Merge pull request CEMeNT-PSAAP#120 from ilhamv/main

update c5g7 examples

examples/c5g7/3d/TDX/input.py

@@ -283,7 +283,7 @@ def set_mat(mat):
 # At highest energy
 
 energy = np.zeros(7)
-energy[-1] = 1.0
+energy[0] = 1.0
 
 source = mcdc.source(
     point=[pitch * 17 / 2, -pitch * 17 / 2, 0.0], time=[0.0, 15.0], energy=energy
@@ -295,10 +295,10 @@ def set_mat(mat):
 
 # Tally
 t_grid = np.linspace(0.0, 20.0, 201)
-mcdc.tally(scores=["fission"], t=t_grid, g=g_grid)
+mcdc.tally(scores=["fission"], t=t_grid)
 
 # Setting
-mcdc.setting(N_particle=1e5, active_bank_buff=10000)
+mcdc.setting(N_particle=1e4, active_bank_buff=1000)
 
 # Run
 mcdc.run()

examples/c5g7/3d/TDX/process.py

@@ -4,53 +4,35 @@
 from matplotlib import cm
 from matplotlib import colors
 
+
 # =============================================================================
 # Plot results
 # =============================================================================
 
-# Results
+# Get results
 with h5py.File("output.h5", "r") as f:
     fis_avg = f["tally/fission/mean"][:]
     fis_sd = f["tally/fission/sdev"][:]
     t = f["tally/grid/t"][:]
-    x = f["tally/grid/x"][:]
-    z = f["tally/grid/z"][:]
-dx = x[1] - x[0]
-dz = z[1] - z[0]
-dV = dx * dx * dz
-
 t_mid = 0.5 * (t[:-1] + t[1:])
 dt = t[1:] - t[:-1]
 
-# Normalize
-norm = np.sum(fis_avg[0]) / dt[0]
-fis_avg /= norm
-fis_sd /= norm
-fis_avg /= dt
-fis_sd /= dt
-
-# Reference
+# Get reference
 with h5py.File("reference.h5", "r") as f:
-    fis_avg_ref = f["tally/fission/mean"][:]
-    fis_sd_ref = f["tally/fission/sdev"][:]
+    fis_ref = f["tally/fission/mean"][:]
+    fis_ref_sd = f["tally/fission/sdev"][:]
 
 # Normalize
-norm = np.sum(fis_avg_ref[:, 0]) / dt[0]
-fis_avg_ref /= norm
-fis_sd_ref /= norm
-fis__ref = np.zeros_like(fis_avg_ref[0])
-fis__sd_ref = np.zeros_like(fis_avg_ref[0])
-for i in range(7):
-    fis__ref += fis_avg_ref[i]
-    fis__sd_ref += np.square(fis_sd_ref[i])
-fis__sd_ref = np.sqrt(fis__sd_ref)
-fis__ref /= dt
-fis__sd_ref /= dt
-
+norm = fis_ref[0] / dt[0]
+fis_avg /= norm * dt
+fis_sd /= norm * dt
+fis_ref /= norm * dt
+fis_ref_sd /= norm * dt
 
-plt.plot(t_mid, fis__ref, "-m", fillstyle="none", label="Ref. (MC)")
+# Plot
+plt.plot(t_mid, fis_ref, "-m", fillstyle="none", label="Ref. (MC)")
 plt.fill_between(
-    t_mid, fis__ref - fis__sd_ref, fis__ref + fis__sd_ref, alpha=0.2, color="m"
+    t_mid, fis_ref - fis_ref_sd, fis_ref + fis_ref_sd, alpha=0.2, color="m"
 )
 plt.plot(t_mid, fis_avg, "ok", fillstyle="none", label="MC")
 plt.fill_between(t_mid, fis_avg - fis_sd, fis_avg + fis_sd, alpha=0.2, color="k")