T0xyq+6+YoV5r+vup+7g+nfU07v7jVX1oCTHJzlkA2u5WZKfT/LiDawBgIEY2QEA7Mlum+TLS4FCd3+5uy9cmP8LVfWhqjqrqr4nSarqiKr6l6r61/nvXeb2x1XVG6rqb5K8o6r2r6oTqur0edmjl2+8Ji+oqo/O2/jJuf2kJPsnOW2pbTVV9cCq+tuF539aVY+bpz9TVb+1wn7coqreMdf250lqbt+/qv5uHrHx0TVs/9QkB85995r35/R5pMwTF/bzT6vqY/O6T66qRy7Ud8t5+vCqes9CHdd6/arqrlX1gXlUyUeq6pAkv5vkTnPbC+blnr5Qx28tvDa/XlXnVtU/JLnLtl5bADYnIzsAgD3ZO5L8ZlV9PMk/ZBox8d6F+V/u7nvOl0j8SpInJPm3JPfv7iur6r8l+e0kPzEv/4NJ7t7dF1fVbyd5V3f/XFXdLMkHquofuvvyhfX/eJLDktwjyS2TnF5V7+vuH6uqr3X3YVup+yer6r7z9B8n+fQ29nOl/XhWkn/q7udU1Q8nOW5e9qgkF3b3DydJVd10G+s+Kslfz9OPT/LV7v6Bqto3yT9X1TuSfH+mYOH7ktwmyceSnLCN9f56Vnj9kjwpyR9396urap8keyV5RpK7Lb1eVfXgTCNNjsgU4pxUVfdPcnmSY+Z69k7yoSQf3EYdAGxCwg4AYI/V3V+rqnsluV+SByV5XVU9o7tfMS/y5vnvBzMFE0ly0yQnziMKOsn1F1Z5SndfPE8/OMmPLdwT4gZJbpfknIXl75vkNd19VZIvVtV7k/xAkpO2UfoWl7FU1QO3sfxK+3H/penu/ruqumRuPyvJ71fV85P8bXf/41bW+YKq+r0kt05yn7ntwUnuvjRqI9Nrdci8raX9vLCq3rWNepfWtdLrd2qSX6+qg5K8ubs/UVUr9X1wkn+dn99oruPGSd7S3V9Prh5BAwDXIuwAAPZo8wfw9yR5T1WdleTYJK+YZy/dL+OqXPO+57lJ3t3dj6iq2899lyyO2qgkP9Hd566y+Wt9St9OV2bLy4tvsGz+SvuRTGHNFrr743MA9LAkv1NV7+ju56ywzadnClF+McmJSe6VaX9+obvfvrhgVT1spW2tUPti3Vt7/c6pqtOS/HCSt1fVE5J8atkyleR3uvvPl9XxtFXqAICruWcHALDHqqq7zCM0lhyW5LPb6HbTJJ+fpx+3ynJvz3TPj6V7YXz/Csu8L9MlKXtV1a0yjYD4wBpKX+6zSQ6tqn3ny07W8uso70vymLm2hyY5YJ7+ziRf7+6/TPL7Se65tRV097czXUZzvap6SKZ9fnJVXX9e13dX1f7zto6Z9/O2mUbRLPlMpqAkueZyoGQrr19V3THJp7r7RZlGwNw9yWWZRm0s9v25qrrR3OfAqrr1XMcjqmq/qrpxkh9dw+sEwCZkZAcAsCe7UZI/me8JcWWS83LNvSu25vcyXcbyv5KsdjnGc5P8UZKPzB/YP5Ppl18WvSXTfT4+nGnEwa929xeu2y7k/2/nDnH2KsIwDD+zEyyimyDB12G6gS6AChyEbZDgCASPRjQN5g8hKHDUkGBxTTiI70uooAVHcnNdcszMHHln3rPrul6ec77a9sO2n/fX+MbbfLzti3POw7Zvt/1yX3+024jKH9tebXv6D3tf55xPtz3b9v62d7Y93O/827bHu93zvd1GZH667/f6OT4753y07bvX1t/0/T7Y9uSc82rbr9s+uf8j5fk558dt31zX9eE5591tL+6t5PdtT67rejjnfLnt+90C0ZtGdAD4nzvX5SUgAAD/3jnn893+B/L1f30WAPg7xlgAAACAFC87AAAAgBQvOwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASBE7AAAAgBSxAwAAAEgROwAAAIAUsQMAAABIETsAAACAFLEDAAAASPkThZfauQpJX10AAAAASUVORK5CYII=\n" }, "metadata": { "needs_background": "light" } } ], "source": [ "trigger_grid(supply_sweep, alpha_sweep)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These plots demonstrate that the trigger functions the share of of max conviction required to pass a proposal remains constant under variations in both alpha and effective supply -- both of these variables scale the the conviction required to pass a proposal and the max conviction possible by the same amount." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.5-final" } }, "nbformat": 4, "nbformat_minor": 2 }