Update README.md

Cell_behavior_initial_steps/single_cell_prolif_migr.py

+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
+from Gts_selection import L, Lx, Ly
+from bio2mslib.analysis.models import CellModels as DM
+from matplotlib.pyplot import figure
+
+#Declaring saving paths for results
+ls_images=[]
+results_path = os.getcwd()+os.sep+"Single_cell"
+path_simulation_gif =os.getcwd()+os.sep+"Single_cell"
+path_simulation = results_path+os.sep+"prolif_migr"
+if os.path.isdir(path_simulation) == False :
+    os.mkdir(path_simulation)
+        
+#Reopening choosen surface
+with open('Gts_Sample_100.cvs', 'rb') as csv_file:
+     Gts = pickle.load(csv_file)
+
+# #Visual preentation in image of the matrix
+# im1 = plt.imshow(Gts, cmap="bone")
+# plt.show()
+#Gs is ground seeded, a copy of the choosen surface to seed the cells,
+Gs = copy.deepcopy(Gts)
+
+#uni_cell is the seeding of a single cell inside the treated surface.
+uni_cell = Gs[(86,8)]
+Gs[(86,8)] = 1
+
+#Variable deffinition for PDE proliferation & migration model
+Cd =  1*10**-5 #Cell density
+NO2 = 10**2 #nutrient concentration
+Cdmax = 10**7 #maximum cell density
+Dm = 0.001 #Cell motility coefficient
+CRgrw = 1 #rate of cell growth
+CRNO2 =10**-8 #Consumption rate of nutrients
+DNO2 = 2*10**-5
+dt = 1 #time step
+time_lapse = 0.1
+
+Gscopy = copy.deepcopy(Gs)
+Laplace = ndimage.laplace(Gs)
+#Migration 
+iter = 0
+while iter<= 15:
+    for mi in range(1, len(Lx)-1):
+        for mj in range(1, len(Ly)-1):
+                x = random.randint(-1,1)#horizontal value for the movement of the cell
+                y = random.randint(-1,1)#vertival value for the movement of the cell
+                if Gs[mi,mj]==1 and (x != 0 or y!= 0) and ((mi+x)<len(Lx)) and ((mj+y)< len(Ly)):
+                    Gs[mi+x,mj+y]= 1
+                    Gs[mi,mj]=0
+                    #Proliferation after migration
+                    Gs[mi,mj] = Gscopy[mi,mj] + dt*Dm*Laplace[mi,mj]*(1-(Gscopy[mi,mj]/Cdmax))+CRgrw*1*Gscopy[mi,mj]*(1-(Gscopy[mi,mj]/Cdmax))                
+                    if Gs[mi,mj]>0 and Gs[mi,mj]!=0.7 and Gs[mi,mj]!=0.5 :
+                        Gs[mi,mj]=1
+                        zoom = True
+                        im2 = plt.imshow(Gs, cmap="bone", norm = None)
+                        plt.show()
+                        name = 'Single_cell_SMAT_sample'+str(iter)+'.png'
+                        plt.imsave(os.path.join(path_simulation, name), Gs, cmap="bone")
+                        filename = name
+                        ls_images.append(filename)
+                        iter+=1
+                        
+WD().create_gif_from_images(files_path=results_path+os.sep+"prolif_migr",results_path=path_simulation_gif,filename='Cell_behavior_SMAT.gif', time_lapse= time_lapse, deleteOriginFiles=0)
+
+