Slicing matrices



In [1]:

    
import numpy as np
from inet import utils



In [2]:

    
nPV = 2 
matrix = np.loadtxt('../data/2_170411_01.syn', dtype=int)# load an example matrix
ncells = matrix.shape[0]
matrix









    Out[2]:





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

Select only reciprocal inhibition (II)

Reciprocal connections are bidirectional connections between PV interneurons



In [3]:

    
matrix[:2][:,(0,1)] # II = matrix[ :nPV][ :,range(nPV)]









    Out[3]:





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



In [4]:

    
utils.II_slice(matrix,2)









    Out[4]:





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

Select connections from inhibitory to excitatory neurons (IE)



In [5]:

    
utils.IE_slice(matrix,2)









    Out[5]:





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



In [6]:

    
matrix[:2][:,(2,3,4,5,6)] # IE = matrix[ :nPV][ :,range(nPV,ncells)]









    Out[6]:





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

Select connections from excitatory to inhibitory neurons (EI)



In [7]:

    
utils.EI_slice(matrix,2)









    Out[7]:





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



In [8]:

    
matrix[2:][:,(0,1)] # EI = matrix[nPV:][,:range(nPV)]









    Out[8]:





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



In [ ]: