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Task/Percolation-Mean-run-density/Fortran/percolation-mean-run-density.f

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+! loosely translated from python.  We do not need to generate and store the entire vector at once.
+! compilation: gfortran -Wall -std=f2008 -o thisfile thisfile.f08
+
+program percolation_mean_run_density
+  implicit none
+  integer :: i, p10, n2, n, t
+  real :: p, limit, sim, delta
+  data n,p,t/100,0.5,500/
+  write(6,'(a3,a5,4a7)')'t','p','n','p(1-p)','sim','delta%'
+  do p10=1,10,2
+     p = p10/10.0
+     limit = p*(1-p)
+     write(6,'()')
+     do n2=10,15,2
+        n = 2**n2
+        sim = 0
+        do i=1,t
+           sim = sim + mean_run_density(n,p)
+        end do
+        sim = sim/t
+        if (limit /= 0) then
+           delta = abs(sim-limit)/limit
+        else
+           delta = sim
+        end if
+        delta = delta * 100
+        write(6,'(i3,f5.2,i7,2f7.3,f5.1)')t,p,n,limit,sim,delta
+     end do
+  end do
+
+contains
+
+  integer function runs(n, p)
+    integer, intent(in) :: n
+    real, intent(in) :: p
+    real :: harvest
+    logical :: q
+    integer :: count, i
+    count = 0
+    q = .false.
+    do i=1,n
+       call random_number(harvest)
+       if (harvest < p) then
+          q = .true.
+       else
+          if (q) count = count+1
+          q = .false.
+       end if
+    end do
+    runs = count
+  end function runs
+
+  real function mean_run_density(n, p)
+    integer, intent(in) :: n
+    real, intent(in) :: p
+    mean_run_density = real(runs(n,p))/real(n)
+  end function mean_run_density
+
+end program percolation_mean_run_density