diff --git a/fsm.py b/fsm.py
index 77a3096..2116764 100644
--- a/fsm.py
+++ b/fsm.py
@@ -1,9 +1,98 @@
+import numpy as np
+import matplotlib.pyplot as plt
+from numba import jit
 
-class FSM():
-
-    def __init__(self):
-        
-
+@jit(nopython=True)
+def gsi(isweepStart, isweepEnd, istep, jsweepStart, jsweepEnd, jstep, u):
+    bx = len(u)-1
+    by = len(u[0])-1
+    for i in range(isweepStart, isweepEnd, istep):
+        for j in range(jsweepStart, jsweepEnd, jstep):
+            # Local Solver
+            if not((i == 0) or (i == bx)):
+                a = min(u[i-1][j], u[i+1][j])
+            else:
+                if((i == 0)):
+                    a = min(u[i][j], u[i+1][j])
+                else:
+                    a = min(u[i][j], u[i-1][j])
+            if not((j==0) or (j == by)):
+                b = min(u[i][j-1], u[i][j+1])
+            else:
+                if((j == 0)):
+                    b = min(u[i][j], u[i][j+1])
+                else:
+                    b = min(u[i][j], u[i][j-1])
+            ubar = inf
+            if(abs(a-b) >= f[i][j]*h):
+                ubar = min(a,b) + f[i][j]*h
+            else:
+                ubar = (a + b + np.sqrt(2*(f[i][j]*h)**2 - (a - b)**2))/2
+            u[i][j] = min(ubar, u[i][j])
+    return u
+def norm_2(mat1, mat2, h):
+    return np.sqrt(sum(sum(abs(mat1-mat2) ** 2))* h**2)
 
+    
 if __name__ == "__main__":
-    print("-")
\ No newline at end of file
+    gridNum =500
+    center = round((gridNum)/2.0)
+    inf = 10**6 # Assign Large positive value as Sup-Viscosity Solution
+    h = 0.02 # 
+    u = np.zeros((gridNum+1, gridNum+1))
+    f = np.zeros((gridNum+1, gridNum+1))
+    for i in range(0, gridNum+1, 1):
+        for j in range(0, gridNum+1, 1):
+            u[i][j] = inf
+    # ------  A Layer Model ----------------------
+    for i in range(0, gridNum+1, 1):
+        for j in range(0, gridNum+1, 1):
+            if i < center:
+                f[i][j] = 1/1
+            else:
+                f[i][j] = 1/2
+    #---------------------------------------------
+    src_x = 0
+    src_y = 0
+    u[src_x][src_y] = 0
+    # --------------------------------------------
+    dict1 = {
+    "1": [gridNum,-1,0, gridNum,-1,0],
+    "2": [gridNum,-1,0, 0,1,gridNum+1],
+    "3": [0, 1,gridNum+1, gridNum,-1,0],
+    "4": [0, 1,gridNum+1, 0,1,gridNum+1]
+    }
+    MaxIteration = 3 # In simple model error less than tolerance after 1-2 Iteration 
+    last_u = u.copy()
+    # While(error<tolerance)
+    for i in range(MaxIteration):
+        [isweepStart,istep,isweepEnd,jsweepStart,jstep, jsweepEnd] = dict1["1"]
+        u = gsi(isweepStart, isweepEnd, istep, jsweepStart, jsweepEnd, jstep, u)
+        [isweepStart,istep,isweepEnd,jsweepStart,jstep, jsweepEnd] = dict1["2"]
+        u = gsi(isweepStart, isweepEnd, istep, jsweepStart, jsweepEnd, jstep, u)    
+        [isweepStart,istep,isweepEnd,jsweepStart,jstep, jsweepEnd] = dict1["3"]
+        u = gsi(isweepStart, isweepEnd, istep, jsweepStart, jsweepEnd, jstep, u)
+        [isweepStart,istep,isweepEnd,jsweepStart,jstep, jsweepEnd] = dict1["4"]
+        u = gsi(isweepStart, isweepEnd, istep, jsweepStart, jsweepEnd, jstep, u)
+        print(norm_2(u, last_u,h))
+        last_u = u.copy()
+    print('---------------')
+    
+    # ------  Show some figure ----------------------
+    fig = plt.figure(figsize=(5, 5), dpi=300)  
+    ax = plt.gca()  
+    plt.imshow(u)
+    ax.invert_yaxis()
+    plt.title("FSM")
+    cbar = plt.colorbar(fraction=0.05, pad=0.05)
+    plt.show()
+    
+    fig = plt.figure(figsize=(5, 5), dpi=300)  
+    ax = plt.gca()  
+    print(len(u))
+    wait_item = abs(u)
+    ctr = plt.contour(wait_item, levels=14,rightside_up =True)
+    plt.clabel(ctr,fontsize=6,colors=('r'))
+    k = plt.imshow(1/f)
+    plt.show()
+