Aragon_Conviction_Voting/models/v3/model/parts/sys_params.py

49 lines
2.2 KiB
Python

import numpy as np
# Initial values
initial_values = {
'initial_sentiment': 0.6,
'n': 30, #initial participants
'm': 7, #initial proposals
'initial_funds': 4867.21, # in honey, as of 8-5-2020
'supply': 22392.22, # Honey total supply balance as of 8-5-2020
}
# andrew TODO
# <There alpha to their half life then rescale half life to our alpha >
# Explaing how alpha works, refine alpha notebook and v3.
# Alpha from solidity code - uint256 _decay = 9999599; // 3 days halftime. halftime_alpha = (1/2)**(1/t)
# Half life associated with solidity code alpha (in number of blocks on xDai).
# Our simulation is associated with timesteps, so our half life is based of of days.
# Parameters
params = {
'beta': [0.2], # maximum share of funds a proposal can take
'rho': [0.0025], # tuning param for the trigger function
'alpha': [2**(-1/3)], # timescale set in days with 3 day halflife (see above)
'gamma': [0.001], # expansion of supply per per day
'sensitivity': [.75],
'tmin': [1], #unit days; minimum periods passed before a proposal can pass
'min_supp': [1], #number of tokens that must be stake for a proposal to be a candidate
'base_completion_rate': [45], # expected number of days to complete a proposals.
'base_failure_rate': [180], # expected number of days until a proposal will fail
'base_engagement_rate' :[0.3], # Probability of being active on a certain day if 100% sentiment (Andrew AUDIT)
'lowest_affinity_to_support': [0.3], # lowest affinity to required to support a proposal
}
# Pull out trigger stuff from v3 and add to notebook. Link to and trigger notebook.
# ANDREW AUDIT explanations
# add metrics - think about health matrics of the system
# fraction of supply of use for voting (effectiev supply over total supply)
# fraction of supply in the funding pool
# fraction of projects that are active vs completed vs killed
# Fraction of projects in each of the states
# fraction of money in the different states
# cadCAD model is micro founded, metrics are macro or at the insitutional level. If you are interested in insitutional dynamics, link to cryptoeconomics paper
# write what metrics are: views on a complex data structure.
# Update differential spec