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%matplotlib inline
import os

working_directory = os.path.pardir

import sys
sys.path.insert(0, working_directory)

from models import smc
import matplotlib.pyplot as plt
import numpy as np
import logging


    

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log = logging.getLogger(__name__)
log.setLevel(logging.DEBUG)


    

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true_t1 = 2.5
noise = smc.GaussianDistribution(standard_deviation=0.1)


    

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model = smc.T1Model(true_t1, noise=noise)


    

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parameter_space = np.linspace(2, 3, 1000)


    

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prior = np.ones(1000) / sum(np.ones(1000))


    

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simulator = smc.SequentialMonteCarlo(model, parameter_space, prior, number_of_iterations=20)


    

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weights = [weight for weight in simulator]


    

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print(weights)


    

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plt.plot(parameter_space, weights[19].weights)
plt.show()


    

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prior


    

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weights[1].weights


    

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print([a for a in range(10)])


    

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