1797 lines
722 KiB
Plaintext
1797 lines
722 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Aragon Conviction Voting Model - Version 3\n",
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"\n",
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"New to this version 3 model are the following elements:\n",
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"\n",
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"* Adding the realism that not all participant tokens are being allocated to proposals at each timestep.\n",
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"* Refactored parameters and system initialization to make more readable and consistent.\n",
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"* Changed file structure and file names to align with emerging cadCAD standards.\n",
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"* Making the distinction between effective and total supply.\n",
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"* Refining alpha calculations to more accurately reflect the 1Hive implementation. Discussion of alpha and its relation to alpha in the contract and how it relates to the timescales\n",
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"* Updated differential specification and write-up to respect new state variables\n",
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"* Moved all unit denominations to Honey, the 1Hive governance token.\n",
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"* Added system health metrics\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# An Introduction to Conviction Voting\n",
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"\n",
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"Conviction Voting is an approach to organizing a communities preferences into discrete decisions in the management of that communities resources. Strictly speaking conviction voting is less like voting and more like signal processing. Framing the approach and the initial algorithm design was done by Michael Zargham and published in a short research proposal [Social Sensor Fusion](https://github.com/BlockScience/conviction/blob/master/social-sensorfusion.pdf). This work is based on a dynamic resource allocation algorithm presented in Dr. Zargham's PhD Thesis.\n",
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"\n",
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"The work proceeded in collaboration with the Commons Stack, including expanding on the python implementation to makeup part of the Commons Simulator game. An implemention of Conviction Voting as a smart contract within the Aragon Framework was developed by 1Hive.org and is currently being used for community decision making for allocations of their community currency, Honey.\n",
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"\n",
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"\n",
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"## The Word Problem\n",
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"\n",
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"Suppose a group of people want to coordinate to make a collective decision. Social dynamics such as discussions, signaling, and even changing ones mind based on feedback from others input play an important role in these processes. While the actual decision making process involves a lot of informal processes, in order to be fair the ultimate decision making process still requires a set of formal rules that the community collecively agrees to, which serves to functionally channel a plurality of preferences into a discrete outcomes. In our case we are interested in a procedure which supports asynchronous interactions, an provides visibility into likely outcomes prior to their resolution to serve as a driver of good faith, debate and healthy forms of coalition building. Furthermore, participations should be able to show support for multiple initiatives, and to vary the level of support shown. Participants have a quantity of signaling power which may be fixed or variable, homogenous or heterogenous. For the purpose of this document, we'll focus on the case where the discrete decisions to be made are decisions to allocate funds from a shared funding pool towards projects of interest to the community.\n",
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"\n",
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"## Converting to a Math Problem\n",
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"\n",
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"Let's start taking these words and constructing a mathematical representation that supports a design that meets the description above. To start we need to define participants.\n",
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"\n",
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"### Participants\n",
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"Let $\\mathcal{A}$ be the set of participants. Consider a participant $a\\in \\mathcal{A}$. Any participant $a$ has some capacity to participate in the voting process through their token holdings $h[a]$. In a homogenous fixed token quantity system (like you might see in a democratic allocation of equal tokens per each participant), $h[a] = h$ for all $a\\in \\mathcal{A}$ where $h$ is a constant. The access control process managing how one becomes a participant determines the total supply of \"votes\" $S = \\sum_{a\\in \\mathcal{A}} = n\\cdot h$ where the number of participants is $n = |\\mathcal{A}|$. In a smart contract setting, the set $\\mathcal{A}$ is a set of addresses, and $h[a]$ is a quantity of tokens held by each address $a\\in \\mathcal{A}$. \n",
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"\n",
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"### Proposals & Shared Resources\n",
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"Next, we introduce the idea of proposals. Consider a proposal $i\\in \\mathcal{C}$. Any proposal $i$ is associated with a request for resources $r[i]$. Those requested resources would be allocated from a constrained pool of communal resources currently totaling $R$. The pool of resources may become depleted because when a proposal $i$ passes the reserve is decremented by $R^+= R-r[i]$. Therefore it makes sense for us to consider what fraction of the shared resources are being request $\\mu_i = \\frac{r[i]}{R}$, which means that thre resource depletion from passing proposals can be bounded by requiring $\\mu_i < \\mu$ where $\\mu$ is a constant representing the maximum fraction of the shared resources which can be dispersed by any one proposal. In order for the system to be sustainable a source of new resources is required. In the case where $R$ is funding, new funding can come from revenues, donations, or in some DAO use cases minting tokens.\n",
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"\n",
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"### Participants Preferences for Proposals\n",
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"\n",
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"Most of the interesting information in this system is distributed amongst the participants and it manifests as preferences over the proposals. This can be visualized as a matrix $W\\in \\mathbb{R}^{n \\times m}$, with participants holding randomized affinities from -1 to +1 over all proposals.\n",
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"\n",
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"\n",
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"These private hidden signals drive discussions and voting actions. Each participant individually decides how to allocate their votes across the available proposals. Participant $a$ supports proposal $i$ by setting $x[a,i]>0$ but they are limited by their total token holdings $\\sum_{k\\in \\mathcal{C}} x[a,k] \\le h[a]$. Assuming each participant chooses a subset of the proposals to support, a support graph is formed.\n",
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"\n",
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"\n",
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"## Aggregating Information\n",
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"\n",
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"In order to break out of the synchronous ad hoc voting model, a dynamical systems model of this system is introduced, which is explored further below.\n",
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"\n",
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"### Participants Allocate Voting Power\n",
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"\n",
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"\n",
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"In the above diagram, we examine the participant view. Participant $a$ with holdings $h$ at time $t$ supports proposals $i$ and $j$ with $x$ conviction. The sum of all conviction asserted by participant $a$ is between 0 and the total holdings of participant $a$.\n",
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"\n",
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"### System Accounts Proposal Conviction\n",
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"\n",
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"\n",
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"In the above diagram, we examine the proposal view. Proposal $j$ with total conviction $y$ at time $t$ is supported by participants $a$, $b$ and $c$ with $x$ conviction. The total conviction $y$ at time $t+1$ is equal to the total conviction at time $t$ decremented by an exponential decay $\\\\alpha$ plus the sum of all conviction from $k$ agents in time step $t$.\n",
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"\n",
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"### Understanding Alpha\n",
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"Below are some graphs used to demonstrate, play with, and understand the shapes and choices for the $\\\\alpha$ parameter, which regulates the half life decay rate of the agent preference conviction growth and decay. Alpha from solidity code is defined as: \n",
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"```uint256 _decay = 9999599; // 3 days halftime. halftime_alpha = (1/2)**(1/t)```\n",
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"Half life associated with solidity code alpha (in number of blocks on xDai). \n",
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"\n",
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"The half-life of this system is defined by $T$ such that $y_T = y_0/2$ which satisfies the equation\n",
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"\n",
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"$\\frac{1}{2} = \\alpha^T$\n",
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"\n",
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"thus the Half life in epochs for a given $\\alpha$ is\n",
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"\n",
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"$T = \\log_\\alpha \\frac{1}{2} = -\\log_\\alpha 2$\n",
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"\n",
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"and conversely the $\\alpha$ which achieves a desired half-life $T$ is\n",
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"\n",
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"$\\alpha = 2^{-1/T} = \\frac{1}{\\sqrt[T]{2}}$\n",
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"\n",
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"Further note that the relationship between $T$ and $\\alpha$ is sensative to timescaling. Suppose we wanted a half-life of 3 days but our discrete time scale simulation has 1 day timesteps, then we must use $T = 3$ in the above equation to equal:\n",
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"\n",
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"$\\alpha = 2^{-1/3}$\n",
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"\n",
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"\n",
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"See the [Deriving_Alpha](Deriving_Alpha.ipynb) notebook for more details around alpha and how it is derived.\n",
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"\n",
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"\n",
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"## Converting Signals to Discrete Decisions\n",
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"\n",
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"Conviction can be considered like a fluctuating kinetic energy, with the Trigger function acting as a required activation energy for proposals to pass. This is the mechanism by which a continuous community preference turns into a discrete action event: passing a proposal. See [Trigger Function Explanation](Trigger_Function_Explanation.ipynb) for more details around the trigger function and how it works."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Resolving Passed Proposals\n",
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"\n",
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"\n",
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"\n",
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"This diagram shows the trigger function logic, which depends on token supply $S$, total resources available $R$ and total conviction $y$ at time $t$, as well as the proposal's requested resources $r$, the maximum share of funds a proposal can take ($\\beta$) and a tuning parameter for the trigger function ($\\rho$). Essentially, this function controls the maximum amount of funds that can be requested by a proposal ($\\beta$), using an equation resembling electron repulsion to ensure conviction increases massively beyond that point.\n",
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"\n",
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"## Social Systems Modeling\n",
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"\n",
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"In the conviction voting model, multiple graph structures are used to represent participants and proposals to represent a subjective, exploratory modeling of the social system interacting.\n",
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"\n",
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"### Sentiment\n",
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"\n",
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"Global Sentiment denotes the outside world appreciating the output of the community.\n",
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"Local Sentiment denotes the agents within the system feeling good about the community.\n",
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"Sentiment increases when proposals pass and work is completed in the community, and decreases when proposals fail and community progress stalls.\n",
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"\n",
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"### Relationships between Participants\n",
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"\n",
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"Edges from participant to participant denote influence (to represent subjective social influence) and are assigned randomly as mixing processes.\n",
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"\n",
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"### Relationships between Proposals\n",
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"\n",
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"Edges from proposal to proposal represent conflict, either positive or negative.\n",
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"Some proposals are synergistic (passing one makes the other more desirable).\n",
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"Some proposals are (partially) substitutable (passing one makes the other less desirable).\n",
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"\n",
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"\n",
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"### Notion of Honey supply\n",
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"#### Total supply = $S$\n",
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"#### Effective supply = $E$, honey committed towards votes (whether for proposals or abstain)\n",
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"#### Funding Pool = $F$, community funding pool where proposals are funded from\n",
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"#### Other supply = $L$, effectively slack. Funds could be in cold storage, in liquidity pools or otherwise in any address not actively participating in conviction voting.\n",
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"$$S = F + E + L$$ \n",
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"\n",
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"System has the right to do direct mints:\n",
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"$$F^+ = F + minted tokens$$\n",
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"$$S^+ = S + minted tokens$$\n",
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"\n",
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"The system may also see the arrival of new funds which come from outside supply and are donated to the funding pool:\n",
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"$$L^+ = L - donated tokens$$\n",
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"$$F^+ = F + donated tokens$$\n",
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"\n",
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"When tokens are added to a liquidity pool or cold wallet and removed from staking on proposals:\n",
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"$$L^+ = L + tokens$$ \n",
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"$$E^+ = E - tokens$$ \n",
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"\n",
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"When tokens are removed from a liquidity pool or cold wallet and staked towards proposals:\n",
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"$$L^+ = L - tokens$$ \n",
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"$$E^+ = E + tokens$$\n",
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"\n",
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"Tokens in $L$ or $E$ are defined at the level of the account holding them.\n"
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]
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},
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{
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"cell_type": "markdown",
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||
"metadata": {},
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"source": [
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"## cadCAD Overview\n",
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"\n",
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"In the cadCAD simulation [methodology](https://community.cadcad.org/t/differential-specification-syntax-key/31), we operate on four layers: **Policies, Mechanisms, States**, and **Metrics**. Information flows do not have explicit feedback loop unless noted. **Policies** determine the inputs into the system dynamics, and can come from user input, observations from the exogenous environment, or algorithms. **Mechanisms** are functions that take the policy decisions and update the States to reflect the policy level changes. **States** are variables that represent the system quantities at the given point in time, and **Metrics** are computed from state variables to assess the health of the system, essentially views on a complex data structure. Metrics can often be thought of as KPIs, or Key Performance Indicators. \n",
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"\n",
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"\n",
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||
"At a more granular level, to setup a model, there are system conventions and configurations that must be [followed.](https://community.cadcad.org/t/introduction-to-simulation-configurations/34)\n",
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"\n",
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||
"The way to think of cadCAD modeling is analogous to machine learning pipelines which normally consist of multiple steps when training and running a deployed model. There is preprocessing, which includes segregating features between continuous and categorical, transforming or imputing data, and then instantiating, training, and running a machine learning model with specified hyperparameters. cadCAD modeling can be thought of in the same way as states, roughly translating into features, are fed into pipelines that have built-in logic to direct traffic between different mechanisms, such as scaling and imputation. Accuracy scores, ROC, etc. are analogous to the metrics that can be configured on a cadCAD model, specifying how well a given model is doing in meeting its objectives. The parameter sweeping capability of cadCAD can be thought of as a grid search, or way to find the optimal hyperparameters for a system by running through alternative scenarios. A/B style testing that cadCAD enables is used in the same way machine learning models are A/B tested, except out of the box, in providing a side by side comparison of muliple different models to compare and contrast performance. Utilizing the field of Systems Identification, dynamical systems models can be used to \"online learn\" by providing a feedback loop to generative system mechanisms. \n",
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"\n",
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"cadCAD models are micro founded with metrics being at the macro or the institutional level. If you are interested in insitutional dynamics, see Dr. Zargham's recent paper: [Voshmgir, Shermin and Zargham, Michael (2019) Foundations of Cryptoeconomic Systems. Working Paper Series / Institute for Cryptoeconomics / Interdisciplinary Research, 1. Research Institute for Cryptoeconomics, Vienna.](https://epub.wu.ac.at/7309/)\n",
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"\n",
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"\n",
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"## Differential Specification \n",
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"\n",
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"\n",
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"## File structure\n",
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"* ```Aragon_Conviction_Voting_Model.ipynb```\n",
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"* model\n",
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"\n",
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"In the model folder there exist 4 files and folder, the [```config.py```](model/config.py), [```partial_state_update_block.py```](model/partial_state_update_block.py), [```run.py```](model/run.py), and [```state_variables.py```](model/state_variables.py). The [```config.py```](model/config.py) contains the simulation configurations, aggregating the partial states, and the state variables. The [```partial_state_update_block.py```](model/partial_state_update_block.py) contains the partial state update blocks and how they update the state variables. [```state_variables.py```](model/state_variables.py) defines the state variables and [```run.py```](model/run.py) actually runs the simulation.\n",
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"\n",
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"The mechanisms of the model live within the parts subfolder as:\n",
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"* [```system.py```](model/parts/system.py)\n",
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"* [```participants.py```](model/parts/participants.py)\n",
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"* [```proposals.py```](model/parts/proposals.py)\n",
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"\n",
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"The initial parameters and hyperparameters of the system are defined in [```sys_params.py```](model/sys_params.py) and helper functions, plots, trigger function, etc are in the [```utils.py```](model/utils.py).\n",
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"\n",
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"### Note:\n",
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"When running this notebook simulation, be sure to run from \"Kernal\" -> \"Restart & Run All\"\n",
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"\n",
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"## Schema of the states \n",
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"The model consists of a temporal in memory graph database called *network* containing nodes of type **Participant** and type **Proposal**. Participants will have *holdings* and *sentiment* and Proposals will have *funds_required, status* (candidate or active), and *conviction* The model as three kinds of edges:\n",
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"* (Participant, participant), we labeled this edge type \"influencer\" and it contains information about how the preferences and sentiment of one participant influence another.\n",
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"* (Proposal, Proposal), we labeled this edge type \"conflict\" and it contains information about how synergistic or anti-synergistic two proposals are; basically people are likely to support multiple things that have synergy (meaning once one is passed there is more utility from the other) but they are not likely to pass things that have antisynergy (meaning once one is passed there is less utility from the other).\n",
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"* The edges between Participant and Proposal, which are described below.\n",
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" \n",
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"\n",
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"Edges in the network go from nodes of type Participant to nodes of type Proposal with the edges having the key *type*, of which all will be set to *support*. Edges from participant $i$ to proposal $j$ will have the following additional characteristics:\n",
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"* Each pairing (i,j) will have *affinity*, which determines how much $i$ likes or dislikes proposal $j$.\n",
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"* Each participant $i$, assigns its $tokens$ over the edges (i,j) for all $j$ such that the summation of all $j$ such that ```Sum_j = network.edges[(i,j)]['tokens'] = network.nodes[i]['holdings']```. This value of tokens for participants on proposals must be less than or equal to the total number of tokens held by the participant.\n",
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"* Each pairing (i,j) will have *conviction* local to that edge whose update at each timestep is computed using the value of *tokens* at that edge.\n",
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"* Each proposal *j* will have a *conviction* which is equal to the sum of the conviction on its inbound edges: ```network.nodes[j]['conviction'] = Sum_i network.edges[(i,j)]['conviction']```. \n",
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"\n",
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"\n",
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"The other state variables in the model are *funds*, *sentiment*, *effective_supply*, *total_supply*, and the metrics variables of: *fractionOfSupplyForVoting*, *fractionOfSupplyInPool*, *fractionOfProposalStages*, *fractionOfFundStages*.\n",
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"\n",
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"The system consists of 100 time steps without a parameter sweep or monte carlo.\n",
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"\n",
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" \n",
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"## Partial State Update Blocks \n",
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"\n",
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"Each partial state update block is kind of a like a phase in a phased based board game. Everyone decides what to do and it reconciles all decisions. One timestep is a full turn, with each block being a phase of a timestep or turn. We will walk through the individaul Partial State update blocks one by one below."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"```\n",
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"{\n",
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"# system.py: \n",
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"'policies': { \n",
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" 'random': driving_process\n",
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"},\n",
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"'variables': {\n",
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" 'network': update_network,\n",
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" 'effective_supply':increment_supply,\n",
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"}\n",
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"```\n",
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"\n",
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"To simulate the arrival of participants and proposal into the system, we have a driving process to represent the arrival of individual agents. We use a random uniform distribution generator, over [0, 1), to calculate the number of new participants. We then use an exponential distribution to calculate the particpant's tokens by using a loc of 0.0 and a scale of expected holdings, which is calculated by .1*supply/number of existing participants. We calculate the number of new proposals by \n",
|
||
"```\n",
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||
"proposal_rate = 1/median_affinity * (1+total_funds_requested/funds)\n",
|
||
"rv2 = np.random.rand()\n",
|
||
"new_proposal = bool(rv2<1/proposal_rate)\n",
|
||
"```\n",
|
||
"The network state variable is updated to include the new participants and proposals, while the *effective_supply* state variable is updated for the addition of new particpant's funds. \n",
|
||
"```\n",
|
||
" {\n",
|
||
" 'policies': { \n",
|
||
" 'random': minting_rule\n",
|
||
" },\n",
|
||
" 'variables': {\n",
|
||
" 'total_supply': mint_to_supply,\n",
|
||
" 'funds':mint_to_funds,\n",
|
||
"\n",
|
||
" }\n",
|
||
"},\n",
|
||
"```\n",
|
||
"A behavior called *minting_rule* is included to record the general expansion of system supply every timestep. The *total_supply* and *funds* state variables are incrased with these minted values.\n",
|
||
"[To see the partial state update's code, click here](model/parts/system.py)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"```\n",
|
||
"{\n",
|
||
" # participants.py \n",
|
||
" 'policies': {\n",
|
||
" 'completion': check_progress \n",
|
||
" },\n",
|
||
" 'variables': { \n",
|
||
" 'sentiment': update_sentiment_on_completion, #not completing projects decays sentiment, completing bumps it\n",
|
||
" 'network': complete_proposal\n",
|
||
" }\n",
|
||
"},\n",
|
||
"```\n",
|
||
"\n",
|
||
"In the next phase of the turn, [to see the logic code, click here](model/parts/participants.py), the *check_progress* behavior checks for the completion of previously funded proposals. The code calculates the completion and failure rates as follows:\n",
|
||
"\n",
|
||
"```\n",
|
||
"likelihood = 1.0/(base_completion_rate+np.log(grant_size))\n",
|
||
"\n",
|
||
"failure_rate = 1.0/(base_failure_rate+np.log(grant_size))\n",
|
||
"if np.random.rand() < likelihood:\n",
|
||
" completed.append(j)\n",
|
||
"elif np.random.rand() < failure_rate:\n",
|
||
" failed.append(j)\n",
|
||
"```\n",
|
||
"With the base_completion_rate being 100 and the base_failure_rate as 200. \n",
|
||
"\n",
|
||
"The mechanism then updates the respective *network* nodes and updates the sentiment variable on proposal completion. "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"```\n",
|
||
" # proposals.py\n",
|
||
" 'policies': {\n",
|
||
" 'release': trigger_function \n",
|
||
" },\n",
|
||
" 'variables': { \n",
|
||
" 'funds': decrement_funds, \n",
|
||
" 'sentiment': update_sentiment_on_release, #releasing funds can bump sentiment\n",
|
||
" 'network': update_proposals \n",
|
||
" }\n",
|
||
"},\n",
|
||
" ```\n",
|
||
" \n",
|
||
"The [trigger release function](model/parts/proposals.py) checks to see if each proposal passes or not. If a proposal passes, funds are decremented by the amount of the proposal, while the proposal's status is changed in the network object."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"```\n",
|
||
"{ \n",
|
||
" # participants.py\n",
|
||
" 'policies': { \n",
|
||
" 'participants_act': participants_decisions\n",
|
||
" },\n",
|
||
" 'variables': {\n",
|
||
" 'network': update_tokens \n",
|
||
" }\n",
|
||
"}\n",
|
||
"```\n",
|
||
"\n",
|
||
"The Participants decide based on their affinity if which proposals they would like to support,[to see the logic code, click here](model/parts/participants.py). Proposals that participants have high affinity for receive more support and pledged tokens than proposals with lower affinity and sentiment. We then update everyone's holdings and their conviction for each proposal.\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"```\n",
|
||
" {\n",
|
||
" # metrics.py\n",
|
||
" 'policies': {\n",
|
||
" 'calculations': kpi_calculations\n",
|
||
" },\n",
|
||
" 'variables':{\n",
|
||
" 'fractionOfSupplyForVoting': kpi_fractionOfSupplyForVoting,\n",
|
||
" 'fractionOfSupplyInPool': kpi_fractionOfSupplyInPool,\n",
|
||
" 'fractionOfProposalStages':kpi_proposal_stages,\n",
|
||
" 'fractionOfFundStages': kpi_fractionOfFundStages\n",
|
||
" }\n",
|
||
" }\n",
|
||
"```\n",
|
||
"\n",
|
||
"In the Metrics section we create KPI's to calculate the system's health. To see the logic, [click here](model/parts/metrics.py)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Model next steps\n",
|
||
"\n",
|
||
"The the model described above is the third iteration model that covers the core mechanisms of the Aragon Conviction Voting model. Below are next additional dynamics we can attend to enrich the model, and provide workstreams for subsequent iterations of this lab notebook.\n",
|
||
"\n",
|
||
"* Add a uniswap instance\n",
|
||
" * A next step to model the 1Hive ecosystem would be to model the Uniswap interface. With this interface, agents would be able to add or remove liquidity, buy or redeem Honey for more voting power, and ultimately enter or leave the system. \n",
|
||
"* Mixing of token holdings among participants\n",
|
||
" * Introducing heterogeneous token holdings would be another next step in creating a model more representative of the live system.\n",
|
||
"* Proposals which are good or no good together\n",
|
||
" * Introducing conflict \n",
|
||
"* Affects of outcomes on sentiment"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Simulation"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Configuration\n",
|
||
"Let's factor out into its own notebook where we review the config object and its partial state update blocks. We will initialize the network x object and pull out the simulation configuration, state_variables, and partial state update blocks from the [config.py](model/config.py)."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
|
||
" import pandas.util.testing as tm\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Params (config.py) : {'beta': 0.2, 'rho': 0.0025, 'alpha': 0.7937005259840998, 'gamma': 0.001, 'sensitivity': 0.75, 'tmin': 1, 'min_supp': 1, 'base_completion_rate': 45, 'base_failure_rate': 180, 'base_engagement_rate': 0.3, 'lowest_affinity_to_support': 0.3}\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from model import config\n",
|
||
"from model.parts.sys_params import initial_values\n",
|
||
"from model.parts.utils import *"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from copy import deepcopy\n",
|
||
"from cadCAD import configs\n",
|
||
"\n",
|
||
"# Initialize network x\n",
|
||
"for c in configs:\n",
|
||
" c.initial_state = deepcopy(c.initial_state)\n",
|
||
" c.initial_state['network'] = initialize_network(initial_values['n'],initial_values['m'],\n",
|
||
" initial_values['funds'],\n",
|
||
" initial_values['supply'],c.sim_config['M'])\n",
|
||
" \n",
|
||
"# pull out configurations to illustrate\n",
|
||
"sim_config,state_variables,partial_state_update_blocks = config.get_configs()\n",
|
||
"state_variables['network'] = c.initial_state['network']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"[{'policies': {'random': <function model.parts.system.driving_process(params, step, sL, s)>},\n",
|
||
" 'variables': {'network': <function model.parts.system.update_network(params, step, sL, s, _input)>,\n",
|
||
" 'effective_supply': <function model.parts.system.increment_supply(params, step, sL, s, _input)>}},\n",
|
||
" {'policies': {'random': <function model.parts.system.minting_rule(params, step, sL, s)>},\n",
|
||
" 'variables': {'total_supply': <function model.parts.system.mint_to_supply(params, step, sL, s, _input)>,\n",
|
||
" 'funds': <function model.parts.system.mint_to_funds(params, step, sL, s, _input)>}},\n",
|
||
" {'policies': {'completion': <function model.parts.participants.check_progress(params, step, sL, s)>},\n",
|
||
" 'variables': {'sentiment': <function model.parts.participants.update_sentiment_on_completion(params, step, sL, s, _input)>,\n",
|
||
" 'network': <function model.parts.participants.complete_proposal(params, step, sL, s, _input)>}},\n",
|
||
" {'policies': {'release': <function model.parts.proposals.trigger_function(params, step, sL, s)>},\n",
|
||
" 'variables': {'funds': <function model.parts.proposals.decrement_funds(params, step, sL, s, _input)>,\n",
|
||
" 'sentiment': <function model.parts.proposals.update_sentiment_on_release(params, step, sL, s, _input)>,\n",
|
||
" 'network': <function model.parts.proposals.update_proposals(params, step, sL, s, _input)>}},\n",
|
||
" {'policies': {'participants_act': <function model.parts.participants.participants_decisions(params, step, sL, s)>},\n",
|
||
" 'variables': {'network': <function model.parts.participants.update_tokens(params, step, sL, s, _input)>}},\n",
|
||
" {'policies': {'calculations': <function model.parts.metrics.kpi_calculations(params, step, sL, s)>},\n",
|
||
" 'variables': {'fractionOfSupplyForVoting': <function model.parts.metrics.kpi_fractionOfSupplyForVoting(params, step, sL, s, _input)>,\n",
|
||
" 'fractionOfSupplyInPool': <function model.parts.metrics.kpi_fractionOfSupplyInPool(params, step, sL, s, _input)>,\n",
|
||
" 'fractionOfProposalStages': <function model.parts.metrics.kpi_proposal_stages(params, step, sL, s, _input)>,\n",
|
||
" 'fractionOfFundStages': <function model.parts.metrics.kpi_fractionOfFundStages(params, step, sL, s, _input)>}}]"
|
||
]
|
||
},
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"partial_state_update_blocks"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Parameters\n",
|
||
"\n",
|
||
"Initial values are the starting values for the simulation."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'sentiment': 0.6, 'n': 30, 'm': 7, 'funds': 4867.21, 'supply': 22392.22}"
|
||
]
|
||
},
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"initial_values"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"$n$ is initial participants, whereas $m$ is initial proposals.\n",
|
||
"\n",
|
||
"Sim_config holds the global hyperparameters for the simulations"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"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}"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"sim_config[0]['M']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Initial state variable values"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'network': <networkx.classes.digraph.DiGraph at 0x7f40b11e4c90>,\n",
|
||
" 'funds': 4867.21,\n",
|
||
" 'sentiment': 0.6,\n",
|
||
" 'effective_supply': 14020.008000000002,\n",
|
||
" 'total_supply': 22392.22,\n",
|
||
" 'fractionOfSupplyForVoting': 0,\n",
|
||
" 'fractionOfSupplyInPool': 0,\n",
|
||
" 'fractionOfProposalStages': 0,\n",
|
||
" 'fractionOfFundStages': 0}"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"state_variables"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Hyperparameter explanations:\n",
|
||
"* $\\beta$ = .2 Upper bound on share of funds dispersed in the example Trigger Function\n",
|
||
"* $\\rho$ = 0.002 Scale Parameter for the example Trigger Function\n",
|
||
"* $\\alpha$ : 0.79370 timescale set in days with 3 day halflife\n",
|
||
"* $\\gamma$: 0.001 The expansion of supply per per day\n",
|
||
"* sensitivity of participant decisions to changes in affinity \n",
|
||
"* tmin = 1 unit days; minimum periods passed before a proposal can pass\n",
|
||
"* min_supp = 50 number of tokens that must be stake for a proposal to be a candidate\n",
|
||
"* base_completion_rate: 45, expected number of days to complete a proposals.\n",
|
||
"* base_failure_rate: 180, expected number of days until a proposal will fail\n",
|
||
"* base_engagement_rate: 0.3, probability of being active on a certain day \n",
|
||
"* lowest_affinity_to_support: 0.3, lowest affinity to required to support a proposal\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"#### Exploring the State Data Structure\n",
|
||
"\n",
|
||
"A graph is a type of temporal data structure that evolves over time. A graph $\\mathcal{G}(\\mathcal{V},\\mathcal{E})$ consists of vertices or nodes, $\\mathcal{V} = \\{1...\\mathcal{V}\\}$ and is connected by edges $\\mathcal{E} \\subseteq \\mathcal{V} \\times \\mathcal{V}$.\n",
|
||
"\n",
|
||
"See *Schema of the states* above for more details\n",
|
||
"\n",
|
||
"\n",
|
||
"Let's explore!"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# To explore our model prior to the simulation, we extract key components from our networkX object into lists.\n",
|
||
"proposals = get_nodes_by_type(state_variables['network'], 'proposal')\n",
|
||
"participants = get_nodes_by_type(state_variables['network'], 'participant')\n",
|
||
"supporters = get_edges_by_type(state_variables['network'], 'support')\n",
|
||
"influencers = get_edges_by_type(state_variables['network'], 'influence')\n",
|
||
"competitors = get_edges_by_type(state_variables['network'], 'conflict')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'type': 'participant',\n",
|
||
" 'holdings': 630.2817780891644,\n",
|
||
" 'sentiment': 0.5966804611949916}"
|
||
]
|
||
},
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"#sample a participant\n",
|
||
"state_variables['network'].nodes[participants[0]]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Count of Participants')"
|
||
]
|
||
},
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": "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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Let's look at the distribution of participant holdings at the start of the sim\n",
|
||
"plt.hist([ state_variables['network'].nodes[i]['holdings'] for i in participants])\n",
|
||
"plt.title('Histogram of Participants Token Holdings')\n",
|
||
"plt.xlabel('Amount of Honey')\n",
|
||
"plt.ylabel('Count of Participants')\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:563: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if not cb.iterable(width):\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:660: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if cb.iterable(node_size): # many node sizes\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0.5, 1.0, 'Participants Social Network')"
|
||
]
|
||
},
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"nx.draw_spring(state_variables['network'], nodelist = participants, edgelist=influencers)\n",
|
||
"plt.title('Participants Social Network')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'type': 'proposal',\n",
|
||
" 'conviction': 0,\n",
|
||
" 'status': 'candidate',\n",
|
||
" 'age': 0,\n",
|
||
" 'funds_requested': 2698.2388515058383,\n",
|
||
" 'trigger': inf}"
|
||
]
|
||
},
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"#lets look at proposals\n",
|
||
"state_variables['network'].nodes[proposals[0]]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Proposals initially start without any conviction, and with the status of a candidate. If the proposal's amount of conviction is greater than it's trigger, then the proposal moves to active and it's funds requested are granted. "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"All initial proposal start with 0 conviction and state 'candidate'we can simply examine the amounts of funds requested"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"funds_array = np.array([state_variables['network'].nodes[i]['funds_requested'] for i in proposals])\n",
|
||
"conviction_required = np.array([trigger_threshold(r, initial_values['funds'], initial_values['supply'], sim_config[0]['M']['alpha'],sim_config[0]['M']) for r in funds_array])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Amount of Honey requested(as a Fraction of Funds available)')"
|
||
]
|
||
},
|
||
"execution_count": 13,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.bar( proposals, funds_array/initial_values['funds'])\n",
|
||
"plt.title('Bar chart of Proposals Funds Requested')\n",
|
||
"plt.xlabel('Proposal identifier')\n",
|
||
"plt.ylabel('Amount of Honey requested(as a Fraction of Funds available)')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0, 0.5, 'Amount of Conviction')"
|
||
]
|
||
},
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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Iu7shFjMzW0FFrsL6XZWyiV2dcUQsBY4DbgYeAa6JiJmSxks6KFW7CFhP0hzgBKDtUt/jgK2A70makT4bdjUmMzMrrqNzINsB2wP9K86DrAus0R0zj4g/AX+qKPtervt14NNVxjsNOK07YjAzs3I6OgeyLXAAMIDlz4O8AvxHLYMyM7PG19E5kBuAGyTtGhH39GBMZmbWBIqcAzk2nbQGQNJASRfXMCYzM2sCRRLI+yPixbaeiHgB2LF2IZmZWTMokkD6SBrY1pPeRljkEShmZrYSK5IIzgbukXQt2bOwDgVOr2lUZmbW8Io8C+sySa1A2yPTD4mIhzsax8zMVn4d3QeybkS8nA5ZPQ1cmRs2KCIW90SAZmbWmDraA7mS7D6Q6WTPvmqj1L9lDeMyM7MG19F9IAekv93x3CszM1vJdHoVlqRJkkZLWrMnAjIzs+ZQ5DLes4GPAI9ImijpUEnd8iwsMzNrXkWuwroTuDO9w3wPsudgXUz2UEUzM+ulCt0QKKkf2QMVPwvsBFxay6DMzKzxdZpAJF0D7AzcBJwH3BkRb9c6MDMza2xF9kAuAkZHxLJaB2NmZs2jyDmQmyXtJmlYvn5EXFbDuMzMrMEVOYR1OTAcmAG07YUE4ARiZtaLFTmE1QKMiIjotKaZmfUaRe4DeQjYqNaBmJlZcymyB7I+8LCkqcAbbYURcVDNojIzs4ZXJIGMq3UQZmbWfArdiS5pMPChVDQ1Ip6tbVhmZtboijxM8TPAVODTwGeAeyUdWuvAzMyssRU5hHUy8KG2vQ5JGwC3ARNrGZiZmTW2Ildh9ak4ZLWo4HhmZrYSK7IHcpOkm4Hfpv7PAn+uXUhmZtYMipxEP0nSIcDuqWhCRFxf27DMzKzRtZtAJG0FDI6IuyPiOuC6VL67pOER8VhPBWlmZo2no3MZ5wIvVyl/KQ0zM7NerKMEMjgiHqwsTGXDahaRmZk1hY4SyIAOhvXrjplL2k/SLElzJI2tMnx1SVen4femR8q3DftOKp8lad/uiMfMzIrrKIG0SvqPykJJRwPTuzrj9I71nwP7AyOA0ZJGVFT7EvBCRGwFnAOcmcYdARwGbA/sB5yfpmdmZj2ko6uwjgeul3Q47yaMFmA14JPdMO+dgTkRMRdA0lXAKODhXJ1RvPssronAeZKUyq+KiDeAxyXNSdO7pxviMjOzAtpNIBHxDLCbpI8B70vFN0bE7d00702Bebn++cAu7dWJiKWSXgLWS+V/qxh302ozkXQMcAzA0KFDuyVwMzMrdh/IHcAdPRBLTUTEBGACQEtLi1+KZWbWTer5SJIFwGa5/iGprGodSX2B/mSPUikyrpmZ1VC7CUTS6jWe9zRga0lbSFqN7KT4pIo6k4AxqftQ4Pb0at1JwGHpKq0tgK3JnhhsZmY9pKM9kHsAJF1eixlHxFLgOOBm4BHgmoiYKWm8pLa3HV4ErJdOkp8AjE3jzgSuITvhfhPwtYhYVos4zcysOmUb9FUGSA8BPwBOBU6qHJ4eb9JUWlpaorW1td5hmJk1FUnTI6Klsryjk+jHAoeT3VB4YMWwID0by8zMeqeOLuP9K/BXSa0RcVEPxmRmZk2gyPtALpf0DeCjqf9O4BcR8VbtwjIzs0ZXJIGcD6ya/gIcAVwAHF2roMzMrPEVSSAfiogP5Ppvl/RArQIyM7PmUORGwmWShrf1SNoS8CWzZma9XJE9kJOAOyTNBQRsDhxV06jMzKzhFXkW1mRJWwPbpqJZ6Sm4ZmbWixXZAyEljL/XOBYzM2si9XyYopmZNTEnEDMzK6XTBCJpcpEyMzPrXdo9ByJpDWBNYH1JA8muwAJYl3be/mdmZr1HRyfRv0z2XvRNyN6J3pZAXgbOq3FcZmbW4Dp6mOJPgJ9I+npE/KwHYzIzsyZQ5D6Qn0naDRiWrx8Rl9UwLjMza3CdJpD0RsLhwAzefYRJAE4gZma9WJEbCVuAEdHeqwvNzKxXKnIfyEPARrUOxMzMmkuRPZD1gYclTQXeeQZWRBxUs6jMzKzhFUkg42odhJmZNZ8iV2Hd2ROBmJlZcylyFdYrZFddAaxG9nrbVyNi3VoGZmZmja3IHsg6bd2SBIwCPlzLoMzMrPGt0NN4I/N7YN8axWNmZk2iyCGsQ3K9fcjuC3m9ZhGZmVlTKHIV1oG57qXAE2SHsczMrBcrcg7kqJ4IxMzMmkuRF0oNkXS9pGfT53eShvREcGZm1riKnET/NTCJ7L0gmwB/SGVmZtaLFUkgG0TEryNiafpcAmzQlZlKGiTpVkmz09+B7dQbk+rMljQmla0p6UZJj0qaKemMrsRiZmblFEkgiyR9XtIq6fN5YFEX5zsWmBwRWwOTU/9yJA0CTgF2AXYGTsklmh9FxHbAjsC/Sdq/i/GYmdkKKpJAvgh8BngaWAgcCnT1xPoo4NLUfSlwcJU6+wK3RsTiiHgBuBXYLyJei4g7ACLiTeA+wOdkzMx6WJGrsJ4EuvvJu4MjYmHqfhoYXKXOpsC8XP/8VPYOSQPILjP+STfHZ2ZmnShyI+EWwNd57yttO0wqkm6j+ntETs73RERIWuGXVUnqC/wW+GlEzO2g3jHAMQBDhw5d0dmYmVk7itxI+HvgIrKrr94uOuGI2Ku9YZKekbRxRCyUtDHwbJVqC4CRuf4hwJRc/wRgdkSc20kcE1JdWlpa/FZFM7NuUiSBvB4RP+3m+U4CxgBnpL83VKlzM/CD3InzfYDvAEg6DegPHN3NcZmZWUFFTqL/RNIpknaVtFPbp4vzPQPYW9JsYK/Uj6QWSb8CiIjFwKnAtPQZHxGL002MJwMjgPskzZDkRGJm1sOK7IHsABwB7MG7h7Ai9ZcSEYuAPauUt5Lbq4iIi4GLK+rMB1R23mZm1j2KJJBPA1umS2bNzMyAYoewHgIG1DoQMzNrLkX2QAYAj0qaBrzRVtjZZbxmZrZyK5JATql5FGZm1nSK3Il+Z75f0u7AaODO6mOYmVlvUGQPBEk7Ap8jO6H+OPC7WgZlZmaNr90EImkbsj2N0cDzwNWAIuJjPRSbmZk1sI72QB4F7gIOiIg5AJK+2SNRmZlZw+voMt5DyB7ffoekCyXtiW/gMzOzpN0EEhG/j4jDgO2AO4DjgQ0lXSBpn54K0MzMGlOnNxJGxKsRcWVEHEj2RNz7gW/XPDIzM2toRe5Ef0dEvBAREyLiPc+xMjOz3mWFEoiZmVkbJxAzMyvFCcTMzEpxAjEzs1KcQMzMrBQnEDMzK8UJxMzMSnECMTOzUpxAzMysFCcQMzMrxQnEzMxKcQIxM7NSnEDMzKwUJxAzMyvFCcTMzEpxAjEzs1KcQMzMrBQnEDMzK8UJxMzMSqlLApE0SNKtkmanvwPbqTcm1ZktaUyV4ZMkPVT7iM3MrFK99kDGApMjYmtgcupfjqRBwCnALsDOwCn5RCPpEGBJz4RrZmaV6pVARgGXpu5LgYOr1NkXuDUiFkfEC8CtwH4AktYGTgBO64FYzcysinolkMERsTB1Pw0MrlJnU2Bern9+KgM4FTgbeK2zGUk6RlKrpNbnnnuuCyGbmVle31pNWNJtwEZVBp2c74mIkBQrMN0PAsMj4puShnVWPyImABMAWlpaCs/HzMw6VrMEEhF7tTdM0jOSNo6IhZI2Bp6tUm0BMDLXPwSYAuwKtEh6giz+DSVNiYiRmJlZj6nXIaxJQNtVVWOAG6rUuRnYR9LAdPJ8H+DmiLggIjaJiGHA7sA/nDzMzHpevRLIGcDekmYDe6V+JLVI+hVARCwmO9cxLX3GpzIzM2sAiug9pwVaWlqitbW13mGYmTUVSdMjoqWy3Heim5lZKU4gZmZWihOImZmV4gRiZmalOIGYmVkpTiBmZlaKE4iZmZXiBGJmZqU4gZiZWSlOIGZmVooTiJmZleIEYmZmpTiBmJlZKU4gZmZWihOImZmV4gRiZmalOIGYmVkpTiBmZlaKE4iZmZXiBGJmZqU4gZiZWSlOIGZmVooTiJmZleIEYmZmpSgi6h1Dj5H0HPBkveNYQesDz9c7iB7mNvcObnPz2DwiNqgs7FUJpBlJao2IlnrH0ZPc5t7BbW5+PoRlZmalOIGYmVkpTiCNb0K9A6gDt7l3cJubnM+BmJlZKd4DMTOzUpxAzMysFCeQBiBpkKRbJc1Ofwe2U29MqjNb0pgqwydJeqj2EXddV9osaU1JN0p6VNJMSWf0bPQrRtJ+kmZJmiNpbJXhq0u6Og2/V9Kw3LDvpPJZkvbtybi7omybJe0tabqkB9PfPXo69jK6so7T8KGSlkg6sadi7hYR4U+dP8BZwNjUPRY4s0qdQcDc9Hdg6h6YG34IcCXwUL3bU+s2A2sCH0t1VgPuAvavd5vaaecqwGPAlinWB4ARFXW+CvwidR8GXJ26R6T6qwNbpOmsUu821bjNOwKbpO73AQvq3Z5atjc3fCJwLXBivduzIh/vgTSGUcClqftS4OAqdfYFbo2IxRHxAnArsB+ApLWBE4DTeiDW7lK6zRHxWkTcARARbwL3AUN6IOYydgbmRMTcFOtVZG3Pyy+LicCekpTKr4qINyLicWBOml6jK93miLg/Ip5K5TOBfpJW75Goy+vKOkbSwcDjZO1tKk4gjWFwRCxM3U8Dg6vU2RSYl+ufn8oATgXOBl6rWYTdr6ttBkDSAOBAYHItguwGnbYhXycilgIvAesVHLcRdaXNeZ8C7ouIN2oUZ3cp3d608fdt4Ps9EGe361vvAHoLSbcBG1UZdHK+JyJCUuFrqyV9EBgeEd+sPK5ab7Vqc276fYHfAj+NiLnlorRGJGl74Exgn3rHUmPjgHMiYknaIWkqTiA9JCL2am+YpGckbRwRCyVtDDxbpdoCYGSufwgwBdgVaJH0BNn63FDSlIgYSZ3VsM1tJgCzI+Lcbgi3VhYAm+X6h6SyanXmp6TYH1hUcNxG1JU2I2kIcD3whYh4rPbhdllX2rsLcKiks4ABwNuSXo+I82ofdjeo90kYfwLghyx/QvmsKnUGkR0nHZg+jwODKuoMo3lOonepzWTne34H9Kl3WzppZ1+yk/9b8O4J1u0r6nyN5U+wXpO6t2f5k+hzaY6T6F1p84BU/5B6t6Mn2ltRZxxNdhK97gH4E5Ad+50MzAZuy/1ItgC/ytX7ItmJ1DnAUVWm00wJpHSbybbwAngEmJE+R9e7TR209ePAP8iu1Dk5lY0HDkrda5BdgTMHmApsmRv35DTeLBr0SrPubDPwXeDV3HqdAWxY7/bUch3nptF0CcSPMjEzs1J8FZaZmZXiBGJmZqU4gZiZWSlOIGZmVooTiJmZleIEYislScskzZD0kKRrJa1Z75jaSLpE0qFVysdLes/Nl5JGSvpjF+b33xX9/5Pr/mF6ovEPJR0r6Qtl52O9jy/jtZWSpCURsXbq/g0wPSJ+nBveN7JnEtUjtkuAP0bExIL1R5LdH3BAyfm9syyqDHuJ7B6cZSWmW7dlaI3BeyDWG9wFbJW25O+SNAl4WNIakn6d3j1xv6SPAUg6UtINkqak95Cc0jYhSSekvZqHJB2fytZK7yd5IJV/NpV/T9K0VDah7emr7cnvmaT3Szwq6T6yR/W31VlL0sWSpqaYR+Vivk7STSnms1L5GWRPtJ2REimSlqS/k4C1gemSPitpXNv7KCQNT9OanpbZdrkYfyHpXrJH8lsv5mdh2UotPXdof+CmVLQT8L6IeFzSt8ie5bhD+oG8RdI2qd7OZO+jeA2YJulGsrvfjyJ7fpGAeyXdSfYeiKci4hNpnv3TNM6LiPGp7HLgAOAPBWJeA7gQ2IPszuWrc4NPBm6PiC+mJxFPTQ+tBPgg2fs03gBmSfpZRIyVdFxEfLByPhFxUNo7+WCa77jc4AnAsRExW9IuwPkpHsieBLBbmb0WW7l4D8RWVv0kzQBagX8CF6XyqZG9WwNgd+AKgIh4FHgSaEsgt0bEooj4F3Bdqrs7cH1EvBoRS1L5R4AHgb0lnSnpIxHxUprGx5S9fe5Bsh/f7QvGvh3weETMjuwY8xW5YfsAY1PbppA9ImNoGjY5Il6KiNeBh4HNC85vOcoeMb4bcG2azy+BjXNVrnXyMPAeiK28/lW51Z2OIL1acPzKk4PtniyMiFSrdQEAAAFdSURBVH9I2onseUinSZpMdnjnfKAlIualrfs1Cs67IwI+FRGzlivM9hLy781YRvnvdx/gxWp7LUnRZWgrOe+BWG92F3A4QDp0NZTsoYWQ7VEMktSP7G2Jd6f6Byt7J/tawCeBuyRtArwWEVeQPWV4J95NFs+nLfr3XHXVgUeBYZKGp/7RuWE3A19vO58iaccC03tL0qpFZx4RLwOPS/p0mockfaDo+NZ7eA/EerPzgQvSIaalwJER8Ub6bZ5K9rj4IcAVEdEK71xBNTWN/6uIuF/SvsAPJb0NvAV8JSJelHQh8BDZGxenFQ0qIl6XdAxwo6TXyBLXOmnwqcC5wN8l9SF7xH1nV2dNSPXvi4jDC4ZxONmy+S6wKtlrWh8o2gbrHXwZr1kFSUeSHXo6rt6xmDUyH8IyM7NSvAdiZmaleA/EzMxKcQIxM7NSnEDMzKwUJxAzMyvFCcTMzEr5X/lYVVBlNA9pAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"plt.bar( proposals, conviction_required)\n",
|
||
"plt.title('Bar chart of Proposals Conviction Required')\n",
|
||
"plt.xlabel('Proposal identifier')\n",
|
||
"plt.ylabel('Amount of Conviction')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"Conviction is a concept that arises in the edges between participants and proposals in the initial conditions there are no votes yet so we can look at that later however, the voting choices are driven by underlying affinities which we can see now."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"Text(0.5, 55.73999999999998, 'Participant_id')"
|
||
]
|
||
},
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 1440x360 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"m = len(proposals)\n",
|
||
"n = len(participants)\n",
|
||
"\n",
|
||
"affinities = np.empty((n,m))\n",
|
||
"for i_ind in range(n):\n",
|
||
" for j_ind in range(m):\n",
|
||
" i = participants[i_ind]\n",
|
||
" j = proposals[j_ind]\n",
|
||
" affinities[i_ind][j_ind] = state_variables['network'].edges[(i,j)]['affinity']\n",
|
||
"\n",
|
||
"dims = (20, 5)\n",
|
||
"fig, ax = plt.subplots(figsize=dims)\n",
|
||
"\n",
|
||
"sns.heatmap(affinities.T,\n",
|
||
" xticklabels=participants,\n",
|
||
" yticklabels=proposals,\n",
|
||
" square=True,\n",
|
||
" cbar=True,\n",
|
||
" cmap = plt.cm.RdYlGn,\n",
|
||
" ax=ax)\n",
|
||
"\n",
|
||
"plt.title('Affinities between participants and proposals')\n",
|
||
"plt.ylabel('Proposal_id')\n",
|
||
"plt.xlabel('Participant_id')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Run simulation\n",
|
||
"\n",
|
||
"Now we will create the final system configuration, append the genesis states we created, and run our simulation."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from cadCAD.configuration import Experiment\n",
|
||
"\n",
|
||
"# Create configuration\n",
|
||
"exp = Experiment()\n",
|
||
"\n",
|
||
"exp.append_configs(\n",
|
||
" sim_configs=sim_config,\n",
|
||
" initial_state=state_variables,\n",
|
||
" seeds=1,\n",
|
||
" partial_state_update_blocks=partial_state_update_blocks\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"metadata": {
|
||
"tags": []
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"\n",
|
||
" ___________ ____\n",
|
||
" ________ __ ___/ / ____/ | / __ \\\n",
|
||
" / ___/ __` / __ / / / /| | / / / /\n",
|
||
"/ /__/ /_/ / /_/ / /___/ ___ |/ /_/ /\n",
|
||
"\\___/\\__,_/\\__,_/\\____/_/ |_/_____/\n",
|
||
"by cadCAD\n",
|
||
"\n",
|
||
"Execution Mode: local_proc\n",
|
||
"Configuration Count: 2\n",
|
||
"Dimensions of the first simulation: (Timesteps, Params, Runs, Vars) = (100, 11, 1, 9)\n",
|
||
"Execution Method: local_simulations\n",
|
||
"SimIDs : [0, 1]\n",
|
||
"SubsetIDs: [0, 0]\n",
|
||
"Ns : [0, 0]\n",
|
||
"ExpIDs : [0, 0]\n",
|
||
"Total execution time: 326.79s\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import numpy as np\n",
|
||
"import pandas as pd\n",
|
||
"from model import run\n",
|
||
"pd.options.display.float_format = '{:.2f}'.format\n",
|
||
"\n",
|
||
"%matplotlib inline\n",
|
||
"\n",
|
||
"rdf = run.run()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"After the simulation has run successfully, we perform some postprocessing to extract node and edge values from the network object and add as columns to the pandas dataframe. For the rdf, we take only the values at the last substep of each timestep in the simulation."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"df= run.postprocessing(rdf,0)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style scoped>\n",
|
||
" .dataframe tbody tr th:only-of-type {\n",
|
||
" vertical-align: middle;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>network</th>\n",
|
||
" <th>funds</th>\n",
|
||
" <th>sentiment</th>\n",
|
||
" <th>effective_supply</th>\n",
|
||
" <th>total_supply</th>\n",
|
||
" <th>fractionOfSupplyForVoting</th>\n",
|
||
" <th>fractionOfSupplyInPool</th>\n",
|
||
" <th>fractionOfProposalStages</th>\n",
|
||
" <th>fractionOfFundStages</th>\n",
|
||
" <th>simulation</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th>age_all</th>\n",
|
||
" <th>conviction_all</th>\n",
|
||
" <th>triggers_all</th>\n",
|
||
" <th>conviction_share_of_trigger_all</th>\n",
|
||
" <th>percentageOfActiveProposals</th>\n",
|
||
" <th>percentageOfCompletedProposals</th>\n",
|
||
" <th>percentageOfKilledProposals</th>\n",
|
||
" <th>percentageOfActiveFundsRequested</th>\n",
|
||
" <th>percentageOfCompletedFundsRequested</th>\n",
|
||
" <th>percentageOfKilledFundsRequested</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
|
||
" <td>4889.60</td>\n",
|
||
" <td>0.60</td>\n",
|
||
" <td>14020.01</td>\n",
|
||
" <td>22414.61</td>\n",
|
||
" <td>0.63</td>\n",
|
||
" <td>4.58</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[1, 1, 1, 1, 1, 1, 1]</td>\n",
|
||
" <td>[72.9628948739454, 0.0, 0.0, 237.1959249033470...</td>\n",
|
||
" <td>[inf, inf, inf, inf, inf, inf, inf]</td>\n",
|
||
" <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.43</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.38</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>12</th>\n",
|
||
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
|
||
" <td>4912.02</td>\n",
|
||
" <td>0.60</td>\n",
|
||
" <td>14020.01</td>\n",
|
||
" <td>22437.03</td>\n",
|
||
" <td>0.62</td>\n",
|
||
" <td>4.57</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[2, 2, 2, 2, 2, 2, 2]</td>\n",
|
||
" <td>[900.3097153802602, 0.0, 0.0, 425.458455260418...</td>\n",
|
||
" <td>[inf, nan, nan, inf, inf, nan, inf]</td>\n",
|
||
" <td>[0.0, nan, nan, 0.0, 0.0, nan, 0.0]</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.43</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.38</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</th>\n",
|
||
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
|
||
" <td>4934.45</td>\n",
|
||
" <td>0.60</td>\n",
|
||
" <td>14020.01</td>\n",
|
||
" <td>22459.46</td>\n",
|
||
" <td>0.62</td>\n",
|
||
" <td>4.55</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[3, 3, 3, 3, 3, 3, 3, 1, 1]</td>\n",
|
||
" <td>[1556.9753219873946, 0.0, 0.0, 810.60521531135...</td>\n",
|
||
" <td>[inf, nan, nan, inf, inf, nan, inf, 5563.19335...</td>\n",
|
||
" <td>[0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.217...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.44</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.38</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>24</th>\n",
|
||
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
|
||
" <td>4956.91</td>\n",
|
||
" <td>0.60</td>\n",
|
||
" <td>14240.84</td>\n",
|
||
" <td>22481.92</td>\n",
|
||
" <td>0.63</td>\n",
|
||
" <td>4.54</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[4, 4, 4, 4, 4, 4, 4, 2, 2, 1, 1]</td>\n",
|
||
" <td>[2078.1711593471455, 0.0, 0.0, 1058.8147525782...</td>\n",
|
||
" <td>[inf, nan, nan, inf, inf, nan, inf, nan, 4780....</td>\n",
|
||
" <td>[0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.436...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.36</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.38</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>30</th>\n",
|
||
" <td>(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...</td>\n",
|
||
" <td>4979.40</td>\n",
|
||
" <td>0.60</td>\n",
|
||
" <td>14240.84</td>\n",
|
||
" <td>22504.41</td>\n",
|
||
" <td>0.63</td>\n",
|
||
" <td>4.52</td>\n",
|
||
" <td>{'percentageOfActive': 0.0, 'percentageOfCompl...</td>\n",
|
||
" <td>{'percentageOfActiveFundsRequested': 0.0, 'per...</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>[5, 5, 5, 5, 5, 5, 5, 3, 3, 2, 2, 1]</td>\n",
|
||
" <td>[2491.844569600303, 0.0, 0.0, 1249.12643758267...</td>\n",
|
||
" <td>[inf, nan, nan, inf, inf, nan, inf, nan, 4853....</td>\n",
|
||
" <td>[0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.600...</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.42</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>0.38</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>5 rows × 43 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" network funds sentiment \\\n",
|
||
"6 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4889.60 0.60 \n",
|
||
"12 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4912.02 0.60 \n",
|
||
"18 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4934.45 0.60 \n",
|
||
"24 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4956.91 0.60 \n",
|
||
"30 (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,... 4979.40 0.60 \n",
|
||
"\n",
|
||
" effective_supply total_supply fractionOfSupplyForVoting \\\n",
|
||
"6 14020.01 22414.61 0.63 \n",
|
||
"12 14020.01 22437.03 0.62 \n",
|
||
"18 14020.01 22459.46 0.62 \n",
|
||
"24 14240.84 22481.92 0.63 \n",
|
||
"30 14240.84 22504.41 0.63 \n",
|
||
"\n",
|
||
" fractionOfSupplyInPool fractionOfProposalStages \\\n",
|
||
"6 4.58 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"12 4.57 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"18 4.55 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"24 4.54 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"30 4.52 {'percentageOfActive': 0.0, 'percentageOfCompl... \n",
|
||
"\n",
|
||
" fractionOfFundStages simulation ... \\\n",
|
||
"6 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"12 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"18 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"24 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"30 {'percentageOfActiveFundsRequested': 0.0, 'per... 0 ... \n",
|
||
"\n",
|
||
" age_all \\\n",
|
||
"6 [1, 1, 1, 1, 1, 1, 1] \n",
|
||
"12 [2, 2, 2, 2, 2, 2, 2] \n",
|
||
"18 [3, 3, 3, 3, 3, 3, 3, 1, 1] \n",
|
||
"24 [4, 4, 4, 4, 4, 4, 4, 2, 2, 1, 1] \n",
|
||
"30 [5, 5, 5, 5, 5, 5, 5, 3, 3, 2, 2, 1] \n",
|
||
"\n",
|
||
" conviction_all \\\n",
|
||
"6 [72.9628948739454, 0.0, 0.0, 237.1959249033470... \n",
|
||
"12 [900.3097153802602, 0.0, 0.0, 425.458455260418... \n",
|
||
"18 [1556.9753219873946, 0.0, 0.0, 810.60521531135... \n",
|
||
"24 [2078.1711593471455, 0.0, 0.0, 1058.8147525782... \n",
|
||
"30 [2491.844569600303, 0.0, 0.0, 1249.12643758267... \n",
|
||
"\n",
|
||
" triggers_all \\\n",
|
||
"6 [inf, inf, inf, inf, inf, inf, inf] \n",
|
||
"12 [inf, nan, nan, inf, inf, nan, inf] \n",
|
||
"18 [inf, nan, nan, inf, inf, nan, inf, 5563.19335... \n",
|
||
"24 [inf, nan, nan, inf, inf, nan, inf, nan, 4780.... \n",
|
||
"30 [inf, nan, nan, inf, inf, nan, inf, nan, 4853.... \n",
|
||
"\n",
|
||
" conviction_share_of_trigger_all \\\n",
|
||
"6 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] \n",
|
||
"12 [0.0, nan, nan, 0.0, 0.0, nan, 0.0] \n",
|
||
"18 [0.0, nan, nan, 0.0, 0.0, nan, 0.0, 0.0, 0.217... \n",
|
||
"24 [0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.436... \n",
|
||
"30 [0.0, nan, nan, 0.0, 0.0, nan, 0.0, nan, 0.600... \n",
|
||
"\n",
|
||
" percentageOfActiveProposals percentageOfCompletedProposals \\\n",
|
||
"6 0.00 0.00 \n",
|
||
"12 0.00 0.00 \n",
|
||
"18 0.00 0.00 \n",
|
||
"24 0.00 0.00 \n",
|
||
"30 0.00 0.00 \n",
|
||
"\n",
|
||
" percentageOfKilledProposals percentageOfActiveFundsRequested \\\n",
|
||
"6 0.43 0.00 \n",
|
||
"12 0.43 0.00 \n",
|
||
"18 0.44 0.00 \n",
|
||
"24 0.36 0.00 \n",
|
||
"30 0.42 0.00 \n",
|
||
"\n",
|
||
" percentageOfCompletedFundsRequested percentageOfKilledFundsRequested \n",
|
||
"6 0.00 0.38 \n",
|
||
"12 0.00 0.38 \n",
|
||
"18 0.00 0.38 \n",
|
||
"24 0.00 0.38 \n",
|
||
"30 0.00 0.38 \n",
|
||
"\n",
|
||
"[5 rows x 43 columns]"
|
||
]
|
||
},
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.head(5)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40cb39b4d0>"
|
||
]
|
||
},
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep','sentiment')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The above plot demonstrates system sentiment changing over time as proposals pass or fail."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40ca3aa4d0>"
|
||
]
|
||
},
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['funds', 'candidate_funds'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"In the above graph, funds represent the total available funds, whereas candidate funds represent total funds requested by candidate proposals."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 612x792 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"affinities_plot(df)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The above matrix represents participant affinities towards proposals, ranging from -1 to +1."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.legend.Legend at 0x7f40ca2fc5d0>"
|
||
]
|
||
},
|
||
"execution_count": 23,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot(x='timestep',y=['candidate_count','active_count','completed_count', 'killed_count', 'failed_count'],\n",
|
||
" kind='area')\n",
|
||
"plt.title('Proposal Status')\n",
|
||
"plt.ylabel('count of proposals')\n",
|
||
"plt.legend(ncol = 3,loc='upper center', bbox_to_anchor=(0.5, -0.15))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The above graph shows the number of various types of proposals at a range of timesteps. Ecosystems with more completed proposals will have higher overall agent sentiment than systems with more failed and killed proposals."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.legend.Legend at 0x7f406c7d8150>"
|
||
]
|
||
},
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot(x='timestep',y=['candidate_funds','active_funds','completed_funds', 'killed_funds', 'failed_funds'], kind='area')\n",
|
||
"plt.title('Proposal Status weighted by funds requested')\n",
|
||
"plt.ylabel('Funds worth of proposals')\n",
|
||
"plt.legend(ncol = 3,loc='upper center', bbox_to_anchor=(0.5, -0.15))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"The above graph shows the amount of funds requested by various types of proposals at a range of timesteps."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"nets = df.network.values"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:563: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if not cb.iterable(width):\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:569: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" and cb.iterable(edge_color) \\\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:579: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" for c in edge_color]):\n",
|
||
"/home/aclarkdata/anaconda3/lib/python3.7/site-packages/networkx/drawing/nx_pylab.py:660: MatplotlibDeprecationWarning: \n",
|
||
"The iterable function was deprecated in Matplotlib 3.1 and will be removed in 3.3. Use np.iterable instead.\n",
|
||
" if cb.iterable(node_size): # many node sizes\n",
|
||
"/home/aclarkdata/repos/Aragon_Conviction_Voting/models/v3/model/parts/utils.py:356: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
|
||
" plt.tight_layout()\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"K = 0\n",
|
||
"N = 1\n",
|
||
"\n",
|
||
"snap_plot(nets[K:N], size_scale = 1/300,savefigs=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"On the left side are participants, with the right side of the graph being the proposals. With this graph, we can see the links between the participants and the proposals that they support. The percentage on the right hand are the the amount of the required amount to pass that has been fulfilled.\n",
|
||
"\n",
|
||
"You can move the K and N to different points within the 100 timesteps, 0 indexed, to see how the model evolves overtime. \n",
|
||
"\n",
|
||
"As you can see with the plot above at the start of the simulation, no proposals have been formally supported yet. Below we can see a many interactions between agents and proposals."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"snap_plot(nets[80:81], size_scale = 1/300,savefigs=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40a721b110>"
|
||
]
|
||
},
|
||
"execution_count": 28,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['total_supply','funds'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40a6ecd850>"
|
||
]
|
||
},
|
||
"execution_count": 29,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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LziAZdFfNIGkoGYjIEbZU1AyUDJJGrcnAzKab2VYzWx4Rm2xmm8xscfi6JIyPNLOFZrYs/HlhxDFDw/gqM3vULHhI3Mw6mdmbZvZF+LNjQ9yoiNRdQcl+UlOMTm1axLoo0kjqUjOYAYyuJv6wu2eHr4rlLIuAb7j76QSL2/9PxP5TgeuA/uGr4px3AG+5e3/grfC9iMTQlpJSurVrhcXLxD7S4GpNBu7+LlCnJ0/c/RN33xy+XQGkmVlLM+sJtHf3j9zdgWeAy8L9xgBPh78/HREXkRgp2Fkat4uwSMM4nj6Dm8xsadiMVF3TzreARe6+H+gN5EVsywtjAN3dPT/8vQDofhxlEpF6sKWkVP0FSSbaZDAV6AdkA/nAbyM3mtlA4EHgB8dy0rDWUONKFGY2ycxyzSy3sLDwmAstIrVzdwpKSjWSKMlElQzcfYu7l7l7OfAUMKxim5llAK8A4919dRjeBGREnCIjjAFsCZuRCH9uPcp1n3T3HHfP6dq1azRFF5Fa7Np/iL0HyvSMQZKJKhlU/PEOXQ4sD+MdgNeAO9z9/YodwmagEjM7OxxFNB6YHW6eQ9DZTPizIi4iMVCxfKRqBsml1rmJzOw5YATQxczygHuAEWaWTdCks45/NwfdBJwE3G1md4exUe6+FbiBYGRSGvBG+AJ4AJhlZhOB9cCVx31XIhK1gp37ASWDZFNrMnD3cdWEp9Ww733AfTVsywUGVRMvBi6qrRwi0jgK9MBZUtITyCJymMqnjzW0NKkoGYjIYQp2lpKelkqrVK1NnEyUDETkMAV6xiApKRmIyGG2lJTSXU1ESUfJQEQOEzx9rGcMko2SgYhUOlRWTuGu/RpWmoSUDESkUtHuA5S7njFIRkoGIlJJzxgkLyUDEalUsFPPGCQrJQMRqbRF8xIlLSUDEalUUFJK82ZGZy13mXSUDESkUrDcZUuaNdNyl8lGyUBEKumBs+RV66ylIhJ/Fm3Yzo+eX8zBQ+X1et7C3fv56mlaeTYZKRmINEEfrCpiffFexg7NoL4bdK7I6VPPZ5SmQMlApAnauG0fXdq2ZMoVQ2JdFEkQ6jMQaYI2bt9Ln05psS6GJJBak4GZTTezrWa2PCI22cw2mdni8HVJxLY7zWyVmX1uZhdHxEeHsVVmdkdEPMvMPg7jz5uZxrSJ1CJv+z4yOraOdTEkgdSlZjADGF1N/GF3zw5frwOY2QDgamBgeMwTZpZiZinA48DXgAHAuHBfgAfDc50EbAcmHs8NiSS6snJn84599OmomoHUn1qTgbu/C2yr4/nGADPdfb+7rwVWAcPC1yp3X+PuB4CZwBgzM+BC4MXw+KeBy47xHkSSSkFJKYfKXTUDqVfH02dwk5ktDZuROoax3sDGiH3ywlhN8c7ADnc/VCUuIjXYuG0vgPoMpF5FmwymAv2AbCAf+G29legozGySmeWaWW5hYWFjXFIk7lQkA9UMpD5FlQzcfYu7l7l7OfAUQTMQwCYgcpByRhirKV4MdDCz5lXiNV33SXfPcfecrl27RlN0kSYvb/s+zKBXBz0pLPUnqmRgZj0j3l4OVIw0mgNcbWYtzSwL6A/MBxYA/cORQy0IOpnnuLsD84Cx4fETgNnRlEkkWWzcvpce7VvRsnlKrIsiCaTWh87M7DlgBNDFzPKAe4ARZpYNOLAO+AGAu68ws1nAp8Ah4EZ3LwvPcxMwF0gBprv7ivAStwMzzew+4BNgWr3dnUgCCoaVqr9A6letycDdx1UTrvEPtrvfD9xfTfx14PVq4mv4dzOTiNQib9tezj6xc6yLIQlGTyCLNCEHDpVTUFKqmoHUOyUDkSYkf+c+yh0yOmkkkdQvJQORJmTjtn0AqhlIvVMyEGlC8raHD5zpGQOpZ0oGIk3Ixu17SWlm9NRqZFLPlAxEmpC87fvomd6K5in6X1fql/5FiTQhG7ftVRORNAglA5EmRA+cSUNRMhBpIkoPlrF11376aFipNAAlA5EmIm+7hpVKw1EyEGkiKoeVqmYgDaDWuYlEpOH95ZNNvPJJjbO3A7ClpBTQMwbSMJQMRGJsWd5OfvLCEnp2aEWnNi1r3K9lagrfGNKLbu1q3kckWkoGIjFUerCM/3z+E7q0bcmrN51HeuvUWBdJkpSSgUgMPfjXz1hduIf/mThMiUBiSh3IIjHy3hdF/On9dVzz5UzO669lXCW2lAxEYqC83Ll7znJO7NKG20efGuviiNQtGZjZdDPbambLq9l2q5m5mXUJ36eb2f+Z2RIzW2Fm10bsO8HMvghfEyLiQ81smZmtMrNHzczq4+ZE4tXbn21lTeEebvlqf9JaaC1jib261gxmAKOrBs2sDzAK2BARvhH41N2HEKyd/Fsza2FmnQjWTx5OsMzlPWbWMTxmKnAd0D98HXEtkUTy1D/X0LtDGpec3jPWRREB6pgM3P1dYFs1mx4GbgM8cnegXfjtvm143CHgYuBNd9/m7tuBN4HRZtYTaO/uH7m7A88Al0V7QyLxblneTj5eu41rz8kkVbOPSpyIejSRmY0BNrn7kiqtOr8H5gCbgXbAVe5ebma9gY0R++UBvcNXXjVxkYT01D/X0K5lc646q0+siyJSKaqvJWbWGvgZcHc1my8GFgO9gGzg92bWPuoSHn7dSWaWa2a5hYWF9XFKkUa1acc+XluWz9XD+tCulYaSSvyItmbQD8gCKmoFGcAiMxsGXAs8EDb5rDKztcCpwCaCPoQKGcA7YTyjSrza5/Ld/UngSYCcnByvbh+R+rBtzwFeW5bPwUPl9XreD9cUA3DNOVn1el6R4xVVMnD3ZUC3ivdmtg7IcfciM9sAXAT808y6A6cAa4BVwK8iOo1HAXe6+zYzKzGzs4GPgfHAY9HekMjxevPTLdz58lKKdh9okPOPHZpB7w6aeVTiS52SgZk9R/CtvouZ5QH3uPu0Gna/F5hhZssAA25396LwPPcCC8L9funuFZ3SNxCMWEoD3ghfIo1q9/5D3DN7BS8tymNAz/b86Zph9G2AGULbp+nBf4k/FrTmND05OTmem5sb62JIgth/qIwJ0+ezYN12bhzRj5su7E+L5hrpI4nHzBa6e07VuL6iSNIrL3d+PGsJH63ZxiNXZzMmW4PZJPnoq48kNXfn3tc+5bWl+fz8ktOUCCRpqWYgSeeZD9fx+7dX4QTJoGj3Ab53ThbfP08jfCR5KRlIUtl3oIzf/f0LurZtyZknBAPbMju35rrzTkRTYkkyUzKQpPLSojy27TnA1O+cyfATO8e6OCJxQ30GkjTKy51p761lcEY6w7I6xbo4InFFyUCSxt9XbmFt0R41CYlUQ8lAkkbFtNFfG9Qj1kURiTtKBpIUPtmwnQXrtvO9c7NormmjRY6gDmRJKC8vyuPjNcEsJ45TvPsAqwt3s2HbXtq10rTRIjVRMpCE8dz8Ddz58jI6tWlBi/Dbf3paKgN7pXPpkF6MGtiDti31T16kOvo/QxLC31YU8PNXljHilK48NT5HK4iJHCMlA2lQZeXO5wW7KG/ACRHztu/jlpmfcHpGB574zplKBCJRUDKQBjXjg3Xc++qnDX6dE7u04U/XnEXrFvonLRIN/Z8jDWplfgmd27TggW8NbtDrDMvsRHprLSMpEi0lA2lQ64v30K9bW0YO6B7roojIUahxVRrUuuK9ZHau/9XCRKR+1ZoMzGy6mW01s+XVbLvVzNzMukTERpjZYjNbYWb/iIiPNrPPzWyVmd0REc8ys4/D+PNm1qI+bkxib8/+QxTu2s8JndvEuigiUou61AxmAKOrBs2sD8Gi9hsiYh2AJ4BL3X0gcEUYTwEeB74GDADGmdmA8LAHgYfd/SRgOzAx2puR+LK+eC8AmUoGInGv1mTg7u8C26rZ9DBwGxA5ZvDbwMvuviE8dmsYHwascvc17n4AmAmMsWC2sAuBF8P9ngYui+ZGJP6sL94DwAlqJhKJe1H1GZjZGGCTuy+psulkoKOZvWNmC81sfBjvDWyM2C8vjHUGdrj7oSpxSQBrw2SQ2UU1A5F4d8yjicysNfAzgiai6s43FLgISAM+NLOPjquEh197EjAJoG/fvvV1Wmkg64v20qVtS00BIdIERFMz6AdkAUvMbB2QASwysx4E3+znuvsedy8C3gWGAJuAyBnCMsJYMdDBzJpXiVfL3Z909xx3z+natWsURZfGtK54j0YSiTQRx5wM3H2Zu3dz90x3zyRIAGe6ewEwGzjXzJqHNYjhwEpgAdA/HDnUArgamOPuDswDxoannxCeQxLA+uK9Gkkk0kTUZWjpc8CHwClmlmdmNY72cfeVwF+BpcB84I/uvjzsE7gJmEuQHGa5+4rwsNuBH5vZKoI+hGnHc0MSH/YdKKOgpFQ1A5EmotbGXHcfV8v2zCrvHwIeqma/14HXq4mvIRhtJAlkw7ZgWOkJ6jwWaRL0BLI0iHUVI4lUMxBpEpQMpEGsK6p4xkA1A5GmQMlAGsS64r10atOC9DTNJCrSFCgZSINYX7xHTx6LNCFKBtIg1hfv1ZxEIk2IkoHUu9KDZWzeuU81A5EmRMlA6l3e9r24a7ZSkaZEyUDq3dqicOpqPWMg0mRoBrEk99flBWwpKa3Xc85fG8x4rmcMRJoOJYMktrZoD9c/u7BBzp3ZuTUdWmvROpGmQskgib23qgiAOTedQ0bH+v0W36ZlSr2eT0QalpJBEnv/iyJ6d0jj9N7pBIvOiUiyUgdykiordz5YXcQ5J3VWIhARJYNktXzTTkpKD3HOSV1iXRQRiQNKBkmqor/gy/2UDEREySBpvb+qiFN7tKNru5axLoqIxAElgyS070AZueu2c66aiEQkVKdkYGbTzWyrmS2vZtutZuZm1qVK/CwzO2RmYyNiE8zsi/A1ISI+1MyWmdkqM3vU1KPZoHLXb+NAWTnn9FcyEJFAXWsGM4DRVYNm1gcYBWyoEk8BHgT+FhHrBNwDDCdY5vIeM+sYbp4KXAf0D19HXEvqz3urikhNMYZndYp1UUQkTtQpGbj7u8C2ajY9DNwGeJX4D4GXgK0RsYuBN919m7tvB94ERptZT6C9u3/k7g48A1x2bLchx+L9VUWc2bcjrVvoMRMRCUT918DMxgCb3H1JZKuOmfUGLgcuAM6KOKQ3sDHifV4Y6x3+XjWe0O58eRnz1xbH5NqrC/dw68iTY3JtEYlPUSUDM2sN/Iygiaiq3wG3u3t5fTf9m9kkYBJA37596/XcjWn/oTJm5W6kf7e29OvWttGvPzijA98cmtHo1xWR+BVtzaAfkAVU1AoygEVmNgzIAWaG8S7AJWZ2CNgEjIg4RwbwThjPqBLfVN1F3f1J4EmAnJycqk1TTcbqrXsoK3duuOAkLh3SK9bFERGJLhm4+zKgW8V7M1sH5Lh7EUGSqIjPAF5197+EHci/iug0HgXc6e7bzKzEzM4GPgbGA49FU66m4vMtJQCc2qNdjEsiIhKo69DS54APgVPMLM/MJh7rhdx9G3AvsCB8/TKMAdwA/BFYBawG3jjW8zclnxXsIjXFyNLiLyISJ+pUM3D3cbVsz6whfk2V99OB6dXslwsMqktZEsHnBbvo17UtqSl65k9E4oP+GsXA5wW71EQkInFFyaCR7dx7kPydpZzSo32siyIiUknJoJF9VqDOYxGJP0oGjezzLbsAOEXJQETiiJJBI/usYBftWjWnZ3qrWBdFRKSSkkEjq+g81sSsIhJPlAwakbvzr4JdaiISkbijZNCINu3Yx679hzSSSETijpJBI/q8IOg81kgiEYk3SgaN6LMwGZzcXclAROKLkkEj+rxgF73SW5GelhrrooiIHEZLXR2H8nJny65S8rbvY/OOfZSVH31W7U82blfnsYjEJSWDOnJ3pr23lkf+/gX7y8oBKCv3WhNAVVcO7dMQxRMROS5KBnVQerCMO19exiufbOIrJ3fltJ7BaKCUZtAjPY0+HdPo3SGNFs2P3urWzIzeHdIao8giIsdEyaAaW0pKeXFhHuXht/65nxawfFMJt448mZsuPEkPjIlIwlEyqMazH63nsbdXVb5PT0vlqfE5jBzQPYalEhFpOEoG1di8o5Qe7Vvx3u0XAEHzTrNmqg2ISOKqdWipmU03s61mtryabZYDYJwAAArtSURBVLeamZtZl/D9d8xsqZktM7MPzGxIxL6jzexzM1tlZndExLPM7OMw/ryZtaivm4vWlpJSeqS3onlKM5qnNFMiEJGEV5fnDGYAo6sGzawPwaL2GyLCa4GvuPvpBOsdPxnumwI8DnwNGACMM7MB4TEPAg+7+0nAduCY11eub/k792lWURFJKrUmA3d/F9hWzaaHgdsAj9j3A3ffHr79CMgIfx8GrHL3Ne5+AJgJjLGgJ/ZC4MVwv6eBy6K5kfq0pWQ/3dsrGYhI8ojqCWQzGwNscvclR9ltIvBG+HtvYGPEtrww1hnY4e6HqsRjZlfpQXbvP0QP1QxEJIkccweymbUGfkbQRFTTPhcQJINzoy9ateedBEwC6Nu3b32eutKWklIANROJSFKJpmbQD8gClpjZOoKmoEVm1gPAzAYDfwTGuHtxeMwmIPLR24wwVgx0MLPmVeLVcvcn3T3H3XO6du0aRdFrV7BzP4CaiUQkqRxzMnD3Ze7ezd0z3T2ToGnnTHcvMLO+wMvAd939XxGHLQD6hyOHWgBXA3Pc3YF5wNhwvwnA7OO4n+OWv3MfoJqBiCSXugwtfQ74EDjFzPLM7Gijfe4m6Ad4wswWm1kuQNgncBMwF1gJzHL3FeExtwM/NrNV4bHTor6belDRTKSagYgkk1r7DNx9XC3bMyN+/z7w/Rr2ex14vZr4GoLRRnEhf2cpHVun0io1JdZFERFpNFrPoIotJaWqFYhI0lEyqCJ/Z6n6C0Qk6SgZVFExFYWISDJRMoiw/1AZRbsP0KO91hwQkeSiZBBha0nwjEGP9JYxLomISONSMohQEA4r7ZGumoGIJBclgwgFO8NkoNFEIpJklAwibKmsGSgZiEhyUTKIkL+zlLTUFNq30gJwIpJclAwiFJQEzxhowXsRSTZKBhEKdurpYxFJTkoGEQr09LGIJCklg1B5uQfzEikZiEgSUjIIFe85wKFyV81ARJKSkkGo4hkD9RmISDJSMggVaO1jEUliSgahyqkoVDMQkSRUp6erzGw68HVgq7sPqrLtVmAK0NXdiywYpP8IcAmwF7jG3ReF+04A/l946H3u/nQYHwrMANIIVkO7JVwfud79/JVlzF+77Yj4tj0HSGlmdG6rSepEJPnU9VHbGcDvgWcig2bWBxgFbIgIfw3oH76GA1OB4WbWCbgHyAEcWGhmc9x9e7jPdcDHBMlgNPBGdLd0dL06pNG/e9tqtw3slU5KMz1wJiLJp07JwN3fNbPMajY9DNwGzI6IjQGeCb/Zf2RmHcysJzACeNPdtwGY2ZvAaDN7B2jv7h+F8WeAy2igZHDjBSc1xGlFRJq0qPsMzGwMsMndl1TZ1BvYGPE+L4wdLZ5XTVxERBpJVDOymVlr4GcETUSNxswmAZMA+vbt25iXFhFJaNHWDPoBWcASM1sHZACLzKwHsAnoE7FvRhg7WjyjmvgR3P1Jd89x95yuXbtGWXQREakqqmTg7svcvZu7Z7p7JkHTzpnuXgDMAcZb4Gxgp7vnA3OBUWbW0cw6EtQq5obbSszs7HAk0ngO74MQEZEGVqdkYGbPAR8Cp5hZnplNPMrurwNrgFXAU8ANAGHH8b3AgvD1y4rO5HCfP4bHrKaBOo9FRKR61kDD+RtcTk6O5+bmxroYIiJNipktdPecqnE9gSwiIkoGIiLShJuJzKwQWH8Mh3QBihqoOPEqGe8ZkvO+k/GeITnv+3jv+QR3P2I4ZpNNBsfKzHKraydLZMl4z5Cc952M9wzJed8Ndc9qJhIRESUDERFJrmTwZKwLEAPJeM+QnPedjPcMyXnfDXLPSdNnICIiNUummoGIiNQg4ZOBmY02s8/NbJWZ3RHr8jQUM+tjZvPM7FMzW2Fmt4TxTmb2ppl9Ef7sGOuy1jczSzGzT8zs1fB9lpl9HH7mz5tZi1iXsb6F64S8aGafmdlKM/tSon/WZvaj8N/2cjN7zsxaJeJnbWbTzWyrmS2PiFX72YZzwD0a3v9SMzsz2usmdDIwsxTgcYLV1wYA48xsQGxL1WAOAbe6+wDgbODG8F7vAN5y9/7AW+H7RHMLsDLi/YPAw+5+ErAdONpcWk3VI8Bf3f1UYAjB/SfsZ21mvYGbgZxw6d0U4GoS87OeQbDaY6SaPtvIlSUnEawaGZWETgbAMGCVu69x9wPATIKV2BKOu+dXrDXt7rsI/jj0Jrjfp8PdniZYRS5hmFkG8B8EEx0Sznx7IfBiuEsi3nM6cD4wDcDdD7j7DhL8syZYfyXNzJoDrYF8EvCzdvd3gaoLtdf02VauLBmuFlmxsuQxS/RkUNPqagktXKL0DII1pbuH04QDFADdY1SshvI7gqVXy8P3nYEd7n4ofJ+In3kWUAj8KWwe+6OZtSGBP2t33wRMIVhvPR/YCSwk8T/rCjV9tvX2Ny7Rk0HSMbO2wEvAf7p7SeS2cF3qhBk+ZmZfB7a6+8JYl6WRNQfOBKa6+xnAHqo0CSXgZ92R4FtwFtALaMORTSlJoaE+20RPBjWtrpaQzCyVIBH82d1fDsNbKqqN4c+tsSpfAzgHuDRcbW8mQZPBIwRV5YolXRPxM88D8tz94/D9iwTJIZE/668Ca9290N0PAi8TfP6J/llXqOmzrbe/cYmeDBYA/cMRBy0IOpzmxLhMDSJsK58GrHT3/4rYNAeYEP4+gQRaRc7d73T3jHC1vauBt939O8A8YGy4W0LdM0C4ouBGMzslDF0EfEoCf9YEzUNnm1nr8N96xT0n9GcdoabPtqaVJY+duyf0C7gE+BfBCmo/j3V5GvA+zyWoOi4FFoevSwja0N8CvgD+DnSKdVkb6P5HAK+Gv58IzCdYOe8FoGWsy9cA95sN5Iaf91+Ajon+WQO/AD4DlgP/A7RMxM8aeI6gX+QgQS1wYk2fLWAEIyZXA8sIRltFdV09gSwiIgnfTCQiInWgZCAiIkoGIiKiZCAiIigZiIgISgaSxMKZP28If+9lZi/WdsxxXCvbzC5pqPOLHC8lA0lmHYAbANx9s7uPrWX/45FN8NyHSFzScwaStMysYhbbzwke5jnN3QeZ2TUEs0K2IZgaeArQAvgusB+4xN23mVk/ggd+ugJ7gevc/TMzuwK4BygjmFDtqwQPRaURTBXwa+BV4DFgEJAKTHb32eG1LwfSCSYce9bdf9HA/ylEaF77LiIJ6w5gkLtnhzO9vhqxbRDBzK+tCP6Q3+7uZ5jZw8B4gtlSnwSud/cvzGw48ATB/Eh3Axe7+yYz6+DuB8zsboKnQ28CMLNfEUyf8T0z6wDMN7O/h9ceFl5/L7DAzF5z99yG/A8homQgUr15HqwLscvMdgL/F8aXAYPD2WG/DLwQTJUDBNMjALwPzDCzWQQTqlVnFMEkez8J37cC+oa/v+nuxQBm9jLBVCNKBtKglAxEqrc/4vfyiPflBP/fNCOYSz+76oHufn1YU/gPYKGZDa3m/AZ8y90/PywYHFe17VZtudLg1IEsyWwX0C6aAz1YK2Jt2D9QsRbtkPD3fu7+sbvfTbAITZ9qrjUX+GE4AydmdkbEtpHhmrdpBH0X70dTRpFjoWQgSStsink/XHj8oShO8R1gopktAVbw7yVVHzKzZeF5PwCWEEy1PMDMFpvZVcC9BB3HS81sRfi+wnyCdSmWAi+pv0Aag0YTicSRcDRRZUezSGNRzUBERFQzEBER1QxERAQlAxERQclARERQMhAREZQMREQEJQMREQH+P3tSJQYTD4HEAAAAAElFTkSuQmCC\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['effective_supply'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"As expected *effective_supply* is increasing with the arrival of new participants."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40a6b66590>"
|
||
]
|
||
},
|
||
"execution_count": 30,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['participant_count'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Review system health metrics\n",
|
||
"\n",
|
||
"Below we will analysis system health metrics, such as fraction of supply used for voting, which is effective supply over total supply and percentage of proposals and requested funds in different stages. "
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40a6b66c10>"
|
||
]
|
||
},
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['fractionOfSupplyForVoting'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40ec8d9650>"
|
||
]
|
||
},
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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f1uzHFc1LAl20GQ0NdDAGr0EpFpdrnz6XkkNXb9d6TcLl7GDHveN60dG9YjfFTp7O/GN8MJuPXmLLsUucvJRFYbEu67JYnckD/bnzyqAqfd9LlTbN/PenU8Sn5dbzCuuWkJHHC98f44HP91dpfhLWpV6BrpQ6o5Q6pJSKVEpFVLN9tlLqoGmfXUqpQc1fVCGaJiPXOFjIw6X+vXU7e7lw//hebDpyia3HjO3Txj7oLnW8s25/HdmDnr5uPLXuCPvOpQIVb4g2xuNT+qHRPPNt890g3R1jnBL6bHIOH2yPrmNvYUkNqaGP01qHaa2rzp8KMcAYrfUA4Gng/WYpnRDNqDE1dIA7RgUR5OvGU+uNN0hrGlTUUI72BhZPC+VcSg6v/HCcdk72ZXPDNFZAe1fuG2dciWn7ieYZoLc7Jhk3Rzsm9O/EO5Wan4R1aZYmF631Lq11qunpb0BAbfsLYQmNDXRHewOLp4ZyNjmHxRuOUFBUQrcO1Q84aqiRpnb6jLwi+vl7VJljpjHuvDKIwA6uPLWuat/1xtgdnUJ4oDdPTu2HQUn3SGtW30DXwI9Kqb1Kqbvq2Pd24PvqNiil7lJKRSilImR4v2hpjQ10gFHBxuD9bLdxZaPmqKGXemxyCO2c7Bnc3avunevByd6Op6YaBzaV9l1vrOSsfE4mZDG8hzf+ni5l3SO3SvdIq1TfQB+ltR4CTATuVUpdWd1OSqlxGAN9QXXbtdbva63Dtdbhvr6+1e0ihNmUBrp7HSNFa/LY5BBcHe2A5g10f08XtvxrDA9d3bvZjjm2T0fjDdItJ4lNbXwTyR5T+/mIIOPi57ePKm33r9o/X1hevQJdax1n+jsBWA0Mr7yPUmogsAyYprVu3DLqQphRRm4h7k722DWyWcPf04WHJ/YloL0LXbyaflO0vI4ezjg72DXrMZ/4c38UisXrG99EsjsmBWcHAwO6GL89lLb7n03OqTIwSlhenYGulHJTSrmXPgauBaIq7dMN+AaYo7U+YY6CCtFUGbl1D/uvy62XB7Jj/rgauw5aky6mHjo/HjF2jWyM3TEpDO3evsL1juzlw58HdWbJttMyta+Vqc9vpR+wUyl1ANgDfKu13qiUulspdbdpnyeADsCSmro2CmFp9R32X5emLgLdku4YFURPXzeebEQTSXpOIccuZjA8sEOVbY9NDsHRzsBT6+q3wpNoGXUGutY6Wms9yPSnv9b6WdPrS7XWS02P79Batzd1a6ypa6MQFtVcgd6aONobeHp6KOdTclmyrWFNJHvOpKA1XGZqPy/Pz+OPCcx+ONy42r9oftb/vVGIZtIWAx3gip4+TAvrzNJtp4lJqn8TyZ6YZBztDFWmGSg194pA+nZyZ/H6w3Wu8CRahgS6aDPaaqCDcQoDJ3sDT6yNqncTye6YFMK6etV4s9bezsAz00OJT8/jrZ9ONmdxRSNJoIs2w7hAtFUt0tViOno4869re7PjZBLfHqp7Eeys/CKi4tKrbW4pLzzQm+vDA/hwZwzHL2Y2V3FFI0mgizYhr7CY/KKSNltDB5hzeSChXTxYvP4ImXmFte6772wqJRqGBdYe6AAPTwyhnbM9j605JDdILUwCXbQJGXmNHyVqK+wMimemDyAxK5/XN9XeRBJxJgWDgiHd29d5XG83RxZO7MvvZ1JZtTe2uYorGkECXbQJGaZRok3th97ahXX14ubh3Vi+K6Zsybvq7DmTQr/OHrRzql8T1ayhXRnavT3Pf3+M1OyC5iquaCAJdNEmNGUeF1sz/0998XZz5NE1URSXVG0iKSgqIfJ8Wr2aW0oZDIpn/xJKem4hL2481pzFFQ0ggS7ahHSpoZfxdHXgscn9OHA+jc/2nKuy/XB8OnmFJQ0KdIC+nTy4Y1QPPv/9PBFnUpqruKIBJNBFmyA19IqmhXVmZK8OvLTxGAmZeRW2/W4K4/DAutvPK/vH1cF08XLh0dVRFBaXNEtZRf1JoIs2oXS1Igl0I6UUT08LJb+whGc2HK2w7fczqQR2cK2ybF59uDra89TU/hy/lGmWtU1F7STQRZsgNfSqgnzbcc/Ynqw7EM+Ok8b1CbTWRJwxLmjRWNf08+Oafn68ufmkrG7UwiTQhc16e8tJIk0r1afnFuLqaIeDnfzKl3fP2J708HHjsTVR5BUWczoxi9ScQoY3IdABFk3tj1LwpEze1aLkt1vYpPTcQl758QT3fbaP3IJi4yjRRi5sYcucHex4drpxfvO3t5zi9zPGlSQb035eXmcvF/55TW+2HEtgY9TF5iiqqAcJdGGTohOzAIhNzeXNn0626Xlc6nJFLx+uG9KF97af5quI8/i0c6SHT9PXTJ17RSD9O3vw5LrDZQO7hHlJoAubdDrROKvgZT28+WBHNIfj0iXQa/HopBDcnOzZdy6N8O7ezTLnu72dgeevG0BSVj6v/nC8GUop6iKBLmzS6cQs7A2Kt28egqeLA/HpedIHvRYd2jnxyMQQAIb1aFr7eXkDA7y49fJAPv7tLPvPpTbbcUX1JNCFTYpOzKJ7B1d83Z14bLIxqKSGXrtZ4QEsmT2EG4d1bdbj/uva3vi5O7Pwm0PSN93MJNCFTTqdmE1P33YA/GVwF+4c3YMpg/wtXCrrppRi0gB/3Oo5f0t9uTs7sGhaf45dlL7p5iaBLmxOYXEJZ5Oz6dnRGOhKKR6d3I9xfTpauGRt15/6d+Lafn68sfmE9E03Iwl0YXPOp+RQWKwJaoaeGqL5LJrWH3uDgUfX1H/VJNEwEujC5pT2cCmtoQvr4O/pwr+v7c32E4msOxBv6eLYJAl0YXNK+6D39JFAtzZzLg8krKsXi9cfkXnTzUACXdic04lZ+LRzwtNVerVYGzuD4vnrBpCeW8iz3x2t+w2iQSTQhc0x9nCR9nNrFeLvwV1XBrFqbyy/nEqydHFsigS6sDmnE7MI8pXmFmv2wPhgAju48sjqQ+QWFFu6ODZDAl3YlJTsAtJyCqWGbuWcHex47roBnE3O4c2fal+wWtSfBLqwKadLb4hKDxerd0VPH24I78oHO6JrXbBa1J8EurAppxOMgd5LmlxahUcmhdDe1ZGHvzlIkUwL0GQS6MKmnE7MwtHeQGcvF0sXRdSDp6sDi6f1Jyoug//7RaYFaCoJdGFTohOzCfJxw87Q9OlfRcuYGNqJa/r58dqmE5xNzrZ0cVo1CXRhU04nZpVNyiVah9IFqx0MBh7++pBMC9AEEujCZuQVFnMuJYcg6eHS6nTydGbhpBB+jU7mi9/PW7o4rZYEurAZ244nUqJheDMu0CBazo3DujIiyJtnvzvKpYw8SxenVZJAFzZj/cF4Org5cnlQB0sXRTSCwaB44bqBFBSV8LjMyNgoEujCJmTnF/HT0UtMGuCPvZ38WrdWgT5u/POa3vx45BLfHbpo6eK0OvKbL2zC5qOXyCss4c+DOlu6KKKJbh/VgwFdPHlyXRQpMiNjg0igC5uw/sAFOnk4E969vaWLIprI3s7ASzMHkpZTyOL1hy1dnFZFAl20euk5hfx8IoEpA/0xSP9zmxDi78G8cb1YExnPlmOXLF2cVqNega6UOqOUOqSUilRKRVSzXSml3lJKnVJKHVRKDWn+ogpRvR+OXKSwWEtzi425b1wvevu145FvosjIK7R0cVqFhtTQx2mtw7TW4dVsmwgEm/7cBbzbHIUToj42HLxAN29XBgZ4Wrooohk52ht4aeYgEjLzeF4Ww6iX5mpymQZ8rI1+A7yUUv7NdGwhapSWU8Avp5KYMtAfpaS5xdaEdfXiztFBrNxznp0nZTGMutQ30DXwo1Jqr1Lqrmq2dwHKD++KNb1WgVLqLqVUhFIqIjExseGlFaKS4xczKS7RXCZ9z23WQ9f0JsjHjQVfHyQ7v8jSxbFq9Q30UVrrIRibVu5VSl3ZmJNprd/XWodrrcN9fX0bcwghKohJMk7mFOQjw/1tlbODHS/NHEh8ei4vbjxm6eJYtXoFutY6zvR3ArAaGF5plziga7nnAabXhDCrmKRsmS63DQgP9Oa2ywP5+Nez/BadbOniWK06A10p5aaUci99DFwLRFXabR1wq6m3ywggXWt9odlLK0Ql0UnZBHZwlely24D5E/rQzduVBV8fJKdAml6qU58auh+wUyl1ANgDfKu13qiUulspdbdpn++AaOAU8AEwzyylFaKSmKRsekhzS5vg6mjPSzMHcjY5h5d/OG7p4lgl+7p20FpHA4OqeX1puccauLd5iyZE7YpLNGeTs7k6xM/SRREtZERQB267vDvLd51hYqi/zKxZiYwUFVZl37lUbl/+e70GksSl5lJYrOnh49oCJRPWYv6EvgS0d2H+qgPkFhRbujhWRQJdWJVdp5L46VgCz26oeyBJdJJxQegePrJCUVvi5mTPSzMGcUaaXqqQQBdWJTXHWDP/IuI8W48n1LpvaZdFaUNvey7v2YFbL+/OR7ti2BOTYuniWA0JdGFVUnMK6OjuRHDHdiz8+hDpuTU3vcQkZePuZI9PO8cWLKGwFgtMTS//WXVAer2YSKALq5KWU4ivuxOvzBpEYlY+T284UuO+MUnZ9PB1kyH/bZSbkz0vzxzE2eQcXtooTS8ggS6sTEp2Ae1dHRnU1Yu7xwSxam8sPx2tfvpU6bIoRgR1YO4VgSzfdYZfT8uAIwl0YVXScgrwcnUA4IHxwfTt5M7D3xwiLafiyjV5hcXEpeVKoAvmT+hD9w6u/GfVAbLa+FwvEujCqqTmFNLe1dgm7mRvxyuzBpGaXcCT6yquXHMuJQet5YaoMA44enXWIOLScnmujU+zK4EurEZxiSYjr5D2pho6QGgXT+67qhdrI+PZGPXHbBLRiaWTckmXRWGc6+WOUT34bPc5tp9ouzO5SqALq5GeW4jW0N6tYq+Ve8f1IrSLB4+ujiI5Kx/4o8tioAwqEib/urYPvTq2Y8HXB2vtHWXLJNCF1Ug1tZOXNrmUcrAz8OqsMDLzinh0dRRaa2KSsvB1d8Ld2aG6Q4k2yNnBjldnDSIhM5/F62vuHWXLJNCF1Si98enlWjWk+3Ry55/X9mbj4YusjYyXHi6iWoO6ejFvbE++3hfLpiNtb3FpCXRhNVKzjV+TK9fQS905Ooih3dvzxNoojl3MlEUtRLXuvyqYfv4eLPzmYFkTXVshgS6sRk1NLqXsDIpXZw2isFiTmVckNXRRLUd7A6/dMIiM3CIeW2NsomsrJNCF1UgzzePi5VZzu3igjxsLJ/UFoLefe4uUS7Q+fTt58NA1vfk+ythE11bUOR+6EC0lJacAe4PC3an2X8s5I7ozoIsngwK8WqhkojW668ogNh25yBNro7gsyBt/T9tfplBq6MJqlI4SrWtuFqUUg7u1xyDLzola2BkUr10fRmGxZv6qg5SU2H7TiwS6sBqp2YV41dB+LkRjBPq48ejkEHacTOKT3WctXRyzk0AXViM1p6DCKFEhmsPsy7oxprcvz313lOjELEsXx6wk0IXVSCs3j4sQzUUpxUszB+Jkb8dDXx6gqLjE0kUyGwl0YTWMNXQJdNH8/DycefYvoRw4n8Y7W09bujhmI4EurILWmrScwlq7LArRFFMGdmZaWGfe2nKSA+fTLF0cs5BAF1Yhp6CYguISqaELs1o8NZSO7k489GUkuQXFli5Os5NAF1bhj1GiUkMX5uPp6sArswYRnZjNC9/b3tzpEujCKpSNEpUaujCzkb18+OvIQFb8epafbWzudAl0YRVSsmufx0WI5rRgQl96+7Xj318dKPvdswUS6MIqSJOLaEnODna8ccNg0nIKeOSbQzYzgZcEurAK0uQiWlq/zh78+9o+bDx8kVV7Yy1dnGYhgS6sQmoti1sIYS53jA7ish7ePLXuMOeScyxdnCaTQBdWIS2nEHdnexzs5FdStBw7g+K1G8IwGBQPfrG/1Y8ilX89wirIKFFhKV28XHhmeij7zrX+UaQS6MIqpOYUyg1RYTHTwrow3TSKdN+5VEsXp9Ek0EWLySssJj23sNptxrnQpYYuLGfx9FA6eTjz0BeRZOUXWbo4jSKBLlrMovWHufb1n6vt9ytT5wpL83B24PUbwjifksOidYctXZxGkUAXLSYmKZtLGfnMX3WwSvb0xo4AABkQSURBVL9fWdxCWIPhPby5d1wvvtoby7cHL1i6OA0mgS5aTGJmPm6Odmw+eolPd58re72gqISs/CK5KSqswgPjgwnr6sXCbw4Sl5Zr6eI0iAS6aDFJWQX8ZUgXRgf78My3RziVkAlAWq5plKhMnSusgIOdgTdvDKO4RPPQF5EUt6K1SCXQRYsoKCohPbcQ33bOvDprEK6O9ty/MpL8omIZJSqsTvcObiyaFsqemBSW/tx6ujLWO9CVUnZKqf1KqQ3VbOumlNpq2n5QKTWpeYspWrvk7HwAfNwd6ejhzMszB3L0QgYvbTxOqukmqbcEurAiM4Z04c+DOvPaphPsbyVdGRtSQ/8HUNMEwo8BX2qtBwM3AkuaWjBhW5IyjaHt284JgPEhftx2eXc+3BnDmsh4QIb9C+uilOIZU1fGf3weSWZe9V1urUm9Al0pFQBMBpbVsIsGPEyPPYH4phdN2JLErDwAfNydyl5bOCmEPn7urNxjvEHa3k1q6MK6eLo48OaNYcSm5vDEWuvvyljfGvobwHygpokOngJuUUrFAt8B91e3k1LqLqVUhFIqIjHRtiaWF7WrXEMH4xSmb900GEd746+h9EMX1ig80JsHxgezen8cq/db96yMdQa6UmoKkKC13lvLbjcBy7XWAcAk4H9KqSrH1lq/r7UO11qH+/r6NrrQovVJzDK1oZcLdIA+ndx5/i8DGN+3Iy4OdpYomhB1um9cL4YFtuex1VGcTc62dHFqVJ8a+khgqlLqDPA5cJVS6pNK+9wOfAmgtf4VcAZ8mrGcopVLyjL2QXdxrBraM4YG8OHcYSilLFAyIepmb2fgjRsHY2dQPLByPwVF1jkrY52BrrVeqLUO0FoHYrzhuUVrfUul3c4B4wGUUiEYA13aVESZpKwCfN2d6t5RCCvVxcuFF2cM5EBsOq9tOmHp4lSr0f3QlVKLlVJTTU//BdyplDoArATmaltZ00k0i8TMvCrNLUK0NhMH+HPT8G68t/00O08mWbo4VTQo0LXW27TWU0yPn9BarzM9PqK1Hqm1HqS1DtNa/2iOworWKymrQAJd2IQnpvSjl287HvoyksTMfEsXpwIZKSpaRFJWPj7u0i1RtH4ujnb89+bBZOQW8q+vDlBiRVMDSKALsyssLiEtp1Bq6MJm9O3kweNT+rH9RCLLdkZbujhlJNCF2SVnGfugS6ALWzL7sm5MDO3ESxuPE3k+zdLFASTQRQsobWeUXi7CliileOG6gfh5OHP/yn1kWMHUABLowuySahhUJERr5+nqwFs3hRGflsfCrw9VWbilpUmgC7MrHSXqK4EubNDQ7t7869refHvoAiv3nLdoWSTQhdmV1dCll4uwUXdf2ZPRwT4sWn+YYxczLFYOCXRhdkmZBbg62uHqaG/poghhFgaD4rXrw/BwceDeT/eRU1BkmXJY5KyiTUnMypcbosLm+bo78eYNYUQnZfP4GstMtSuBLswuKTNfboiKNuGKXj7cf1UwX++LZdXelp9qVwJdmF1SVj4+7aT9XLQN/xgfzIggbx5fE1W2EHpLkUAXZmcMdKmhi7bBzqB488bBuDraMe/TfeQWFLfYuSXQhVkVFpeQKsP+RRvj5+HM6zeEcTIhiyfXRbXYeSXQhVmVDfuXm6Kijbmyty/3ju3FlxGxfLOvZdrTJdCFWSXJoCLRhj14dTCX9fDm0dUt054ugS7MqmyUqAwqEm2QvZ2Bt25qufZ0CXRhVkmZMo+LaNv8PJx540Zje/rja83bni6BLswqSabOFYLRwb48cFUwq/bG8mWE+eZ7kUAXZpWYmY+Lgx1uTjLsX7RtD4wPZmSvDjy+JoqjF8wz34sEujCrJBn2LwRg7J/+xg2D8XBxYPX+OLOcQ6pNwqwSM2WUqBClfN2dWH/fKPw8zFPJkRq6MKsL6bn4e7lYuhhCWI1Ons4opcxybAl0YTZaay6k59HZ09nSRRGiTZBAF2aTkl1AflEJ/p5SQxeiJUigC7O5kJ4HQGcvqaEL0RIk0IXZxKXlAtBZ2tCFaBES6MJsLpgCXZpchGgZEujCbC6k5+FoZ6CDm3RbFKIlSKALs4lPz6OTpzMGg3m6aAkhKpJAF2ZzIS0Xf+myKESLkUAXZnMhPY8uckNUiBYjgS7MorhEczEjD3/psihEi5FAF2aRkJlHcYmWHi5CtCAJdGEW8WkyqEiIliaBLsziQroMKhKipUmgC7O4YKqhS5OLEC1HAl2YRXx6Lm6Odng4y5T7QrSUege6UspOKbVfKbWhhu3XK6WOKKUOK6U+a74iitYoPs04D7q55n0WQlTVkOrTP4CjgEflDUqpYGAhMFJrnaqU6thM5ROt1IX0PBlUJEQLq1cNXSkVAEwGltWwy53AO1rrVACtdULzFE+0VvFpMqhIiJZW3yaXN4D5QEkN23sDvZVSvyilflNKTahuJ6XUXUqpCKVURGJiYiOKaztSsgvQWlu6GGaRX1RMUla+3BAVooXVGehKqSlAgtZ6by272QPBwFjgJuADpZRX5Z201u9rrcO11uG+vr6NLHLrFxWXzvBnN/PSD8ctXRSzuJSeDyCjRIVoYfWpoY8EpiqlzgCfA1cppT6ptE8ssE5rXai1jgFOYAx4UY13t52mqETz7rbTbDgYb+niNIucgiKKio1f4MoWtpAauhAtqs5A11ov1FoHaK0DgRuBLVrrWyrttgZj7RyllA/GJpjo5i2q0bnkHB78fD+5BcXmOLzZxSRl813UBe4Y1YMh3bz4z1cHOXYxw9LFarIZ7/7K3I9+p6i4pNygIqmhC9GSGt0PXSm1WCk11fT0ByBZKXUE2Ar8R2ud3BwFrOx0YhZrD8Tz8DcHW2Ub9PvbT+NgZ+DvY3qy9JahuDvbc9fHe0nLKbB00RqtuERz8lImO08l8fz3x8rWEpU2dCFaVoMCXWu9TWs9xfT4Ca31OtNjrbX+p9a6n9Z6gNb6c3MUFmBc3478+9o+rI2MZ9mOGHOdxiwSMvL4em8cM4cG4OvuREcPZ969ZSgX0nO5f+V+ikta339QAJcy8igq0QS0d+HDnTF8GXGe9q4OuDjaWbpoQrQprXKk6LyxPZk0oBPPf3+UHSct31smKi6df315gIy8wlr3+/CXGIpKSrhrdFDZa0O7t+fpaaHsOJnESz8cM3dRzaK0zXzxtP5c1sObs8k5UjsXwgJaZaArpXh55iCCO7pz32f7OZucbbZzvfrjca5b8gs5BUU17vPmTyf5el8s//wikpJKteySEs2JS5l8tvscn/12jokD/An0cauwz43Du3HLiG6893M0ayPjzHId5hSXagz0bt5uLJk9hC5eLgT7tbNwqYRoe1ploAO4Odnz/q1DAbjr471k59ccuE2xOzqFfefS+M9X1bfZp2QXsPVYAr06tmPz0QRe33wCgKLiEpbtiGboM5u49vXtPLL6EO2c7XlwfPWdf56Y0p/hgd4s+PogUXHpZrkWcymtoXfxcqFDOyd+eOhKXpwx0MKlEqLtabWBDtC9gxvv3DyEkwmZ/PPLqrXj5hCXlouniwPfHrrAkm2nq2xfFxlHUYnm7ZsHc314AP/dcool204xfckvPPPtUQYEePHyzIFs/fdYdj18FcF+7tWex9HewDuzh9De1ZG//28vSVn5FbZrra32JnBcWi7ebo5lbebtnOxxdpD2cyFaWqsOdIBRwT48MimEHw5f4r9bTjXrsUuXUbtlRDemDurMKz8eZ8uxSxX2+WZ/HP38PejbyYOnp4cyuJsXL208zqWMfN65eQgr/jqMWeFd6eHjVudEVb7uTrw/J5ykrHzmfbKPgiJjv+4D59MY/+rP3PfZfrP8p9VUcam5MsxfCCvQ6gMd4PZRPbhucBde33yCHw9fbLbjli6j1sXLlRdnDKSfvwf/WBnJqYQsAE5eyuRgbDrXDekCgJO9HR/cGs6Tf+7H5n+OYfJA/wbPNjggwJOXZg5kz5kUFq0/zLId0cxcuoukrHy+PXShrEnHmsSlSaALYQ1sItCVUjx33QAGBXjy0BeRHL+Y2SzHjU/7Y4CMi6Md798ajpODgbs+jiA9p5Cv98VhZ1BMC+tS9h6fdk78dWQPPF0cGn3eaWFd+PuYID7dfY5nvj3K2D4d2T5/XFmTzrcHLzT52pqL1tpYQ28vgS6EpdlEoAM4O9jx3pxw3JzsuePj30nNbvpAnTjTqjultc8uXi68e8tQzqfmcP/n+1mzP44xvX3xdXdq8rkqm/+nvtw+qgdPTw/l/TlD8XJ15OnpoQzt3p5/f3WAw/HWceM0LaeQ3MJiqaELYQVsJtABOnk6s3TOUC6l53PvZ/soLK5pcsj6Ka2h+5cLq2GB3iyeFsr2E4lczMhjxpCAJp2jJnYGxeNT+jFnRPeyZhsnezvevWUIXq4O3PVx1RunllA2b4sEuhAWZ1OBDjCkW3ueu24Au04n88yGI006Vryph0s7p4rrgNw0vBt3XRlEkI8b40Nadi2Pju7OZTdO7/lkb9mNU0uJNfVBD5AmFyEszuYCHWDm0ADuHN2DFb+e5bPd5xp9nLjU3Bprno9MCmHzP8dYpHvegABPXp41iN/PpPL4miiLdmcs3wddCGFZNhnoAA9PDGFMb1+eWBvF7ujGzRNm7L1R84yBBoPl1sucOqgz947ryRcR51m+64zFyhGXmourox1ero2/CSyEaB42G+h2BsVbNw2mWwdX7vl0H+dTchp8jPi0mmvo1uBf1/Thmn5+PL3hCNtPWGZOm3hTl0VZDFoIy7PZQAfwdHHgw9uGUVRcwh0rIshqwPQAmXmFZOQVWXWgGwyK128Io7efO/d+to/TiVktXoY4K/9PT4i2xKYDHaCHjxtLZg/lVGIWD35e/ylqS+f0tvawaudkzwe3huNgZ+DOFcb+8S0pLk36oAthLWw+0ME4PcCTf+7H5qMJvFzPdTz/uNln/avudPV2Zampf/x9K/eVLQVnbjkFRaRkF8gNUSGsRJsIdIA5I7oz+7JuLP35NF/vja1z//hW1r96eA9vnp0+gB0nk3i6id0166v0ZyRdFoWwDvZ172IblFI8NbU/MUnZLPzmEN07uBIe6F3j/vFpudgbFB3drb+GXur6YV05mZDJBzti6OXnzpwR3Rv0fq11g25uVh5JK4SwrDZTQwdwsDOwZPYQOns58/f/7a2150t8Wh6dPJ2xs2DXxMZ4eGIIV/XtyFPrDvPLqaR6vy/yfBrhz2xmY1Ttk5vFp+WWNemULmzRWr7FCGHr2lSgA3i5OvLh3GEU1NHzpbX23rAzKN68MYxevu2455O99e758vaWkyRnF/DQF5E1LrBxPiWHsS9v4+//20txiSYuLQd7g8LPo/V8ixHClrW5QAfo6duOJbOHcCoxiwdqWJy5Nc/x7e7swLLbjD1fbl9e90RlpxIy2Xw0gTkjutPe1YHbV/zOpYy8Kvu9t/00hSUl/HQsgee/O0pcam6r/BYjhK1qk4EOMDrYl6em9mfLsQSe++5ohW2lC1t0bgU9XGrS1duV9+YMJT4tj3s+Nc75cvRCBvM+3ctlz23m6IWMsn3f3x6Ns4OBh67pzYdzh5GZV8QdKyLILSgu2ychM48vI2K5Ibwrc68IZNnOGDYfTWi1/+kJYYvabKCDsefL3CsC+XBnDJ/uPlv2eunCFq2xyaW88EBvXpw5gN+iU5jw5nYmvrmD7SeSKCrW3LEigsTMfC5l5LF6fxzXh3fF282REH8P3rpxMFHx6RWW9fu/nWcoKi7h72N68tjkEK7s7UtWfpEEuhBWpE0HOsDjU/oxro8vT6w9zM6TxpuIra3LYm3+MjiAB68OJiW7gAfGB/PLgqtY8bfhpGQXcOfHEby77TTFJZo7RgWVvefqfn48MjGE76Mu8sqPx0nPLeST384ycYA/PXzcsLcz8PbNgxnVy4exfVt2tkkhRM2UpWbqCw8P1xERERY5d2WZeYXMfPdX4tNzWT3vCo5cyOSBlfv58aEr6V3Dos6tTeUuiRujLnLPp3vRGiYP9Oedm4dU2f+R1YdYuec8w3t4sycmhW8fGEX/zp4tXXQhRDlKqb1a6/DqtrX5GjoYbyJ+ODccJ3sDf1seUdbLw9+z9bahV1a5f/mE0E4snNgXZwcD94zpWe3+i6eFMrJXB/bEpDC2j6+EuRBWTmro5ew/l8qN7/9GflEJHs72HHzqT5YuktnlFRbXOqd7ek4hL2w8yt9G9iDYRr6tCNGaSQ29ngZ3a8+r1w8CbKP9vD7qWqDD09WB568bKGEuRCvQZob+19eUgZ3JLSjG0V7+rxNCtC4S6NWYFd7V0kUQQogGk2qoEELYCAl0IYSwERLoQghhIyTQhRDCRkigCyGEjZBAF0IIGyGBLoQQNkICXQghbITF5nJRSiUCZ+vc8Q8+QP0XybQdbfG62+I1Q9u87rZ4zdC06+6utfatboPFAr2hlFIRNU1IY8va4nW3xWuGtnndbfGawXzXLU0uQghhIyTQhRDCRrSmQH/f0gWwkLZ43W3xmqFtXndbvGYw03W3mjZ0IYQQtWtNNXQhhBC1kEAXQggb0SoCXSk1QSl1XCl1Sin1sKXLYw5Kqa5Kqa1KqSNKqcNKqX+YXvdWSm1SSp00/d3e0mU1B6WUnVJqv1Jqg+l5D6XUbtNn/oVSytHSZWxOSikvpdQqpdQxpdRRpdTlbeGzVko9ZPr9jlJKrVRKOdvaZ62U+j+lVIJSKqrca9V+tsroLdO1H1RKDWnKua0+0JVSdsA7wESgH3CTUqqfZUtlFkXAv7TW/YARwL2m63wY+ElrHQz8ZHpui/4BHC33/EXgda11LyAVuN0ipTKfN4GNWuu+wCCM127Tn7VSqgvwABCutQ4F7IAbsb3PejkwodJrNX22E4Fg05+7gHebcmKrD3RgOHBKax2ttS4APgemWbhMzU5rfUFrvc/0OBPjP/AuGK91hWm3FcB0y5TQfJRSAcBkYJnpuQKuAlaZdrGp61ZKeQJXAh8CaK0LtNZptIHPGuOyly5KKXvAFbiAjX3WWuvtQEqll2v6bKcBH2uj3wAvpZR/Y8/dGgK9C3C+3PNY02s2SykVCAwGdgN+WusLpk0XAT8LFcuc3gDmAyWm5x2ANK11kem5rX3mPYBE4CNTM9MypZQbNv5Za63jgFeAcxiDPB3Yi21/1qVq+mybNd9aQ6C3KUqpdsDXwINa64zy27Sxj6lN9TNVSk0BErTWey1dlhZkDwwB3tVaDwayqdS8YqOfdXuMNdIeQGfAjapNEzbPnJ9tawj0OKBruecBptdsjlLKAWOYf6q1/sb08qXSr2CmvxMsVT4zGQlMVUqdwdicdhXG9mUv09dysL3PPBaI1VrvNj1fhTHgbf2zvhqI0Vonaq0LgW8wfv62/FmXqumzbdZ8aw2B/jsQbLoT7ojxJso6C5ep2ZnajT8EjmqtXyu3aR1wm+nxbcDali6bOWmtF2qtA7TWgRg/2y1a69nAVmCmaTebum6t9UXgvFKqj+ml8cARbPyzxtjUMkIp5Wr6fS+9bpv9rMup6bNdB9xq6u0yAkgv1zTTcFprq/8DTAJOAKeBRy1dHjNd4yiMX8MOApGmP5Mwtif/BJwENgPeli6rGX8GY4ENpsdBwB7gFPAV4GTp8jXztYYBEabPew3Qvi181sAi4BgQBfwPcLK1zxpYifEeQSHGb2O31/TZAgpjL77TwCGMPYAafW4Z+i+EEDaiNTS5CCGEqAcJdCGEsBES6EIIYSMk0IUQwkZIoAshhI2QQBetmmnWwnmmx52VUqvqek8TzhWmlJpkruML0VQS6KK18wLmAWit47XWM+vYvynCMI4NEMIqST900aoppUpn3zyOcdBGiNY6VCk1F+OMdm4YpyZ9BXAE5gD5wCStdYpSqifGgR2+QA5wp9b6mFJqFvAkUIxxEqmrMQ58ccE4NPt5YAPwXyAUcACe0lqvNZ37L4AnxomWPtFaLzLzj0II7OveRQir9jAQqrUOM81SuaHctlCMs1Y6YwzjBVrrwUqp14FbMc7y+D5wt9b6pFLqMmAJxvlkngD+pLWOU0p5aa0LlFJPYBzJdx+AUuo5jFMV/E0p5QXsUUptNp17uOn8OcDvSqlvtdYR5vxBCCGBLmzZVm2cWz5TKZUOrDe9fggYaJrZ8grgK+PUIoBxKDrAL8BypdSXGCeRqs61GCcW+7fpuTPQzfR4k9Y6GUAp9Q3GqR0k0IVZSaALW5Zf7nFJueclGH/3DRjn4g6r/Eat9d2mGvtkYK9Samg1x1fADK318QovGt9XuS1T2jaF2clNUdHaZQLujXmjNs43H2NqLy9d33GQ6XFPrfVurfUTGBej6FrNuX4A7jfNHIhSanC5bdeY1pF0wdiW/0tjyihEQ0igi1bN1Kzxi2lB3pcbcYjZwO1KqQPAYf5Y3vBlpdQh03F3AQcwTvPaTykVqZS6AXga483Qg0qpw6bnpfZgnNv+IPC1tJ+LliC9XIRoZqZeLmU3T4VoKVJDF0IIGyE1dCGEsBFSQxdCCBshgS6EEDZCAl0IIWyEBLoQQtgICXQhhLAR/w8on0All77pFQAAAABJRU5ErkJggg==\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['fractionOfSupplyInPool'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40a64b8c90>"
|
||
]
|
||
},
|
||
"execution_count": 33,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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P+JuD1w7ia+lb6nqeTTxxNnVm+ZnlvNjqRXS05K9LkqSSyRZ6FbuRcYN/o//lxVYvYqSrHmNbX68+vW16FxquWBxFUXjd6XWu3b7GjuiyiydJkvR0kwm9iq2/sB4VKoa2GVr2wsXoZtmNFsYt+OX0L6iELFYkSVLJZEKvQpl5mWy8uBFfS1+a1Wv2UNvQUrR43el1IlIi2Bezr5IjlGrC41I+9/bt27z11lu0aNECd3d3unXrxpEjR6okLlAXR3N0dCxzmd9/r/gDz0aNGsXGjRsBdVE1Ozs7XFxc8Pb25sKFCw8Vb1UoWLisKsiEXoW2R20nJTuFYW2HPdJ2etv0pmndpiwNW0pNjUp62tXG8rljx46lYcOGXLp0idDQUFasWEFCQkKlx1URD5vQH7RmzRpOnTrFyJEjC1WCvKe4qo+1gUzoVWjjxY20MG6BR+NiRxiVm66WLm85v0V4YjiBMYGVE9xTSJbPvV8+9+zZsxw5coRZs2ahpaVOAzY2NvTt2xeAb7/9FkdHRxwdHfnuu+8KHb9Ro0bRunVrhg0bxu7du/H29qZVq1YcPXoUUD8gYsSIEXTs2JFWrVqxbNmyIr+Lko7btGnTCAoKwtXVlYULF5a4nBCCd955Bzs7O/z8/DTlBR50rzQvQN26dfnggw9wcXHh0KFDpX7GB/9GQP2F6ObmhpOTE2PGjCE7O1sT870Sux9++CEA//zzj+ZsyM/Pj5s3bxaJbcOGDTg6OuLi4kLXrl1L+KutoJLuOKrqV22/U/R84nnhuNJR/Hb2t0rZXm5+rnjuz+fEoM2DRL4qv1K2WZ0K3fG2baoQy/tU7mvb1DJjkOVz75fP3bx5sxgwYECxxykkJEQ4OjqK27dvi/T0dGFvby+OHz8uoqKihLa2tggLCxP5+fmiXbt2YvTo0UKlUolNmzaJ/v37CyHU5WednZ3FnTt3RHx8vGjWrJm4du1aoTt1SztuBe8CLWm5P//8U1Na99q1a8LY2Fhs2LBB83u7V+Z33rx54uWXXxZCCAGI9evXl/kZH/wbmT9/vub3ceHCBSGEECNGjBALFy4UCQkJonXr1ppy1/dK7CYlJWmmLVu2TEyePLnI78DR0VHExsYWWu9B8k7Rx8Rfl/5CV0uXF2yL1tF4GDpaOox3Gc+F5Avsvbq3Urb5NJLlc8sWHBzMwIEDMTIyom7durz44ouaR9bZ2Njg5OSElpYWDg4O9OjRA0VRcHJyKvT5+vfvj6GhIaampvj6+mpa7wU/Q0nHrTzL7d+/X1Na18LCgu7duxda796DOA4cOKB5nJy2tjaDBg0q8zM++DcSHBzMhQsXsLGxoXXr1gCMHDmS/fv3Y2xsjIGBAa+//jp//fWXpuRwbGwsvXr1wsnJifnz5xdb8M3b25tRo0axbNmySusCkgObq0BWXhb/RP6DX3M/GhhUXjGf52ye46ewn/A/6U93q+5lDnt8bD03t8Z2Lcvnqjk4OHDq1Cny8/PR1tYudX8FFfxMWlpamvdaWlqFPl9Z5W1LO27lWW7btkLVvItYs2YNHh6FuzoNDAzK9VkrUppXR0eHo0ePsmfPHjZu3MjixYvZu3cv7777LpMnT6Zfv34EBgYyY8aMIusuXbqUI0eOsHXrVtzd3QkNDaVRo0ZlxleaJzQjPN7+vfIv6TnpDG41uFK3e6+VHpESwa7oXZW67aeFLJ+r1qJFCzw8PPjiiy8024mOjmbr1q106dKFTZs2cefOHTIyMvj77781zyAtr82bN5OVlUViYiKBgYGFqkXe+wzFHbcHS/SWtFzXrl01pXWvX79OQEBAheIr7TM++DfSuXNn7OzsiI6O1vTHr1q1Ch8fH27fvk1qaip9+vRh4cKFnDp1CoDU1FSaNm0KwK+//lpsDJcvX6Z9+/bMnDkTMzMzYmJiKvQZiiNb6FXgz0t/YlXPqkoeUNHLuhfLTi9j8cnF9GjeA10t3UrfR20my+fe9/PPP/PBBx/QsmVLTffI/PnzadeuHaNGjdKUwR07dixubm4ldhkVx9nZGV9fXxISEpg+fToWFhaF1i/puDk7O6OtrY2LiwujRo3ivffeK3a5gQMHsnfvXuzt7bGysqJjx9LLaDyotM/44N/I+PHjMTAwYMWKFbz00kvk5eXh6enJuHHjSEpKon///mRlZSGE4NtvvwXUF4ZfeuklTExM6N69O1FRUUVimDJlCpcuXUIIQY8ePXBxcanQZyhWSZ3rVf2qrRdFI1MiheNKR/Fz2M9Vto+AqwHCcaWjWHduXZXto7LJ8rkV96SWzy34TM4nzeP2NyIvitawTRGb0Fa06d+yf9kLPySfZj60e6YdS04t4U5u1dygItU8WT5XqihZPrcSqYSKXn/2olWDVvzg90OV7utU/CmGbxvO265vM95lfJXuqzLI8rmSVHGyfG4NOnHrBDcybtDXtm+V78vFzAU/Kz9WnllJYmZile9PkqTHn0zolWhr5FYMdQzLLItbWSa2m0h2fjZLTi2plv1JkvR4kwm9kuTm57Lryi58LX2po1unWvZpY2zDS61fYuPFjVxKLnpThiRJTxeZ0CtJ8LVgUrNTq6W7paAJrhMw0jXim6PfyMJdkvSUK1dCVxSlt6IoFxRFiVAUZVox80cpihKvKMrJu6+xlR/q421r1FZM9E3KfKxcZWtg0IAJrhM4cuMIe2NkSYAnweNSPtfa2lpTXTE0NBQbGxtOnDjBli1bmDtXfTfvjBkzNLfOFyxRWx4Fy+UGBgZibGyMq6srbdu25csvv6ysj1wpCh6LJ1mZCV1RFG3AH3gOsAeGKopiX8yi64UQrndfP1dynI+1jNwMAmMC6Wnds0Zu9HnZ7mVaNmjJgmMLyM7Prvb9Pw1qY/nce8LCwhg8eDDr16/Hzc2Nfv36MW1akXbbI+vSpQsnT54kJCSE1atXc/z48ULzK/MYP63K00L3AiKEEJFCiBxgHVB1g6xryI6oHVxOufxQ6+65uofs/Gyet32+kqMqHx0tHT7y/IjY27GsCl9VIzE8CWT53PvlczMzMwH1sLgBAwawatUqzV2T5XkIQ0nHLDQ0FBcXF1xcXPD39y92XSMjI9zd3YmIiNCU2vX29mbEiBFER0fTvXt3nJ2d6dGjh6bo2KhRoxg3bhweHh60bt2a//3vfwBkZWUxevRonJyccHNz05QAOHv2LF5eXri6uuLs7Kwp/DVgwADc3d1xcHAodPZyT0ZGBn379sXFxQVHR8dCJReeBOW59b8pULDIQCzQvpjlBimK0hW4CLwvhChSmEBRlDeBNwGsrKwqHm0VEUIw/cB0OjftzELfhRVef2f0TiyMLHAxq4Rbdx9SR4uOdLfszk9hP9HHpg8WdS1qLJayfHP0G84nna/UbbZp2IapXlPLXO7ChQv88ssveHt7M2bMGPz9/fn777/ZvHkzZmZmrF+/nk8//ZTly5cDkJOTQ0hICDk5ObRp04b169fj6elJWloahoaG/PLLLxgbG3Ps2DGys7Px9vamZ8+egLrGytmzZ7GwsMDb25sDBw4wceJEvv32WwICAjA1NQXg66+/pmHDhuTn59OjRw/CwsJo3bo1b731Fvv378fGxqZQtcWvv/6a7t27s3z5clJSUvDy8sLPz4+zZ88ycuTIQp/Xw8ODs2fP4urqysyZMwkJCWHx4sWa+f3792f16tV07ty53Mc6NzeXd999t9hjNnr0aBYvXkzXrl2LfbAEqGvMHD58mOnTpxMeHk54eDjBwcEYGhrywgsvMHLkSEaOHMny5cuZOHGippRCdHQ0R48e5fLly/j6+hIREYG/vz+KonD69GnOnz9Pz549uXjxIkuXLuW9995j2LBh5OTkaKoZLl++nIYNG5KZmYmnpyeDBg0qVBBrx44dWFhYaM5qUlNTy31cHgeVdVH0H8BaCOEM/AsUW41GCPGTEMJDCOFhZmZWSbt+dJl5mWTlZ3H4+mFyVbkVWjcjN4NDcYfobtW91Kps1WGal/o0ec7ROTUax+NMls8tzM/Pj59//rlC5VsvXLhQ7DFLSUkhJSVF87CGESNGFFovKCgINzc3evbsybRp0zT1cvr164ehoSEAhw4d4tVXX9WsHxwcrFn/5ZdfRktLi1atWmFra6vpVho+fDgAbdq0oXnz5ly8eJGOHTsye/ZsvvnmG65cuaLZ/qJFi3BxcaFDhw7ExMQUKdnr5OTEv//+y9SpUwkKCsLY2Lgih7PGlaeFfg2wLPC+2d1pGkKIgne2/AzMe/TQqk9SVhIAt3NvExYfhntj93KvG3QtiFxVLn7N/aoqvHIzr2vOeJfxfBv6LXuv7qW7VfeyV6oB5WlJVxVZPrewxYsXM27cON5++21Nd1FZhBDFHrOUlJRS1+vSpYumq6Sgso7xPRUpa/vqq6/Svn17tm7dSp8+ffjxxx/R0tJi9+7dHDp0iDp16mi+DAtq3bo1x48fZ9u2bXz22Wf06NGDzz//vFzxPQ7K00I/BrRSFMVGURQ9YAiwpeACiqKYF3jbDzhXeSFWveSsZM3PB64dqNC6e6/spaFBQ1zNXCs7rIcy3H44LRu0ZM7RObLOSzFk+dzCtLS0+P333zl//ny5E5ednV2xx6xBgwY0aNBA06pes2ZNubZXUKdOnVi3bp1m/YIXbzds2IBKpeLy5ctERkZiZ2dHly5dNPu5ePEiV69e1Rw7W1tbJk6cSP/+/QkLCyM1NRUTExPq1KnD+fPnOXz4cJH9x8XFUadOHYYPH86UKVOKXLh93JXZQhdC5CmK8g6wE9AGlgshziqKMhN11a8twERFUfoBeUASMKoKY650ydnqhG6ka8SBuANMbDexXOvl5Oew/9p+elv3Rlur/A8JqEq6Wrp83vFzXtv+GktOLeEDjw8Kzd8RvYOdUTuZ02UOBjoGNRRlzZHlc4syMDBgy5Yt+Pj40Lhx4zJbzHp6emzcuLHYY7ZixQrGjBmDoiiaawkV8f333zN69Gjmz5+PmZkZK1as0MyzsrLCy8uLtLQ0li5dioGBAW+//Tbjx4/HyckJHR0dVq5cib6+Pn/88QerVq1CV1eXJk2a8Mknn2BkZMTSpUtp27YtdnZ2dOjQocj+T58+zZQpU9DS0kJXV5clS56wu7BLKsNY1a/HqXzupkubhONKR/FZ8GfCcaWjSLiTUK719sXsE44rHcX+mP1VHGHFfXHgC+Hyq4s4k3BGMy3+TrzosKaDcFzpKOYemVut8cjyuRX3pJbPrQojR47UPDP0aSLL5z6Ee10u957/eeh68f2pD9p7dS9Guka0Ny9u0E/NmuwxmYYGDfn8wOfk5qu7A+Ydm0d2fjY9rHqw+txqjlw/UsNRSqWR5XOlipIJHUjKTkJXSxePJh6Y6JuUqx89X5VPQEwAXZt2RU9brxqirJj6evWZ3mE6F5Mv8vOZnzkYd5DtUdsZ6zSWOV3mYF3fms8OfEZaTlpNh1ptrK2tOXPmTE2HUW7vv/8+J0+eJDw8nDVr1mgeQPw0WrlyJYMHV+4jHWsj+Qg6ICUrBRN9E7QULTo17cTBuIOohKrUhzCfjD9JUlYSPZr3qMZIK8bXylfzYGlTQ1Os6lnxutPr6GvrM7vzbEZsH8HcI3OZ3WV2iduITInkw/0fkpqtHo9rqGPIp+0/fagSB0KIGh/aKUlPCvEQtZlkCx11l4uJgQkA3hbeJGUllXnjy56re9DT0qNL04o9PLe6TfOaRj3detzIuMGnHT5FX1s9lM7JzIk3nd/kn8h/2BZZ/BPU81X5fHbgM27duUXnpp3p3LQzQgim7J/C9dvXKxSHgYEBiYmJsoCYJJWDEILExEQMDCo2cEG20FF3udxL6PdansHXgrFvVFzJGrWg2CA8zT2rrVTuw2po0JBF3RdxMfkinSw6FZr3pvObHL5+mJmHZ+Jk6oRlfctC81efW83phNPM6zqP52yeAyA6NZohW4fwwb4P+LX3r+hql692TbNmzYiNjSU+Pr5yPpgk1XIGBgY0a9asQuvIhI66y6Vpo6YAmBqaYt/Inn2x+3jT+c1il49NjyU6LZohbYZUZ5gPzfUZV1yfKTpOXkdLh7ld5jL4n8F8tP8jfnvuN02CvpJ2he9PfI+vpS+9rXtr1m8r9m0AACAASURBVLE2tmaW9yzeD3yf+SHz+aT9J+WKQVdXV3PXoyRJVUN2uVC4ywXAz8qPsPgwbmbcLHb5exdNvS28qyW+qmRR14KZnWZyJvEM80PmczbhLGcTzvL5gc/R09bjsw6fFen39mvux2v2r7H2/Fq2Rm6tocglSXrQU5/Qc/NzSc9NL5TQ713oLKm+eHBcME3rNqV5/ebVEmNV82vux8utX2bt+bUM2TqEIVuHcPzWcaZ4TOGZOs8Uu84k90m4N3bni4NfEJ4YXs0RS5JUnKe+yyUlW11/wkT/fkK3NbbF1tiWPVf2MLTN0ELL5+bncuT6Efq16FerRmx80v4TnrV+luw8dT11EwMTnM2cS1xeV0uX//j8hyFbh/BewHus67uORoaNSlxekqSq99S30O8V5irYQgfoYdWDkJshheq8AJy4dYLMvEw6Ny1/udEngbaWNh3MO+Bj6YOPpU+pyfyeRoaN+M73O5KzkpkcOJn4O/EkZCYUecmRLZJUPZ76Fvq9Oi4PJnS/5n4sO72MwJhABrYaqJkefC0YHS0dvJp4VWucjyuHRg582elLpgVNo/uG4qs7dm7amUXdF9XI05wk6WlSaxK6EILotGhsjCs2kuJeC7yhQcNC09s2bIuFkQV7ru4pnNDjgnF/xv2xH65Ynfra9sXEwISYtCLPNCEuI47lZ5Yz58gcpneYXqu6qSTpcVNrEvrv539n7tG5bOq/iRYNWpR7vXsJvYF+g0LTFUWhR/MerDu/jozcDIx0jbiZcZNLyZeY7D65UmOvDTpZdIISHpKkoPDLmV+wrm/Naw6vVW9gkvQUqRV96ImZififUD+/MDotukLrJmcno6AUSeigHr6Yq8olKDYIgINxBwHwbvrkD1esThPbTeTZ5s+yIGQBe68WP3JIkqRHVysS+qITi8jIUz9U4EbGjQqtm5yVjLG+cbH1zF3MXGhk0IipQVNxX+XOjEMzeMbwGVo1aFUpcT8ttBQtvu78NQ6NHJi6fyph8WE1HZIk1UpPfJfLmYQz/H3pb82NLg+T0ItrnYN65MfXnb/m6I2jmmleTbxkP/BDMNQxZHGPxYzYPoIJeyaw6rlVWBtbF1lOCEGeKq/cJQUkSbrviUvoeao8VEIFgEAw58gcGhk2YpzLOAJiArieUbGiUcnZyUUuiBbk3dRbdrFUkkaGjVjqt5QR20cwbvc4VvdZjamhaaFlvjr8FXuu7mFZz2W0NmldQ5FK0pPpietyWRW+CvfV7rivdsdjtQdhCWG87/4+dfXqYm5k/lAt9AeHLEpVx6q+Ff49/EnKSmL87vGF6rHvit7FhosbSMtJ441dbxCZGlmDkUrSk+eJS+jtGrfjvXbvaV6zO8/medvnAWhi1KTCLfSkrKQSu1ykquFo6sjCbguJSIngnT3vkJmXyc2Mm3x56EucTJ3Y8PwGFBTG7hzLlbQrNR2uJD0xnrguFxczF1zMXIqd18SoCfF34slV5ZbrJhaVUJGanVpql4tUNbybejO3y1w+2v8R7we8T57II1eVy5wuc2hevzk/9/yZMTvHMHDzQAy0i9aErqdXjxW9V2BRt4SxkpL0FHriEnppzI3MEQji78QX+kfPzc8t9iJbek46+SJfdrnUkF7Wvbidc5sZh2YAMKPjDE3Bs5YmLVnRewV/XfpLc83kHoFgw4UNLDm1hK+8v6rusCXpsVWrEnoToyYAXM+4rknoNzJu8Pzfz/Od73dF6q/cq+Miu1xqzqDWg1AUhZj0GF5s9WKheS0atGCK55Ri19NStFhzbg1jHMdU+O7gkmyP2k7IjZBi57Vp1IbBrQZX+Qin7Pxsvj/+PU5mTvSy7lWl+5Jqn1qV0M2NzIHCY9FPJ5wmOz+bHVE7iiT0e5UWZZdLzXowkZfH646vs/HiRn44+QPzfeY/cgy7onfx0f6PqKdXr0h3Xb7I54+LfxByI4QvO32JgY66CyhXlUtWXhb19Oo98v4BMvMyeW/vexy6fkgT02cdPpNnkFK51aqEXrCFfs+l5EsABF0LKvLg55IqLUqPv0aGjRjedjjLTi9jrNNY7BraFZqfp8rj+M3jZOSqbzjT0dKhg0WHYq+tnEs8x6fBn+Ji5sLyXsvR09YrNF8Iwc+nf2bRiUVcTbvKBLcJBMYEsit6F3mqPDb22/jIffl3cu/wzt53NF8aiZmJ/HDqB0JuhrDAZwGeTTwfafvS06FcCV1RlN7AfwFt4GchxNwSlhsEbAQ8hRDFn7tWoTq6daivV79QC/1eQk/KSuJc4jkcTB0080oqzCU9GUY6jGTd+XUsPrGYhb4LAfVZ16aITay/sL7IENaBLQcy03tmoWnxd+J5d++7NDBowHe+3xVJ5qCu6/OG8xu0aNCCj4M+Zvzu8ehr69O1WVeCrwUz4+AMfnz2x3J3x6TnpBMYE8jBuINk5WUB6pIVkamRzO5yf9SWj6UPH+77kEkBk1j//Hqa1avY8yWlp0+ZCV1RFG3AH3gWiAWOKYqyRQgR/sBy9YD3gCNVEWh5NTFqUjihp1zCo7EHoTdD2X9tf7EJXfahP5mM9Y0Z5TiK7098j9sqt0Lz2pu3Z4rHFE0S/OvSX6y/sJ6X7V7G0dQRgJz8HCYFTiItJ43fnvutyE1OD+pu1Z0NL2zgfNJ5Oll0oq5eXdaeX8vsI7PZFLGpUFXOB6XnpLP36l52RO/g8PXD5KnyaGTQSHN2qKuly/yu8+lp3VOzTmuT1vj38OeV/73C5MDJrOqzCn1t/Yc6VtLToTwtdC8gQggRCaAoyjqgP/Dgc8e+Ar4Bir+KVU3Mjcw1XS6ZeZlcTbtKX5u+5OTnEBQbxHiX8Zplk7OTMdQx1PSJSk+e1+xfQ19bX9PS1dHSwdfSF9sGtoWWs6pnxe4ru5lzdA6rnluFgsLsI7MJiw/j227f0qZhm3Ltz6q+FVb1rTTvX7F7hV3Ru5h/bD6dLDphrG9MQEwAR64fIV/kA+qGw6G4Q+SocrAwsmB42+H4NffDydSpUBdgcSzrWTKn8xze2fsOs4/MZkbHGZxPOk9gTCC2DWzlhVOpkPIk9KZAwULXsUD7ggsoitIOsBRCbFUUpcSErijKm8CbAFZWViUt9kiaGDXhxK0TAFxOuYxA0MqkFYqi8MPJH0jMTNQ8Ki05q/Tb/qXHn4GOASMdRpa5XF29ukxyn8T0A9PZGrmVzLxM/rz0J284vcGzzZ996P1rKVp82elLBm0ZxNhdY0nITOB27m2M9Y0x1DEEQF9bn5fsXuI5m+dwNnWu8EgZH0sf3nB6g2WnlxEUG0R8Zrxm30a6RrXu6VnSw3vki6KKomgB3wKjylpWCPET8BOAh4dHlTyXrIlRE9Jy0riTe0fTf97KpBXmdc3xP+nPgbgD9GvRDyi9MJdU+/Rr0Y8/LvzBvGPzuJ17m85NOzPBdcIjb9eqvhUfenzId8e/o7tVd/q16IdnE88yW98VMcF1AjcybpCak8o7Vu/g1cSLSQGTmLJvCqv7rK7QMwCk2qs8Cf0aYFngfbO70+6pBzgCgXdbHk2ALYqi9KuJC6MFhy5eTL6IgbYBzeo2Q1EUTA1NCYoNup/QyyjMJdUuWooW07ymMWzbMCzrWTK3y9xiyyY/jFfavMIrbV6plG0VR1tLm9ldZhea9n337xm6dSgT9kzg976/y7/lJ8Teq3vp3LRzsRfgH1V5EvoxoJWiKDaoE/kQ4NV7M4UQqYDmapKiKIHAhzWRzKHw0MVLKZdo0aCF5p+2c9PO7Lm6hzxVHjpaOiRnJdOyQcuaCFOqIc5mzizxW0IL4xYY6xvXdDiPxLyuOYu6L2L0jtFMCpjET8/+JK8HPQIhBFFpUZy8dZJT8ac4eetkoSHQTes2ZVbnWTg0cihlK6XbcnkLnwZ/ynvt3mOs09jKCLuQMhO6ECJPUZR3gJ2ohy0uF0KcVRRlJhAihNhS6VE9goIt9EvJl+jarKtmXtdmXdkUsYkZB2fQQL8BCZkJssvlKVSb+pydzZyZ3WU2H+77kI+DPmaBz4IyzzoSMxP5/fzvZOdlA1Bfvz4j7Edo+vxrs9z8XM4kniH0ZigpWeobCwWCmPQYTtw6obnZsL5efVzMXPBu6o0WWggEO6N3MmLbCKZ6TuVlu5crfC3k4LWDfHHgC9qbt2ekfdnXfR5GufrQhRDbgG0PTPu8hGW7PXpYD8+sjhkKCmcTz5KUlVTo6UKdLDphVc+KXVd2AeqLVa7PuNZUqJJUKXpZ9+LWnVvMOzaPecfmMc1rWqnJ5stDXxIYE6hpzWfmZXLsxjEW91j8xA+LTM9JZ/qB6cTdjisyTyCISo0iO1/9RVbwC+yZOs/g08yHdo3b4WrmirWxdZFrIGOdxvJJ8CfMOjKLkJshfNHxC+rq1S1XXOcSz/F+4PvYNrBlYbeFVfYAl1p1pyiox/Oa1TEj6Jr6OaCtTO4ndCNdI7a+uLWmQpOkKjPCfgQ3Mm7wW/hvNDZqzBjHMcUudyjuEAExAYVO+TdHbGb6gem8H/A+//X972P7tKic/BwuJV8iT+QBYKBtQGuT1povLyEEXxz8gsCYQLybeqNQ9EvNo7EHHo09cGvsVuFrDiYGJvj38Gf5meUsPrGYMwlnmNd1Hk5mTqWuF3c7jrf3vE19/fr80OOHSisVUZxal9BB3Y9+77mVBRO6JNVmH3h8QPydeBaGLqSBfoMiNXLyVHnMOzaPZnWbMcJ+hGZ6/5b9yVHlMPPQTD7c9yELui0oV/npyqISKs4lnuNSyiWEKDr4LS0njcPXDxN6M5TMvMxC83pb92am90wMdQz5/fzv/HvlXya7T2a04+gqiVVL0WKs01jcG7szdf9UXtv+GhPbTWSkw8hiRzWl56QzYc8EsvOyWfbcMhobNa6SuO6plQnd3MicsPgwGho0LPPuP0mqLe49jDstN40vD32Jka5RoRuPNlzcQERKBN91+65I18pLrV8iNz+XOUfnMGXfFOZ3nV+lLfW0nDQOxh0kKDaI4GvBmrpKJbGub83AlgNxb+xOHd06gLrw3pKTS4hOi+ZN5zdZELIAn2Y+5bov4VG5PePGhhc28OWhL/k29FsOXDvArM6zNIMyQF287cN9HxKdGs0Pfj/Q0qTqB2DU2oQOFOo/l6Snga62Lgu7LWTcv+OYFjSNnPwcrOtbk6vKxf+kP+2btKe7Vfdi13217asIBHOPzmVy4GT+0+0/lTq0LiY9hoCrAeyL3cfxm8fJE3kY6xvTyaITXZp2wcXMBR2toilJX1tfczNgQZ2bdsaxkSNT909lcuBkzI3M+brz15U6/r80xvrG/MfnP/x16S++OfYNL255kameU7E1Vt+l/OelPzkYd5AvO31JR4uO1RKTUtwpTnXw8PAQISFVM7Jxzbk1zD06l+FthzPVa2qV7EOSHmfpOem8vvN1ziWd00zTVrT544U/ynz49h8X/uCrw1/hbeFNH9s+gPralE8zH03ruCJ2RO3gx7AfiUiJAKBlg5Z0s+yGTzMfnEydHvlegOjUaBafXMxox9GPNKTwUVxJu8LHQR9zOuF0oeljHMfwvvv7lbovRVFChRAexc6rjQl9z9U9TAqYxJedvnyoWtuSVBvcyb3D8VvHNU98sqxnWe6Hgfx16S++PPRloadFOTRyYInfkgqVm45MjWTwlsFYG1szoMUAfK18saxnWfaKT6BcVS6hN0PJyc8BoK5uXdyecav0h6I8dQk9ITOBKfumMKfLnEJ9WpIklV9yVjK3c28DEJ4YzqfBn9K0blN+fPbHcv1fqYSKkdtHEpkayeYBm+X1rEpSWkKvns6mamZqaMqK3itkMpekR2BiYIJlPUss61nSy7oXS/yWcPPOTUZuH8mVtCtlrr/u/DpOxp9kqtdUmcyrSa1M6JIkVT7PJp4s77WczLxMRmwbwen40yUuG3c7ju+Of4e3hTcv2L5QjVE+3Wpll4skSVXnStoVxv07jsSsRBb4LMC+kT3bo7azLXIbtzJvAZCZm0meyGNT/02P/Hg+qbCnrg9dkqSqlZCZwIQ9EzifdB4FhXyRj0Mjh0LPdu1t3bvahus9TUpL6LVyHLokSVXL1NCUFb1W8P2J79HT1qNfi36yJvtjQCZ0SZIeSh3dOvI+j8eMvCgqSZJUS8iELkmSVEvIhC5JklRLyIQuSZJUS8iELkmSVEvIhC5JklRLyIQuSZJUS8iELkmSVEvIhC5JklRLyIQuSZJUS8iELkmSVEuUK6EritJbUZQLiqJEKIoyrZj54xRFOa0oyklFUYIVRbGv/FAlSZKk0pSZ0BVF0Qb8gecAe2BoMQn7dyGEkxDCFZgHfFvpkUqSJEmlKk8L3QuIEEJECiFygHVA/4ILCCHSCrw1AmqmyLokSdJTrDzlc5sCMQXexwLtH1xIUZQJwGRAD+he3IYURXkTeBPAysqqorFKkiRJpai0i6JCCH8hRAtgKvBZCcv8JITwEEJ4mJmZVdauJUmSJMqX0K8BlgXeN7s7rSTrgAGPEpQkSZJUceVJ6MeAVoqi2CiKogcMAbYUXEBRlFYF3vYFLlVeiJIkSVJ5lNmHLoTIUxTlHWAnoA0sF0KcVRRlJhAihNgCvKMoih+QCyQDI6syaEmSJKmocj1TVAixDdj2wLTPC/z8XiXHJUmSJFWQvFNUkiSplpAJXZIkqZaQCV2SJKmWkAldkiSplpAJXZIkqZaQCV2SJKmWkAldkiSplpAJXZIkqZaQCV2SJKmWkAldkiSplpAJXZIkqZaQCV2SJKmWkAldkiSplpAJXZIkqZaQCV166oTFppByJ6emw5CkSicTuvRU+Tf8Jv39D+AfEFHToUhSpZMJXXpqhMWmMHHtCYSAS7du13Q4klTpyvXEIkl60sUm32HMyhAaGulh1bAOkfEZNR2SJFU6mdClWinxdjZT/wzjVno2AHEpWWTn5bP2jfb8cyqOIwGJZOflo6+jXcORSlLlkQldqnXy8lW8u/YEIVeS8W7RCIBn6hnwlo8trRrXw8bMCJWAq4l3aNW4Xg1HK0mVRyZ0qdb5Zsd5Dl5O5D8vuTDIvVmR+bamdQGITMiQCV2qVeRFUalW2XzyGsuCohjZsXmxyRzAxswIgKgE2Y8u1S4yoUu1RmzyHab+GYaXdUM+e96+xOXqG+hiWlefyHg50kWqXWRCl2qNFQeiycsXLBziiq526X/atqZGsoUu1TrlSuiKovRWFOWCoigRiqJMK2b+ZEVRwhVFCVMUZY+iKM0rP1RJKll6Vi7rj8XQx8mcpg0My1zextRIDl2Uap0yE7qiKNqAP/AcYA8MVRTlwfPZE4CHEMIZ2AjMq+xAJak0G0NjuZ2dx5jONuVa3tbMiMSMHFLv5FZsR0HfwrIeEH/xIaKUpKpVnha6FxAhhIgUQuQA64D+BRcQQgQIIe7cfXsYKP5qlCRVgXyVYMWBaNybm+Bq2aBc69iY3r0wmliBVvrNsxDwNVwLgWW+cHbTw4QrSVWmPAm9KRBT4H3s3WkleR3YXtwMRVHeVBQlRFGUkPj4+PJHKUml2HPuJleT7jDGu3ytcwBbs7tDF8t7YVSlgn8mgYExjAsGszawYSTs/BTyZKEv6fFQqRdFFUUZDngA84ubL4T4SQjhIYTwMDMzq8xdS0+x5QeiaNrAkF4Ojcu9jlXDOmgpFRi6eHwlxB6FnrOgiROM3g6eb8ChxbC8FyRFPlzwklSJypPQrwGWBd43uzutEEVR/IBPgX5CiOzKCa/2SM7IwT8gguy8/JoOpVYJvZLM4cgkRnZqjk4ZI1sK0tPRwrK8NV1u34LdM8C6C7gMVU/T0YO+C+Dl3yDpMiztCqfWgxAP90EkqRKU507RY0ArRVFsUCfyIcCrBRdQFMUN+BHoLYS4VelR1gJ/Ho9l/s4L6GgpvOXToqbDqRWycvOZsvEU5sYGDPWyqvD6tqZGRJbUQt/4OpzZeP+9li70/RYUpfBy9v3Boh389Qb8/SZc2Kpezsi0wvFI0qMqM6ELIfIURXkH2AloA8uFEGcVRZkJhAghtqDuYqkLbFDUf/BXhRD9qjDuJ07olWQAFu+NYLB7MxrV1a/hiJ5883deIDI+g9Wvt6eegW6F17cxrcvhyCRUKoGWVoFEHXdCnczbPA+NHdTTmncCs9bFb6iBJYz8HxxcBIFz4MpBdddMg7ujd/XqQBPnol8GklTJylXLRQixDdj2wLTPC/zsV8lx1SpCCEKuJONm1YDTsal8t/sSXw1wrOmwHkuBF27xv7DrvOxhiae1CUoJSfBwZCLLD0QxokNzOrd6uNawrZkRmbn53EjLwqLg2PV988CgAQxYAgb1y7cxbR3oMhla94a/31K/Cmr5LPT9D5jIWzSkqiOLc1WDmKRM4tOzmdijFS7NGrDq8BVe69hcFoZ6QG6+iumbzxCTlMnG0FgcLOoz0K0phnpFS9wu3XcZq4Z1mPZcm4fen63p/ZoumoR+/RRc2Aa+n5Y/mRfU2B7e2AsxRyD/7hj3m2cgYA780AF8P4H249VfAJJUyeRfVTUIuZIEgEdzE553Muev47F8ve0cK0d71XBkj5dNJ64Rk5TJ90PdSM/KY8WBKGZtPVfssga6Wqx6vT1G+g//J3yvSFdk/G28W95t5e+bB/rG4PXmQ28XbV2w7nz/fQtfsB8A2z6EXZ/BybXQZz5Yez/8Pkpyci1cC4WOb0ND28rfvvRYkwm9GoRcSaaevg6tG9dDW0thYo9WzNp6jl1nb9DToUm5tvFL8P2heSV1Qzzu8lUCBQr3VxeY90PgZezN6/O8szmKojDUy5KE2zmIYkaO1NHXoe4jJHOAJvUNmKO3AquADI6nvIxDW3v0z/8PfKaBYfluUCq3BpYwdB2c+wd2fgIr+4DDi2DhencBBcxdwKqjegTNwzj0A+z8WP1zyHJwfgXcR4Hu3bMPQxN1HOWVfRvysu6GpwV1Gj5cXI+b1FjYPhVuhd+fZmIDToPV101KOzMTAk6thYg9YNsN2vR9rI6LUtw/S3Xw8PAQISEhNbLv6tZr4X4aGxvw2xh1izwnT0V//wMk3M5m16SumBiV/g98NfEOXecHANDNzoyZ/RyxalSnyuOuTEIIXl12hMvxtxnRoTmvtrcqdGF488lrvLfuJEuHu9PbsXxfco8sLwfV1+aohAodVADk6NRF74Mz6uRXVXLuQPBC9UXUewnzHl0jsPWBlj2gRffyt7KD/gN7ZkLbftBrNhxeok7qeZmFl7PrA53fB8syzg5Df4WtH4CqQGmEph7QYbx6ZI92xS9CV5mrhyFgNpjZqb/EmroXfwFaCAj7A7ZNAVUe2PVWf1EJAbHHIOUKaOtD657qL9vWvUDP6P76yVfgn/cgMgD060N2GmjpgI0PtH1BndzrPlPlH1dRlFAhhEex82RCr1qpmbm4ztzF+36tmdijlWZ6eFwa/RYH09fZnP8OcSt1Gz8HRTJr6zkm+LZg5YFo8lSC/w5xq77EVwlCopMYvPQQLcyMuByfgZ6OFv1cLHitY3McLYzp+d1+tBWF7e91KbYFXyVuhsOSjqj6LyH8thHXD67l34wWTP3o8+oZhZSXcz9h5mWrE1PEboj4F1KuqqebWIPrMHUi1S/hmkvgXPXoGqeXYMDS+/3zt2+pE9W9//Ebp+Hoj5CZrL45yuDuWYiekToRtu0HWtrqbe37Bmx91UkKICsVTv6uHnNfzwI8xoD7yGpJYCXKz1N/ke2bC3VM1THmZ6uPmXExZyLZ6XD9pPosaMAPhb8shYDYEDi9AcI3we2boGMITdupkz7AtePqLwq/GerPfyNMXf4hfDMkRwGK+oxLT30XMtq60NxbfQzN2lTaKCeZ0GtQwIVbjF5xjN/HtqdTy8KjMf67+xILd19k6fB29HY0L3EbLy09SHpWHjsmdeV6aiZDfzpME2MD1r3ZsarDrzRvrQrhcGQShz7uTlxKJisORPP3iWvcycnHulEdohPvsPhVN553tqi+oM78CRvHwFtBYO5MxK3bPLtwH+N8WjC198NfbH1kQqjvPL28Fy5sh8t7oE4j6PIBeLwOugb3l903HwJmqZN+v+/VCbk0ORnq1veFbaC6e5NbWqz6C8TYCp5pA5d2gdtweP67wi1xlUr9ZXN4ibqVqqUL9v3Uya25d9UPy0y8DIf875/V3DoHccfVX0Z9FgBC3aUVvkWdvB+kKGD3HHR4u/TjpMqHq4fgzF/qfdxj3Ax6fF6020oIdffNuX8gOvj+cc1OU18QB3WXjt1z6la/VaeH71ZDJvQatWDnBZbsu8zpGT2po1e4zzc3X8UA/wPcSM1i1/tdi20Vxqdn4zV7NxO7t+L9Z9XjoGf9L5zfDl8h7IueGOg+/g85jkrIoPt/Anm7Wwum9LqfKNOycvn7+DVWH75CHT1t/nrbG+3qap0D7P0aghbAJ9c1SfLdtSfYe+4mwVO7l9kVVm2uhaq7UyIDoZ45eE9St46PLFXfweo8RN3iLCuZl0SVDxd3wMHFcPUgdPsYfKaWnqATLqm7dE6sgexUaNQK2r0GFm7312vYAuqX3FCpkDN/wpaJIFTqLzcAHX3o+hG4vFI5+6gKaXHqL+UL2yAqSH0GoV8fnpsHrkMfapMyodegIT8dIiM7n3/e7Vzs/PM30ui3+ACe1ib8OtqryO3ra49e5eO/TrNtYhfsLdQXa/4Nv8kbv4Ww/s0OtLdtVOWf4VFN33SG9cdiCJ7qyzP1DcpeobqsH67udpl4XDPp0s10en63nwndWvJhL7saDK4YUfvV3StXDpCt1wD9nBTy7AehM3jZwyfzB2WmVOyCcM4ddRdF6K8Qc7jwPEVLfR3AdZi620GnnN1YuVkQte/+sM+I3RC6App5weDlFbuw+zjJyYDIfeovT7fhZV/HKEFpCV2OcqlCufkqTsakMMSz5NvS2zSpz6wBjny0MYwFuy4WGVe98+wNLBsaVG0QMwAAHzBJREFU0tb8fv+pl3VDFAUORyY99gk9OSOHDaEx9He1eLySOcCt8/BM20KTWjWuRx8nc1YejGZsFxsa1Kn+VvofITHoait0sG2EuXGBG55suoJNVwJ2/In2gYXcEC7MDX+J4bsjGO1tUzlnFBUd3aNXB1xfVb8SIiA9Tj1dqNQt0lNrYeNodZVKh4HqswmrDiW3/vNyYO0r6rORgjq9Cz2+eLwuxlaUnhG06aN+VRGZ0KvQ2bg0snJVeFqXPqzpZQ9LTsWksHTfZVyaGfOck/o0NT0rl4MRibzWsXmhoYrGdXRp26Q+R6ISgVYlbLWaJURA+vUikwNPxFI3VzC2S/FnKDUmL1vdT+0woMisd7u3ZGvYdd5de4KWz6gvcLk3N6mW/v1NJ67x0cYwzfvmjerwgrMFo72taVRXnx1nbvD2PgO8W/6HiT1a4bE/kkV7I9h+5gbb3+tSoQJllc60pfp1j2039Y1UkYEQtl49wiR0JTSwAsdB4DhYXVrh3t+2SgWbJ6iXf26e+uIlqIcRmlhX5yd5YsmEXoWO363f4t687CFwn79gz9m4ND7ccIq6Bjp0aWVG4IV4cvJV9CpmNEsH20asOXKF7Lx89HVquB89/QYs6aTuH3zAQOAFA210ArdCu5Hq4XiV1T3wKBIugchXjz54QJsm9RnW3ootp+I4GZNCTp6K349cpVMLUxpWYb96TNIdpm86g0dzE2b0c+BIVBJBl+LxD4zg5+BIXnC2YPPJOFwsG/DjCHfq6Ongad2QrWH/b+/Ow6Oq7sePv8/MZE/IQhZCCBBCIEAgYRUEFEEsm1JRBJeqVPTrvjz119r61FZ/6s9WW1yqVhTB6ldQQRGRoqAoyp4gBEIgJAGykIQsZCGBrOf3x7kJCSSQZSaTmZzX8+RJZuZm5lxu+Mydz/2cz8nhoY/3smZvFgsu8WnQLkxmdcwHTlN17YfXq0qSba+r0s3AwepNddiNqormwKcw9c9wxf9c/rm1i+iAbkP7s4rp1cOdXr6XTzW4Wcy8fccoFi7dyW+W7WZadDDnamoJ9HZlVN+L3xDGDwjg/W3HSMwquewnAJuLXw61VXDLh03qt/dlFvP3jYd4PiaPARlfqv/MPr3VRazY21pudtUZ8g+r7xekXOq9cONwXrhxOKDy6tOXbOXjXSd4eGr7PxEVlVfx+ndHmRodzOSowCafumrrJL/7dD8SWLIgjvAAT2LCfLlnUgSpp8p464c0Pv8lm8ggL5bfPbbJBfZZw3sRF+7Hq5uPMjcurOteKHfzhtiF6qu8QOXeD36hZuf++De1zdjFqppHaxcd0G0oMauEEX18W719qK8H3zx+Fcu3HefNLamcqaxh4djwZis/xkUYefS0QvsG9JoqVe0QNV2VsDXy3o69HHJ3I+yWacBLkPJfdRZWf3YWNhqG3wIx8zq/nvnUIRBm6DnwsptGhfgwOSqQ/+w4wX1XReJqUWmNVbszWLk7g/uuimRmTK9L1s/X1NbxyMq9bEstZMX248T28eWBKQOJNNoPrNt/kt3Hi/jH/FjCA5pOGhsY7MM/b4njqZnReLlaLmp3IITg9zMGc9u7u/ho5wkWT3aAKf9egSp4j10MZXmQvE7Vx0/+ne5K2QE6oNtISUU1xwrKuXl025ZXdXcx88CUSG4e3YeVuzO4cWTzq/35eboS3asHu44V8Yg1Btxeh9ZC+amLPiKXnK3m20N53Do23EgJmdUMw6Fz1X/gA5+qvOrGP6ip8AOmqMAePdu2szTrnToMPSNbXXnx20kRLFq+hw0Hcvj1yDAO55byzLokTAIe+ngvMWE9ePK6wVw9KKjZ1gwvf3uEbamFvGic9b/1Qyr3f5TQZJvZI0KZN6rl1R2DfVr+pHdlZCCTowJ5c0sqC8aGt6udsN34hMC4e+09CqegA7qNJGYXAxDbp309QYJ83JrMLG3OFREBrNqTQVVNXcNZY3tV1aiKnHERbTzb3/VvVYM8YGqTu9cnnqSqpo6bmntD8wlRVQtXPqImbiR+quqMv3xIrdsZOVWd7Q+eZbs+GfnJENL6FsZXRwUxIMiL97cdY0ZMLx5ftY8e7hY2PDaZn1IKWLI5hbuX72FkXz8enRbFlEaB/evEHN75MZ07xvfltitUjnv+mD78nFpAeWUNAC5mU4tvBq31f341mBv+tY03vk/lqRnRnTfjVusydEC3kcSsEgCGtyHl0lbjB/RkxfbjHMguZnS/jgW+935O5+8bj7Du4YmMuPBNqDANqisAKDpbh2/4MMwWi5oqnZ0AM18GU9M3lDUJWQwK8WZ42GX2P3gIXPsXNQPv5F41O+/Ql3D0G5USCY1t/iza1Vv1H+93Zdt3tvosFB1T6Z5WMpkEiyZG8Oe1B1n8QTyHc8tYfvdYgn3cuWl0H+bEhrI6IYu3tqSxaPkeIoO8Gi6gHswuZWRfP56ZM6zh+VzMJq4ZbN0004g+ftwQ25ulW9P5OjGHm0aFMW1ICC5G5UsPDwt9/B2rB5DWNjqg28i+zGIGBHrh62G7j771Z9M/HS3oUECXUvLJnkwA1u072TSgH/8ZVsxuuBkAnCKA9F4zGeaSg4+rz0Uz3tLyz7A3o5g/zYpu/RmnECqnHjZarfZzcq+awn3yF6CZyW95SbB8prq4Ov058G7DouMFKeo5g9s2vf+mUWG8vPEwP6cWcOeEflwTfT4gu1nM3H5FP+aPDueLX7JYn5hDbZ0a9zXRQTwzZ1iHP0W1xivzY5k+NIRP4zN5Y0sqr3+f2uTx2D6+/HpkGNfH9iZQr5rldHRAt5HErGIm2HjST4CXK6P7+fPq5qPsOV7EoisjuCY6uM3T53emF3GisIIe7hbWJ+bwp1lDzn9c37NMNXG64Q3iTxSz8qckFvrsY3TOKlxELV+4Xk/mz7nMGSHoa1zMW5OQhUnAr+NazgdfUuPg3pKqctj6Cmx/A5K+OJ93N7vAqN/A+IfUpJfmnDIqXIKar3BpiaerhSemD2LToTz+OLP533W1mFgwtq/dygddLSauj+3N9bG9yS4+y8HskobeXJlFFazdl82zXx3i5W+OsPr+KxtmH2vOQQd0G8gtOUdeaSWx4Vbuqd2MZXeN4ePdGXy44wSL/xNPeIAHt47ry/zR4QT5tO4M7NP4THzcLDw9ewh/WHOA+BOn1dl/eYFqODR2MQy9ga1ZR/hC9uSFJ1/kTPEpDv60lrV5Ufy4KYV/bkpp8pxTBgfZdmaoq5dK1cQuhD3vqTQKqN4Z3z+vSimvefp8v3FhUrl+s0Xlz00u6qJoGy2aGMGiiRFW3BHbCfPzIKzx0nrAvVcN4HBuKXcu280jK/fy1SOTLuoxpDkufSRtYH+WuiB6US7aBvw8XXlwykDunTyAb5Py+GjnCf6+8QhLNqVw3dBe3DI2nEkDA1s8ay85W82GAznMH9OHOSN685d1Sazbn60C+v6Vqr3r6LsASM4tIyLQC3cXM+5BoUye9wCTgZySs2w6lEdJheq9IQTMGm6lpkyXEzRYrf7T2PFtqnLmyweb3h8QqRpP5SWpckVHnkbeAdG9erBkQRx3LNvFc18d4qWbRth7SJqV6IBuA4lZxVhMgmGd+HHWxWxi9ohQZo8IJfXUGT7elcEXv2Tx9YEcQn3dmTcqjBtHhjEwuGlP7XX7sqmsqWPBmL54uVm4dkgIGw7k8tc5Q7EkrIDw8Q2Tb47kljV7kTPU14M7J/TvhL1spf4T4d4tcHyr6pENcK5UVeR8vljdHnaj/cbXBUwcGMgDV0fy1g9pTIoK7Ny2xZrN6IBuA/szSxjcy8duM/YGBnvzzPVD+cPMwXyXfIpP4zN5+4c03tySxvAwX+bG9WbOiN6qp/qeTIaG9iAmTL35XB/bm/WJOSTt+C+xhakw+UkAyitryCiqYH4b6+rtxmRSte2Nxd2u6uZ3vq0Wc+jmnpg+iO1phTy15gC/ZBQzfWgIY/r527cfjNYhOqBbQV7pOQ7llDJlkKq0SMwqZnYXOONxs5iZNTyUWcNDOVV2jq/25/DFL1k8/3UyL2xIZkQfP5JOlvLc3GEN1ShTBgfh426hNn6pWix56FwAjuSpBQMG92ph1RxHYDKpyUsx8+w9ki7BxWzizdtH8ee1B/lwxwmW/XwMP08XpgwKYuqQEK6OCsLXs3umpRyVDuhW8OrmFFbuzuSKiADuu2oApedqiLVh/Xl7BPu4c8+kCO6ZFEFa/hm+TsxhfeJJArxcmRt7vhrFzWLmxsEexBz+gdqxizAblSJHclVAj+6lqyKcSZifB+/fPZYzlTVsTcln86E8fkjJZ+0+1Qa3vurUJAQxYb5cHRXI1YODiO3jp8/ku6BWBXQhxAzgNcAMvCelfOmCx68CXgVGAAullKutPdCu7NDJUsL8PEjOKeWeD9SiHZ1R4dJekUHePDotikenRVFXJy+aUXiHTwKuooadAXMYb9x3JLcML1czffw9Ln5CzeF5u1kaPs3V1kn2ZRazM72Qymq1nFplTR17jhfxL6O23cfNwvjInkwaGMjEgT2JDPLu0CxXzTouG9CFEGbgTWA6kAXsEUKsk1IearRZBnA38KQtBtmV1dZJjuSVcdu4fjwwJZIXvj5EekE5UUYf7a6uuenhA/M2cpRw1mT7NwT05JxSBvXy0dPJuwGzSTC6n3+zbZ+LK6rYllrIz6n5/HS0gE2H8gDVqmLCgJ6ENXrDD/V1Z1xEAIOC9d9NZ2nNGfo4IFVKmQ4ghFgFzAUaArqU8rjxWJ0NxtilZRRVcK66juhQH4J83Hh14Uh7D6ljSrIwZe7kaNA9bErOo6a2DrNJcCSvjJmXWMha6x78PF0bqqkAThSWsyOtkB3phexML+T0QVW6KpFU10rjd1wY2z+AMf38GdM/gJiwHvbv4e+kWhPQw4DMRrezgCva82JCiPuA+wD69u1ijfjb6XBOKQBDnCW3nPQFAN6jF1C8toDdx4qIDPamuKKaaEe+IKrZRL+eXvTr6cXCcU3/P0spyTp9ll3HitiVXkj8idMNZ/OuFhPDw3wZ1dePkX39iQv3I9TXXadsrKBTL4pKKZcCS0EtEt2Zr20rybllmAREhThGiuWyDqyG3iMZO2oM7l9/y8akXKbWqp4lOqBrrSWEIDzAk/AAz4YW0vlllSScKCLhxGn2ZhTzwY4TvPvTMQCCfdyYGh3Ms3OH6bP3DmhNQM8GGi+z3ce4TwOO5JbS35g96fAK0yBnH1z3PB6uZqYMCuabpNyGhYp1hYvWEUE+bsyICWWGkbqrrKklOaeM/ZnFJJw4zao9mZSdq+GNW0fqnHs7tSag7wGihBARqEC+ELjNpqNyIIdzy4jp3bVKFC9JSqiraX7a+8HP1fdhqk57RkwvNibl8llCJr16uOuaZM2q3Cxm4sL9iAv3464r+zM8zJcXNiQT5OPGX64fqlMw7XDZQlIpZQ3wMPANkAx8KqVMEkI8J4S4AUAIMVYIkQXMB94RQiTZctBdRXllDScKKxwrFbHtNXg+BN6bDt89B2lbVOdCKeHgauh7JfiquvRrooNxMQvS88uJDnWgfdQc0r1XDeCeSRGs2H6cd7am23s4DqlVOXQp5QZgwwX3PdPo5z2oVEy34nCzJ6WEvR+An3EB6+dX4ad/gMkCIcPUwsmzXmnY3NfDhQmRgWxNyXecfdQc2tOzhnCqrJKX/nuYYB835o3qdmGlQ/RM0Q6onz05JNRBcssnf4GidLj+ddVBsbIMMnbCie2QsUN1IxzWdFr8jGG92JqS7zxVPFqXZjIJXpk/gsIzlfx+dSI9vd24elAbFi/p5nRA74DDOaV4u1ku6jndZR1co/qADzUaU7n5QNR09dWCG+J6c6zgDFOHWHe5NE1riZvFzDu/Gc0t7+zkgY8S+OS+CTZdytGZ6GYMHZCcW8agEG/HuCJfV6cueg689vzqPq3g7Wbh6dlD6eFIq8hrDs/H3YUPFo3F39OVRSt2k3W6wt5Dcgg6oLeTlJIjuWVEO0q6JWMHlJ2E4TfbeySa1irBPdz54LfjqKyu4/6PEjhn9JXRWqYDejvllp6j5Gw1Q+x9sbCuFmqrL7/dwdXg4gmDZ9p+TJpmJQODvXl1YRwHs0v50+cHkNIp5iPajM6hX8aBrBISThQ13O7X04vJUYEczqmvcLHzGfqKOXByL4TGQtgYCBulvvwjzvc+ra2GpLUqmLt62Xe8mtZG04aE8MS1g1iyOYWYMF8WTezf8JiuVW9KB/TL+P2aRJKNfi31Qnq4Ee6v+oTbtZyvJAsytkP/ySpoxy+DnW+qx9x9ITQOQkeA2RXOFkGMTrdojumRqQM5eLKE59Yf4rn1qi+gh4uZJQvimBHTy86j6zp0QL+EujpJWv4Z7prQj8evHYQE9hwvYtXuDH5IySci0AtfDzteLEz5Rn2f/Q+1WHJtNZxKVuWJJ/dCzn7YtRRqK8EjAAZOs99YNa0DTCbBkgVxrNqdwZnKGgA2J+fxxCf7CA+YwDBHmq1tQzqgX8LJkrNU1dQRHdoDfy9XAH41rBe/GtaLnJKz2D2dl7IR/PtD4CB12+yizshDR6g6c1BBviAFXDzA4ma3oWpaR3m7WVg8eUDD7duu6Mvcf23j3g/iWfvwRIJ93O04uq5BXxS9hGMF5QBEBF6cdw719aC3PevPq8oh/UcYNPN8rrw5Zhc1CzRgQMvbaJoDCvZx5907x3C6opr/+TCBvRmnyS4+S3Vtt1uWoYE+Q7+E+oA+oJmAbnfpP6pUyuAZ9h6JptlNTJgvSxbE8sD/7mXeW9sb7jc3MzdEAHeM7+fUjb90QL+E9PxyvN0sBPnYIFVRUaQm+LT3Dyvlv+DWQzXT0rRubEZMKD88OYX0/HJyS8+RV3qOmtqL86HHC8tZsf04AV6uPDotyg4jtT0d0C8hvaCciEAv67+bZ+6GZdMhKBpib4URC6BHG5Z3q6tTF0Qjp4LF1bpj0zQHVL9y0qVIKXG1mPjnphRCfd2ZPyb8kts7Ih3QL+FYwRlGhrd+mnzrn/hH9d3NBzb/Bb57FvpOgOg5MGTO+W6ILcnZB2fyYJBOt2haawkheGneCE6VVvLHzw+QeuoMbsbCNO4uJgI8XfHzdCXAyxV/Txf8PF3xdrM0fIh2MZuaTeV0JTqgt6Cyppas02eZN9IG7TuzElRlyuLNUJAKiZ/A4fXwzR/Vl0eAuogZMAACIlQli39/Feh9QlV1izBB1HXWH5umOTFXi4m37xjFouV72txzPTzAg28fvxoP1667OpkO6C04UViBlDAgyMoXRKWE7HgYaHQ4DBwIU59WX4VpKpVSkKLa3GbsgAOfAY3ygSYLCDP0GQdePa07Nk3rBnzcXVj9QNNrT2erajldUUVReRWnK6o4XVFNcUUV5ZWqf0zJ2Wr+/WMaK3dn8NtJEfYYdqvogN6C9Pz6ChcrL/5cnAHl+dBn9MWP9YyECQ82va+mCkoy4fQxKM5Uv1+arfLumqZZhYerGQ/XS5ci78s8zb9/TOO2K/p22TWEdUBvQX3JYv9AT+s+cXa8+h42pnXbW1xVoO8Zad1xaJrWJo9NG8St7+5k1e4M7p7YNc/S9cSiFhwrOEOQjxs+1u4DnpUAFnc12UfTNIcxIbIn4yICePvHtC7bylcH9Bak55fbZkJRdrxqmmXWC0ZomqN5bFoUeaWVfBafae+hNEunXFpwrKCc64aFWPdJa6tVw6yxi637vJqmdYorI3sypp8/f9t4hNV7s3G3mHB3MePuYsLNYsbNYmoyV7D+PrdGj7tZTEyIDLRJp1Yd0JtRUlFNYXlVsz1cOiTvINScg7BmLohqmtblCSF4cd5wXtt8lLLKGs5V11JcUUVlTR3nqmuprDnfR6ZOSqprJZXVtZyrqaO27ny12os3DtcBvbMcK6xvymXlCpes+guiOqBrmqMaFOLDm7ePavPv1dTWUVVbR2V1nc2qZHRAb0Z6/hmg+S6LHZK9F7yCLj8TVNM0p2Mxm7CYTXjasFtHqy6KCiFmCCGOCCFShRBPNfO4mxDiE+PxXUKI/tYeaGc6VlCO2SToG2CDksWwMe1vyKVpmnYJlw3oQggz8CYwExgK3CqEGHrBZvcAp6WUA4ElwN+sPdDOlF5QTri/B64WKxYBnS1WM0Cbm1CkaZpmBa1JuYwDUqWU6QBCiFXAXOBQo23mAn81fl4N/EsIIaQNluje8/lrBB1819pP28TjtRJPVzO8acUFLGrOqe+tnVCkaZrWRq0J6GFA46LLLOCKlraRUtYIIUqAnkBB442EEPcB9wH07du+PLLFuydFnrafpeXn7wnW7oM+YAr00/3LNU2zjU69KCqlXAosBRgzZky7zt5HXncHXHeHVcelaZrmDFqTJM4GGneC72Pc1+w2QggL4AsUWmOAmqZpWuu0JqDvAaKEEBFCCFdgIbDugm3WAcYy89wMfG+L/LmmaZrWssumXIyc+MPAN4AZeF9KmSSEeA6Il1KuA5YBHwohUoEiVNDXNE3TOlGrcuhSyg3Ahgvue6bRz+eA+dYdmqZpmtYWutuipmmak9ABXdM0zUnogK5pmuYkdEDXNE1zEsJe1YVCiHzgRBt+JZALZp52E91xv7vjPkP33O/uuM/Qsf3uJ6UMau4BuwX0thJCxEspu10jlO64391xn6F77nd33Gew3X7rlIumaZqT0AFd0zTNSThSQF9q7wHYSXfc7+64z9A997s77jPYaL8dJoeuaZqmXZojnaFrmqZpl6ADuqZpmpNwiIB+uUWqnYEQIlwIsUUIcUgIkSSEeMy4P0AIsUkIcdT47m/vsVqbEMIshPhFCLHeuB1hLDaeaiw+bsN10u1DCOEnhFgthDgshEgWQkzoJsf6CePv+6AQYqUQwt3ZjrcQ4n0hxCkhxMFG9zV7bIXyurHviUKIUR157S4f0Fu5SLUzqAF+J6UcCowHHjL28yngOyllFPCdcdvZPAYkN7r9N2CJsej4adQi5M7mNWCjlDIaiEXtv1MfayFEGPAoMEZKGYNqx70Q5zveK4AZF9zX0rGdCUQZX/cBb3fkhbt8QKfRItVSyiqgfpFqpyKlzJFS7jV+LkP9Bw9D7esHxmYfAL+2zwhtQwjRB5gNvGfcFsBU1GLj4Jz77AtchVpHAClllZSyGCc/1gYL4GGsbOYJ5OBkx1tKuRW1LkRjLR3bucB/pLIT8BNChLb3tR0hoDe3SHWYncbSKYQQ/YGRwC4gREqZYzyUC4TYaVi28irwe6DOuN0TKJZS1hi3nfF4RwD5wHIj1fSeEMILJz/WUsps4BUgAxXIS4AEnP94Q8vH1qrxzRECercihPAG1gCPSylLGz9mLOvnNHWmQog5wCkpZYK9x9LJLMAo4G0p5UignAvSK852rAGMvPFc1Btab8CLi1MTTs+Wx9YRAnprFql2CkIIF1Qw/18p5efG3Xn1H8GM76fsNT4bmAjcIIQ4jkqlTUXllv2Mj+TgnMc7C8iSUu4ybq9GBXhnPtYA1wLHpJT5Uspq4HPU34CzH29o+dhaNb45QkBvzSLVDs/IHS8DkqWU/2z0UOMFuO8CvuzssdmKlPKPUso+Usr+qOP6vZTydmALarFxcLJ9BpBS5gKZQojBxl3TgEM48bE2ZADjhRCext97/X479fE2tHRs1wF3GtUu44GSRqmZtpNSdvkvYBaQAqQBT9t7PDbax0moj2GJwD7jaxYqp/wdcBTYDATYe6w22v8pwHrj5wHAbiAV+Axws/f4bLC/cUC8cbzXAv7d4VgDzwKHgYPAh4Cbsx1vYCXqGkE16tPYPS0dW0CgqvjSgAOoCqB2v7ae+q9pmuYkHCHlommaprWCDuiapmlOQgd0TdM0J6EDuqZpmpPQAV3TNM1J6ICuOTSja+GDxs+9hRCrL/c7HXitOCHELFs9v6Z1lA7omqPzAx4EkFKelFLefJntOyIONTdA07okXYeuOTQhRH33zSOoSRtDpJQxQoi7UR3tvFCtSV8BXIHfAJXALCllkRAiEjWxIwioAO6VUh4WQswH/gLUoppIXYua+OKBmpr9/4D1wBtADOAC/FVK+aXx2jcCvqhGSx9JKZ+18T+FpmG5/Caa1qU9BcRIKeOMLpXrGz0Wg+pa6Y4Kxn+QUo4UQiwB7kR1elwK3C+lPCqEuAJ4C9VT5hngV1LKbCGEn5SySgjxDGom38MAQogXUe0KfiuE8AN2CyE2G689znj9CmCPEOJrKWW8Lf8hNE0HdM2ZbZGqt3yZEKIE+Mq4/wAwwuhseSXwmWotAqip6ADbgBVCiE9RTaSacx2qudiTxm13oK/x8yYpZSGAEOJzVGsHHdA1m9IBXXNmlY1+rmt0uw71t29C9eKOu/AXpZT3G2fss4EEIcToZp5fADdJKY80uVP93oW5TJ3b1GxOXxTVHF0Z4NOeX5Sq3/wxI19ev75jrPFzpJRyl5TyGdRiFOHNvNY3wCNG50CEECMbPTbdWEfSA5XL39aeMWpaW+iArjk0I62xzViQ9+V2PMXtwD1CiP1AEueXN3xZCHHAeN7twH5Um9ehQoh9QogFwP9FXQxNFEIkGbfr7Ub1tk8E1uj8udYZdJWLplmZUeXScPFU0zqLPkPXNE1zEvoMXdM0zUnoM3RN0zQnoQO6pmmak9ABXdM0zUnogK5pmuYkdEDXNE1zEv8f2+E8LeGuT3EAAAAASUVORK5CYII=\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['percentageOfActiveProposals','percentageOfCompletedProposals','percentageOfKilledProposals'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f40a617b250>"
|
||
]
|
||
},
|
||
"execution_count": 34,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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\n",
|
||
"text/plain": [
|
||
"<Figure size 432x288 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {
|
||
"needs_background": "light"
|
||
},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"df.plot('timestep',['percentageOfActiveFundsRequested','percentageOfCompletedFundsRequested','percentageOfKilledFundsRequested'])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Conclusion\n",
|
||
"\n",
|
||
"We have created a conviction voting model that closely adheres to the 1Hive implementation. This notebook describes the use case, how the model works, and provides descriptions of how it fits together."
|
||
]
|
||
}
|
||
],
|
||
"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": "3.7.5"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|