In [1]:

    

import os.path as op
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline


    

In [2]:

    

plt.style.use('ggplot')


    

In [3]:

    

import shablona as sb
data_path = op.join(sb.__path__[0], 'data')


    

In [4]:

    

ortho_x, ortho_y, ortho_n = sb.transform_data(op.join(data_path, 'ortho.csv'))
para_x, para_y, para_n = sb.transform_data(op.join(data_path, 'para.csv'))


    

In [5]:

    

model = sb.Model()


    

In [6]:

    

ortho_fit = model.fit(ortho_x, ortho_y)
para_fit = model.fit(para_x, para_y)


    

In [7]:

    

ortho_fit.params


    

    
Out[7]:





array([ 0.46438638,  0.13845926])

In [8]:

    

para_fit.params


    

    
Out[8]:





array([ 0.57456788,  0.13684096])

In [9]:

    

fig, ax = plt.subplots(1)
x_predict = np.linspace(0, 1, 100)
for x, y, n in zip(ortho_x, ortho_y, ortho_n):
    ax.plot(x, y, 'bo', markersize=n)
    ax.plot(x_predict, ortho_fit.predict(x_predict), 'b')

for x,y,n in zip(para_x, para_y, para_n):
    ax.plot(x, y, 'go', markersize=n)
    ax.plot(x_predict, para_fit.predict(x_predict), 'g')

ax.set_xlabel('Contrast in interval 1')
ax.set_ylabel("Proportion answers '1'")
ax.set_ylim([-0.1, 1.1])
ax.set_xlim([-0.1, 1.1])
fig.set_size_inches([8,8])


    

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