Noisy T1 Relaxation Model

In [2]:

    

%matplotlib inline
import os

working_directory = os.path.pardir

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

from distributions import NormalDistribution
import matplotlib.pyplot as plt
import numpy as np


    

In [3]:

    

norm = NormalDistribution()


    

In [4]:

    

norm.sample(3)


    

    
Out[4]:





array([-2.84380165, -0.59322433,  0.35796748])

In [5]:

    

plt.plot(norm.distribution.pdf(np.linspace(-3, 3, 100)))
plt.show()


    

In [6]:

    

from t1_simulator import *


    

In [7]:

    

plt.plot(np.linspace(0, 1, 1000), create_noise_process(np.linspace(0, 1, 1000)))
plt.show()


    

In [19]:

    

taus = np.linspace(0, 10, 1000)
noise = create_noise_process(taus, amplitude=1)


    

In [20]:

    

plt.plot(taus, calculate_t1_noisy(taus, 1))
plt.axis([0, 10, 0, 1.5])
plt.show()


    

In [25]:

    

plt.plot(taus, calculate_t1_noisy(
            taus, 1, create_noise_process(taus, amplitude=0.01))
        )
plt.axis([0, 10, 0, 1.5])


    

    
Out[25]:





[0, 10, 0, 1.5]






    

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