add the benchmark example

Author: AhmedMagdyHendawy

PyLinearSolver/IterativeSolvers.py

@@ -1,12 +1,11 @@
 try:
     from julia.api import Julia
     from julia import Main
+
+    julia = Julia()
+    Main.eval("using IterativeSolvers")
 except: 
     print("Installing Julia is Required")
- 
-def start():
-    julia = Julia()
-    Main.using("IterativeSolvers")
 
 def cg(A,b,**kwargs):
     '''

examples/benchmark_scipy.py

@@ -10,24 +10,18 @@
 A = np.random.rand(n,n) 
 A = A * A.T 
 b = np.random.rand(n)
-IterativeSolvers.start()
 
 start = time.time()
 x = IterativeSolvers.cg(A,b)
-print("Iterative Solvers CG Computational Time: %.3f"%(time.time()-start))
+print("Iterative Solvers CG Computational Time: %.7f"%(time.time()-start))
 print("Iterative Solvers CG Solution: ",x)
 
 start = time.time()
 x = linalg.cg(A,b)
-print("Scipy CG Computational Time: %.3f"%(time.time()-start))
+print("Scipy CG Computational Time: %.7f"%(time.time()-start))
 print("Scipy CG Solution: ",x)
 
 start = time.time()
-x = IterativeSolvers.cg(A,b)
-print("Iterative Solvers CG Computational Time: %.3f"%(time.time()-start))
-print("Iterative Solvers CG Solution: ",x)
-# N= 10
-
-# N = 100
-
-# N = 1000
+x = IterativeSolvers.gmres(A+2,b)
+print("Iterative Solvers CG Computational Time: %.7f"%(time.time()-start))
+print("Iterative Solvers CG Solution: ",x)