General/MagnaSim.py

#! /usr/bin/env python3

import math
import numpy as np
import pandas as pd

class Populations:
    """
    This class is made of a pd.Series of the clients and the operation that 
    can be made on the population.
    """
    def __init__(self, carac):
        """
        Population constructor, initialises the client population with
        the caracterictic given to it.
        """
        self.population = pd.Series()
        self.nmbr = carac
        self.add_client(self.nmbr)
        """
        We have to define more caracteristics. We will start with a
        simple serie of inds and their number
        """
        return

    def add_client(self, nb):#Need to add an arg "habits"
        """
        Add 'nb' clients to the population.
        """
        start = len(self.population)
        end = start + nb
        inds = []
        for i in range(nb):
            inds.append(Individu())
        self.population = self.population.append(pd.Series(inds, index=range(start, end)))
        self.nmbr += nb
        return
    

class Individu: #tout OK
    """
    This class define the clients, it's caracteristics being :
        - User habits :
            - The habits with the Magna Wallet and the 3 tokens :
                -self.magna_wallet_btc
                -self.magna_wallet_eth
                -self.magna_wallet_mgn
            They containe statisctical law of the user habits.
    The methods of this class operate on only one client.
    """

    def __init__(self):#OK
        """
        Constructeur d'une instance 'individu'.
        Ce constructeur fait appel aux fonction especes et aleatoire
        pour initialisé les variables d'un individu aux valeurs propres
        à son espèce.
        """
        # Those 3 caracteristic are the users habits concerning the client
        # use of Magna Wallet
        self.magna_wallet_btc = (
            np.random.normal(
                loc=0.00001, scale=0.002),
            abs(np.random.normal(
                loc=0.002, scale=0.01))
        )
        self.magna_wallet_eth = (
            np.random.normal(
                loc=0.01, scale=0.9),
            abs(np.random.normal(
                loc=0.5, scale=5))
        )
        self.magna_wallet_mgn = (
            np.random.normal(
                loc=1, scale=10),
            abs(np.random.normal(
                loc=10, scale=50))
        )
        return