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#Gst generator,it is possible to choose a type of texture for the cell couture.
 
import numpy as np
 
import pickle
 
import random
 
import matplotlib.pyplot as ptl
 
import copy
 
from matplotlib import pyplot as plt
 
import random
 
from scipy import ndimage
 
from bio2mslib.inout.inout import WriteData as WD
 
import os
 
 
#Selection of desire treated surface, Gts
 
First_Pickle= True
 
square_grid=False
 
highs_grid=False
 
diagonal=True
 
 
if First_Pickle== True:
 
#L is the matrix dimension
 
L =12
 
Lx =np.linspace(0, L, 12)
 
Ly =np.linspace(0, L, 12)
 
#G is the ground, an empty matrix to add the desire surface
 
G= np.zeros((L,L))
 
#Gts us the ground for treated surface
 
Gts = copy.deepcopy(G)
 
if square_grid==True:
 
# #Square grid
 
for i in range (1,len(Lx)-1):
 
for j in range(1,len(Ly)-1):
 
if ((i % 2) !=0) or ((j % 2) ==0):
 
Gts[i,j] = 0.5
 
elif highs_grid==True:
 
for i in range (1,len(Lx)-1):
 
for j in range(1,len(Ly)-1):
 
if i==0 or j==0 or i==len(Lx)-1 or j==len(Ly)-1:
 
Gst[i,j] = 0.5
 
elif i==1 or j==1 or i==len(Lx)-2 or j==len(Ly)-2:
 
Gts[i,j] = 0.7
 
elif diagonal==True:
 
for i in range (1,len(Lx)-1):
 
for j in range (1,len(Ly)-1):
 
if (i == j):
 
Gts[i,j]=0.5
 
else:
 
with open('G_surface_empty.pkl', 'rb') as csv_file:
 
Gts = pickle.load(csv_file)
 
 
with open('G_surface_empty.pkl', 'wb') as csv_file:
 
pickle.dump(Gts,csv_file)
 
 
im = plt.imshow(Gts, cmap="copper_r")
 
plt.show()
 
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