trunc_triangles = ccb.prepare_triangles(1.0, L) # Using 1.0 instead of vol_frac_goal in order to obtain enough inputs.
#ccb.optimize_midpoints(L, trunc_triangles)
with open('trunc_triangles_0.data', 'wb') as f:
pickle.dump(L, f, pickle.HIGHEST_PROTOCOL)
pickle.dump(trunc_triangles, f, pickle.HIGHEST_PROTOCOL)
grain_ids_0, overlaps_0, voxel_indices_0 = ccb_c.populate_voxels(M, L, trunc_triangles, nr_tries, delta, vol_frac_goal)
phases_0, good_voxels_0, euler_angles_0, phase_volumes_0, grain_volumes_0 = ccb_c.calc_grain_prop(M, grain_ids_0, trunc_triangles)
surface_voxels_0, gb_voxels_0, interface_voxels_0 = ccb_c.calc_surface_prop(M, grain_ids_0)
vol_frac_WC_0 = phase_volumes_0[1]/np.float(np.sum(phase_volumes_0))
vol_frac_Co_0 = 1 - vol_frac_WC_0
mass_frac_WC_0 = ccb.mass_fraction(vol_frac_WC_0)
d_eq_0 = ccb.volume_to_eq_d(grain_volumes_0*delta_x**3)
sum_gb_voxels_0 = np.sum(gb_voxels_0)
contiguity_0 = sum_gb_voxels_0 / np.float(sum_gb_voxels_0 + np.sum(interface_voxels_0))
ccb.write_hdf5('testfile_0.hdf5', 3*[M], 3*[delta_x], trunc_triangles, grain_ids_0, phases_0, good_voxels_0, euler_angles_0, surface_voxels_0, gb_voxels_0, interface_voxels_0, overlaps_0)
# Compute actual volume fraction:
print "generated volume fraction of Co (before tweaks):", vol_frac_Co_0
# Make new copies to play with the unlimited monte carle potts simulation.
if False:
grain_ids_1 = grain_ids_0.copy()
gb_voxels_1 = gb_voxels_0.copy()
pickle.dump(trunc_triangles, f, pickle.HIGHEST_PROTOCOL)
if m_coarse == m:
grain_ids_0, overlaps_0, voxel_indices_0 = ccb_c.populate_voxels(M, L, trunc_triangles, nr_tries, M, 1.0)
else:
if nr_tries > 0:
# Optimization: Use coarser grid for packing, then insert packed grains into fine grid
grain_ids_coarse_0, overlaps_coarse_0, voxel_indices_coarse_0 = ccb_c.populate_voxels(M_coarse, L, trunc_triangles, nr_tries, M_coarse, 1.0)
grain_ids_0, overlaps_0, voxel_indices_0 = ccb_c.populate_voxels(M, L, trunc_triangles, 1, 0, 1.0)
phases_0, good_voxels_0, euler_angles_0, phase_volumes_0, grain_volumes_0 = ccb_c.calc_grain_prop(M, grain_ids_0, trunc_triangles)
surface_voxels_0, gb_voxels_0, interface_voxels_0 = ccb_c.calc_surface_prop(M, grain_ids_0)
vol_frac_WC_0 = phase_volumes_0[1]/np.float(np.sum(phase_volumes_0))
vol_frac_Co_0 = 1 - vol_frac_WC_0
mass_frac_WC_0 = ccb.mass_fraction(vol_frac_WC_0)
d_eq_0 = ccb.volume_to_eq_d(grain_volumes_0*delta_x**3)
sum_gb_voxels_0 = np.sum(gb_voxels_0)
contiguity_0 = sum_gb_voxels_0 / np.float(sum_gb_voxels_0 + np.sum(interface_voxels_0))
# Compute the Co connectivity (important parameter for mass transport through the Co matrix) by counting the unique grains
co_grain_sizes, co_ids = ccb.compute_co_grain_sizes(M, grain_ids_0)
#ccb.write_hdf5(fname + '_nopotts.dream3d', 3*[M], 3*[delta_x], trunc_triangles, grain_ids_0, phases_0, good_voxels_0, euler_angles_0, surface_voxels_0, gb_voxels_0, interface_voxels_0, overlaps_0)
# Compute actual volume fraction:
print("Generated volume fraction of Co (before tweaks):", vol_frac_Co_0)
print("Contiguity (before tweaks)", contiguity_0)
# Make new copies to play with the monte carlo potts simulation.
grain_ids_2 = grain_ids_0.copy()
