Connectivity between three-nodes motifs

In [1]:

    

# loading python modules
import numpy as np
np.random.seed(0)

%matplotlib inline  

from __future__ import division


    

In [2]:

    

# loading custom inet modules
from inet import DataLoader, __version__
from inet.motifs import iiconcounter

from inet.utils import II_slice
print('Inet version {}'.format(__version__))


    

    




Inet version 0.0.12

In [3]:

    

# use the dataset to create the null hypothesis
mydataset = DataLoader('../data/PV')


    

    




 190 syn  files loaded

In [4]:

    

# for the moment, we only count experiments with 3 PVs
# later we use mydataset.PV[2:]|
PV3 = sum(mydataset.IN[3].values())
PV3


    

    
Out[4]:





8

In [5]:

    

# select experiments with only 3 PVs
pvlist =  list()
for i in range(len(mydataset)):
    if '3_1' in mydataset.experiment[i]['fname']:
        pvlist.append(i)
        print('{:3d} --> {}'.format(i, mydataset.experiment[i]['fname']))


    

    




  3 --> 3_170824_01.syn
 42 --> 3_170822_01.syn
 45 --> 3_170829_01.syn
 59 --> 3_170830_02.syn
118 --> 3_170622_03.syn
131 --> 3_170412_01.syn
156 --> 3_170830_01.syn
183 --> 3_171016_01.syn

In [6]:

    

#check that experiment
II_slice(mydataset.experiment[56]['matrix'],3)


    

    
Out[6]:





array([[0, 1, 1],
       [0, 0, 0],
       [0, 0, 0]])

In [7]:

    

matrix = II_slice(mydataset.experiment[56]['matrix'],3)
matrix


    

    
Out[7]:





array([[0, 0, 0],
       [1, 0, 3],
       [3, 1, 0]])

In [8]:

    

mymatrix = matrix.copy()
mymatrix[mymatrix==2]=0
mymatrix


    

    
Out[8]:





array([[0, 0, 0],
       [1, 0, 3],
       [3, 1, 0]])

In [9]:

    

iiconcounter(matrix)


    

    
Out[9]:





{'ii_con_c1e': {'found': 0, 'tested': 0},
 'ii_con_c2': {'found': 0, 'tested': 0},
 'ii_con_c2e': {'found': 0, 'tested': 0},
 'ii_con_chem': {'found': 0, 'tested': 0},
 'ii_con_elec': {'found': 0, 'tested': 10}}

In [12]:

    

np.nonzero(mymatrix)


    

    
Out[12]:





(array([1, 1, 2, 2]), array([0, 2, 0, 1]))

In [24]:

    

pre, post = np.nonzero(mymatrix)
np.unique(post, return_index=1, return_counts=1)


    

    
Out[24]:





(array([0, 1, 2]), array([0, 3, 1]), array([2, 1, 1]))

In [10]:

    

# count number of total convergent motifs
mydataset.motif['ii_con']


    

    
Out[10]:





{'found': 1, 'tested': 21}

In [11]:

    

# select recording of the only convergent motifs
for i in pvlist:
    if mydataset.experiment[i]['motif']['ii_con'] ['found']:
        print(i)


    

    




56

In [12]:

    

# count number of total convergent motifs
mydataset.motif['ii_div']


    

    
Out[12]:





{'found': 2, 'tested': 21}

In [13]:

    

# select recording of the only convergent motifs
for i in pvlist:
    if mydataset.experiment[i]['motif']['ii_div']['found']:
        print(i)


    

    




56

In [14]:

    

# count number of total convergent motifs++
mydataset.motif['ii_lin']


    

    
Out[14]:





{'found': 2, 'tested': 21}

In [15]:

    

# select recording of the only convergent motifs
for i in pvlist:
    if mydataset.experiment[i]['motif']['ii_lin']['found']:
        print(i)


    

    




56

In [16]:

    

matrix = II_slice(mydataset.experiment[56]['matrix'],3)


    

In [17]:

    

matrix[1,1]=2


    

In [18]:

    

for i in range(3):
    print(matrix[:,i])


    

    




[0 1 3]
[0 2 1]
[0 3 0]

In [19]:

    

np.nonzero(matrix[:,0])


    

    
Out[19]:





(array([1, 2]),)

In [38]:

    

from itertools import permutations


    

In [79]:

    

permutations?


    

In [82]:

    

for i,j in permutations(np.array([1,2,3]), 2):
    print(i,j)


    

    




(1, 2)
(1, 3)
(2, 1)
(2, 3)
(3, 1)
(3, 2)

In [86]:

    

permutations(3, 2)


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-86-9d47d0673c7d> in <module>()
----> 1 permutations(3, 2)

TypeError: 'int' object is not iterable

In [77]:

    

matrix


    

    
Out[77]:





array([[0, 0, 0],
       [1, 2, 3],
       [3, 1, 0]])

In [ ]: