# General configuration
import json

with open('settings.json', 'r') as f:
    settings = json.load(f)

network_params = settings[0]
environment_params = settings[1]


'''
environment_params = {
    # Zombie model
    'bite_prob': 0.01,  # 0-1
    'heal_prob': 0.01,  # 0-1

    # Bass model
    'innovation_prob': 0.001,
    'imitation_prob': 0.005,

    # Sentiment Correlation model
    'outside_effects_prob': 0.2,
    'anger_prob': 0.06,
    'joy_prob': 0.05,
    'sadness_prob': 0.02,
    'disgust_prob': 0.02,

    # Big Market model
    ## Names
    'enterprises': ["BBVA", "Santander", "Bankia"],
    ## Users
    'tweet_probability_users': 0.44,
    'tweet_relevant_probability': 0.25,
    'tweet_probability_about': [0.15, 0.15, 0.15],
    'sentiment_about': [0, 0, 0],  # Default values
    ## Enterprises
    'tweet_probability_enterprises': [0.3, 0.3, 0.3],

    # SISa
    'neutral_discontent_spon_prob': 0.04,
    'neutral_discontent_infected_prob': 0.04,
    'neutral_content_spon_prob': 0.18,
    'neutral_content_infected_prob': 0.02,

    'discontent_neutral': 0.13,
    'discontent_content': 0.07,
    'variance_d_c': 0.02,

    'content_discontent': 0.009,
    'variance_c_d': 0.003,
    'content_neutral': 0.088,

    'standard_variance': 0.055,

    # Spread Model M2 and Control Model M2
    'prob_neutral_making_denier': 0.035,

    'prob_infect': 0.075,

    'prob_cured_healing_infected': 0.035,
    'prob_cured_vaccinate_neutral': 0.035,

    'prob_vaccinated_healing_infected': 0.035,
    'prob_vaccinated_vaccinate_neutral': 0.035,
    'prob_generate_anti_rumor': 0.035
}
'''