From e6f96245a3d569797ecf7ad5d6af0517c1d11ac3 Mon Sep 17 00:00:00 2001 From: kashepavadan Date: Tue, 10 Jun 2025 06:58:02 -0400 Subject: [PATCH] stake concentration scenarios --- ...tal-stake-inference-v2-concentration.ipynb | 274 ++++++++++++++++++ 1 file changed, 274 insertions(+) create mode 100644 cryptarchia/total-stake-inference-v2-concentration.ipynb diff --git a/cryptarchia/total-stake-inference-v2-concentration.ipynb b/cryptarchia/total-stake-inference-v2-concentration.ipynb new file mode 100644 index 0000000..6a7bc3c --- /dev/null +++ b/cryptarchia/total-stake-inference-v2-concentration.ipynb @@ -0,0 +1,274 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "f443be50-1b6b-41e2-ad7c-5ac96a92d620", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from dataclasses import dataclass" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "fb9d4f63-ec30-453f-bcd0-569bbec371dd", + "metadata": {}, + "outputs": [], + "source": [ + "# Cryptarchia lottery function\n", + "def phi(f, alpha):\n", + " return 1 - (1-f)**alpha\n", + "\n", + "evaluations = 100\n", + "\n", + "# sim params\n", + "@dataclass\n", + "class Params:\n", + " epochs: int\n", + " sims: int\n", + " stake: np.array\n", + " T: int\n", + " f: float\n", + " beta: float\n", + " D_init: float\n", + "\n", + " @property\n", + " def h_at_fixpoint(self):\n", + " D_inf = gauss_field_mean(f=self.f, stake=self.stake)\n", + " return D_inf / np.log(1/(1-self.f)) * self.beta\n", + " \n", + " def __str__(self):\n", + " import dataclasses\n", + " \"\"\"Returns a string containing only the non-default field values.\"\"\"\n", + " s = ', '.join(f'{field.name}={getattr(self, field.name)!r}'\n", + " for field in dataclasses.fields(self)\n", + " if field.name != \"stake\")\n", + " s += f\", stake=(N={len(self.stake)}, mean={self.stake.mean():.2f}, var={self.stake.var():.2f})\"\n", + " return f'{type(self).__name__}({s})'" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "f48a89b1-4344-40e5-bf5a-daf62ec78c28", + "metadata": {}, + "outputs": [], + "source": [ + "# Generate stake distribution\n", + "def make_params(i):\n", + " np.random.seed(0)\n", + " N = 100\n", + " stake = np.random.uniform(0, 1, N) ** (i*2+1)\n", + " return Params(\n", + " epochs=100,\n", + " sims=10,\n", + " stake = stake,\n", + " D_init = stake.sum(),\n", + " T=int(10 * 2160 / (1/30)),\n", + " f=(1/30),\n", + " beta=0.8,\n", + " )\n", + "\n", + "vary_stake_params = [make_params(i) for i in range(evaluations)]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "e0ec9157-b947-4c81-970e-44aaaab92690", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.0023676874989447\n", + "1.0021728136582488\n", + "0.9989441779606686\n", + "1.003955035311425\n", + "0.9979128359075979\n", + "0.9967952390649157\n", + "1.0001131994785077\n", + "0.99866810490959\n", + "0.9995305561970589\n", + "0.9997020400432076\n", + "1.0028640464671794\n", + "0.995343753465011\n", + "1.0036888790103764\n", + "1.0039446357780037\n", + "1.002557224168902\n", + "1.0003009698995637\n", + "0.9966325192773976\n", + "0.999436155646863\n", + "1.0011055293050062\n", + "1.0012279020800763\n", + "0.9990862424911157\n", + "0.997983883190692\n", + "1.0056627472828505\n", + "1.0006951489102047\n", + "1.001951867753856\n", + "0.9995214922046258\n", + "1.0013051452681387\n", + "1.0001817762795295\n", + "1.001608577673848\n", + "1.0038323848688284\n", + "1.0029932115677838\n", + "1.0003573361376639\n", + "1.003303592256525\n", + "1.0012569341316524\n", + "1.0018154781780149\n", + "1.0010950688825906\n", + "0.9996986603721826\n", + "1.000756095178297\n", + "0.9995523752140102\n", + "1.003774673701196\n", + "1.0003575532958902\n", + "1.0012981753073091\n", + "0.9978712655730252\n", + "1.003281264794399\n", + "0.9991788422690455\n", + "1.0011078223742378\n", + "1.0020954816178498\n", + "1.000739932296818\n", + "0.9988078306842825\n", + "0.9968900678807892\n", + "1.000864844322923\n", + "0.9998740756506\n", + "0.9980890735520648\n", + "1.002656619284327\n", + "0.9988414987618709\n", + "1.0004452231212286\n", + "0.9958673196051097\n", + "0.9991714022881629\n", + "1.0032095137702322\n", + "1.0008233557865724\n", + "1.0026222753306888\n", + "1.0013655476449954\n", + "0.9998654558692787\n", + "1.0033415367294272\n", + "0.9987153107971387\n", + "1.0012824835057033\n", + "0.9937233071014235\n", + "0.9997935494663815\n", + "1.0048485325144536\n", + "0.9991182204497144\n", + "1.0020339308569641\n", + "0.9963310368309534\n", + "1.0006471586251764\n", + "1.0003753817973977\n", + "0.9977052796136576\n", + "1.0016008233878853\n", + "0.9982784543024911\n", + "0.9989604814105922\n", + "1.0027289956627992\n", + "1.0013661585488796\n", + "1.0001146931055065\n", + "1.0039070420413319\n", + "0.998357365426491\n", + "0.9999655060178652\n", + "1.0012139475076505\n", + "0.9993777836068626\n", + "1.0030245480963764\n", + "0.9986899832582905\n", + "1.0043352357161304\n", + "0.9966449039639956\n", + "0.9969206081727975\n", + "0.9958884500230614\n", + "1.000974943095099\n", + "1.001983074962574\n", + "0.9973382580701099\n", + "0.9978631358338254\n", + "0.9996035309131692\n", + "1.0021079444554886\n", + "0.9990394538510513\n", + "1.001959060801767\n" + ] + } + ], + "source": [ + "ratios = []\n", + "for j in range(evaluations):\n", + " vsp = vary_stake_params[j]\n", + " D_values_j = []\n", + " \n", + " # Initial stake estimate \n", + " D_ell = vsp.D_init * 0.75\n", + " \n", + " for i in range(0, vsp.epochs):\n", + " \n", + " # Running one epoch of the cryptarchia lottery\n", + " alpha = vsp.stake / D_ell\n", + " p_lottery = phi(vsp.f, alpha)\n", + " wins = np.random.uniform(0, 1, (vsp.T, len(vsp.stake))) < p_lottery\n", + " \n", + " # Total Stake Inference\n", + " empirical_slot_activation_rate = (wins.sum(axis=1) != 0).sum() / vsp.T\n", + " error = vsp.f - empirical_slot_activation_rate\n", + " \n", + " # Learning coefficient\n", + " h = vsp.beta * (D_ell / vsp.f)\n", + " \n", + " # New total stake estimate\n", + " D_ell = D_ell - h * error\n", + " D_values_j.append(D_ell)\n", + " \n", + " ratios.append(np.mean(D_values_j[-10:] / np.full_like(range(0, 10), vsp.D_init, dtype=float)))\n", + " print(ratios[j])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "e993f286-400b-4338-84fe-b1ef00325056", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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