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Gts_selection.py 1.59 KiB
#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()