def log_planet_count_dist(sys_list):
planet_count_dist = {}
planet_size_dist = {size: 0 for size in planets.planet_sizes}
for system in sys_list:
planet_count = 0
for planet in fo.sys_get_planets(system):
this_size = fo.planet_get_size(planet)
if this_size in planets.planet_sizes:
planet_count += 1
planet_size_dist[this_size] += 1
planet_count_dist.setdefault(planet_count, [0])[0] += 1
planet_tally = sum(planet_size_dist.values())
count_distribution_table = Table(
[Text('planets in system'), Text('num of systems'), Float('% of systems', precession=1)],
table_name='Planet Count Distribution'
)
for planet_count, sys_count in planet_count_dist.items():
count_distribution_table.add_row((planet_count, sys_count[0], 100.0 * sys_count[0] / len(sys_list)))
print(count_distribution_table)
print()
size_distribution = Table(
[Text('size'), Text('count'), Float('% of planets', precession=1)],
table_name='Planet Size Distribution'
)
for planet_size, planet_count in sorted(planet_size_dist.items()):
size_distribution.add_row((planet_size, planet_count, 100.0 * planet_count / planet_tally))
print(size_distribution)
print()
def log_planets():
universe = fo.get_universe()
planets_table = Table([
Text('id'),
Text('name'),
Text('system'),
Text('type'),
Sequence('specials'),
Text('species'),
Sequence('buildings')
],
table_name='Planets summary')
# group planets by system
for sid in fo.get_systems():
for pid in fo.sys_get_planets(sid):
planet = universe.getPlanet(pid)
planet_type = fo.planet_get_type(pid).name
planet_size = fo.planet_get_size(pid).name
if planet_type != planet_size:
planet_type = '%s %s' % (planet_type, planet_size)
buildings = [
universe.getBuilding(x).name for x in planet.buildingIDs
]
planets_table.add_row([
pid, planet.name, planet.systemID, planet_type,
list(planet.specials), planet.speciesName, buildings
])
# Printing too much info at once will lead to truncation of text
for line in planets_table.get_table().split('\n'):
print line
def log_planets():
universe = fo.get_universe()
planets_table = Table(
[Text('id'), Text('name'), Text('system'), Text('type'),
Sequence('specials'), Text('species'), Sequence('buildings')],
table_name='Planets summary')
# group planets by system
for sid in fo.get_systems():
for pid in fo.sys_get_planets(sid):
planet = universe.getPlanet(pid)
planet_type = fo.planet_get_type(pid).name
planet_size = fo.planet_get_size(pid).name
if planet_type != planet_size:
planet_type = '%s %s' % (planet_type, planet_size)
buildings = [universe.getBuilding(x).name for x in planet.buildingIDs]
planets_table.add_row([
pid, planet.name, planet.systemID, planet_type, list(planet.specials), planet.speciesName, buildings
])
# Printing too much info at once will lead to truncation of text
for line in planets_table.get_table().split('\n'):
print line
def log_planet_count_dist(sys_list):
planet_count_dist = {}
planet_size_dist = {size: 0 for size in planets.planet_sizes}
for system in sys_list:
planet_count = 0
for planet in fo.sys_get_planets(system):
this_size = fo.planet_get_size(planet)
if this_size in planets.planet_sizes:
planet_count += 1
planet_size_dist[this_size] += 1
planet_count_dist.setdefault(planet_count, [0])[0] += 1
planet_tally = sum(planet_size_dist.values())
count_distribution_table = Table(
[Text('planets in system'), Text('num of systems'), Float('% of systems', precession=1)],
table_name='Planet Count Distribution'
)
for planet_count, sys_count in planet_count_dist.items():
count_distribution_table.add_row((planet_count, sys_count[0], 100.0 * sys_count[0] / len(sys_list)))
print count_distribution_table
print
size_distribution = Table(
[Text('size'), Text('count'), Float('% of planets', precession=1)],
table_name='Planet Size Distribution'
)
for planet_size, planet_count in sorted(planet_size_dist.items()):
size_distribution.add_row((planet_size, planet_count, 100.0 * planet_count / planet_tally))
print size_distribution
print
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 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 execute_turn_events():
print "Executing turn events for turn", fo.current_turn()
# creating fields
systems = fo.get_systems()
radius = fo.get_universe_width() / 2.0
if random() < max(0.0003 * radius, 0.03):
if random() < 0.4:
field_type = "FLD_MOLECULAR_CLOUD"
size = 5.0
else:
field_type = "FLD_ION_STORM"
size = 5.0
x = y = radius
dist_from_center = 0.0
while (dist_from_center < radius) or any(hypot(fo.get_x(s) - x, fo.get_y(s) - y) < 50.0 for s in systems):
angle = random() * 2.0 * pi
dist_from_center = radius + uniform(min(max(radius * 0.02, 10), 50.0), min(max(radius * 0.05, 20), 100.0))
x = radius + (dist_from_center * sin(angle))
y = radius + (dist_from_center * cos(angle))
print "...creating new", field_type, "field, at distance", dist_from_center, "from center"
if fo.create_field(field_type, x, y, size) == fo.invalid_object():
print >> sys.stderr, "Turn events: couldn't create new field"
# creating monsters
gsd = fo.get_galaxy_setup_data()
monster_freq = MONSTER_FREQUENCY[gsd.monsterFrequency]
# monster freq ranges from 30 (= one monster per 30 systems) to 3 (= one monster per 3 systems)
# (example: low monsters and 150 Systems results in 150 / 30 * 0.001 = 0.005)
if monster_freq > 0 and random() < len(systems) / monster_freq * 0.001:
#only spawn Krill at the moment, other monsters can follow in the future
if random() < 1:
monster_type = "SM_KRILL_1"
else:
monster_type = "SM_FLOATER"
# search for systems without planets or fleets
candidates = [s for s in systems if len(fo.sys_get_planets(s)) <= 0 and len(fo.sys_get_fleets(s)) <= 0]
if not candidates:
print >> sys.stderr, "Turn events: unable to find system for monster spawn"
else:
system = choice(candidates)
print "...creating new", monster_type, "at", fo.get_name(system)
# create monster fleet
monster_fleet = fo.create_monster_fleet(system)
# if fleet creation fails, report an error
if monster_fleet == fo.invalid_object():
print >> sys.stderr, "Turn events: unable to create new monster fleet"
else:
# create monster, if creation fails, report an error
monster = fo.create_monster(monster_type, monster_fleet)
if monster == fo.invalid_object():
print >> sys.stderr, "Turn events: unable to create monster in fleet"
return True
def log_planet_type_summary(sys_list):
planet_type_summary = {k: 0 for k in planets.planet_types}
for system in sys_list:
for planet in fo.sys_get_planets(system):
planet_type_summary[fo.planet_get_type(planet)] += 1
planet_total = sum(planet_type_summary.values())
print "Planet Type Summary for a total of %d placed planets" % planet_total
for planet_type, planet_count in planet_type_summary.items():
print "%-12s %4.1f%%" % (planet_type.name, 100.0 * planet_count / planet_total)
def count_planets_in_systems(systems, planet_types_filter=HS_ACCEPTABLE_PLANET_TYPES):
"""
Return the total number of planets in the specified group of systems,
only count the planet types specified in planet_types_filter.
"""
num_planets = 0
for system in systems:
num_planets += len([p for p in fo.sys_get_planets(system) if fo.planet_get_type(p) in planet_types_filter])
return num_planets
def count_planets_in_systems(systems, planet_types_filter=HS_ACCEPTABLE_PLANET_TYPES):
"""
Return the total number of planets in the specified group of systems,
only count the planet types specified in planet_types_filter.
"""
num_planets = 0
for system in systems:
num_planets += len([p for p in fo.sys_get_planets(system) if fo.planet_get_type(p) in planet_types_filter])
return num_planets
def log_planet_type_summary(sys_list):
planet_type_summary = {k: 0 for k in planets.planet_types}
for system in sys_list:
for planet in fo.sys_get_planets(system):
planet_type_summary[fo.planet_get_type(planet)] += 1
planet_total = sum(planet_type_summary.values())
print "Planet Type Summary for a total of %d placed planets" % planet_total
for planet_type, planet_count in planet_type_summary.items():
print "%-12s %4.1f%%" % (planet_type.name,
100.0 * planet_count / planet_total)
def log_systems():
universe = fo.get_universe()
systems_table = Table(
[Text('id'), Text('name'), Sequence('planets'), Sequence('connections'), Text('star')],
table_name='System summary')
for sid in fo.get_systems():
system = universe.getSystem(sid)
systems_table.add_row([
sid, system.name, fo.sys_get_planets(sid), fo.sys_get_starlanes(sid), system.starType.name
])
# Printing too much info at once will lead to truncation of text
for line in systems_table.get_table().split('\n'):
print(line)
def log_systems():
universe = fo.get_universe()
systems_table = Table(
[Text('id'), Text('name'), Sequence('planets'), Sequence('connections'), Text('star')],
table_name='System summary')
for sid in fo.get_systems():
system = universe.getSystem(sid)
systems_table.add_row([
sid, system.name, fo.sys_get_planets(sid), fo.sys_get_starlanes(sid), system.starType.name
])
# Printing too much info at once will lead to truncation of text
for line in systems_table.get_table().split('\n'):
print line
def name_planets(system):
"""
Sets the names of the planets of the specified system.
Planet name is system name + planet number (as roman number)
unless it's an asteroid belt, in that case name is system
name + 'asteroid belt' (localized).
"""
# iterate over all planets in the system
sys_name = fo.get_name(system)
for planet in fo.sys_get_planets(system):
name = fo.user_string("NEW_PLANET_NAME")
name = name.replace("%1%", sys_name)
name = name.replace("%2%", fo.planet_cardinal_suffix(planet))
fo.set_name(planet, name)
def name_planets(system):
"""
Sets the names of the planets of the specified system.
Planet name is system name + planet number (as roman number)
unless it's an asteroid belt, in that case name is system
name + 'asteroid belt' (localized).
"""
# iterate over all planets in the system
sys_name = fo.get_name(system)
for planet in fo.sys_get_planets(system):
name = fo.user_string("NEW_PLANET_NAME")
name = name.replace("%1%", sys_name)
name = name.replace("%2%", fo.planet_cardinal_suffix(planet))
fo.set_name(planet, name)
def log_planet_type_summary(sys_list):
planet_type_summary_table = {k: 0 for k in planets.planet_types}
for system in sys_list:
for planet in fo.sys_get_planets(system):
planet_type_summary_table[fo.planet_get_type(planet)] += 1
planet_total = sum(planet_type_summary_table.values())
type_summary_table = Table(
[Text('planet type', align='<'), Float('% of planets', precession=1)],
table_name='Planet Type Summary for a total of %d placed planets' % planet_total
)
for planet_type, planet_count in sorted(planet_type_summary_table.items()):
type_summary_table.add_row((planet_type.name, 100.0 * planet_count / planet_total))
print type_summary_table
print
def log_planet_type_summary(sys_list):
planet_type_summary_table = {k: 0 for k in planets.planet_types}
for system in sys_list:
for planet in fo.sys_get_planets(system):
planet_type_summary_table[fo.planet_get_type(planet)] += 1
planet_total = sum(planet_type_summary_table.values())
type_summary_table = Table(
[Text('planet type', align='<'), Float('% of planets', precession=1)],
table_name='Planet Type Summary for a total of %d placed planets' % planet_total
)
for planet_type, planet_count in sorted(planet_type_summary_table.items()):
type_summary_table.add_row((planet_type.name, 100.0 * planet_count / planet_total))
print(type_summary_table)
print()
def log_planet_count_dist(sys_list):
planet_count_dist = {}
planet_size_dist = {size : 0 for size in planets.planet_sizes}
for system in sys_list:
planet_count = 0
for planet in fo.sys_get_planets(system):
this_size = fo.planet_get_size(planet)
if this_size in planets.planet_sizes:
planet_count += 1
planet_size_dist[this_size] += 1
planet_count_dist.setdefault(planet_count, [0])[0] += 1
planet_tally = sum(planet_size_dist.values())
print "Planet Count Distribution: planets_in_system | num_systems | % of systems"
for planet_count, sys_count in planet_count_dist.items():
print "\t\t\t%2d | %5d | %4.1f%%" % (planet_count, sys_count[0], 100.0 * sys_count[0] / len(sys_list))
print
print "Planet Size Distribution: size | count | % of planets"
for planet_size, planet_count in planet_size_dist.items():
print "\t\t%-12s | %5d | %4.1f%%" % (planet_size, planet_count, 100.0 * planet_count / planet_tally)
def log_planet_count_dist(sys_list):
planet_count_dist = {}
planet_size_dist = {size: 0 for size in planets.planet_sizes}
for system in sys_list:
planet_count = 0
for planet in fo.sys_get_planets(system):
this_size = fo.planet_get_size(planet)
if this_size in planets.planet_sizes:
planet_count += 1
planet_size_dist[this_size] += 1
planet_count_dist.setdefault(planet_count, [0])[0] += 1
planet_tally = sum(planet_size_dist.values())
count_distribution_table = Table(
Text("planets in system"),
Text("num of systems"),
Number("% of systems", precession=1),
table_name="Planet Count Distribution",
)
for planet_count, sys_count in planet_count_dist.items():
count_distribution_table.add_row(
planet_count,
sys_count[0],
100.0 * sys_count[0] / len(sys_list),
)
count_distribution_table.print_table(print)
print()
size_distribution = Table(
Text("size"),
Text("count"),
Number("% of planets", precession=1),
table_name="Planet Size Distribution",
)
for planet_size, planet_count in sorted(planet_size_dist.items()):
size_distribution.add_row(
planet_size,
planet_count,
100.0 * planet_count / planet_tally,
)
size_distribution.print_table(print)
print()
def log_planet_type_summary(sys_list):
planet_type_summary_table = {k: 0 for k in planets.planet_types}
for system in sys_list:
for planet in fo.sys_get_planets(system):
planet_type_summary_table[fo.planet_get_type(planet)] += 1
planet_total = sum(planet_type_summary_table.values())
type_summary_table = Table(
Text("planet type", align="<"),
Number("% of planets", precession=1),
table_name="Planet Type Summary for a total of %d placed planets" %
planet_total,
)
for planet_type, planet_count in sorted(planet_type_summary_table.items()):
type_summary_table.add_row(
planet_type.name,
100.0 * planet_count / planet_total,
)
type_summary_table.print_table(print)
print()
def log_planet_count_dist(sys_list):
planet_count_dist = {}
planet_size_dist = {size: 0 for size in planets.planet_sizes}
for system in sys_list:
planet_count = 0
for planet in fo.sys_get_planets(system):
this_size = fo.planet_get_size(planet)
if this_size in planets.planet_sizes:
planet_count += 1
planet_size_dist[this_size] += 1
planet_count_dist.setdefault(planet_count, [0])[0] += 1
planet_tally = sum(planet_size_dist.values())
print "Planet Count Distribution: planets_in_system | num_systems | % of systems"
for planet_count, sys_count in planet_count_dist.items():
print "\t\t\t%2d | %5d | %4.1f%%" % (
planet_count, sys_count[0], 100.0 * sys_count[0] / len(sys_list))
print
print "Planet Size Distribution: size | count | % of planets"
for planet_size, planet_count in planet_size_dist.items():
print "\t\t%-12s | %5d | %4.1f%%" % (planet_size, planet_count, 100.0 *
planet_count / planet_tally)
def log_systems():
universe = fo.get_universe()
systems_table = Table(
Text("id"),
Text("name"),
Sequence("planets"),
Sequence("connections"),
Text("star"),
table_name="System summary",
)
for sid in fo.get_systems():
system = universe.getSystem(sid)
systems_table.add_row(
sid,
system.name,
fo.sys_get_planets(sid),
fo.sys_get_starlanes(sid),
system.starType.name,
)
systems_table.print_table(print)
def name_planets(system):
"""
Sets the names of the planets of the specified system.
Planet name is system name + planet number (as roman number)
unless it's an asteroid belt, in that case name is system
name + 'asteroid belt' (localized).
"""
planet_number = 1
# iterate over all planets in the system
for planet in fo.sys_get_planets(system):
# use different naming methods for "normal" planets and asteroid belts
if fo.planet_get_type(planet) == fo.planetType.asteroids:
# get localized text from stringtable
name = fo.user_string("PL_ASTEROID_BELT_OF_SYSTEM")
# %1% parameter in the localized string is the system name
name = name.replace("%1%", fo.get_name(system))
else:
# set name to system name + planet number as roman number...
name = fo.get_name(system) + " " + fo.roman_number(planet_number)
# ...and increase planet number
planet_number += 1
# do the actual renaming
fo.set_name(planet, name)
def name_planets(system):
"""
Sets the names of the planets of the specified system.
Planet name is system name + planet number (as roman number)
unless it's an asteroid belt, in that case name is system
name + 'asteroid belt' (localized).
"""
planet_number = 1
# iterate over all planets in the system
for planet in fo.sys_get_planets(system):
# use different naming methods for "normal" planets and asteroid belts
if fo.planet_get_type(planet) == fo.planetType.asteroids:
# get localized text from stringtable
name = fo.user_string("PL_ASTEROID_BELT_OF_SYSTEM")
# %1% parameter in the localized string is the system name
name = name.replace("%1%", fo.get_name(system))
else:
# set name to system name + planet number as roman number...
name = fo.get_name(system) + " " + fo.roman_number(planet_number)
# ...and increase planet number
planet_number += 1
# do the actual renaming
fo.set_name(planet, name)
def log_planets():
universe = fo.get_universe()
planets_table = Table(
Text("id"),
Text("name"),
Text("system"),
Text("type"),
Sequence("specials"),
Text("species"),
Sequence("buildings"),
table_name="Planets summary",
)
# group planets by system
for sid in fo.get_systems():
for pid in fo.sys_get_planets(sid):
planet = universe.getPlanet(pid)
planet_type = fo.planet_get_type(pid).name
planet_size = fo.planet_get_size(pid).name
if planet_type != planet_size:
planet_type = "%s %s" % (planet_type, planet_size)
buildings = [
universe.getBuilding(x).name for x in planet.buildingIDs
]
planets_table.add_row(
pid,
planet.name,
planet.systemID,
planet_type,
list(planet.specials),
planet.speciesName,
buildings,
)
planets_table.print_table(print)
def generate_natives(native_freq, systems, empire_home_systems):
"""
Adds non-empire-affiliated native populations to planets.
"""
# first, calculate the chance for natives on a planet based on the native frequency that has been passed
# get the corresponding value for the specified natives frequency from the universe tables
native_chance = universe_tables.NATIVE_FREQUENCY[native_freq]
# a value of 0 means no natives, in this case return immediately
if native_chance <= 0:
return
# compile a list of planets where natives can be placed
# select only planets sufficiently far away from player home systems
# list of planets safe for natives
EMPIRE_TO_NATIVE_MIN_DIST = 2
empire_exclusions = set(
itertools.chain.from_iterable(
fo.systems_within_jumps_unordered(EMPIRE_TO_NATIVE_MIN_DIST, [e])
for e in empire_home_systems))
native_safe_planets = set(
itertools.chain.from_iterable([
fo.sys_get_planets(s) for s in systems
if s not in empire_exclusions
]))
print(
"Number of planets far enough from players for natives to be allowed:",
len(native_safe_planets))
# if there are no "native safe" planets at all, we can stop here
if not native_safe_planets:
return
# get all native species
native_species = fo.get_native_species()
print("Species that can be added as natives:")
print("... " + "\n... ".join(native_species))
# create a map with a list for each planet type containing the species
# for which this planet type is a good environment
# we will need this afterwards when picking natives for a planet
natives_for_planet_type.clear() # just to be safe
natives_for_planet_type.update(
{planet_type: []
for planet_type in planets.planet_types})
planet_types_for_natives.clear()
planet_types_for_natives.update(
{species: set()
for species in native_species})
# iterate over all native species we got
for species in native_species:
# check the planet environment for all planet types for this species
for planet_type in planets.planet_types:
# if this planet type is a good environment for the species, add it to the list for this planet type
if fo.species_get_planet_environment(
species, planet_type) == fo.planetEnvironment.good:
natives_for_planet_type[planet_type].append(species)
planet_types_for_natives[species].add(planet_type)
# randomly add species to planets
# iterate over the list of "native safe" planets we compiled earlier
for candidate in native_safe_planets:
# select a native species to put on this planet
planet_type = fo.planet_get_type(candidate)
# check if we have any native species that like this planet type
if not natives_for_planet_type[planet_type]:
# no, continue with next planet
continue
universe_statistics.potential_native_planet_summary[planet_type] += 1
# make a "roll" against the chance for natives to determine if we shall place natives on this planet
if random.random() > native_chance:
# no, continue with next planet
continue
universe_statistics.settled_native_planet_summary[planet_type] += 1
# randomly pick one of the native species available for this planet type
natives = random.choice(natives_for_planet_type[planet_type])
# put the selected natives on the planet
fo.planet_set_species(candidate, natives)
# set planet as homeworld for that species
fo.species_add_homeworld(natives, candidate)
# set planet focus
# check if the preferred focus for the native species is among the foci available on this planet
available_foci = fo.planet_available_foci(candidate)
preferred_focus = fo.species_preferred_focus(natives)
if preferred_focus in available_foci:
# if yes, set the planet focus to the preferred focus
fo.planet_set_focus(candidate, preferred_focus)
elif available_foci:
# if no, and there is at least one available focus, just take the first of the list
# otherwise don't set any focus
fo.planet_set_focus(candidate, available_foci[0])
print("Added native", natives, "to planet", fo.get_name(candidate))
# increase the statistics counter for this native species, so a species summary can be dumped to the log later
universe_statistics.species_summary[natives] += 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)
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):
"""
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 generate_monsters(monster_freq, systems):
"""
Adds space monsters to systems.
"""
# first, calculate the basic chance for monster generation in a system
# based on the monster frequency that has been passed
# get the corresponding value for the specified monster frequency from the universe tables
basic_chance = universe_tables.MONSTER_FREQUENCY[monster_freq]
# a value of 0 means no monsters, in this case return immediately
if basic_chance <= 0:
return
print "Default monster spawn chance:", basic_chance
expectation_tally = 0.0
actual_tally = 0
# get all monster fleets that have a spawn rate and limit both > 0 and at least one monster ship design in it
# (a monster fleet with no monsters in it is pointless) and store them in a list
fleet_plans = fo.load_monster_fleet_plan_list()
# create a map where we store a spawn counter for each monster fleet
# this counter will be set to the spawn limit initially and decreased every time the monster fleet is spawned
# this map (dict) needs to be separate from the list holding the fleet plans because the order in which items
# are stored in a dict is undefined (can be different each time), which would result in different distribution
# even when using the same seed for the RNG
spawn_limits = {
fp: fp.spawn_limit()
for fp in fleet_plans if fp.spawn_rate() > 0.0 and fp.spawn_limit() > 0
and fp.ship_designs()
}
# map nests to monsters for ease of reporting
nest_name_map = {
"KRAKEN_NEST_SPECIAL": "SM_KRAKEN_1",
"SNOWFLAKE_NEST_SPECIAL": "SM_SNOWFLAKE_1",
"JUGGERNAUT_NEST_SPECIAL": "SM_JUGGERNAUT_1"
}
tracked_plan_tries = {name: 0 for name in nest_name_map.values()}
tracked_plan_counts = {name: 0 for name in nest_name_map.values()}
tracked_plan_valid_locations = {
fp: 0
for fp in fleet_plans if fp.name() in tracked_plan_counts
}
tracked_nest_valid_locations = {nest: 0 for nest in nest_name_map}
if not fleet_plans:
return
universe = fo.get_universe()
# Fleet plans that include ships capable of altering starlanes.
## @content_tag{CAN_ALTER_STARLANES} universe_generator special handling for fleets containing a hull design with this tag.
fleet_can_alter_starlanes = {
fp
for fp in fleet_plans if any([
universe.getGenericShipDesign(design).hull_type.hasTag(
"CAN_ALTER_STARLANES") for design in fp.ship_designs()
])
}
# dump a list of all monster fleets meeting these conditions and their properties to the log
print "Monster fleets available for generation at game start:"
for fleet_plan in fleet_plans:
print "...", fleet_plan.name(), ": spawn rate", fleet_plan.spawn_rate(
),
print "/ spawn limit", fleet_plan.spawn_limit(),
print "/ effective chance", basic_chance * fleet_plan.spawn_rate(),
if len(systems) < 100:
# Note: The WithinStarlaneJumps condition in fp.location()
# is the most time costly function in universe generation
print "/ can be spawned at", len(
[s for s in systems if fleet_plan.location(s)]), "systems"
else:
print # to terminate the print line
if fleet_plan.name() in nest_name_map.values():
statistics.tracked_monsters_chance[
fleet_plan.name()] = basic_chance * fleet_plan.spawn_rate()
# initialize a manager for monsters that can alter the map
# required to prevent their placement from disjoining the map
starlane_altering_monsters = StarlaneAlteringMonsters(systems)
# for each system in the list that has been passed to this function, find a monster fleet that can be spawned at
# the system and which hasn't already been added too many times, then attempt to add that monster fleet by
# testing the spawn rate chance
for system in systems:
# collect info for tracked monster nest valid locations
for planet in fo.sys_get_planets(system):
for nest in tracked_nest_valid_locations:
# print "\t tracked monster check planet: %d size: %s for nest: %20s | result: %s"
# % (planet, fo.planet_get_size(planet), nest, fo.special_location(nest, planet))
if fo.special_location(nest, planet):
tracked_nest_valid_locations[nest] += 1
# collect info for tracked monster valid locations
for fp in tracked_plan_valid_locations:
if fp.location(system):
tracked_plan_valid_locations[fp] += 1
# filter out all monster fleets whose location condition allows this system and whose counter hasn't reached 0.
# Note: The WithinStarlaneJumps condition in fp.location() is
# the most time costly function in universe generation.
suitable_fleet_plans = [
fp for fp in fleet_plans
if spawn_limits[fp] and fp.location(system) and (
fp not in fleet_can_alter_starlanes
or starlane_altering_monsters.can_place_at(system, fp))
]
# if there are no suitable monster fleets for this system, continue with the next
if not suitable_fleet_plans:
continue
# randomly select one monster fleet out of the suitable ones and then test if we want to add it to this system
# by making a roll against the basic chance multiplied by the spawn rate of this monster fleet
expectation_tally += basic_chance * sum(
[fp.spawn_rate()
for fp in suitable_fleet_plans]) / len(suitable_fleet_plans)
fleet_plan = random.choice(suitable_fleet_plans)
if fleet_plan.name() in tracked_plan_tries:
tracked_plan_tries[fleet_plan.name()] += 1
if random.random() > basic_chance * fleet_plan.spawn_rate():
print(
"\t\t At system %4d rejected monster fleet %s from %d suitable fleets"
% (system, fleet_plan.name(), len(suitable_fleet_plans)))
# no, test failed, continue with the next system
continue
actual_tally += 1
if fleet_plan.name() in tracked_plan_counts:
tracked_plan_counts[fleet_plan.name()] += 1
# all prerequisites and the test have been met, now spawn this monster fleet in this system
# create monster fleet
try:
if fleet_plan in fleet_can_alter_starlanes:
starlane_altering_monsters.place(system, fleet_plan)
else:
populate_monster_fleet(fleet_plan, system)
# decrement counter for this monster fleet
spawn_limits[fleet_plan] -= 1
except MapGenerationError as e:
report_error(str(e))
continue
print "Actual # monster fleets placed: %d; Total Placement Expectation: %.1f" % (
actual_tally, expectation_tally)
# finally, compile some statistics to be dumped to the log later
statistics.monsters_summary = [(fp.name(), fp.spawn_limit() - counter)
for fp, counter in spawn_limits.iteritems()]
statistics.tracked_monsters_tries.update(tracked_plan_tries)
statistics.tracked_monsters_summary.update(tracked_plan_counts)
statistics.tracked_monsters_location_summary.update([
(fp.name(), count)
for fp, count in tracked_plan_valid_locations.iteritems()
])
statistics.tracked_nest_location_summary.update([
(nest_name_map[nest], count)
for nest, count in tracked_nest_valid_locations.items()
])
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 = 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 setup_empire(empire, empire_name, home_system, starting_species, player_name):
"""
Sets up various aspects of an empire, like empire name, homeworld, etc.
"""
# set empire name, if no one is given, pick one randomly
if not empire_name:
print "No empire name set for player", player_name, ", picking one randomly"
empire_name = next(empire_name_generator)
fo.empire_set_name(empire, empire_name)
print "Empire name for player", player_name, "is", empire_name
# check starting species, if no one is given, pick one randomly
if starting_species == "RANDOM" or not starting_species:
print "Picking random starting species for player", player_name
starting_species = next(starting_species_pool)
print "Starting species for player", player_name, "is", starting_species
statistics.empire_species[starting_species] += 1
# pick a planet from the specified home system as homeworld
planet_list = fo.sys_get_planets(home_system)
# if the system is empty, report an error and return false, indicating failure
if not planet_list:
report_error("Python setup_empire: got home system with no planets")
return False
homeworld = random.choice(planet_list)
# set selected planet as empire homeworld with selected starting species
fo.empire_set_homeworld(empire, homeworld, starting_species)
# set homeworld focus
# check if the preferred focus for the starting species is among
# the foci available on the homeworld planet
available_foci = fo.planet_available_foci(homeworld)
preferred_focus = fo.species_preferred_focus(starting_species)
if preferred_focus in available_foci:
# if yes, set the homeworld focus to the preferred focus
print "Player", player_name, ": setting preferred focus", preferred_focus, "on homeworld"
fo.planet_set_focus(homeworld, preferred_focus)
elif len(available_foci) > 0:
# if no, and there is at least one available focus,
# just take the first of the list
if preferred_focus == "":
print "Player", player_name, ": starting species", starting_species, "has no preferred focus, using",\
available_foci[0], "instead"
else:
print "Player", player_name, ": preferred focus", preferred_focus, "for starting species",\
starting_species, "not available on homeworld, using", available_foci[0], "instead"
fo.planet_set_focus(homeworld, available_foci[0])
else:
# if no focus is available on the homeworld, don't set any focus
print "Player", player_name, ": no available foci on homeworld for starting species", starting_species
# give homeworld starting buildings
# use the list provided in scripting/starting_unlocks/buildings.inf
print "Player", player_name, ": add starting buildings to homeworld"
for building in load_string_list(os.path.join(fo.get_resource_dir(), "scripting/starting_unlocks/buildings.inf")):
fo.create_building(building, homeworld, empire)
# unlock starting techs, buildings, hulls, ship parts, etc.
# use default content file
print "Player", player_name, ": add unlocked items"
for item in fo.load_item_spec_list():
fo.empire_unlock_item(empire, item.type, item.name)
# add premade ship designs to empire
print "Player", player_name, ": add premade ship designs"
for ship_design in fo.design_get_premade_list():
fo.empire_add_ship_design(empire, ship_design)
# add starting fleets to empire
# use default content file
print "Player", player_name, ": add starting fleets"
fleet_plans = fo.load_fleet_plan_list()
for fleet_plan in fleet_plans:
# first, create the fleet
fleet = fo.create_fleet(fleet_plan.name(), home_system, empire)
# if the fleet couldn't be created, report an error and try to continue with the next fleet plan
if fleet == fo.invalid_object():
report_error("Python setup empire: couldn't create fleet %s" % fleet_plan.name())
continue
# second, iterate over the list of ship design names in the fleet plan
for ship_design in fleet_plan.ship_designs():
# create a ship in the fleet
# if the ship couldn't be created, report an error and try to continue with the next ship design
if fo.create_ship("", ship_design, starting_species, fleet) == fo.invalid_object():
report_error("Python setup empire: couldn't create ship %s for fleet %s"
% (ship_design, fleet_plan.name()))
return True
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_monsters(monster_freq, systems):
"""
Adds space monsters to systems.
"""
# first, calculate the basic chance for monster generation in a system
# based on the monster frequency that has been passed
# get the corresponding value for the specified monster frequency from the universe tables
inverse_monster_chance = fo.monster_frequency(monster_freq)
# as the value in the universe table is higher for a lower frequency, we have to invert it
# exception: a value of 0 means no monsters, in this case return immediately
if inverse_monster_chance <= 0:
return
basic_chance = 1.0 / float(inverse_monster_chance)
print "Default monster spawn chance:", basic_chance
expectation_tally = 0.0
actual_tally = 0
# get all monster fleets that have a spawn rate and limit both > 0 and at least one monster ship design in it
# (a monster fleet with no monsters in it is pointless) and store them with a spawn counter in a dict
# this counter will be set to the spawn limit initially and decreased every time the monster fleet is spawned
fleet_plans = {
fp: fp.spawn_limit()
for fp in fo.load_monster_fleet_plan_list(
"space_monster_spawn_fleets.txt") if fp.spawn_rate() > 0.0
and fp.spawn_limit() > 0 and fp.ship_designs()
}
# map nests to monsters for ease of reporting
nest_name_map = dict(
zip([
"KRAKEN_NEST_SPECIAL", "SNOWFLAKE_NEST_SPECIAL",
"JUGGERNAUT_NEST_SPECIAL"
], ["SM_KRAKEN_1", "SM_SNOWFLAKE_1", "SM_JUGGERNAUT_1"]))
tracked_plan_tries = {name: 0 for name in nest_name_map.values()}
tracked_plan_counts = {name: 0 for name in nest_name_map.values()}
tracked_plan_valid_locations = {
fp: 0
for fp, limit in fleet_plans.iteritems()
if fp.name() in tracked_plan_counts
}
tracked_nest_valid_locations = {nest: 0 for nest in nest_name_map}
if not fleet_plans:
return
# dump a list of all monster fleets meeting these conditions and their properties to the log
print "Monster fleets available for generation at game start:"
for fleet_plan in fleet_plans:
print "...", fleet_plan.name(), ": spawn rate", fleet_plan.spawn_rate(
),
print "/ spawn limit", fleet_plan.spawn_limit(),
print "/ effective chance", basic_chance * fleet_plan.spawn_rate(),
if len(systems) < 1000:
print "/ can be spawned at", len(
[s for s in systems if fleet_plan.location(s)]), "systems"
else:
print # to terminate the print line
if fleet_plan.name() in nest_name_map.values():
statistics.tracked_monsters_chance[
fleet_plan.name()] = basic_chance * fleet_plan.spawn_rate()
# for each system in the list that has been passed to this function, find a monster fleet that can be spawned at
# the system and which hasn't already been added too many times, then attempt to add that monster fleet by
# testing the spawn rate chance
for system in systems:
# collect info for tracked monster nest valid locations
for planet in fo.sys_get_planets(system):
for nest in tracked_nest_valid_locations:
#print "\t tracked monster check planet: %d size: %s for nest: %20s | result: %s" % (planet, fo.planet_get_size(planet), nest, fo.special_location(nest, planet))
if fo.special_location(nest, planet):
tracked_nest_valid_locations[nest] += 1
# collect info for tracked monster valid locations
for fp in tracked_plan_valid_locations:
if fp.location(system):
tracked_plan_valid_locations[fp] += 1
# filter out all monster fleets whose location condition allows this system and whose counter hasn't reached 0
suitable_fleet_plans = [
fp for fp, counter in fleet_plans.iteritems()
if counter and fp.location(system)
]
# if there are no suitable monster fleets for this system, continue with the next
if not suitable_fleet_plans:
continue
# randomly select one monster fleet out of the suitable ones and then test if we want to add it to this system
# by making a roll against the basic chance multiplied by the spawn rate of this monster fleet
expectation_tally += basic_chance * sum(
[fp.spawn_rate()
for fp in suitable_fleet_plans]) / len(suitable_fleet_plans)
fleet_plan = random.choice(suitable_fleet_plans)
if fleet_plan.name() in tracked_plan_tries:
tracked_plan_tries[fleet_plan.name()] += 1
if random.random() > basic_chance * fleet_plan.spawn_rate():
print "\t\t At system %4d rejected monster fleet %s from %d suitable fleets" % (
system, fleet_plan.name(), len(suitable_fleet_plans))
# no, test failed, continue with the next system
continue
actual_tally += 1
if fleet_plan.name() in tracked_plan_counts:
tracked_plan_counts[fleet_plan.name()] += 1
# all prerequisites and the test have been met, now spawn this monster fleet in this system
print "Spawn", fleet_plan.name(), "at", fo.get_name(system)
# decrement counter for this monster fleet
fleet_plans[fleet_plan] -= 1
# create monster fleet
monster_fleet = fo.create_monster_fleet(system)
# if fleet creation fails, report an error and try to continue with next system
if monster_fleet == fo.invalid_object():
util.report_error(
"Python generate_monsters: unable to create new monster fleet %s"
% fleet_plan.name())
continue
# add monsters to fleet
for design in fleet_plan.ship_designs():
# create monster, if creation fails, report an error and try to continue with the next design
if fo.create_monster(design, monster_fleet) == fo.invalid_object():
util.report_error(
"Python generate_monsters: unable to create monster %s" %
design)
print "Actual # monster fleets placed: %d; Total Placement Expectation: %.1f" % (
actual_tally, expectation_tally)
# finally, compile some statistics to be dumped to the log later
statistics.monsters_summary = [(fp.name(), fp.spawn_limit() - counter)
for fp, counter in fleet_plans.iteritems()]
statistics.tracked_monsters_tries.update(tracked_plan_tries)
statistics.tracked_monsters_summary.update(tracked_plan_counts)
statistics.tracked_monsters_location_summary.update([
(fp.name(), count)
for fp, count in tracked_plan_valid_locations.iteritems()
])
statistics.tracked_nest_location_summary.update([
(nest_name_map[nest], count)
for nest, count in tracked_nest_valid_locations.items()
])
def generate_monsters(monster_freq, systems):
"""
Adds space monsters to systems.
"""
# first, calculate the basic chance for monster generation in a system
# based on the monster frequency that has been passed
# get the corresponding value for the specified monster frequency from the universe tables
basic_chance = universe_tables.MONSTER_FREQUENCY[monster_freq]
# a value of 0 means no monsters, in this case return immediately
if basic_chance <= 0:
return
print "Default monster spawn chance:", basic_chance
expectation_tally = 0.0
actual_tally = 0
# get all monster fleets that have a spawn rate and limit both > 0 and at least one monster ship design in it
# (a monster fleet with no monsters in it is pointless) and store them in a list
fleet_plans = fo.load_monster_fleet_plan_list()
# create a map where we store a spawn counter for each monster fleet
# this counter will be set to the spawn limit initially and decreased every time the monster fleet is spawned
# this map (dict) needs to be separate from the list holding the fleet plans because the order in which items
# are stored in a dict is undefined (can be different each time), which would result in different distribution
# even when using the same seed for the RNG
spawn_limits = {fp: fp.spawn_limit() for fp in fleet_plans
if fp.spawn_rate() > 0.0 and fp.spawn_limit() > 0 and fp.ship_designs()}
# map nests to monsters for ease of reporting
nest_name_map = {"KRAKEN_NEST_SPECIAL": "SM_KRAKEN_1",
"SNOWFLAKE_NEST_SPECIAL": "SM_SNOWFLAKE_1",
"JUGGERNAUT_NEST_SPECIAL": "SM_JUGGERNAUT_1"}
tracked_plan_tries = {name: 0 for name in nest_name_map.values()}
tracked_plan_counts = {name: 0 for name in nest_name_map.values()}
tracked_plan_valid_locations = {fp: 0 for fp in fleet_plans if fp.name() in tracked_plan_counts}
if not fleet_plans:
return
universe = fo.get_universe()
# Fleet plans that include ships capable of altering starlanes.
# @content_tag{CAN_ALTER_STARLANES} universe_generator special handling
# for fleets containing a hull design with this tag.
fleet_can_alter_starlanes = {fp for fp in fleet_plans
if any([universe.getGenericShipDesign(design).hull_type.hasTag("CAN_ALTER_STARLANES")
for design in fp.ship_designs()])}
# dump a list of all monster fleets meeting these conditions and their properties to the log
print "Monster fleets available for generation at game start:"
fp_location_cache = {}
for fleet_plan in fleet_plans:
print "...", fleet_plan.name(), ": spawn rate", fleet_plan.spawn_rate(),
print "/ spawn limit", fleet_plan.spawn_limit(),
print "/ effective chance", basic_chance * fleet_plan.spawn_rate(),
fp_location_cache[fleet_plan] = set(fleet_plan.locations(systems))
print ("/ can be spawned at", len(fp_location_cache[fleet_plan]),
"of", len(systems), "systems")
if fleet_plan.name() in nest_name_map.values():
universe_statistics.tracked_monsters_chance[fleet_plan.name()] = basic_chance * fleet_plan.spawn_rate()
# initialize a manager for monsters that can alter the map
# required to prevent their placement from disjoining the map
starlane_altering_monsters = StarlaneAlteringMonsters(systems)
# collect info for tracked monster nest valid locations
planets = [p for s in systems for p in fo.sys_get_planets(s)]
tracked_nest_valid_locations = {nest: len(fo.special_locations(nest, planets))
for nest in nest_name_map}
# for each system in the list that has been passed to this function, find a monster fleet that can be spawned at
# the system and which hasn't already been added too many times, then attempt to add that monster fleet by
# testing the spawn rate chance
random.shuffle(systems)
for system in systems:
# collect info for tracked monster valid locations
for fp in tracked_plan_valid_locations:
if system in fp_location_cache[fp]:
tracked_plan_valid_locations[fp] += 1
# filter out all monster fleets whose location condition allows this system and whose counter hasn't reached 0.
suitable_fleet_plans = [fp for fp in fleet_plans
if system in fp_location_cache[fp]
and spawn_limits.get(fp, 0)
and (fp not in fleet_can_alter_starlanes
or starlane_altering_monsters.can_place_at(system, fp))]
# if there are no suitable monster fleets for this system, continue with the next
if not suitable_fleet_plans:
continue
# randomly select one monster fleet out of the suitable ones and then test if we want to add it to this system
# by making a roll against the basic chance multiplied by the spawn rate of this monster fleet
expectation_tally += basic_chance * sum([fp.spawn_rate()
for fp in suitable_fleet_plans]) / len(suitable_fleet_plans)
fleet_plan = random.choice(suitable_fleet_plans)
if fleet_plan.name() in tracked_plan_tries:
tracked_plan_tries[fleet_plan.name()] += 1
if random.random() > basic_chance * fleet_plan.spawn_rate():
print("\t\t At system %4d rejected monster fleet %s from %d suitable fleets"
% (system, fleet_plan.name(), len(suitable_fleet_plans)))
# no, test failed, continue with the next system
continue
actual_tally += 1
if fleet_plan.name() in tracked_plan_counts:
tracked_plan_counts[fleet_plan.name()] += 1
# all prerequisites and the test have been met, now spawn this monster fleet in this system
# create monster fleet
try:
if fleet_plan in fleet_can_alter_starlanes:
starlane_altering_monsters.place(system, fleet_plan)
else:
populate_monster_fleet(fleet_plan, system)
# decrement counter for this monster fleet
spawn_limits[fleet_plan] -= 1
except MapGenerationError as err:
report_error(str(err))
continue
print "Actual # monster fleets placed: %d; Total Placement Expectation: %.1f" % (actual_tally, expectation_tally)
# finally, compile some statistics to be dumped to the log later
universe_statistics.monsters_summary = [
(fp.name(), fp.spawn_limit() - counter) for fp, counter in spawn_limits.iteritems()
]
universe_statistics.tracked_monsters_tries.update(tracked_plan_tries)
universe_statistics.tracked_monsters_summary.update(tracked_plan_counts)
universe_statistics.tracked_monsters_location_summary.update(
(fp.name(), count) for fp, count in tracked_plan_valid_locations.iteritems())
universe_statistics.tracked_nest_location_summary.update(
(nest_name_map[nest], count) for nest, count in tracked_nest_valid_locations.items())
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 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 setup_empire(empire, empire_name, home_system, starting_species,
player_name):
"""
Sets up various aspects of an empire, like empire name, homeworld, etc.
"""
# set empire name, if no one is given, pick one randomly
if not empire_name:
print "No empire name set for player", player_name, ", picking one randomly"
empire_name = next(empire_name_generator)
fo.empire_set_name(empire, empire_name)
print "Empire name for player", player_name, "is", empire_name
# check starting species, if no one is given, pick one randomly
if starting_species == "RANDOM" or not starting_species:
print "Picking random starting species for player", player_name
starting_species = next(starting_species_pool)
print "Starting species for player", player_name, "is", starting_species
universe_statistics.empire_species[starting_species] += 1
# pick a planet from the specified home system as homeworld
planet_list = fo.sys_get_planets(home_system)
# if the system is empty, report an error and return false, indicating failure
if not planet_list:
report_error("Python setup_empire: got home system with no planets")
return False
homeworld = random.choice(planet_list)
# set selected planet as empire homeworld with selected starting species
fo.empire_set_homeworld(empire, homeworld, starting_species)
# set homeworld focus
# check if the preferred focus for the starting species is among
# the foci available on the homeworld planet
available_foci = fo.planet_available_foci(homeworld)
preferred_focus = fo.species_preferred_focus(starting_species)
if preferred_focus in available_foci:
# if yes, set the homeworld focus to the preferred focus
print "Player", player_name, ": setting preferred focus", preferred_focus, "on homeworld"
fo.planet_set_focus(homeworld, preferred_focus)
elif len(available_foci) > 0:
# if no, and there is at least one available focus,
# just take the first of the list
if preferred_focus == "":
print "Player", player_name, ": starting species", starting_species, "has no preferred focus, using",\
available_foci[0], "instead"
else:
print "Player", player_name, ": preferred focus", preferred_focus, "for starting species",\
starting_species, "not available on homeworld, using", available_foci[0], "instead"
fo.planet_set_focus(homeworld, available_foci[0])
else:
# if no focus is available on the homeworld, don't set any focus
print "Player", player_name, ": no available foci on homeworld for starting species", starting_species
# give homeworld starting buildings
print "Player", player_name, ": add starting buildings to homeworld"
for item in fo.load_starting_buildings():
fo.create_building(item.name, homeworld, empire)
# unlock starting techs, buildings, hulls, ship parts, etc.
# use default content file
print "Player", player_name, ": add unlocked items"
for item in fo.load_item_spec_list():
fo.empire_unlock_item(empire, item.type, item.name)
# add premade ship designs to empire
print "Player", player_name, ": add premade ship designs"
for ship_design in fo.design_get_premade_list():
fo.empire_add_ship_design(empire, ship_design)
# add starting fleets to empire
# use default content file
print "Player", player_name, ": add starting fleets"
fleet_plans = fo.load_fleet_plan_list()
for fleet_plan in fleet_plans:
# first, create the fleet
fleet = fo.create_fleet(fleet_plan.name(), home_system, empire)
# if the fleet couldn't be created, report an error and try to continue with the next fleet plan
if fleet == fo.invalid_object():
report_error("Python setup empire: couldn't create fleet %s" %
fleet_plan.name())
continue
# second, iterate over the list of ship design names in the fleet plan
for ship_design in fleet_plan.ship_designs():
# create a ship in the fleet
# if the ship couldn't be created, report an error and try to continue with the next ship design
if fo.create_ship("", ship_design, starting_species,
fleet) == fo.invalid_object():
report_error(
"Python setup empire: couldn't create ship %s for fleet %s"
% (ship_design, fleet_plan.name()))
return True
def execute_turn_events():
print "Executing turn events for turn", fo.current_turn()
# creating fields
systems = fo.get_systems()
radius = fo.get_universe_width() / 2.0
if random() < max(0.0003 * radius, 0.03):
if random() < 0.4:
field_type = "FLD_MOLECULAR_CLOUD"
size = 5.0
else:
field_type = "FLD_ION_STORM"
size = 5.0
x = y = radius
dist_from_center = 0.0
while (dist_from_center < radius) or any(
hypot(fo.get_x(s) - x,
fo.get_y(s) - y) < 50.0 for s in systems):
angle = random() * 2.0 * pi
dist_from_center = radius + uniform(
min(max(radius * 0.02, 10), 50.0),
min(max(radius * 0.05, 20), 100.0))
x = radius + (dist_from_center * sin(angle))
y = radius + (dist_from_center * cos(angle))
print "...creating new", field_type, "field, at distance", dist_from_center, "from center"
if fo.create_field(field_type, x, y, size) == fo.invalid_object():
print >> sys.stderr, "Turn events: couldn't create new field"
# creating monsters
gsd = fo.get_galaxy_setup_data()
monster_freq = MONSTER_FREQUENCY[gsd.monsterFrequency]
# monster freq ranges from 1/30 (= one monster per 30 systems) to 1/3 (= one monster per 3 systems)
# (example: low monsters and 150 Systems results in 150 / 30 * 0.01 = 0.05)
if monster_freq > 0 and random() < len(systems) * monster_freq * 0.01:
#only spawn Krill at the moment, other monsters can follow in the future
if random() < 1:
monster_type = "SM_KRILL_1"
else:
monster_type = "SM_FLOATER"
# search for systems without planets or fleets
candidates = [
s for s in systems if len(fo.sys_get_planets(s)) <= 0
and len(fo.sys_get_fleets(s)) <= 0
]
if not candidates:
print >> sys.stderr, "Turn events: unable to find system for monster spawn"
else:
system = choice(candidates)
print "...creating new", monster_type, "at", fo.get_name(system)
# create monster fleet
monster_fleet = fo.create_monster_fleet(system)
# if fleet creation fails, report an error
if monster_fleet == fo.invalid_object():
print >> sys.stderr, "Turn events: unable to create new monster fleet"
else:
# create monster, if creation fails, report an error
monster = fo.create_monster(monster_type, monster_fleet)
if monster == fo.invalid_object():
print >> sys.stderr, "Turn events: unable to create monster in fleet"
return True
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 execute_turn_events():
print("Executing turn events for turn", fo.current_turn())
# creating fields
systems = fo.get_systems()
radius = fo.get_universe_width() / 2.0
field_types = [
"FLD_MOLECULAR_CLOUD", "FLD_ION_STORM", "FLD_NANITE_SWARM",
"FLD_METEOR_BLIZZARD", "FLD_VOID_RIFT"
]
if random() < max(0.00015 * radius, 0.03):
field_type = choice(field_types)
size = 5.0
x = y = radius
dist_from_center = uniform(0.35, 1.0) * radius
angle = random() * 2.0 * pi
x = radius + (dist_from_center * sin(angle))
y = radius + (dist_from_center * cos(angle))
print("...creating new", field_type, "field, at distance",
dist_from_center, "from center")
if fo.create_field(field_type, x, y, size) == fo.invalid_object():
print("Turn events: couldn't create new field", file=sys.stderr)
# creating monsters
gsd = fo.get_galaxy_setup_data()
monster_freq = MONSTER_FREQUENCY[gsd.monsterFrequency]
# monster freq ranges from 1/30 (= one monster per 30 systems) to 1/3 (= one monster per 3 systems)
# (example: low monsters and 150 Systems results in 150 / 30 * 0.01 = 0.05)
if monster_freq > 0 and random() < len(systems) * monster_freq * 0.01:
# only spawn Krill at the moment, other monsters can follow in the future
if random() < 1:
monster_type = "SM_KRILL_1"
else:
monster_type = "SM_FLOATER"
# search for systems without planets or fleets
candidates = [
s for s in systems if len(fo.sys_get_planets(s)) <= 0
and len(fo.sys_get_fleets(s)) <= 0
]
if not candidates:
print("Turn events: unable to find system for monster spawn",
file=sys.stderr)
else:
system = choice(candidates)
print("...creating new", monster_type, "at", fo.get_name(system))
# create monster fleet
monster_fleet = fo.create_monster_fleet(system)
# if fleet creation fails, report an error
if monster_fleet == fo.invalid_object():
print("Turn events: unable to create new monster fleet",
file=sys.stderr)
else:
# create monster, if creation fails, report an error
monster = fo.create_monster(monster_type, monster_fleet)
if monster == fo.invalid_object():
print("Turn events: unable to create monster in fleet",
file=sys.stderr)
return True
def generate_natives(native_freq, systems, empire_home_systems):
"""
Adds non-empire-affiliated native populations to planets.
"""
# first, calculate the chance for natives on a planet based on the native frequency that has been passed
# get the corresponding value for the specified natives frequency from the universe tables
inverse_native_chance = fo.native_frequency(native_freq)
# as the value in the universe table is higher for a lower frequency, we have to invert it
# exception: a value of 0 means no natives, in this case return immediately
if inverse_native_chance <= 0:
return
native_chance = 1.0 / float(inverse_native_chance)
# compile a list of planets where natives can be placed
# select only planets sufficiently far away from player home systems
native_safe_planets = [] # list of planets safe for natives
for candidate in systems:
if not is_too_close_to_empire_home_systems(candidate, empire_home_systems):
# this system is sufficiently far away from all player homeworlds, so add it's planets to our list
native_safe_planets += fo.sys_get_planets(candidate)
print "Number of planets far enough from players for natives to be allowed:", len(native_safe_planets)
# if there are no "native safe" planets at all, we can stop here
if not native_safe_planets:
return
# get all native species
native_species = fo.get_native_species()
print "Species that can be added as natives:"
print "... " + "\n... ".join(native_species)
# create a map with a list for each planet type containing the species
# for which this planet type is a good environment
# we will need this afterwards when picking natives for a planet
natives_for_planet_type.clear() # just to be safe
natives_for_planet_type.update( {planet_type: [] for planet_type in planets.planet_types} )
planet_types_for_natives.clear()
planet_types_for_natives.update( {species: set() for species in native_species} )
# iterate over all native species we got
for species in native_species:
# check the planet environment for all planet types for this species
for planet_type in planets.planet_types:
# if this planet type is a good environment for the species, add it to the list for this planet type
if fo.species_get_planet_environment(species, planet_type) == fo.planetEnvironment.good:
natives_for_planet_type[planet_type].append(species)
planet_types_for_natives[species].add(planet_type)
# randomly add species to planets
# iterate over the list of "native safe" planets we compiled earlier
for candidate in native_safe_planets:
# select a native species to put on this planet
planet_type = fo.planet_get_type(candidate)
# check if we have any native species that like this planet type
if not natives_for_planet_type[planet_type]:
# no, continue with next planet
continue
statistics.potential_native_planet_summary[planet_type] += 1
# make a "roll" against the chance for natives to determine if we shall place natives on this planet
if random.random() > native_chance:
# no, continue with next planet
continue
statistics.settled_native_planet_summary[planet_type] += 1
# randomly pick one of the native species available for this planet type
natives = random.choice(natives_for_planet_type[planet_type])
# put the selected natives on the planet
fo.planet_set_species(candidate, natives)
# set planet as homeworld for that species
fo.species_add_homeworld(natives, candidate)
# set planet focus
# check if the preferred focus for the native species is among the foci available on this planet
available_foci = fo.planet_available_foci(candidate)
preferred_focus = fo.species_preferred_focus(natives)
if preferred_focus in available_foci:
# if yes, set the planet focus to the preferred focus
fo.planet_set_focus(candidate, preferred_focus)
elif available_foci:
# if no, and there is at least one available focus, just take the first of the list
# otherwise don't set any focus
fo.planet_set_focus(candidate, available_foci[0])
print "Added native", natives, "to planet", fo.get_name(candidate)
# increase the statistics counter for this native species, so a species summary can be dumped to the log later
statistics.species_summary[natives] += 1
def generate_monsters(monster_freq, systems):
"""
Adds space monsters to systems.
"""
# first, calculate the basic chance for monster generation in a system
# based on the monster frequency that has been passed
# get the corresponding value for the specified monster frequency from the universe tables
basic_chance = universe_tables.MONSTER_FREQUENCY[monster_freq]
# a value of 0 means no monsters, in this case return immediately
if basic_chance <= 0:
return
print "Default monster spawn chance:", basic_chance
expectation_tally = 0.0
actual_tally = 0
# get all monster fleets that have a spawn rate and limit both > 0 and at least one monster ship design in it
# (a monster fleet with no monsters in it is pointless) and store them in a list
fleet_plans = fo.load_monster_fleet_plan_list()
# create a map where we store a spawn counter for each monster fleet
# this counter will be set to the spawn limit initially and decreased every time the monster fleet is spawned
# this map (dict) needs to be separate from the list holding the fleet plans because the order in which items
# are stored in a dict is undefined (can be different each time), which would result in different distribution
# even when using the same seed for the RNG
spawn_limits = {fp: fp.spawn_limit() for fp in fleet_plans
if fp.spawn_rate() > 0.0 and fp.spawn_limit() > 0 and fp.ship_designs()}
# map nests to monsters for ease of reporting
nest_name_map = dict(zip(["KRAKEN_NEST_SPECIAL", "SNOWFLAKE_NEST_SPECIAL", "JUGGERNAUT_NEST_SPECIAL"], ["SM_KRAKEN_1", "SM_SNOWFLAKE_1", "SM_JUGGERNAUT_1"]))
tracked_plan_tries = {name: 0 for name in nest_name_map.values()}
tracked_plan_counts = {name: 0 for name in nest_name_map.values()}
tracked_plan_valid_locations = {fp: 0 for fp in fleet_plans if fp.name() in tracked_plan_counts}
tracked_nest_valid_locations = {nest: 0 for nest in nest_name_map}
if not fleet_plans:
return
# dump a list of all monster fleets meeting these conditions and their properties to the log
print "Monster fleets available for generation at game start:"
for fleet_plan in fleet_plans:
print "...", fleet_plan.name(), ": spawn rate", fleet_plan.spawn_rate(),
print "/ spawn limit", fleet_plan.spawn_limit(),
print "/ effective chance", basic_chance * fleet_plan.spawn_rate(),
if len(systems) < 1000:
print "/ can be spawned at", len([s for s in systems if fleet_plan.location(s)]), "systems"
else:
print # to terminate the print line
if fleet_plan.name() in nest_name_map.values():
statistics.tracked_monsters_chance[fleet_plan.name()] = basic_chance * fleet_plan.spawn_rate()
# for each system in the list that has been passed to this function, find a monster fleet that can be spawned at
# the system and which hasn't already been added too many times, then attempt to add that monster fleet by
# testing the spawn rate chance
for system in systems:
# collect info for tracked monster nest valid locations
for planet in fo.sys_get_planets(system):
for nest in tracked_nest_valid_locations:
#print "\t tracked monster check planet: %d size: %s for nest: %20s | result: %s" % (planet, fo.planet_get_size(planet), nest, fo.special_location(nest, planet))
if fo.special_location(nest, planet):
tracked_nest_valid_locations[nest] += 1
# collect info for tracked monster valid locations
for fp in tracked_plan_valid_locations:
if fp.location(system):
tracked_plan_valid_locations[fp] += 1
# filter out all monster fleets whose location condition allows this system and whose counter hasn't reached 0
suitable_fleet_plans = [fp for fp in fleet_plans if spawn_limits[fp] and fp.location(system)]
# if there are no suitable monster fleets for this system, continue with the next
if not suitable_fleet_plans:
continue
# randomly select one monster fleet out of the suitable ones and then test if we want to add it to this system
# by making a roll against the basic chance multiplied by the spawn rate of this monster fleet
expectation_tally += basic_chance * sum([fp.spawn_rate() for fp in suitable_fleet_plans]) / len(suitable_fleet_plans)
fleet_plan = random.choice(suitable_fleet_plans)
if fleet_plan.name() in tracked_plan_tries:
tracked_plan_tries[fleet_plan.name()] += 1
if random.random() > basic_chance * fleet_plan.spawn_rate():
print "\t\t At system %4d rejected monster fleet %s from %d suitable fleets" % (system, fleet_plan.name(), len(suitable_fleet_plans))
# no, test failed, continue with the next system
continue
actual_tally += 1
if fleet_plan.name() in tracked_plan_counts:
tracked_plan_counts[fleet_plan.name()] += 1
# all prerequisites and the test have been met, now spawn this monster fleet in this system
print "Spawn", fleet_plan.name(), "at", fo.get_name(system)
# decrement counter for this monster fleet
spawn_limits[fleet_plan] -= 1
# create monster fleet
monster_fleet = fo.create_monster_fleet(system)
# if fleet creation fails, report an error and try to continue with next system
if monster_fleet == fo.invalid_object():
util.report_error("Python generate_monsters: unable to create new monster fleet %s" % fleet_plan.name())
continue
# add monsters to fleet
for design in fleet_plan.ship_designs():
# create monster, if creation fails, report an error and try to continue with the next design
if fo.create_monster(design, monster_fleet) == fo.invalid_object():
util.report_error("Python generate_monsters: unable to create monster %s" % design)
print "Actual # monster fleets placed: %d; Total Placement Expectation: %.1f" % (actual_tally, expectation_tally)
# finally, compile some statistics to be dumped to the log later
statistics.monsters_summary = [(fp.name(), fp.spawn_limit() - counter) for fp, counter in spawn_limits.iteritems()]
statistics.tracked_monsters_tries.update(tracked_plan_tries)
statistics.tracked_monsters_summary.update(tracked_plan_counts)
statistics.tracked_monsters_location_summary.update([(fp.name(), count) for fp, count in tracked_plan_valid_locations.iteritems()])
statistics.tracked_nest_location_summary.update([(nest_name_map[nest], count) for nest, count in tracked_nest_valid_locations.items()])
