def gather_data_to_n_files(
metropolis_state, final_sweep, order_5_damping=0, order_6_damping=0, initial_sweep=0, save_every_n_sweeps=10
):
"""
Runs a monte carlo simulation using the metropolis state (a class
instance of a descendant class of metropolis).
Saves as many sphere files as necessary. There's no progress file.
The parameters order_5_damping and order_6_damping do
nothing. They're here for consistency.
"""
# Reset the current sweep so that we start from the specified sweep
metropolis_state.reset_current_sweep(initial_sweep)
# Start time!
start_time = make_time_string()
# Immediately save a file
fname = metropolis_state.make_file_name_v2(final_sweep, start_time)
write_sphere_to_file(fname + output_suffix)
write_statistics_file(metropolis_state, st.vertex_count(sd.vertex.instances.values()), fname + STATISTICS_SUFFIX)
while metropolis_state.get_current_sweep() < final_sweep:
metropolis_state.sweep(save_every_n_sweeps)
fname = metropolis_state.make_file_name_v2(final_sweep, start_time)
write_sphere_to_file(fname + output_suffix)
write_statistics_file(
metropolis_state, st.vertex_count(sd.vertex.instances.values()), fname + STATISTICS_SUFFIX
)
# Print a happy message
print "All done! :)"
def gather_data_to_1_file(
metropolis_state, final_sweep, order_5_damping=0, order_6_damping=0, initial_sweep=0, save_every_n_sweeps=10
):
"""
Runs a monte carlo simulation using the metropolis state (a class
instance of a descendant class of metropolis).
Saves one sphere file and one progress file.
The parameters order_5_damping and order_6_damping do
nothing. They're here for consistency.
"""
# Reset the current sweep so that we start from the specified sweep
metropolis_state.reset_current_sweep(initial_sweep)
# Make the filename
filename = metropolis_state.make_file_name_v1(final_sweep)
# Immediately make a progress file and a current state
write_sphere_to_file(filename + output_suffix)
write_progress_file(metropolis_state, final_sweep, save_every_n_sweeps, filename + tracking_suffix)
write_statistics_file(metropolis_state, st.vertex_count(sd.vertex.instances.values()), filename + STATISTICS_SUFFIX)
# Rewrite each file every save_every_n_sweeps
while metropolis_state.get_current_sweep() < final_sweep:
metropolis_state.sweep(save_every_n_sweeps)
write_sphere_to_file(filename + output_suffix)
write_progress_file(metropolis_state, final_sweep, save_every_n_sweeps, filename + tracking_suffix)
write_statistics_file(
metropolis_state, st.vertex_count(sd.vertex.instances.values()), filename + STATISTICS_SUFFIX
)
# Print a happy message
print "All done! :)"
def generate_n_exact_spheres(
metropolis_state, number_spheres, fitness_damping=0, order_6_damping=0, initial_sweep=0, check_every_n_sweeps=10
):
"""
Runs a monte carlo simulation using the metropolis state ( a class
instance of the descendant class of metropolis).
Only saves a sphere if it has surface area a(sphere) such that
1-fitness_damping <= a(sphere) <= 1+fitness_damping.
Note that fitness_damping is in the slot usually allocated to
order_5_damping.
Saves number_spheres spheres and then stops. Note that this is in
the slot usually allocated for final sweep. We run as many sweeps
as necessary.
Checks to see if a sphere has the correct area (i.e., is exact)
every check_every_n_sweeps. This value should probably be smaller
than otherwise, since the spheres will be saved less often than
they will be checked.
The parameters order_6_damping and initial_sweep do
nothing. They're here for consistency.
"""
# The condition for exactness. Takes a metropolis_state
is_exact = (
lambda m: m.get_target_area() - fitness_damping
<= m.current_state.surface_area()
<= m.get_target_area() + fitness_damping
)
# The total number of sphere saved
sphere_count = 0
# Reset the metropolis state to 0.
metropolis_state.reset_current_sweep(0)
# Calculate the start time
start_time = make_time_string()
# Generate spheres
while sphere_count < number_spheres:
# Run a sweep
metropolis_state.sweep(check_every_n_sweeps)
print "Surface area this check: {}".format(metropolis_state.current_state.surface_area())
if is_exact(metropolis_state):
sphere_count += 1 # Increment the number of exact spheres
# we've found
# We treat current sweep as the sphere_count to get more
# meaningful information out of our file names.
metropolis_state.reset_current_sweep(sphere_count)
fname = metropolis_state.make_file_name_v2(number_spheres, start_time)
# Save to file
write_sphere_to_file(fname + output_suffix)
write_statistics_file(
metropolis_state, st.vertex_count(sd.vertex.instances.values()), fname + STATISTICS_SUFFIX
)
# Print a happy message
print "All done! :)"
