def compile_home_system_list(num_home_systems, systems):
"""
Compiles a list with a requested number of home systems.
"""
# if the list of systems to choose home systems from is empty, report an error and return empty list
if not systems:
util.report_error("Python generate_home_system_list: no systems to choose from")
return []
# calculate an initial minimal number of jumps that the home systems should be apart,
# based on the total number of systems to choose from and the requested number of home systems
min_jumps = max(int(float(len(systems)) / float(num_home_systems * 2)), 5)
# try to find the home systems, decrease the min jumps until enough systems can be found, or the min jump distance
# gets reduced to 0 (meaning we don't have enough systems to choose from at all)
while min_jumps > 0:
print "Trying to find", num_home_systems, "home systems that are at least", min_jumps, "jumps apart"
# try to find home systems...
home_systems = find_systems_with_min_jumps_between(num_home_systems, systems, min_jumps)
# ...check if we got enough...
if len(home_systems) >= num_home_systems:
# ...yes, we got what we need, so let's break out of the loop
break
print "Home system min jump conflict: %d systems and %d empires, tried %d min jump and failed"\
% (len(systems), num_home_systems, min_jumps)
# ...no, decrease the min jump distance and try again
min_jumps -= 1
# check if the loop above delivered a list with enough home systems, or if it exited because the min jump distance
# has been decreased to 0 without finding enough systems
# in that case, our galaxy obviously is too crowded, report an error and return an empty list
if len(home_systems) < num_home_systems:
util.report_error("Python generate_home_system_list: requested %d homeworlds in a galaxy with %d systems"
% (num_home_systems, len(systems)))
return []
# make sure all our home systems have a "real" star (that is, a star that is not a neutron star, black hole,
# or even no star at all) and at least one planet in it
for home_system in home_systems:
# if this home system has no "real" star, change star type to a randomly selected "real" star
if fo.sys_get_star_type(home_system) not in starsystems.star_types_real:
star_type = random.choice(starsystems.star_types_real)
print "Home system", home_system, "has star type", fo.sys_get_star_type(home_system),\
", changing that to", star_type
fo.sys_set_star_type(home_system, star_type)
# if this home system has no planets, create one in a random orbit
# we take random values for type and size, as these will be set to suitable values later
if not fo.sys_get_planets(home_system):
print "Home system", home_system, "has no planets, adding one"
planet = fo.create_planet(random.choice(planets.planet_sizes_real),
random.choice(planets.planet_types_real),
home_system, random.randint(0, fo.sys_get_num_orbits(home_system) - 1), "")
# if we couldn't create the planet, report an error and return an empty list
if planet == fo.invalid_object():
util.report_error("Python generate_home_system_list: couldn't create planet in home system")
return []
return home_systems
def generate_fields(systems):
"""
Generates stationary fields in some randomly chosen empty no star systems.
"""
# filter out all empty no star systems
candidates = [
s for s in systems
if (fo.sys_get_star_type(s) == fo.starType.noStar) and (
not fo.sys_get_planets(s))
]
# make sure we have at least one empty no star system, otherwise return without creating any fields
if not candidates:
print("...no empty no star systems found, no fields created")
return
# pick 10-15% of all empty no star systems to create stationary fields in them, but at least one
accepted = sample(candidates,
max(int(len(candidates) * uniform(0.1, 0.15)), 1))
for system in accepted:
# randomly pick a field type
field_type = choice(["FLD_NEBULA_1", "FLD_NEBULA_2", "FLD_NEBULA_3"])
# and create the field
if fo.create_field_in_system(field_type, uniform(40, 120),
system) == fo.invalid_object():
# create field failed, report an error
report_error(
"Python generate_fields: create field %s in system %d failed" %
(field_type, system))
print("...fields created in %d systems out of %d empty no star systems" %
(len(accepted), len(candidates)))
def generate_fields(systems):
"""
Generates stationary fields in some randomly chosen empty no star systems.
"""
# filter out all empty no star systems
candidates = [s for s in systems if (fo.sys_get_star_type(s) == fo.starType.noStar) and (not fo.sys_get_planets(s))]
# make sure we have at least one empty no star system, otherwise return without creating any fields
if not candidates:
print "...no empty no star systems found, no fields created"
return
# pick 10-20% of all empty no star systems to create stationary fields in them, but at least one
accepted = sample(candidates, max(int(len(candidates) * uniform(0.1, 0.2)), 1))
for system in accepted:
# randomly pick a field type
field_type = choice(["FLD_NEBULA_1", "FLD_NEBULA_2"])
# and create the field
if fo.create_field_in_system(field_type, uniform(40, 120), system) == fo.invalid_object():
# create field failed, report an error
report_error("Python generate_fields: create field %s in system %d failed" % (field_type, system))
print "...fields created in %d systems out of %d empty no star systems" % (len(accepted), len(candidates))
def compile_home_system_list(num_home_systems, systems, gsd):
"""
Compiles a list with a requested number of home systems.
"""
print "Compile home system list:", num_home_systems, "systems requested"
# if the list of systems to choose home systems from is empty, report an error and return empty list
if not systems:
report_error(
"Python generate_home_system_list: no systems to choose from")
return []
# calculate an initial minimal number of jumps that the home systems should be apart,
# based on the total number of systems to choose from and the requested number of home systems
# don't let min_jumps be either:
# a.) larger than a defined limit, because an unreasonably large number is really not at all needed,
# and with large galaxies an excessive amount of time can be used in failed attempts
# b.) lower than the minimum jump distance limit that should be considered high priority (see options.py),
# otherwise no attempt at all would be made to enforce the other requirements for home systems (see below)
min_jumps = min(
HS_MAX_JUMP_DISTANCE_LIMIT,
max(int(float(len(systems)) / float(num_home_systems * 2)),
HS_MIN_DISTANCE_PRIORITY_LIMIT))
# home systems must have a certain minimum of systems and planets in their near vicinity
# we will try to select our home systems from systems that match this criteria, if that fails, we will select our
# home systems from all systems and add the missing number planets to the systems in their vicinity afterwards
# the minimum system and planet limit and the jump range that defines the "near vicinity" are controlled by the
# HS_* option constants in options.py (see there)
# we start by building two additional pools of systems: one that contains all systems that match the criteria
# completely (meets the min systems and planets limit), and one that contains all systems that match the criteria
# at least partially (meets the min systems limit)
pool_matching_sys_and_planet_limit = []
pool_matching_sys_limit = []
for system in systems:
systems_in_vicinity = fo.systems_within_jumps_unordered(
HS_VICINITY_RANGE, [system])
if len(systems_in_vicinity) >= HS_MIN_SYSTEMS_IN_VICINITY:
pool_matching_sys_limit.append(system)
if count_planets_in_systems(
systems_in_vicinity) >= min_planets_in_vicinity_limit(
len(systems_in_vicinity)):
pool_matching_sys_and_planet_limit.append(system)
print(
len(pool_matching_sys_and_planet_limit),
"systems meet the min systems and planets in the near vicinity limit")
print len(pool_matching_sys_limit
), "systems meet the min systems in the near vicinity limit"
# now try to pick the requested number of home systems
# we will do this by calling find_home_systems, which takes a list of tuples defining the pools from which to pick
# the home systems; it will use the pools in the order in which they appear in the list, so put better pools first
# we will make two attempts: the first one with the filtered pools we just created, and tell find_home_systems
# to start with the min_jumps jumps distance we calculated above, but not to go lower than
# HS_MIN_DISTANCE_PRIORITY_LIMIT
print "First attempt: trying to pick home systems from the filtered pools of preferred systems"
pool_list = [
# the better pool is of course the one where all systems meet BOTH the min systems and planets limit
(pool_matching_sys_and_planet_limit,
"pool of systems that meet both the min systems and planets limit"),
# next the less preferred pool where all systems at least meets the min systems limit
# specify 0 as number of requested home systems to pick as much systems as possible
(pool_matching_sys_limit,
"pool of systems that meet at least the min systems limit"),
]
home_systems = find_home_systems(num_home_systems, pool_list, min_jumps,
HS_MIN_DISTANCE_PRIORITY_LIMIT)
# check if the first attempt delivered a list with enough home systems
# if not, we make our second attempt, this time disregarding the filtered pools and using all systems, starting
# again with the min_jumps jump distance limit and specifying 0 as number of required home systems to pick as much
# systems as possible
if len(home_systems) < num_home_systems:
print "Second attempt: trying to pick home systems from all systems"
home_systems = find_home_systems(num_home_systems,
[(systems, "complete pool")],
min_jumps, 1)
# check if the selection process delivered a list with enough home systems
# if not, our galaxy obviously is too crowded, report an error and return an empty list
if len(home_systems) < num_home_systems:
report_error(
"Python generate_home_system_list: requested %d homeworlds in a galaxy with %d systems"
% (num_home_systems, len(systems)))
return []
# check if we got more home systems than we requested
if len(home_systems) > num_home_systems:
# yes: calculate the number of planets in the near vicinity of each system
# and store that value with each system in a map
hs_planets_in_vicinity_map = {
s: calculate_home_system_merit(s)
for s in home_systems
}
# sort the home systems by the number of planets in their near vicinity using the map
# now only pick the number of home systems we need, taking those with the highest number of planets
home_systems = sorted(home_systems,
key=hs_planets_in_vicinity_map.get,
reverse=True)[:num_home_systems]
# make sure all our home systems have a "real" star (that is, a star that is not a neutron star, black hole,
# or even no star at all) and at least one planet in it
for home_system in home_systems:
# if this home system has no "real" star, change star type to a randomly selected "real" star
if fo.sys_get_star_type(home_system) not in star_types_real:
star_type = random.choice(star_types_real)
print "Home system", home_system, "has star type", fo.sys_get_star_type(home_system),\
", changing that to", star_type
fo.sys_set_star_type(home_system, star_type)
# if this home system has no planets, create one in a random orbit
# we take random values for type and size, as these will be set to suitable values later
if not fo.sys_get_planets(home_system):
print "Home system", home_system, "has no planets, adding one"
planet = fo.create_planet(
random.choice(planet_sizes_real),
random.choice(planet_types_real), home_system,
random.randint(0,
fo.sys_get_num_orbits(home_system) - 1), "")
# if we couldn't create the planet, report an error and return an empty list
if planet == fo.invalid_object():
report_error(
"Python generate_home_system_list: couldn't create planet in home system"
)
return []
# finally, check again if all home systems meet the criteria of having the required minimum number of planets
# within their near vicinity, if not, add the missing number of planets
print "Checking if home systems have the required minimum of planets within the near vicinity..."
for home_system in home_systems:
# calculate the number of missing planets, and add them if this number is > 0
systems_in_vicinity = fo.systems_within_jumps_unordered(
HS_VICINITY_RANGE, [home_system])
num_systems_in_vicinity = len(systems_in_vicinity)
num_planets_in_vicinity = count_planets_in_systems(systems_in_vicinity)
num_planets_to_add = min_planets_in_vicinity_limit(
num_systems_in_vicinity) - num_planets_in_vicinity
print "Home system", home_system, "has", num_systems_in_vicinity, "systems and", num_planets_in_vicinity,\
"planets in the near vicinity, required minimum:", min_planets_in_vicinity_limit(num_systems_in_vicinity)
if num_planets_to_add > 0:
systems_in_vicinity.remove(
home_system
) # don't add planets to the home system, so remove it from the list
# sort the systems_in_vicinity before adding, since the C++ engine doesn't guarrantee the same
# platform independence as python.
add_planets_to_vicinity(sorted(systems_in_vicinity),
num_planets_to_add, gsd)
# as we've sorted the home system list before, lets shuffle it to ensure random order and return
random.shuffle(home_systems)
return home_systems
def add_planets_to_vicinity(vicinity, num_planets, gsd):
"""
Adds the specified number of planets to the specified systems.
"""
print "Adding", num_planets, "planets to the following systems:", vicinity
# first, compile a list containing all the free orbits in the specified systems
# begin with adding the free orbits of all systems that have a real star (that is, no neutron star, black hole,
# and not no star), if that isn't enough, also one, by one, add the free orbits of neutron star, black hole and
# no star systems (in that order) until we have enough free orbits
# for that, we use this list of tuples
# the first tuple contains all real star types, the following tuples the neutron, black hole and no star types,
# so we can iterate over this list and only add the free orbits of systems that match the respective star types
# each step
# this way we can prioritize the systems we want to add planets to by star type
acceptable_star_types_list = [
star_types_real, (fo.starType.noStar, ), (fo.starType.neutron, ),
(fo.starType.blackHole, )
]
# store the free orbits as a list of tuples of (system, orbit)
free_orbits_map = []
# now, iterate over the list of acceptable star types
for acceptable_star_types in acceptable_star_types_list:
# check all systems in the list of systems we got passed into this function
for system in vicinity:
# if this system has a star type we want to accept in this step, add its free orbits to our list
if fo.sys_get_star_type(system) in acceptable_star_types:
free_orbits_map.extend([
(system, orbit) for orbit in fo.sys_free_orbits(system)
])
# check if we got enough free orbits after completing this step
# we want 4 times as much free orbits as planets we want to add, that means each system shouldn't get more
# than 2-3 additional planets on average
if len(free_orbits_map) > (num_planets * 4):
break
# if we got less free orbits than planets that should be added, something is wrong
# in that case abort and log an error
if len(free_orbits_map) < num_planets:
report_error(
"Python add_planets_to_vicinity: less free orbits than planets to add - cancelled"
)
print "...free orbits available:", free_orbits_map
# as we will pop the free orbits from this list afterwards, shuffle it to randomize the order of the orbits
random.shuffle(free_orbits_map)
# add the requested number of planets
while num_planets > 0:
# get the next free orbit from the list we just compiled
system, orbit = free_orbits_map.pop()
# check the star type of the system containing the orbit we got
star_type = fo.sys_get_star_type(system)
if star_type in [fo.starType.noStar, fo.starType.blackHole]:
# if it is a black hole or has no star, change the star type
# pick a star type, continue until we get a real star
# don't accept neutron, black hole or no star
print "...system picked to add a planet has star type", star_type
while star_type not in star_types_real:
star_type = pick_star_type(gsd.age)
print "...change that to", star_type
fo.sys_set_star_type(system, star_type)
# pick a planet size, continue until we get a size that matches the HS_ACCEPTABLE_PLANET_SIZES option
planet_size = fo.planetSize.unknown
while planet_size not in HS_ACCEPTABLE_PLANET_SIZES:
planet_size = calc_planet_size(star_type, orbit,
fo.galaxySetupOption.high,
gsd.shape)
# pick an according planet type
planet_type = calc_planet_type(star_type, orbit, planet_size)
# finally, create the planet in the system and orbit we got
print "...adding", planet_size, planet_type, "planet to system", system
if fo.create_planet(planet_size, planet_type, system, orbit,
"") == fo.invalid_object():
report_error(
"Python add_planets_to_vicinity: create planet in system %d failed"
% system)
# continue with next planet
num_planets -= 1
def name_star_systems(system_list):
# choose star types and planet sizes, before choosing names, so naming can have special handling of Deep Space
star_type_assignments = {}
planet_assignments = {}
position_list = []
for system in system_list:
star_type = fo.sys_get_star_type(system)
systemxy = fo.get_pos(system)
star_type_assignments[systemxy] = star_type
planet_assignments[systemxy] = fo.sys_get_planets(system)
position_list.append(systemxy)
# will name name a portion of stars on a group basis, where the stars of each group share the same base star name,
# suffixed by different (default greek) letters or characters (options at top of file)
star_name_map = {}
star_names = names.get_name_list("STAR_NAMES")
group_names = names.get_name_list("STAR_GROUP_NAMES")
potential_group_names = []
individual_names = []
stargroup_words[:] = names.get_name_list("STAR_GROUP_WORDS")
stargroup_chars[:] = names.get_name_list("STAR_GROUP_CHARS")
stargroup_modifiers[:] = [stargroup_words, stargroup_chars][options.STAR_GROUPS_USE_CHARS]
for starname in star_names:
if len(starname) > 6: # if starname is long, don't allow it for groups
individual_names.append(starname)
continue
# any names that already have a greek letter in them can only be used for individual stars, not groups
for namepart in starname.split():
if namepart in greek_letters:
individual_names.append(starname)
break
else:
potential_group_names.append(starname)
if not potential_group_names:
potential_group_names.append("XYZZY")
# ensure at least a portion of galaxy gets individual starnames
num_systems = len(system_list)
target_indiv_ratio = [options.TARGET_INDIV_RATIO_SMALL, options.TARGET_INDIV_RATIO_LARGE]\
[num_systems >= options.NAMING_LARGE_GALAXY_SIZE]
# TODO improve the following calc to be more likely to hit target_indiv_ratio if more or less than
# 50% potential_group_names used for groups
num_individual_stars = int(max(min(num_systems * target_indiv_ratio,
len(individual_names)+int(0.5 * len(potential_group_names))),
num_systems - 0.8 * len(stargroup_modifiers) *
(len(group_names)+int(0.5 * len(potential_group_names)))))
star_group_size = 1 + int((num_systems - num_individual_stars) /
(max(1, len(group_names)+int(0.5 * len(potential_group_names)))))
# make group size a bit bigger than min necessary, at least a trio
star_group_size = max(3, star_group_size)
num_star_groups = 1 + int(num_systems/star_group_size) # initial value
# first cluster all systems, then remove some to be individually named (otherwise groups can have too many
# individually named systems in their middle). First remove any that are too small (only 1 or 2 systems).
# The clusters with the most systems are generally the most closely spaced, and though they might make good
# logical candidates for groups, their names are then prone to overlapping on the galaxy map, so after removing
# small groups, remove the groups with the most systems.
random.shuffle(position_list) # just to be sure it is randomized
init_cluster_assgts = cluster_stars(position_list, num_star_groups)
star_groups = {}
for index_pos, index_group in enumerate(init_cluster_assgts):
systemxy = position_list[index_pos]
star_groups.setdefault(index_group, []).append(systemxy)
indiv_systems = []
# remove groups with only one non-deep-system
for groupindex, group_list in star_groups.items():
max_can_transfer = len(potential_group_names)-len(star_groups)+len(individual_names)-len(indiv_systems)
if max_can_transfer <= 0:
break
elif max_can_transfer <= len(group_list):
continue
not_deep, deep_space = check_deep_space(group_list, star_type_assignments, planet_assignments)
if len(not_deep) > 1:
continue
for systemxy in star_groups[groupindex]:
indiv_systems.append(systemxy)
del star_groups[groupindex]
# remove tiny groups
group_sizes = [(len(group), index) for index, group in star_groups.items()]
group_sizes.sort()
while len(indiv_systems) < num_individual_stars and len(group_sizes) > 0:
groupsize, groupindex = group_sizes.pop()
max_can_transfer = len(potential_group_names)-len(star_groups)+len(individual_names)-len(indiv_systems)
if (max_can_transfer <= 0) or (groupsize > 2):
break
if max_can_transfer <= groupsize:
continue
for systemxy in star_groups[groupindex]:
indiv_systems.append(systemxy)
del star_groups[groupindex]
# remove largest (likely most compact) groups
while len(indiv_systems) < num_individual_stars and len(group_sizes) > 0:
groupsize, groupindex = group_sizes.pop(-1)
max_can_transfer = len(potential_group_names)-len(star_groups)+len(individual_names)-len(indiv_systems)
if max_can_transfer <= 0:
break
if max_can_transfer <= groupsize:
continue
for systemxy in star_groups[groupindex]:
indiv_systems.append(systemxy)
del star_groups[groupindex]
num_star_groups = len(star_groups)
num_individual_stars = len(indiv_systems)
random.shuffle(potential_group_names)
random.shuffle(individual_names)
random.shuffle(group_names)
num_for_indiv = min(max(len(potential_group_names)/2, num_individual_stars+1-len(individual_names)),
len(potential_group_names))
individual_names.extend(potential_group_names[:num_for_indiv])
group_names.extend(potential_group_names[num_for_indiv:])
#print "sampling for %d indiv names from list of %d total indiv names"%(num_individual_stars, len(individual_names))
indiv_name_sample = random.sample(individual_names, num_individual_stars)
#indiv_name_assignments = zip([(pos.x, pos.y) for pos in position_list[:num_individual_stars]], indiv_name_sample)
indiv_name_assignments = zip(indiv_systems, indiv_name_sample)
star_name_map.update(indiv_name_assignments)
#print "sampling for %d group names from list of %d total group names"%(num_star_groups, len(group_names))
if len(group_names) < num_star_groups:
group_names.extend([names.random_name(6) for _ in range(num_star_groups - len(group_names))])
group_name_sample = random.sample(group_names, num_star_groups)
for index_group, group_list in enumerate(sorted(star_groups.values())):
star_name_map.update(name_group(group_list, group_name_sample[index_group], star_type_assignments,
planet_assignments))
# assign names from star_name_map to star systems
for system in system_list:
fo.set_name(system, star_name_map.get(fo.get_pos(system), "") or random_star_name())
def name_star_systems(system_list):
# choose star types and planet sizes, before choosing names, so naming can have special handling of Deep Space
star_type_assignments = {}
planet_assignments = {}
position_list = []
for system in system_list:
star_type = fo.sys_get_star_type(system)
systemxy = fo.get_pos(system)
star_type_assignments[systemxy] = star_type
planet_assignments[systemxy] = fo.sys_get_planets(system)
position_list.append(systemxy)
# will name name a portion of stars on a group basis, where the stars of each group share the same base star name,
# suffixed by different (default greek) letters or characters (options at top of file)
star_name_map = {}
star_names = names.get_name_list("STAR_NAMES")
group_names = names.get_name_list("STAR_GROUP_NAMES")
potential_group_names = []
individual_names = []
stargroup_words[:] = names.get_name_list("STAR_GROUP_WORDS")
stargroup_chars[:] = names.get_name_list("STAR_GROUP_CHARS")
stargroup_modifiers[:] = [stargroup_words,
stargroup_chars][options.STAR_GROUPS_USE_CHARS]
for starname in star_names:
if len(starname) > 6: # if starname is long, don't allow it for groups
individual_names.append(starname)
continue
# any names that already have a greek letter in them can only be used for individual stars, not groups
for namepart in starname.split():
if namepart in greek_letters:
individual_names.append(starname)
break
else:
potential_group_names.append(starname)
if not potential_group_names:
potential_group_names.append("XYZZY")
# ensure at least a portion of galaxy gets individual starnames
num_systems = len(system_list)
choice = num_systems >= options.NAMING_LARGE_GALAXY_SIZE
target_indiv_ratio = [
options.TARGET_INDIV_RATIO_SMALL, options.TARGET_INDIV_RATIO_LARGE
][choice]
# TODO improve the following calc to be more likely to hit target_indiv_ratio if more or less than
# 50% potential_group_names used for groups
num_individual_stars = int(
max(
min(num_systems * target_indiv_ratio,
len(individual_names) + int(0.5 * len(potential_group_names))),
num_systems - 0.8 * len(stargroup_modifiers) *
(len(group_names) + int(0.5 * len(potential_group_names)))))
star_group_size = 1 + int(
(num_systems - num_individual_stars) /
(max(1,
len(group_names) + int(0.5 * len(potential_group_names)))))
# make group size a bit bigger than min necessary, at least a trio
star_group_size = max(3, star_group_size)
num_star_groups = 1 + int(num_systems / star_group_size) # initial value
# first cluster all systems, then remove some to be individually named (otherwise groups can have too many
# individually named systems in their middle). First remove any that are too small (only 1 or 2 systems).
# The clusters with the most systems are generally the most closely spaced, and though they might make good
# logical candidates for groups, their names are then prone to overlapping on the galaxy map, so after removing
# small groups, remove the groups with the most systems.
random.shuffle(position_list) # just to be sure it is randomized
init_cluster_assgts = cluster_stars(position_list, num_star_groups)
star_groups = {}
for index_pos, index_group in enumerate(init_cluster_assgts):
systemxy = position_list[index_pos]
star_groups.setdefault(index_group, []).append(systemxy)
indiv_systems = []
# remove groups with only one non-deep-system
for groupindex, group_list in list(star_groups.items()):
max_can_transfer = len(potential_group_names) - len(star_groups) + len(
individual_names) - len(indiv_systems)
if max_can_transfer <= 0:
break
elif max_can_transfer <= len(group_list):
continue
not_deep, deep_space = check_deep_space(group_list,
star_type_assignments,
planet_assignments)
if len(not_deep) > 1:
continue
for systemxy in star_groups[groupindex]:
indiv_systems.append(systemxy)
del star_groups[groupindex]
# remove tiny groups
group_sizes = [(len(group), index) for index, group in star_groups.items()]
group_sizes.sort()
while len(indiv_systems) < num_individual_stars and len(group_sizes) > 0:
groupsize, groupindex = group_sizes.pop()
max_can_transfer = len(potential_group_names) - len(star_groups) + len(
individual_names) - len(indiv_systems)
if (max_can_transfer <= 0) or (groupsize > 2):
break
if max_can_transfer <= groupsize:
continue
for systemxy in star_groups[groupindex]:
indiv_systems.append(systemxy)
del star_groups[groupindex]
# remove largest (likely most compact) groups
while len(indiv_systems) < num_individual_stars and len(group_sizes) > 0:
groupsize, groupindex = group_sizes.pop(-1)
max_can_transfer = len(potential_group_names) - len(star_groups) + len(
individual_names) - len(indiv_systems)
if max_can_transfer <= 0:
break
if max_can_transfer <= groupsize:
continue
for systemxy in star_groups[groupindex]:
indiv_systems.append(systemxy)
del star_groups[groupindex]
num_star_groups = len(star_groups)
num_individual_stars = len(indiv_systems)
random.shuffle(potential_group_names)
random.shuffle(individual_names)
random.shuffle(group_names)
num_for_indiv = min(
max(
len(potential_group_names) // 2,
num_individual_stars + 1 - len(individual_names)),
len(potential_group_names))
individual_names.extend(potential_group_names[:num_for_indiv])
group_names.extend(potential_group_names[num_for_indiv:])
# print "sampling for %d indiv names from list of %d total indiv names" % (
# num_individual_stars, len(individual_names))
indiv_name_sample = random.sample(individual_names, num_individual_stars)
# indiv_name_assignments = zip([(pos.x, pos.y) for pos in position_list[:num_individual_stars]], indiv_name_sample)
star_name_map.update(zip(indiv_systems, indiv_name_sample))
# print "sampling for %d group names from list of %d total group names"%(num_star_groups, len(group_names))
if len(group_names) < num_star_groups:
group_names.extend([
names.random_name(6)
for _ in range(num_star_groups - len(group_names))
])
group_name_sample = random.sample(group_names, num_star_groups)
for index_group, group_list in enumerate(sorted(star_groups.values())):
star_name_map.update(
name_group(group_list, group_name_sample[index_group],
star_type_assignments, planet_assignments))
# assign names from star_name_map to star systems
for system in system_list:
fo.set_name(
system,
star_name_map.get(fo.get_pos(system), "") or random_star_name())
def compile_home_system_list(num_home_systems, systems, gsd):
"""
Compiles a list with a requested number of home systems.
"""
print "Compile home system list:", num_home_systems, "systems requested"
# if the list of systems to choose home systems from is empty, report an error and return empty list
if not systems:
report_error("Python generate_home_system_list: no systems to choose from")
return []
# calculate an initial minimal number of jumps that the home systems should be apart,
# based on the total number of systems to choose from and the requested number of home systems
# don't let min_jumps be either:
# a.) larger than a defined limit, because an unreasonably large number is really not at all needed,
# and with large galaxies an excessive amount of time can be used in failed attempts
# b.) lower than the minimum jump distance limit that should be considered high priority (see options.py),
# otherwise no attempt at all would be made to enforce the other requirements for home systems (see below)
min_jumps = min(HS_MAX_JUMP_DISTANCE_LIMIT, max(int(float(len(systems)) / float(num_home_systems * 2)),
HS_MIN_DISTANCE_PRIORITY_LIMIT))
# home systems must have a certain minimum of systems and planets in their near vicinity
# we will try to select our home systems from systems that match this criteria, if that fails, we will select our
# home systems from all systems and add the missing number planets to the systems in their vicinity afterwards
# the minimum system and planet limit and the jump range that defines the "near vicinity" are controlled by the
# HS_* option constants in options.py (see there)
# we start by building two additional pools of systems: one that contains all systems that match the criteria
# completely (meets the min systems and planets limit), and one that contains all systems that match the criteria
# at least partially (meets the min systems limit)
pool_matching_sys_and_planet_limit = []
pool_matching_sys_limit = []
for system in systems:
systems_in_vicinity = get_systems_within_jumps(system, HS_VICINITY_RANGE)
if len(systems_in_vicinity) >= HS_MIN_SYSTEMS_IN_VICINITY:
pool_matching_sys_limit.append(system)
if count_planets_in_systems(systems_in_vicinity) >= min_planets_in_vicinity_limit(len(systems_in_vicinity)):
pool_matching_sys_and_planet_limit.append(system)
print len(pool_matching_sys_and_planet_limit), "systems meet the min systems and planets in the near vicinity limit"
print len(pool_matching_sys_limit), "systems meet the min systems in the near vicinity limit"
# now try to pick the requested number of home systems
# we will do this by calling find_home_systems, which takes a list of tuples defining the pools from which to pick
# the home systems; it will use the pools in the order in which they appear in the list, so put better pools first
# we will make two attempts: the first one with the filtered pools we just created, and tell find_home_systems
# to start with the min_jumps jumps distance we calculated above, but not to go lower than
# HS_MIN_DISTANCE_PRIORITY_LIMIT
print "First attempt: trying to pick home systems from the filtered pools of preferred systems"
pool_list = [
# the better pool is of course the one where all systems meet BOTH the min systems and planets limit
(pool_matching_sys_and_planet_limit, "pool of systems that meet both the min systems and planets limit"),
# next the less preferred pool where all systems at least meets the min systems limit
# specify 0 as number of requested home systems to pick as much systems as possible
(pool_matching_sys_limit, "pool of systems that meet at least the min systems limit"),
]
home_systems = find_home_systems(num_home_systems, pool_list, min_jumps, HS_MIN_DISTANCE_PRIORITY_LIMIT)
# check if the first attempt delivered a list with enough home systems
# if not, we make our second attempt, this time disregarding the filtered pools and using all systems, starting
# again with the min_jumps jump distance limit and specifying 0 as number of required home systems to pick as much
# systems as possible
if len(home_systems) < num_home_systems:
print "Second attempt: trying to pick home systems from all systems"
home_systems = find_home_systems(num_home_systems, [(systems, "complete pool")], min_jumps, 1)
# check if the selection process delivered a list with enough home systems
# if not, our galaxy obviously is too crowded, report an error and return an empty list
if len(home_systems) < num_home_systems:
report_error("Python generate_home_system_list: requested %d homeworlds in a galaxy with %d systems"
% (num_home_systems, len(systems)))
return []
# check if we got more home systems than we requested
if len(home_systems) > num_home_systems:
# yes: calculate the number of planets in the near vicinity of each system
# and store that value with each system in a map
hs_planets_in_vicinity_map = {s: count_planets_in_systems(get_systems_within_jumps(s, HS_VICINITY_RANGE))
for s in home_systems}
# sort the home systems by the number of planets in their near vicinity using the map
# now only pick the number of home systems we need, taking those with the highest number of planets
home_systems = sorted(home_systems, key=hs_planets_in_vicinity_map.get, reverse=True)[:num_home_systems]
# make sure all our home systems have a "real" star (that is, a star that is not a neutron star, black hole,
# or even no star at all) and at least one planet in it
for home_system in home_systems:
# if this home system has no "real" star, change star type to a randomly selected "real" star
if fo.sys_get_star_type(home_system) not in star_types_real:
star_type = random.choice(star_types_real)
print "Home system", home_system, "has star type", fo.sys_get_star_type(home_system),\
", changing that to", star_type
fo.sys_set_star_type(home_system, star_type)
# if this home system has no planets, create one in a random orbit
# we take random values for type and size, as these will be set to suitable values later
if not fo.sys_get_planets(home_system):
print "Home system", home_system, "has no planets, adding one"
planet = fo.create_planet(random.choice(planet_sizes_real),
random.choice(planet_types_real),
home_system, random.randint(0, fo.sys_get_num_orbits(home_system) - 1), "")
# if we couldn't create the planet, report an error and return an empty list
if planet == fo.invalid_object():
report_error("Python generate_home_system_list: couldn't create planet in home system")
return []
# finally, check again if all home systems meet the criteria of having the required minimum number of planets
# within their near vicinity, if not, add the missing number of planets
print "Checking if home systems have the required minimum of planets within the near vicinity..."
for home_system in home_systems:
# calculate the number of missing planets, and add them if this number is > 0
systems_in_vicinity = get_systems_within_jumps(home_system, HS_VICINITY_RANGE)
num_systems_in_vicinity = len(systems_in_vicinity)
num_planets_in_vicinity = count_planets_in_systems(systems_in_vicinity)
num_planets_to_add = min_planets_in_vicinity_limit(num_systems_in_vicinity) - num_planets_in_vicinity
print "Home system", home_system, "has", num_systems_in_vicinity, "systems and", num_planets_in_vicinity,\
"planets in the near vicinity, required minimum:", min_planets_in_vicinity_limit(num_systems_in_vicinity)
if num_planets_to_add > 0:
systems_in_vicinity.remove(home_system) # don't add planets to the home system, so remove it from the list
add_planets_to_vicinity(systems_in_vicinity, num_planets_to_add, gsd)
# as we've sorted the home system list before, lets shuffle it to ensure random order and return
random.shuffle(home_systems)
return home_systems
def add_planets_to_vicinity(vicinity, num_planets, gsd):
"""
Adds the specified number of planets to the specified systems.
"""
print "Adding", num_planets, "planets to the following systems:", vicinity
# first, compile a list containing all the free orbits in the specified systems
# begin with adding the free orbits of all systems that have a real star (that is, no neutron star, black hole,
# and not no star), if that isn't enough, also one, by one, add the free orbits of neutron star, black hole and
# no star systems (in that order) until we have enough free orbits
# for that, we use this list of tuples
# the first tuple contains all real star types, the following tuples the neutron, black hole and no star types,
# so we can iterate over this list and only add the free orbits of systems that match the respective star types
# each step
# this way we can prioritize the systems we want to add planets to by star type
acceptable_star_types_list = [
star_types_real,
(fo.starType.noStar,),
(fo.starType.neutron,),
(fo.starType.blackHole,)
]
# store the free orbits as a list of tuples of (system, orbit)
free_orbits_map = []
# now, iterate over the list of acceptable star types
for acceptable_star_types in acceptable_star_types_list:
# check all systems in the list of systems we got passed into this function
for system in vicinity:
# if this system has a star type we want to accept in this step, add its free orbits to our list
if fo.sys_get_star_type(system) in acceptable_star_types:
free_orbits_map.extend([(system, orbit) for orbit in fo.sys_free_orbits(system)])
# check if we got enough free orbits after completing this step
# we want 4 times as much free orbits as planets we want to add, that means each system shouldn't get more
# than 2-3 additional planets on average
if len(free_orbits_map) > (num_planets * 4):
break
# if we got less free orbits than planets that should be added, something is wrong
# in that case abort and log an error
if len(free_orbits_map) < num_planets:
report_error("Python add_planets_to_vicinity: less free orbits than planets to add - cancelled")
print "...free orbits available:", free_orbits_map
# as we will pop the free orbits from this list afterwards, shuffle it to randomize the order of the orbits
random.shuffle(free_orbits_map)
# add the requested number of planets
while num_planets > 0:
# get the next free orbit from the list we just compiled
system, orbit = free_orbits_map.pop()
# check the star type of the system containing the orbit we got
star_type = fo.sys_get_star_type(system)
if star_type in [fo.starType.noStar, fo.starType.blackHole]:
# if it is a black hole or has no star, change the star type
# pick a star type, continue until we get a real star
# don't accept neutron, black hole or no star
print "...system picked to add a planet has star type", star_type
while star_type not in star_types_real:
star_type = pick_star_type(gsd.age)
print "...change that to", star_type
fo.sys_set_star_type(system, star_type)
# pick a planet size, continue until we get a size that matches the HS_ACCEPTABLE_PLANET_SIZES option
planet_size = fo.planetSize.unknown
while planet_size not in HS_ACCEPTABLE_PLANET_SIZES:
planet_size = calc_planet_size(star_type, orbit, fo.galaxySetupOption.high, gsd.shape)
# pick an according planet type
planet_type = calc_planet_type(star_type, orbit, planet_size)
# finally, create the planet in the system and orbit we got
print "...adding", planet_size, planet_type, "planet to system", system
if fo.create_planet(planet_size, planet_type, system, orbit, "") == fo.invalid_object():
report_error("Python add_planets_to_vicinity: create planet in system %d failed" % system)
# continue with next planet
num_planets -= 1
def compile_home_system_list(num_home_systems, systems):
"""
Compiles a list with a requested number of home systems.
"""
print "Compile home system list:", num_home_systems, "systems requested"
# if the list of systems to choose home systems from is empty, report an error and return empty list
if not systems:
report_error(
"Python generate_home_system_list: no systems to choose from")
return []
# calculate an initial minimal number of jumps that the home systems should be apart,
# based on the total number of systems to choose from and the requested number of home systems
# Don't let min_jumps be larger than 10, because a larger number is really not at all needed and with large
# galaxies an excessive amount of time can be used in failed attempts
min_jumps = min(
10, max(int(float(len(systems)) / float(num_home_systems * 2)), 5))
# home systems must have a certain minimum of systems in their near vicinity
# we will try to select our home systems from systems that match this criteria, if that fails, we will select our
# home systems from all systems and add the missing number planets to the systems in their vicinity afterwards
# the minimum planet limit and the jump range that defines the "near vicinity" are controlled by the
# HS_* option constants in options.py (see there)
# lets start by filtering out all systems from the pool we got passed into this function that match the criteria
filtered_pool = [s for s in systems if has_min_planets_in_vicinity(s)]
print "Filtering out systems that meet the minimum planets in the near vicinity condition yielded",\
len(filtered_pool), "systems"
print "Using this as the preferred pool for home system selection"
# now try to pick the requested number of home systems by calling find_home_systems
# this function takes two pools, a "complete" pool and one with preferred systems
# it will try to pick the home systems from the preferred pool first, so pass our filtered pool as preferred pool
home_systems = find_home_systems(num_home_systems, systems, filtered_pool,
min_jumps)
# check if the selection process delivered a list with enough home systems
# if not, our galaxy obviously is too crowded, report an error and return an empty list
if len(home_systems) < num_home_systems:
report_error(
"Python generate_home_system_list: requested %d homeworlds in a galaxy with %d systems"
% (num_home_systems, len(systems)))
return []
# check if we got more home systems than we requested
if len(home_systems) > num_home_systems:
# yes: calculate the number of planets in the near vicinity of each system
# and store that value with each system in a map
hs_planets_in_vicinity_map = {
s: count_planets_in_systems(
get_systems_within_jumps(s, HS_VICINITY_RANGE))
for s in home_systems
}
# sort the home systems by the number of planets in their near vicinity using the map
# now only pick the number of home systems we need, taking those with the highest number of planets
home_systems = sorted(home_systems,
key=hs_planets_in_vicinity_map.get,
reverse=True)[:num_home_systems]
# make sure all our home systems have a "real" star (that is, a star that is not a neutron star, black hole,
# or even no star at all) and at least one planet in it
for home_system in home_systems:
# if this home system has no "real" star, change star type to a randomly selected "real" star
if fo.sys_get_star_type(home_system) not in star_types_real:
star_type = random.choice(star_types_real)
print "Home system", home_system, "has star type", fo.sys_get_star_type(home_system),\
", changing that to", star_type
fo.sys_set_star_type(home_system, star_type)
# if this home system has no planets, create one in a random orbit
# we take random values for type and size, as these will be set to suitable values later
if not fo.sys_get_planets(home_system):
print "Home system", home_system, "has no planets, adding one"
planet = fo.create_planet(
random.choice(planet_sizes_real),
random.choice(planet_types_real), home_system,
random.randint(0,
fo.sys_get_num_orbits(home_system) - 1), "")
# if we couldn't create the planet, report an error and return an empty list
if planet == fo.invalid_object():
report_error(
"Python generate_home_system_list: couldn't create planet in home system"
)
return []
# finally, check again if all home systems meet the criteria of having the required minimum number of planets
# within their near vicinity, if not, add the missing number of planets
print "Checking if home systems have the required minimum of planets within the near vicinity..."
for home_system in home_systems:
# calculate the number of missing planets, and add them if this number is > 0
systems_in_vicinity = get_systems_within_jumps(home_system,
HS_VICINITY_RANGE)
num_systems_in_vicinity = len(systems_in_vicinity)
num_planets_in_vicinity = count_planets_in_systems(systems_in_vicinity)
num_planets_to_add = min_planets_in_vicinity_limit(
num_systems_in_vicinity) - num_planets_in_vicinity
print "Home system", home_system, "has", num_systems_in_vicinity, "systems and", num_planets_in_vicinity,\
"planets in the near vicinity, required minimum:", min_planets_in_vicinity_limit(num_systems_in_vicinity)
if num_planets_to_add > 0:
systems_in_vicinity.remove(
home_system
) # don't add planets to the home system, so remove it from the list
add_planets_to_vicinity(systems_in_vicinity, num_planets_to_add)
# as we've sorted the home system list before, lets shuffle it to ensure random order and return
random.shuffle(home_systems)
return home_systems
def compile_home_system_list(num_home_systems, systems):
"""
Compiles a list with a requested number of home systems.
"""
# if the list of systems to choose home systems from is empty, report an error and return empty list
if not systems:
util.report_error(
"Python generate_home_system_list: no systems to choose from")
return []
# calculate an initial minimal number of jumps that the home systems should be apart,
# based on the total number of systems to choose from and the requested number of home systems
min_jumps = max(int(float(len(systems)) / float(num_home_systems * 2)), 5)
# try to find the home systems, decrease the min jumps until enough systems can be found, or the min jump distance
# gets reduced to 0 (meaning we don't have enough systems to choose from at all)
while min_jumps > 0:
print "Trying to find", num_home_systems, "home systems that are at least", min_jumps, "jumps apart"
# try to find home systems...
home_systems = find_systems_with_min_jumps_between(
num_home_systems, systems, min_jumps)
# ...check if we got enough...
if len(home_systems) >= num_home_systems:
# ...yes, we got what we need, so let's break out of the loop
break
print "Home system min jump conflict: %d systems and %d empires, tried %d min jump and failed"\
% (len(systems), num_home_systems, min_jumps)
# ...no, decrease the min jump distance and try again
min_jumps -= 1
# check if the loop above delivered a list with enough home systems, or if it exited because the min jump distance
# has been decreased to 0 without finding enough systems
# in that case, our galaxy obviously is too crowded, report an error and return an empty list
if len(home_systems) < num_home_systems:
util.report_error(
"Python generate_home_system_list: requested %d homeworlds in a galaxy with %d systems"
% (num_home_systems, len(systems)))
return []
# make sure all our home systems have a "real" star (that is, a star that is not a neutron star, black hole,
# or even no star at all) and at least one planet in it
for home_system in home_systems:
# if this home system has no "real" star, change star type to a randomly selected "real" star
if fo.sys_get_star_type(
home_system) not in starsystems.star_types_real:
star_type = random.choice(starsystems.star_types_real)
print "Home system", home_system, "has star type", fo.sys_get_star_type(home_system),\
", changing that to", star_type
fo.sys_set_star_type(home_system, star_type)
# if this home system has no planets, create one in a random orbit
# we take random values for type and size, as these will be set to suitable values later
if not fo.sys_get_planets(home_system):
print "Home system", home_system, "has no planets, adding one"
planet = fo.create_planet(
random.choice(planets.planet_sizes_real),
random.choice(planets.planet_types_real), home_system,
random.randint(0,
fo.sys_get_num_orbits(home_system) - 1), "")
# if we couldn't create the planet, report an error and return an empty list
if planet == fo.invalid_object():
util.report_error(
"Python generate_home_system_list: couldn't create planet in home system"
)
return []
return home_systems
def compile_home_system_list(num_home_systems, systems):
"""
Compiles a list with a requested number of home systems.
"""
print "Compile home system list:", num_home_systems, "systems requested"
# if the list of systems to choose home systems from is empty, report an error and return empty list
if not systems:
report_error("Python generate_home_system_list: no systems to choose from")
return []
# calculate an initial minimal number of jumps that the home systems should be apart,
# based on the total number of systems to choose from and the requested number of home systems
# Don't let min_jumps be larger than 10, because a larger number is really not at all needed and with large
# galaxies an excessive amount of time can be used in failed attempts
min_jumps = min(10, max(int(float(len(systems)) / float(num_home_systems * 2)), 5))
# home systems must have a certain minimum of systems in their near vicinity
# we will try to select our home systems from systems that match this criteria, if that fails, we will select our
# home systems from all systems and add the missing number planets to the systems in their vicinity afterwards
# the minimum planet limit and the jump range that defines the "near vicinity" are controlled by the
# HS_* option constants in options.py (see there)
# lets start by filtering out all systems from the pool we got passed into this function that match the criteria
filtered_pool = [s for s in systems if has_min_planets_in_vicinity(s)]
print "Filtering out systems that meet the minimum planets in the near vicinity condition yielded",\
len(filtered_pool), "systems"
print "Using this as the preferred pool for home system selection"
# now try to pick the requested number of home systems by calling find_home_systems
# this function takes two pools, a "complete" pool and one with preferred systems
# it will try to pick the home systems from the preferred pool first, so pass our filtered pool as preferred pool
home_systems = find_home_systems(num_home_systems, systems, filtered_pool, min_jumps)
# check if the selection process delivered a list with enough home systems
# if not, our galaxy obviously is too crowded, report an error and return an empty list
if len(home_systems) < num_home_systems:
report_error("Python generate_home_system_list: requested %d homeworlds in a galaxy with %d systems"
% (num_home_systems, len(systems)))
return []
# check if we got more home systems than we requested
if len(home_systems) > num_home_systems:
# yes: calculate the number of planets in the near vicinity of each system
# and store that value with each system in a map
hs_planets_in_vicinity_map = {s: count_planets_in_systems(get_systems_within_jumps(s, HS_VICINITY_RANGE))
for s in home_systems}
# sort the home systems by the number of planets in their near vicinity using the map
# now only pick the number of home systems we need, taking those with the highest number of planets
home_systems = sorted(home_systems, key=hs_planets_in_vicinity_map.get, reverse=True)[:num_home_systems]
# make sure all our home systems have a "real" star (that is, a star that is not a neutron star, black hole,
# or even no star at all) and at least one planet in it
for home_system in home_systems:
# if this home system has no "real" star, change star type to a randomly selected "real" star
if fo.sys_get_star_type(home_system) not in star_types_real:
star_type = random.choice(star_types_real)
print "Home system", home_system, "has star type", fo.sys_get_star_type(home_system),\
", changing that to", star_type
fo.sys_set_star_type(home_system, star_type)
# if this home system has no planets, create one in a random orbit
# we take random values for type and size, as these will be set to suitable values later
if not fo.sys_get_planets(home_system):
print "Home system", home_system, "has no planets, adding one"
planet = fo.create_planet(random.choice(planet_sizes_real),
random.choice(planet_types_real),
home_system, random.randint(0, fo.sys_get_num_orbits(home_system) - 1), "")
# if we couldn't create the planet, report an error and return an empty list
if planet == fo.invalid_object():
report_error("Python generate_home_system_list: couldn't create planet in home system")
return []
# finally, check again if all home systems meet the criteria of having the required minimum number of planets
# within their near vicinity, if not, add the missing number of planets
print "Checking if home systems have the required minimum of planets within the near vicinity..."
for home_system in home_systems:
# calculate the number of missing planets, and add them if this number is > 0
systems_in_vicinity = get_systems_within_jumps(home_system, HS_VICINITY_RANGE)
num_systems_in_vicinity = len(systems_in_vicinity)
num_planets_in_vicinity = count_planets_in_systems(systems_in_vicinity)
num_planets_to_add = min_planets_in_vicinity_limit(num_systems_in_vicinity) - num_planets_in_vicinity
print "Home system", home_system, "has", num_systems_in_vicinity, "systems and", num_planets_in_vicinity,\
"planets in the near vicinity, required minimum:", min_planets_in_vicinity_limit(num_systems_in_vicinity)
if num_planets_to_add > 0:
systems_in_vicinity.remove(home_system) # don't add planets to the home system, so remove it from the list
add_planets_to_vicinity(systems_in_vicinity, num_planets_to_add)
# as we've sorted the home system list before, lets shuffle it to ensure random order and return
random.shuffle(home_systems)
return home_systems
