Nblobs = sum([x.Nblobs for x in bodies])
max_angle_shift = max_translation / max_body_length
accepted_moves = 0
acceptance_ratio = 0.5
# Create blobs coordinates array
sample_r_vectors = get_blobs_r_vectors(bodies, Nblobs)
# begin MCMC
# get energy of the current state before jumping into the loop
start_time = time.time()
current_state_energy = many_body_potential_pycuda.compute_total_energy(
bodies,
sample_r_vectors,
periodic_length=periodic_length,
debye_length_wall=read.debye_length_wall,
repulsion_strength_wall=read.repulsion_strength_wall,
debye_length=read.debye_length,
repulsion_strength=read.repulsion_strength,
weight=weight,
blob_radius=blob_radius)
# quaternion to be used for disturbing the orientation of each body
quaternion_shift = Quaternion(np.array([1, 0, 0, 0]))
# for each step in the Markov chain, disturb each body's location and orientation and obtain the new list of r_vectors
# of each blob. Calculate the potential of the new state, and accept or reject it according to the Markov chain rules:
# 1. if Ej < Ei, always accept the state 2. if Ej < Ei, accept the state according to the probability determined by
# exp(-(Ej-Ei)/kT). Then record data.
# Important: record data also when staying in the same state (i.e. when a sample state is rejected)
for step in range(read.initial_step, read.n_steps):
blob_index = 0
Nblobs = sum([x.Nblobs for x in bodies])
max_angle_shift = max_translation / max_body_length
accepted_moves = 0
acceptance_ratio = 0.5
# Create blobs coordinates array
sample_r_vectors = get_blobs_r_vectors(bodies, Nblobs)
# begin MCMC
# get energy of the current state before jumping into the loop
start_time = time.time()
current_state_energy = many_body_potential_pycuda.compute_total_energy(bodies,
sample_r_vectors,
periodic_length = periodic_length,
debye_length_wall = read.debye_length_wall,
repulsion_strength_wall = read.repulsion_strength_wall,
debye_length = read.debye_length,
repulsion_strength = read.repulsion_strength,
weight = weight,
blob_radius = blob_radius)
# quaternion to be used for disturbing the orientation of each body
quaternion_shift = Quaternion(np.array([1,0,0,0]))
# for each step in the Markov chain, disturb each body's location and orientation and obtain the new list of r_vectors
# of each blob. Calculate the potential of the new state, and accept or reject it according to the Markov chain rules:
# 1. if Ej < Ei, always accept the state 2. if Ej < Ei, accept the state according to the probability determined by
# exp(-(Ej-Ei)/kT). Then record data.
# Important: record data also when staying in the same state (i.e. when a sample state is rejected)
for step in range(read.initial_step, read.n_steps):
blob_index = 0